diff --git a/.flake8 b/.flake8
new file mode 100644
index 0000000..e0ea542
--- /dev/null
+++ b/.flake8
@@ -0,0 +1,3 @@
+[flake8]
+max-line-length = 88
+extend-ignore = E203
\ No newline at end of file
diff --git a/.github/workflows/black.yml b/.github/workflows/black.yml
new file mode 100644
index 0000000..21201d6
--- /dev/null
+++ b/.github/workflows/black.yml
@@ -0,0 +1,12 @@
+# Runs the Black automatic formatter.
+
+name: Lint
+
+on: [push, pull_request]
+
+jobs:
+ lint:
+ runs-on: ubuntu-latest
+ steps:
+ - uses: actions/checkout@v3
+ - uses: psf/black@stable
\ No newline at end of file
diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml
new file mode 100644
index 0000000..d12a44e
--- /dev/null
+++ b/.github/workflows/python-package.yml
@@ -0,0 +1,32 @@
+# GHA workflow for running tests.
+#
+# Largely taken from
+# https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+# Please check the link for more detailed instructions
+
+name: Run tests
+
+on: [push]
+
+jobs:
+ build:
+
+ runs-on: ubuntu-latest
+ strategy:
+ matrix:
+ python-version: ["3.9", "3.10"]
+
+ steps:
+ - uses: actions/checkout@v3
+ - name: Set up Python ${{ matrix.python-version }}
+ uses: actions/setup-python@v4
+ with:
+ python-version: ${{ matrix.python-version }}
+ - name: Install dependencies
+ run: |
+ python -m pip install --upgrade pip
+ pip install .
+ pip install pytest
+ - name: Test with pytest
+ run: |
+ pytest tests/
\ No newline at end of file
diff --git a/.gitignore b/.gitignore
index 1f4ae37..0eac814 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,17 +1,22 @@
-# Project-specific files and folders
-unp_notebooks/
-config.txt
-*.out
-*.pt
-*.zip
-*.pkl
-*.out.*
-*.err.*
-*.tar.gz
-*.zip
-*.tar
+# Project specific files
+messing_around/
+tests/test_simulator.ipynb
+*.estimator
+*.h5
+.vscode/
+.DS_Store
+#SBI related folders
sbi-logs/
-*~
+*.png
+*.pdf
+*.png
+
+# Training data, models and other datafiles
+results/
+production/
+*.estimator
+*epoch=*
+*.loss
# Byte-compiled / optimized / DLL files
__pycache__/
diff --git a/LICENSE b/LICENSE
deleted file mode 100644
index f288702..0000000
--- a/LICENSE
+++ /dev/null
@@ -1,674 +0,0 @@
- GNU GENERAL PUBLIC LICENSE
- Version 3, 29 June 2007
-
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- 13. Use with the GNU Affero General Public License.
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-section 13, concerning interaction through a network will apply to the
-combination as such.
-
- 14. Revised Versions of this License.
-
- The Free Software Foundation may publish revised and/or new versions of
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-be similar in spirit to the present version, but may differ in detail to
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-
- Each version is given a distinguishing version number. If the
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- END OF TERMS AND CONDITIONS
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-possible use to the public, the best way to achieve this is to make it
-free software which everyone can redistribute and change under these terms.
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-to attach them to the start of each source file to most effectively
-state the exclusion of warranty; and each file should have at least
-the "copyright" line and a pointer to where the full notice is found.
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- This program is free software: you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
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- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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- You should have received a copy of the GNU General Public License
- along with this program. If not, see .
-
-Also add information on how to contact you by electronic and paper mail.
-
- If the program does terminal interaction, make it output a short
-notice like this when it starts in an interactive mode:
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- Copyright (C)
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- This is free software, and you are welcome to redistribute it
- under certain conditions; type `show c' for details.
-
-The hypothetical commands `show w' and `show c' should show the appropriate
-parts of the General Public License. Of course, your program's commands
-might be different; for a GUI interface, you would use an "about box".
-
- You should also get your employer (if you work as a programmer) or school,
-if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU GPL, see
-.
-
- The GNU General Public License does not permit incorporating your program
-into proprietary programs. If your program is a subroutine library, you
-may consider it more useful to permit linking proprietary applications with
-the library. If this is what you want to do, use the GNU Lesser General
-Public License instead of this License. But first, please read
-.
diff --git a/README.md b/README.md
deleted file mode 100644
index 0c4b843..0000000
--- a/README.md
+++ /dev/null
@@ -1,118 +0,0 @@
-# cryo_em_SBI
-
-
-## Collaborators
-
-
-David Silva-Sánchez, Lars Dingeldein, Roberto Covino, Pilar Cossio
-
-# Dependencies
-
-1. [SBI - Mackelab](https://www.mackelab.org/sbi/install/) (and all their dependencies)
-2. SciPy
-3. NumPy
-4. Pickle
-5. json
-
-# Installing
-
-## Download this repository
-
-`https://github.com/DSilva27/cryo_em_SBI.git`
-
-## Install the module
-`python3 setup.py install`
-
-# Using the code
-
-
-## What can you find in this repo?
-
-1. `cryo_em_sbi`: module for doing sbi with CryoEM data
-2. `Tutorials`: learning how to run the code with two toy models, a simple square and the HSP90
-3. `models`: .npy files containing a 20x20 grid of models. For now only for HSP90 and the square-like system.
-4. `production`: a folder where everything you create is untracked by git.
-5. `README.md`: that's me!
-
-
-## The config file
-
-The config file is simply a json file where you will write the parameters to be used in both generating data and training. It has three main categories called `IMAGES`, `SIMULATION`, `PREPROCESSING`, and `TRAINING`.
-
-### IMAGES
-
-Here you need to set up the parameters to generate the images from 3D atomic coordinates
-
-1. PIXEL_SIZE: the size of the pixel in Angstroms
-2. N_PIXELS: Number of pixels the image will have in one dimension, i.e, the image is N_PIXELS * N_PIXELS.
-3. SIGMA: every atom in the atomic model will be represented as a gaussian centered around its center of mass. This parameter is the standard deviation of that gaussian.
-
-
-### SIMULATION
-
-1. N_SIMULATIONS: the number of images to generate.
-2. MODEL_FILE: the name of the file that contains all the atomics coordinates (check the folder `models`)
-3. DEVICE: either `"cpu"` or `"cuda"`. While for running with with a gpu you can simply write `"cuda"`, in some cases it can be a bit more complicated. Check recommendations at the end of the README.
-4. ROTATIONS: wheter or not to generate images with different orientations (true or false)
-
-### PREPROCESSING
-
-1. SHIFT: wheter or not to randomly shift images (true or false)
-2. CTF: wheter or not to apply CTF effects to images (true or false)
-3. NOISE: wheter or not to add CTF effects to images (true or false)
-4. DEFOCUS: value fo the defocus for the CTF
-5. SNR: The signal-to-noise ratio used to generate the images. Based on https://www.biorxiv.org/content/10.1101/864116v1.
-
-### TRAINING
-
-Parameters used to train an SNPE network using an `"maf"` model.
-
-1. MODEL: model for the neural network (check the SBI documentation)
-2. HIDDEN_FEATURES: number of hidden features in the network.
-3. NUM_TRANSFORMS: number of transforms in the network.
-4. DEVICE: either `"cpu"` or `"cuda"`. While for running with with a gpu you can simply write `"cuda"`, in some cases it can be a bit more complicated. Check recommendations at the end of the README.
-5. POSTERIOR_NAME: the trained posteriors are pickled to use for post-processing. This is simply the name of that file. This is the only optional parameter, if you don't provide it, the name is simply "posterior.pkl".
-
-
-## Prepare for simulating/training
-
-I conveniently created a folder called `production` where nothing will be tracked, i.e, seen by git. You can create all the folders and whatever you want in there. I will refer to the folder where you will be working as your `working directory`.
-
-1. Copy the files from the tutorial you want to reproduce to your `working directory`
-2. Check the example config files in `example_config` and copy the one that suits you the most over to your `working directoy`.
-3. Move to your `working directoy`.
-4. Load modules and activate virtual environment (if running locally on a workstation with slurm)
-
-```
-ml python
-ml gcc/7
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env_try/bin/activate
-```
-
-## Simulating, Preprocessing, and Training
-
-The tutorials have everything you need to do these actions with or without SLURM
-
-
-## Some tips for running with a GPU
-
-I still have to learn more, but here are a few tips.
-
-1. First check that pytorch actually recognizes your GPU
-
-```python
->>> import torch
->>> torch.cuda.is_available() # Check if pytorch sees your GPU
-True # or False
-
->>> torch.cuda.current_device() # Check the index of your GPU
-0 # Or other integer
-
->>> torch.cuda.get_device_name(0)
-'Name of your GPU'
-```
-
-2. If `torch.cuda.current_device()` returns `0` in your config file you should `"DEVICE"` to `"cuda:0"`.
-
-3. If you have multiple GPUs you can choose which one to use using `"cuda:identifier_of_your_gpu"`. For example if you have two GPUs identified by `0` and `1` and you want to use `1`, then you should write `"cuda:1"`. If you wanted to use both GPUs you should write `"cuda:{0, 1}`.
-
diff --git a/README.rst b/README.rst
new file mode 100644
index 0000000..2fe44a7
--- /dev/null
+++ b/README.rst
@@ -0,0 +1,57 @@
+===========
+cryoSBI - Simulation-based Inference for Cryo-EM
+===========
+
+.. start-badges
+
+.. list-table::
+ :stub-columns: 1
+
+ * - tests
+ - | |githubactions|
+
+
+.. |githubactions| image:: https://github.com/DSilva27/cryo_em_SBI/actions/workflows/python-package.yml/badge.svg?branch=cryoSBI
+ :alt: Testing Status
+ :target: https://github.com/DSilva27/cryo_em_SBI/actions
+
+Dependencies
+------------
+
+1. Lampe
+2. SciPy
+3. NumPy
+4. PyTorch
+5. json
+
+Installing
+----------
+
+Download this repository
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+`https://github.com/DSilva27/cryo_em_SBI.git`
+
+Install the module
+~~~~~~~~~~~~~~~~~~
+.. code:: bash
+
+ python3 -m pip install .
+
+Using the code
+--------------
+
+Train posterior from command line
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+.. code:: bash
+
+ train_npe_model \
+ --image_config_file image_config.json \
+ --train_config_file train_config.json\
+ --epochs 450 \
+ --estimator_file ../posterior/test.estimator \
+ --loss_file ../posterior/test.loss \
+ --n_workers 4 \
+ --train_device cuda \
+ --saving_freq 20 \
+ --simulation_batch_size 2048
diff --git a/cryo_em_sbi/__init__.py b/cryo_em_sbi/__init__.py
deleted file mode 100644
index 9dc31e2..0000000
--- a/cryo_em_sbi/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .cryo_em_sbi import CryoEmSbi
diff --git a/cryo_em_sbi/cryo_em_sbi.py b/cryo_em_sbi/cryo_em_sbi.py
deleted file mode 100644
index a6fda2f..0000000
--- a/cryo_em_sbi/cryo_em_sbi.py
+++ /dev/null
@@ -1,307 +0,0 @@
-from cryo_em_sbi.simulating import image_generation
-from cryo_em_sbi.utils import validate_config
-from cryo_em_sbi.preprocessing import preprocessing
-
-import json
-import pickle
-import numpy as np
-from scipy.spatial.transform import Rotation
-import torch
-from sbi.simulators.simutils import simulate_in_batches
-from sbi import utils as utils
-from sbi.inference import SNPE, prepare_for_sbi, simulate_for_sbi
-from sbi.utils.get_nn_models import posterior_nn
-
-
-class CryoEmSbi:
- def __init__(self, config_fname):
-
- self._load_params(config_fname)
- self._load_models()
-
- self.rot_mode = None
- self.quaternions = None
- self._config_rotations()
-
- self._set_prior_and_simulator_simulation()
- self._set_prior_and_simulator_analysis()
-
- def _load_params(self, config_fname):
-
- config = json.load(open(config_fname))
- validate_config.check_params(config)
- self.config = config
-
- return
-
- def _load_models(self):
-
- if "hsp90" in self.config["SIMULATION"]["MODEL_FILE"]:
- self.models = np.load(self.config["SIMULATION"]["MODEL_FILE"])[:, 0]
-
- elif "square" in self.config["SIMULATION"]["MODEL_FILE"]:
- self.models = np.transpose(
- np.load(self.config["SIMULATION"]["MODEL_FILE"]).diagonal(), [2, 0, 1]
- )
-
- print(self.config["SIMULATION"]["MODEL_FILE"])
-
- return
-
- def _config_rotations(self):
-
- if isinstance(self.config["SIMULATION"]["ROTATIONS"], bool):
- if self.config["SIMULATION"]["ROTATIONS"]:
-
- self.rot_mode = "random"
-
- elif isinstance(self.config["SIMULATION"]["ROTATIONS"], str):
-
- self.rot_mode = "list"
- self.quaternions = np.loadtxt(
- self.config["SIMULATION"]["ROTATIONS"], skiprows=1
- )
-
- assert (
- self.quaternions.shape[1] == 4
- ), "Quaternion shape is not 4. Corrupted file?"
-
- return
-
- def _simulator(self, index):
-
- index = int(torch.round(index))
-
- coord = self.models[index]
-
- if self.rot_mode == "random":
-
- quat = image_generation.gen_quat()
- rot_mat = Rotation.from_quat(quat).as_matrix()
- coord = np.matmul(rot_mat, coord)
-
- elif self.rot_mode == "list":
-
- quat = self.quaternions[np.random.randint(0, self.quaternions.shape[0])]
- rot_mat = Rotation.from_quat(quat).as_matrix()
- coord = np.matmul(rot_mat, coord)
-
- image = image_generation.gen_img(coord, self.config["IMAGES"])
-
- image = torch.tensor(
- image.reshape(-1, 1), device=self.config["SIMULATION"]["DEVICE"]
- )
-
- return image
-
- def _preprocessing_simulator(self, images):
-
- preproc_images = images.clone()
-
- if self.config["PREPROCESSING"]["SHIFT"]:
- preproc_images = preprocessing.pad_dataset(
- preproc_images, self.config["PREPROCESSING"], self.config["IMAGES"]
- )
-
- if self.config["PREPROCESSING"]["CTF"]:
- preproc_images = preprocessing.apply_ctf_to_dataset(
- preproc_images,
- self.config["SIMULATION"],
- self.config["IMAGES"],
- self.config["PREPROCESSING"],
- )
-
- if self.config["PREPROCESSING"]["SHIFT"]:
- preproc_images = preprocessing.shift_dataset(
- preproc_images, self.config["SIMULATION"], self.config["IMAGES"]
- )
-
- if self.config["PREPROCESSING"]["NOISE"]:
- preproc_images = preprocessing.add_noise_to_dataset(
- preproc_images, self.config["SIMULATION"], self.config["PREPROCESSING"]
- )
-
- preproc_images = preprocessing.normalize_dataset(
- preproc_images, self.config["SIMULATION"]
- )
-
- return preproc_images
-
- def _analysis_simulator(self, index):
-
- index = int(torch.round(index))
-
- coord = self.models[index]
-
- if self.rot_mode == "random":
-
- quat = image_generation.gen_quat()
- rot_mat = Rotation.from_quat(quat).as_matrix()
- coord = np.matmul(rot_mat, coord)
-
- elif self.rot_mode == "list":
-
- quat = self.quaternions[np.random.randint(0, self.quaternions.shape[0])]
- rot_mat = Rotation.from_quat(quat).as_matrix()
- coord = np.matmul(rot_mat, coord)
-
- image = image_generation.gen_img(coord, self.config["IMAGES"])
-
- if self.config["PREPROCESSING"]["SHIFT"]:
- image = preprocessing.pad_image(image, self.config["IMAGES"])
-
- if self.config["PREPROCESSING"]["CTF"]:
- image = preprocessing.apply_ctf(
- image, self.config["IMAGES"], self.config["PREPROCESSING"]
- )
-
- if self.config["PREPROCESSING"]["SHIFT"]:
- image = preprocessing.apply_random_shift(image, self.config["IMAGES"])
-
- if self.config["PREPROCESSING"]["NOISE"]:
- image = preprocessing.add_noise(image, self.config["PREPROCESSING"])
-
- image = preprocessing.gaussian_normalize_image(image)
-
- image = torch.tensor(
- image.reshape(-1, 1), device=self.config["TRAINING"]["DEVICE"]
- )
-
- return image
-
- def _get_prior(self):
-
- prior = utils.BoxUniform(
- low=0 * torch.ones(1, device=self.config["SIMULATION"]["DEVICE"]),
- high=19 * torch.ones(1, device=self.config["SIMULATION"]["DEVICE"]),
- device=self.config["SIMULATION"]["DEVICE"],
- )
-
- return prior
-
- def _set_prior_and_simulator_simulation(self):
-
- prior = utils.BoxUniform(
- low=0 * torch.ones(1, device=self.config["SIMULATION"]["DEVICE"]),
- high=19 * torch.ones(1, device=self.config["SIMULATION"]["DEVICE"]),
- device=self.config["SIMULATION"]["DEVICE"],
- )
-
- self.simulator, self.prior = prepare_for_sbi(self._simulator, prior)
-
- return
-
- def _set_prior_and_simulator_analysis(self):
-
- prior = utils.BoxUniform(
- low=0 * torch.ones(1, device=self.config["TRAINING"]["DEVICE"]),
- high=19 * torch.ones(1, device=self.config["TRAINING"]["DEVICE"]),
- device=self.config["TRAINING"]["DEVICE"],
- )
-
- self.simulator_analysis, self.prior_analysis = prepare_for_sbi(
- self._analysis_simulator, prior
- )
-
- return
-
- def update_config(self, config):
-
- validate_config.check_params(config)
- self.config = config
-
- self._load_models()
-
- self._set_prior_and_simulator_simulation()
-
- return
-
- def simulate(
- self, num_workers, fname_indices="indices.pt", fname_images="images.pt"
- ):
-
- if "cuda" in self.config["SIMULATION"]["DEVICE"]:
- assert (
- torch.cuda.is_available()
- ), "Your device is cuda but there is no GPU available"
-
- indices, images = simulate_for_sbi(
- self.simulator,
- proposal=self.prior,
- num_simulations=self.config["SIMULATION"]["N_SIMULATIONS"],
- num_workers=num_workers,
- )
-
- torch.save(indices, fname_indices)
- torch.save(images, fname_images)
-
- return indices, images
-
- def preprocess(
- self,
- indices,
- images,
- num_workers,
- batch_size=1,
- fname_output_indices="indices_training.pt",
- fname_output_images="images_training.pt",
- ):
-
- if "cuda" in self.config["PREPROCESSING"]["DEVICE"]:
- assert (
- torch.cuda.is_available()
- ), "Your device is cuda but there is no GPU available"
-
- preproc_images = simulate_in_batches(
- self._preprocessing_simulator,
- images,
- num_workers=num_workers,
- sim_batch_size=batch_size,
- )
-
- # indices = indices.to(self.config["TRAINING"]["DEVICE"])
- # images = images.to(self.config["TRAINING"]["DEVICE"])
-
- torch.save(indices, fname_output_indices)
- torch.save(preproc_images, fname_output_images)
-
- return indices, preproc_images
-
- def train_posterior(
- self, indices, images, num_workers, embedding_net=torch.nn.Identity()
- ):
-
- if "cuda" in self.config["TRAINING"]["DEVICE"]:
- assert (
- torch.cuda.is_available()
- ), "Your device is cuda but there is no GPU available"
-
- torch.set_num_threads(num_workers)
-
- indices = indices.to(self.config["TRAINING"]["DEVICE"])
- images = images.to(self.config["TRAINING"]["DEVICE"])
-
- density_estimator_build_fun = posterior_nn(
- model=self.config["TRAINING"]["MODEL"],
- hidden_features=self.config["TRAINING"]["HIDDEN_FEATURES"],
- num_transforms=self.config["TRAINING"]["NUM_TRANSFORMS"],
- embedding_net=embedding_net,
- )
-
- inference = SNPE(
- prior=self.prior_analysis,
- density_estimator=density_estimator_build_fun,
- device=self.config["TRAINING"]["DEVICE"],
- )
-
- inference = inference.append_simulations(indices, images)
-
- density_estimator = inference.train(
- training_batch_size=self.config["TRAINING"]["BATCH_SIZE"]
- )
- posterior = inference.build_posterior(density_estimator)
-
- with open(self.config["TRAINING"]["POSTERIOR_NAME"], "wb") as handle:
- pickle.dump(posterior, handle)
-
- return posterior
diff --git a/cryo_em_sbi/embedding_nets/conv_nn.py b/cryo_em_sbi/embedding_nets/conv_nn.py
deleted file mode 100644
index 43a07e6..0000000
--- a/cryo_em_sbi/embedding_nets/conv_nn.py
+++ /dev/null
@@ -1,28 +0,0 @@
-from torch import nn
-
-
-class ConvNeuralNet(nn.Module):
- def __init__(self, input_pixels):
- super().__init__()
-
- self.input_pixels = input_pixels
-
- # 2D convolutional layer
- self.conv1 = nn.Conv2d(in_channels=1, out_channels=6, kernel_size=5, padding=2)
-
- # Maxpool layer that reduces 32x32 image to 4x4
- self.pool = nn.MaxPool2d(kernel_size=8, stride=8)
-
- # Fully connected layer taking as input the 6 flattened output arrays from the maxpooling layer
- self.fc = nn.Linear(in_features=6 * 4 * 4, out_features=8)
-
- def forward(self, x):
-
- x = x.view(-1, 1, self.input_pixels, self.input_pixels)
- x = self.pool(nn.functional.relu(self.conv1(x)))
- x = x.view(-1, 6 * 4 * 4)
- x = nn.functional.relu(self.fc(x))
- return x
-
-
-embedding_net = ConvNeuralNet()
diff --git a/cryo_em_sbi/preprocessing/__init__.py b/cryo_em_sbi/preprocessing/__init__.py
deleted file mode 100644
index 2c6f6ca..0000000
--- a/cryo_em_sbi/preprocessing/__init__.py
+++ /dev/null
@@ -1,17 +0,0 @@
-from .padding import pad_image, pad_dataset
-from .ctf import (
- apply_ctf,
- apply_ctf_to_dataset,
-)
-from .noise import (
- add_noise,
- add_noise_to_dataset,
-)
-from .shift import (
- apply_random_shift,
- shift_dataset,
-)
-from .normalization import (
- gaussian_normalize_image,
- normalize_dataset,
-)
diff --git a/cryo_em_sbi/preprocessing/ctf.py b/cryo_em_sbi/preprocessing/ctf.py
deleted file mode 100644
index c3fd158..0000000
--- a/cryo_em_sbi/preprocessing/ctf.py
+++ /dev/null
@@ -1,57 +0,0 @@
-import numpy as np
-import torch
-
-
-def apply_ctf(image, image_params, preproc_params):
- def calc_ctf(n_pixels, amp, phase, b_factor):
-
- ctf = torch.zeros((n_pixels, n_pixels), dtype=np.complex64)
-
- freq_pix_1d = torch.fft.fftfreq(n_pixels, d=image_params["PIXEL_SIZE"])
-
- x, y = torch.meshgrid(freq_pix_1d, freq_pix_1d)
-
- freq2_2d = x**2 + y**2
- imag = torch.zeros_like(freq2_2d) * 1j
-
- env = torch.exp(torch.tensor(-b_factor * freq2_2d * 0.5))
- ctf = (
- amp * torch.cos(torch.tensor(phase * freq2_2d * 0.5))
- - torch.sqrt(torch.tensor(1 - amp**2))
- * torch.sin(torch.tensor(phase * freq2_2d * 0.5))
- + imag
- )
-
- return ctf * env / amp
-
- b_factor = 0.0 # no
- amp = 0.1 # no
-
- elecwavel = 0.019866
- phase = preproc_params["DEFOCUS"] * np.pi * 2.0 * 10000 * elecwavel
-
- ctf = calc_ctf(image.shape[0], amp, phase, b_factor)
-
- conv_image_ctf = torch.fft.fft2(image) * ctf
-
- image_ctf = torch.fft.ifft2(conv_image_ctf).real
-
- return image_ctf
-
-
-def apply_ctf_to_dataset(dataset, image_params, preproc_params):
-
- ctf_images = torch.empty_like(dataset, device=preproc_params["DEVICE"])
- n_pixels = int(np.sqrt(dataset.shape[1]))
-
- for i in range(dataset.shape[0]):
-
- tmp_image = apply_ctf(
- dataset[i].reshape(n_pixels, n_pixels),
- image_params,
- preproc_params,
- )
-
- ctf_images[i] = tmp_image.reshape(1, -1).to(preproc_params["DEVICE"])
-
- return ctf_images
diff --git a/cryo_em_sbi/preprocessing/noise.py b/cryo_em_sbi/preprocessing/noise.py
deleted file mode 100644
index 8e3fbe9..0000000
--- a/cryo_em_sbi/preprocessing/noise.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import numpy as np
-import torch
-
-
-def add_noise(img, preproc_params, radius_coef):
- def circular_mask(n_pixels, radius):
-
- grid = torch.linspace(-0.5 * (n_pixels - 1), 0.5 * (n_pixels - 1), n_pixels)
- r_2d = grid[None, :] ** 2 + grid[:, None] ** 2
- mask = r_2d < radius**2
-
- return mask
-
- mask = circular_mask(n_pixels=img.shape[0], radius=img.shape[0] * radius_coef)
-
- signal_std = img[mask].pow(2).mean().sqrt()
- noise_std = signal_std / np.sqrt(preproc_params["SNR"])
-
- img_noise = img + torch.distributions.normal.Normal(0, noise_std).sample(img.shape)
-
- return img_noise
-
-
-def add_noise_to_dataset(dataset, preproc_params):
-
- images_with_noise = torch.empty_like(dataset, device=preproc_params["DEVICE"])
- n_pixels = int(np.sqrt(dataset.shape[1]))
-
- for i in range(dataset.shape[0]):
-
- tmp_image = add_noise(dataset[i].reshape(n_pixels, n_pixels), preproc_params)
-
- images_with_noise[i] = tmp_image.reshape(1, -1).to(preproc_params["DEVICE"])
-
- return images_with_noise
diff --git a/cryo_em_sbi/preprocessing/normalization.py b/cryo_em_sbi/preprocessing/normalization.py
deleted file mode 100644
index 92df1aa..0000000
--- a/cryo_em_sbi/preprocessing/normalization.py
+++ /dev/null
@@ -1,25 +0,0 @@
-from random import gauss
-import numpy as np
-import torch
-
-
-def gaussian_normalize_image(image):
-
- mean_img = torch.mean(image)
- std_img = torch.std(image)
-
- return (image - mean_img) / std_img
-
-
-def normalize_dataset(dataset, preproc_params):
-
- norm_images = torch.empty_like(dataset, device=preproc_params["DEVICE"])
- n_pixels = int(np.sqrt(dataset.shape[1]))
-
- for i in range(dataset.shape[0]):
-
- tmp_image = gaussian_normalize_image(dataset[i].reshape(n_pixels, n_pixels))
-
- norm_images[i] = tmp_image.reshape(1, -1).to(preproc_params["DEVICE"])
-
- return norm_images
diff --git a/cryo_em_sbi/preprocessing/padding.py b/cryo_em_sbi/preprocessing/padding.py
deleted file mode 100644
index 595d4f7..0000000
--- a/cryo_em_sbi/preprocessing/padding.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import torch
-import numpy as np
-
-from torch.nn.functional import pad
-
-# from torch.nn import ConstantPad2d as pad
-
-
-def pad_image(image, image_params):
-
- pad_width = int(np.ceil(image_params["N_PIXELS"] * 0.1)) + 1
-
- padder = pad(pad_width, 0.0)
-
- padded_image = padder(image)
-
- return padded_image
-
-
-### Preprocessing functions for datasets ###
-def pad_dataset(dataset, image_params, preproc_params):
-
- images = dataset.reshape(
- dataset.shape[0], image_params["N_PIXELS"], image_params["N_PIXELS"]
- )
-
- pad_width = int(np.ceil(image_params["N_PIXELS"] * 0.1)) + 1
-
- padded_images = pad(
- images, (pad_width, pad_width, pad_width, pad_width), "constant", 0.0
- )
-
- return padded_images.reshape(dataset.shape[0], padded_images.shape[1] ** 2).to(
- preproc_params["DEVICE"]
- )
diff --git a/cryo_em_sbi/preprocessing/shift.py b/cryo_em_sbi/preprocessing/shift.py
deleted file mode 100644
index 1d4b530..0000000
--- a/cryo_em_sbi/preprocessing/shift.py
+++ /dev/null
@@ -1,39 +0,0 @@
-import torch
-import numpy as np
-
-
-def apply_random_shift(padded_image, image_params):
-
- shift_x = int(torch.ceil(image_params["N_PIXELS"] * 0.1 * (2 * torch.rand(1) - 1)))
- shift_y = int(torch.ceil(image_params["N_PIXELS"] * 0.1 * (2 * torch.rand(1) - 1)))
-
- pad_width = int(np.ceil(image_params["N_PIXELS"] * 0.1)) + 1
-
- low_ind_x = pad_width - shift_x
- high_ind_x = padded_image.shape[0] - pad_width - shift_x
-
- low_ind_y = pad_width - shift_y
- high_ind_y = padded_image.shape[0] - pad_width - shift_y
-
- shifted_image = padded_image[low_ind_x:high_ind_x, low_ind_y:high_ind_y]
-
- return shifted_image
-
-
-def shift_dataset(dataset, preproc_params, image_params):
-
- shifted_images = torch.empty(
- (dataset.shape[0], image_params["N_PIXELS"] ** 2),
- device=preproc_params["DEVICE"],
- )
- n_pixels = int(np.sqrt(dataset.shape[1]))
-
- for i in range(dataset.shape[0]):
-
- tmp_image = apply_random_shift(
- dataset[i].reshape(n_pixels, n_pixels), image_params
- )
-
- shifted_images[i] = tmp_image.reshape(1, -1).to(preproc_params["DEVICE"])
-
- return shifted_images
diff --git a/cryo_em_sbi/simulating/__init__.py b/cryo_em_sbi/simulating/__init__.py
deleted file mode 100644
index 028b602..0000000
--- a/cryo_em_sbi/simulating/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .image_generation import gen_img, gen_quat
diff --git a/cryo_em_sbi/simulating/image_generation.py b/cryo_em_sbi/simulating/image_generation.py
deleted file mode 100644
index 2c0374c..0000000
--- a/cryo_em_sbi/simulating/image_generation.py
+++ /dev/null
@@ -1,47 +0,0 @@
-import numpy as np
-import torch
-
-
-def gen_quat():
- # Sonya's code
- # Generates a single quaternion
-
- count = 0
- while count < 1:
-
- quat = np.random.uniform(
- -1, 1, 4
- ) # note this is a half-open interval, so 1 is not included but -1 is
- norm = np.sqrt(np.sum(quat**2))
-
- if 0.2 <= norm <= 1.0:
- quat /= norm
- count += 1
-
- return quat
-
-
-def gen_img(coord, image_params):
-
- n_atoms = coord.shape[1]
- norm = 1 / (2 * torch.pi * image_params["SIGMA"] ** 2 * n_atoms)
-
- grid_min = -image_params["PIXEL_SIZE"] * (image_params["N_PIXELS"] - 1) * 0.5
- grid_max = (
- image_params["PIXEL_SIZE"] * (image_params["N_PIXELS"] - 1) * 0.5
- + image_params["PIXEL_SIZE"]
- )
-
- grid = torch.arange(grid_min, grid_max, image_params["PIXEL_SIZE"])
-
- gauss_x = torch.exp(
- -0.5 * (((grid[:, None] - coord[0, :]) / image_params["SIGMA"]) ** 2)
- )
-
- gauss_y = torch.exp(
- -0.5 * (((grid[:, None] - coord[1, :]) / image_params["SIGMA"]) ** 2)
- )
-
- image = torch.matmul(gauss_x, gauss_y.T) * norm
-
- return image
diff --git a/cryo_em_sbi/utils/__init__.py b/cryo_em_sbi/utils/__init__.py
deleted file mode 100644
index a028065..0000000
--- a/cryo_em_sbi/utils/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-from .validate_config import check_params
-from .image_reader import ImageReader
diff --git a/cryo_em_sbi/utils/image_reader.py b/cryo_em_sbi/utils/image_reader.py
deleted file mode 100644
index 2414e89..0000000
--- a/cryo_em_sbi/utils/image_reader.py
+++ /dev/null
@@ -1,125 +0,0 @@
-import numpy as np
-import torch
-import pandas as pd
-import mrcfile
-import os
-from aspire.storage import StarFile
-
-
-class ImageReader:
-
- """
- This class is based on ASPIRE's RelionSource class.
- https://github.com/ComputationalCryoEM/ASPIRE-Python/blob/master/src/aspire/source/relion.py
- """
-
- relion_metadata_fields = {
- "_rlnVoltage": float,
- "_rlnDefocusU": float,
- "_rlnDefocusV": float,
- "_rlnDefocusAngle": float,
- "_rlnSphericalAberration": float,
- "_rlnDetectorPixelSize": float,
- "_rlnCtfFigureOfMerit": float,
- "_rlnMagnification": float,
- "_rlnAmplitudeContrast": float,
- "_rlnImageName": str,
- "_rlnOriginalName": str,
- "_rlnCtfImage": str,
- "_rlnCoordinateX": float,
- "_rlnCoordinateY": float,
- "_rlnCoordinateZ": float,
- "_rlnNormCorrection": float,
- "_rlnMicrographName": str,
- "_rlnGroupName": str,
- "_rlnGroupNumber": str,
- "_rlnOriginX": float,
- "_rlnOriginY": float,
- "_rlnAngleRot": float,
- "_rlnAngleTilt": float,
- "_rlnAnglePsi": float,
- "_rlnClassNumber": int,
- "_rlnLogLikeliContribution": float,
- "_rlnRandomSubset": int,
- "_rlnParticleName": str,
- "_rlnOriginalParticleName": str,
- "_rlnNrOfSignificantSamples": float,
- "_rlnNrOfFrames": int,
- "_rlnMaxValueProbDistribution": float,
- }
-
- def __init__(self, filepath):
-
- self.starfile = self._parse_star_file(filepath)
-
- def _parse_star_file(self, filepath, data_folder=None):
-
- starfile = StarFile(filepath).get_block_by_index(0)
-
- column_types = {
- name: ImageReader.relion_metadata_fields.get(name, str)
- for name in starfile.columns
- }
-
- starfile = starfile.astype(column_types)
-
- if data_folder is not None:
- if not os.path.isabs(data_folder):
- data_folder = os.path.join(os.path.dirname(filepath), data_folder)
- else:
- data_folder = os.path.dirname(filepath)
-
- starfile[["__mrc_index", "__mrc_filename"]] = starfile[
- "_rlnImageName"
- ].str.split("@", 1, expand=True)
- # __mrc_index corresponds to the integer index of the particle in the __mrc_filename stack
- # Note that this is 1-based indexing
- starfile["__mrc_index"] = pd.to_numeric(starfile["__mrc_index"])
-
- # Adding a full-filepath field to the Dataframe helps us save time later
- # Note that os.path.join works as expected when the second argument is an absolute path itself
- starfile["__mrc_filepath"] = starfile["__mrc_filename"].apply(
- lambda filename: os.path.join(data_folder, filename)
- )
-
- return starfile
-
- def read_images(self, indices):
-
- indices = np.asanyarray(indices)
-
- first_mrc_filepath = self.starfile.loc[0]["__mrc_filepath"]
- mrc = mrcfile.open(first_mrc_filepath)
-
- # Get the 'mode' (data type) - TODO: There's probably a more direct way to do this.
- mode = int(mrc.header.mode)
- dtypes = {0: "int8", 1: "int16", 2: "float32", 6: "uint16"}
- assert (
- mode in dtypes
- ), f"Only modes={list(dtypes.keys())} in MRC files are supported for now."
-
- dtype = dtypes[mode]
-
- shape = mrc.data.shape
-
- indices = np.array([0, 1, 2])
-
- images = torch.zeros((indices.shape[0], shape[0] * shape[1]))
-
- for i in range(indices.shape[0]):
-
- mrc_filepath = self.starfile.loc[i]["__mrc_filepath"]
- mrc = mrcfile.open(mrc_filepath)
-
- images[i] = torch.tensor(mrc.data.flatten())
-
- return images
-
-
-def main():
-
- filepath = "/path/to/star_file.star"
- image_reader = ImageReader(filepath)
-
- indices = np.array([0, 1, 2, 3, 4]) # reads the first five images
- images = image_reader.read_images(indices) # shape (5, n_pixels**2)
diff --git a/cryo_em_sbi/utils/validate_config.py b/cryo_em_sbi/utils/validate_config.py
deleted file mode 100644
index 1517be3..0000000
--- a/cryo_em_sbi/utils/validate_config.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import torch
-
-
-def check_params(config):
-
- # Sections
- for section in ["IMAGES", "PREPROCESSING", "SIMULATION", "TRAINING"]:
- assert (
- section in config.keys()
- ), f"Please provide section {section} in config.ini"
-
- image_params = config["IMAGES"]
- simulation_params = config["SIMULATION"]
- training_params = config["TRAINING"]
- preproc_params = config["PREPROCESSING"]
-
- # Images
- for key in ["N_PIXELS", "PIXEL_SIZE", "SIGMA"]:
- assert key in image_params.keys(), f"Please provide a value for {key}"
-
- # Simulation
- for key in ["N_SIMULATIONS", "MODEL_FILE", "DEVICE", "ROTATIONS"]:
- assert key in simulation_params.keys(), f"Please provide a value for {key}"
-
- # Preprocessing
- for key in ["SHIFT", "CTF", "NOISE", "DEFOCUS", "SNR", "DEVICE", "REDUCED_PIXELS"]:
- assert key in preproc_params.keys(), f"Please provide a value for {key}"
-
- # Training
-
- for key in ["MODEL", "HIDDEN_FEATURES", "NUM_TRANSFORMS", "BATCH_SIZE", "DEVICE"]:
- assert key in training_params.keys(), f"Please provide a value for {key}"
-
- if "POSTERIOR_NAME" not in training_params.keys():
- training_params["POSTERIOR_NAME"] = "posterior.pkl"
-
- return
diff --git a/models/square_models.npy b/models/square_models.npy
deleted file mode 100644
index 20bd7f5..0000000
Binary files a/models/square_models.npy and /dev/null differ
diff --git a/production/.gitignore b/production/.gitignore
deleted file mode 100644
index 26b58d7..0000000
--- a/production/.gitignore
+++ /dev/null
@@ -1,3 +0,0 @@
-*
-!empty.txt
-!.gitignore
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..f068847
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,33 @@
+[build-system]
+requires = ["setuptools", "setuptools-scm"]
+build-backend = "setuptools.build_meta"
+
+
+[project]
+name = "cryosbi"
+authors = [
+ { name = "David Silva-Sanchez", email = "david.silva@yale.edu"},
+ { name = "Lars Dingeldein"},
+ { name = "Pilar Cossio"},
+ { name = "Roberto Covino"}
+]
+
+
+version = "0.2"
+dependencies = [
+ "lampe",
+ "zuko",
+ "torch",
+ "numpy",
+ "matplotlib",
+ "scipy",
+ "torchvision",
+ "mrcfile"
+]
+
+
+[project.scripts]
+train_npe_model = "cryo_sbi.inference.command_line_tools:cl_npe_train_no_saving"
+train_npe_model_vram = "cryo_sbi.inference.command_line_tools:cl_npe_train_from_vram"
+train_npe_model_disk = "cryo_sbi.inference.command_line_tools:cl_npe_train_from_disk"
+generate_training_data = "cryo_sbi.inference.command_line_tools:cl_generate_training_data"
diff --git a/quaternions/QUAT_36864 b/quaternions/QUAT_36864
deleted file mode 100644
index 7dffa76..0000000
--- a/quaternions/QUAT_36864
+++ /dev/null
@@ -1,36865 +0,0 @@
-36864
-0.73558612 0.02408112 0.46279412 0.49412012
-0.73243612 0.07213912 0.42948612 0.52333112
-0.72615012 0.11988812 0.39433912 0.55030012
-0.71675412 0.16712412 0.35750412 0.57491312
-0.70428912 0.21364412 0.31913712 0.59706412
-0.68880812 0.25924912 0.27940412 0.61665812
-0.67037812 0.30374412 0.23847412 0.63361112
-0.64907612 0.34693912 0.19652412 0.64785212
-0.62499612 0.38864712 0.15373112 0.65931812
-0.59823912 0.42869212 0.11028112 0.66796112
-0.56892012 0.46690112 0.06635812 0.67374312
-0.53716512 0.50311012 0.02215112 0.67664112
-0.50311012 0.53716512 -0.02215112 0.67664112
-0.46690112 0.56892012 -0.06635812 0.67374312
-0.42869212 0.59823912 -0.11028112 0.66796112
-0.38864712 0.62499612 -0.15373112 0.65931812
-0.34693912 0.64907712 -0.19652412 0.64785212
-0.30374412 0.67037812 -0.23847412 0.63361112
-0.25924912 0.68880812 -0.27940412 0.61665812
-0.21364412 0.70428912 -0.31913712 0.59706412
-0.16712412 0.71675412 -0.35750412 0.57491312
-0.11988812 0.72615012 -0.39433912 0.55030012
-0.07213912 0.73243612 -0.42948612 0.52333012
-0.02408112 0.73558612 -0.46279412 0.49412012
--0.02408112 0.73558612 -0.49412012 0.46279412
--0.07213912 0.73243612 -0.52333112 0.42948612
--0.11988812 0.72615012 -0.55030012 0.39433912
--0.16712412 0.71675412 -0.57491312 0.35750412
--0.21364412 0.70428912 -0.59706412 0.31913712
--0.25924912 0.68880812 -0.61665812 0.27940412
--0.30374412 0.67037812 -0.63361112 0.23847412
--0.34693912 0.64907712 -0.64785212 0.19652412
--0.38864712 0.62499612 -0.65931812 0.15373112
--0.42869212 0.59823912 -0.66796112 0.11028112
--0.46690112 0.56892012 -0.67374312 0.06635812
--0.50311012 0.53716512 -0.67664112 0.02215112
--0.53716512 0.50311012 -0.67664112 -0.02215112
--0.56892012 0.46690112 -0.67374312 -0.06635812
--0.59823912 0.42869212 -0.66796112 -0.11028112
--0.62499612 0.38864712 -0.65931812 -0.15373112
--0.64907612 0.34693912 -0.64785212 -0.19652412
--0.67037812 0.30374412 -0.63361112 -0.23847412
--0.68880812 0.25924912 -0.61665812 -0.27940412
--0.70428912 0.21364412 -0.59706412 -0.31913712
--0.71675412 0.16712412 -0.57491312 -0.35750412
--0.72615012 0.11988812 -0.55030012 -0.39433912
--0.73243612 0.07213912 -0.52333112 -0.42948612
--0.73558612 0.02408112 -0.49412012 -0.46279412
-0.76335412 0.02499012 0.39295412 0.51210712
-0.76008512 0.07486212 0.35861912 0.53671112
-0.75356112 0.12441312 0.32274912 0.55901712
-0.74381112 0.17343212 0.28549612 0.57892912
-0.73087512 0.22170912 0.24702112 0.59636212
-0.71481012 0.26903512 0.20748812 0.61124112
-0.69568412 0.31521012 0.16706712 0.62350212
-0.67357812 0.36003512 0.12593012 0.63309412
-0.64858912 0.40331812 0.08425412 0.63997512
-0.62082212 0.44487512 0.04221712 0.64411512
-0.59039612 0.48452612 0.00000012 0.64549712
-0.55744312 0.52210212 -0.04221812 0.64411512
-0.52210212 0.55744312 -0.08425412 0.63997512
-0.48452612 0.59039612 -0.12593012 0.63309412
-0.44487512 0.62082212 -0.16706712 0.62350212
-0.40331812 0.64858912 -0.20748812 0.61124112
-0.36003512 0.67357912 -0.24702112 0.59636212
-0.31521012 0.69568412 -0.28549612 0.57892912
-0.26903512 0.71481012 -0.32274912 0.55901712
-0.22170912 0.73087512 -0.35861912 0.53671112
-0.17343212 0.74381112 -0.39295412 0.51210712
-0.12441312 0.75356112 -0.42560612 0.48531012
-0.07486212 0.76008512 -0.45643612 0.45643512
-0.02499012 0.76335412 -0.48531112 0.42560612
--0.02499012 0.76335412 -0.51210712 0.39295412
--0.07486212 0.76008512 -0.53671112 0.35861912
--0.12441412 0.75356112 -0.55901712 0.32274912
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diff --git a/quaternions/QUAT_4608 b/quaternions/QUAT_4608
deleted file mode 100644
index 8c42a79..0000000
--- a/quaternions/QUAT_4608
+++ /dev/null
@@ -1,4609 +0,0 @@
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diff --git a/quaternions/QUAT_576 b/quaternions/QUAT_576
deleted file mode 100644
index 9600e95..0000000
--- a/quaternions/QUAT_576
+++ /dev/null
@@ -1,577 +0,0 @@
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--0.22094212 0.53340212 0.75434412 0.31246012
--0.35146912 0.45804312 0.64777012 0.49705212
--0.45804312 0.35146912 0.49705212 0.64777012
--0.53340212 0.22094212 0.31246012 0.75434412
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--0.09229612 0.70105712 0.61237212 0.35355312
--0.27059812 0.65328112 0.50000012 0.50000012
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--0.49705212 0.64777012 0.45804312 0.35146912
--0.64777012 0.49705212 0.35146912 0.45804312
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--0.02664412 0.20237812 0.59594412 0.77664912
--0.07811512 0.18858612 0.37462612 0.90442712
--0.12426312 0.16194312 0.12777812 0.97057012
--0.16194312 0.12426312 -0.12777812 0.97057012
--0.18858612 0.07811512 -0.37462612 0.90442712
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-0.37717212 0.15623012 0.91287112 0.00000012
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--0.32388512 0.24852612 -0.45643512 0.79056912
--0.37717212 0.15623012 -0.64549712 0.64549712
--0.40475612 0.05328712 -0.79056912 0.45643512
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--0.05328712 0.40475612 0.79056912 0.45643512
--0.15623012 0.37717212 0.64549712 0.64549712
--0.24852612 0.32388512 0.45643512 0.79056912
--0.32388512 0.24852612 0.23626812 0.88176612
--0.37717212 0.15623012 0.00000012 0.91287112
--0.40475612 0.05328712 -0.23626812 0.88176612
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-0.07535912 0.57241112 0.64777012 0.49705212
--0.07535912 0.57241112 0.49705212 0.64777012
--0.22094212 0.53340212 0.31246012 0.75434512
--0.35146912 0.45804312 0.10657412 0.80951112
--0.45804312 0.35146912 -0.10657412 0.80951112
--0.53340212 0.22094212 -0.31246012 0.75434512
--0.57241112 0.07535912 -0.49705212 0.64777012
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 34c8280..0000000
--- a/setup.py
+++ /dev/null
@@ -1,29 +0,0 @@
-"""Create instructions to build cryo-Bife's path optimization version."""
-import setuptools
-
-requirements = []
-
-setuptools.setup(
- name="cryo_em_SBI",
- maintainer=[
- "David Silva-Sánchez",
- "Lars Dingeldein",
- "Roberto Covino",
- "Pilar Cossio",
- ],
- version="0.0.1",
- maintainer_email=[
- "david.silva@yale.edu",
- ],
- description="Simulation-based inference of CryoEM data",
- long_description=open("README.md", encoding="utf8").read(),
- long_description_content_type="text/markdown",
- url="https://github.com/DSilva27/cryo_em_SBI.git",
- packages=setuptools.find_packages(),
- install_requires=requirements,
- classifiers=[
- "Programming Language :: Python :: 3",
- "Operating System :: OS Independent",
- ],
- zip_safe=False,
-)
diff --git a/src/cryo_sbi/__init__.py b/src/cryo_sbi/__init__.py
new file mode 100644
index 0000000..c40eea7
--- /dev/null
+++ b/src/cryo_sbi/__init__.py
@@ -0,0 +1 @@
+from cryo_sbi.wpa_simulator.cryo_em_simulator import CryoEmSimulator
diff --git a/src/cryo_sbi/inference/__init__.py b/src/cryo_sbi/inference/__init__.py
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/src/cryo_sbi/inference/__init__.py
@@ -0,0 +1 @@
+
diff --git a/src/cryo_sbi/inference/command_line_tools.py b/src/cryo_sbi/inference/command_line_tools.py
new file mode 100644
index 0000000..6e77bd3
--- /dev/null
+++ b/src/cryo_sbi/inference/command_line_tools.py
@@ -0,0 +1,62 @@
+import argparse
+from cryo_sbi.inference.train_npe_model import (
+ npe_train_no_saving,
+)
+
+
+def cl_npe_train_no_saving():
+ cl_parser = argparse.ArgumentParser()
+
+ cl_parser.add_argument(
+ "--image_config_file", action="store", type=str, required=True
+ )
+ cl_parser.add_argument(
+ "--train_config_file", action="store", type=str, required=True
+ )
+ cl_parser.add_argument("--epochs", action="store", type=int, required=True)
+ cl_parser.add_argument("--estimator_file", action="store", type=str, required=True)
+ cl_parser.add_argument("--loss_file", action="store", type=str, required=True)
+ cl_parser.add_argument(
+ "--train_from_checkpoint",
+ action="store",
+ type=bool,
+ nargs="?",
+ required=False,
+ const=True,
+ default=False,
+ )
+ cl_parser.add_argument(
+ "--state_dict_file", action="store", type=str, required=False, default=False
+ )
+ cl_parser.add_argument(
+ "--n_workers", action="store", type=int, required=False, default=1
+ )
+ cl_parser.add_argument(
+ "--train_device", action="store", type=str, required=False, default="cpu"
+ )
+ cl_parser.add_argument(
+ "--saving_freq", action="store", type=int, required=False, default=20
+ )
+ cl_parser.add_argument(
+ "--simulation_batch_size",
+ action="store",
+ type=int,
+ required=False,
+ default=1024,
+ )
+
+ args = cl_parser.parse_args()
+
+ npe_train_no_saving(
+ image_config=args.image_config_file,
+ train_config=args.train_config_file,
+ epochs=args.epochs,
+ estimator_file=args.estimator_file,
+ loss_file=args.loss_file,
+ train_from_checkpoint=args.train_from_checkpoint,
+ model_state_dict=args.state_dict_file,
+ n_workers=args.n_workers,
+ device=args.train_device,
+ saving_frequency=args.saving_freq,
+ simulation_batch_size=args.simulation_batch_size,
+ )
diff --git a/src/cryo_sbi/inference/models/__init__.py b/src/cryo_sbi/inference/models/__init__.py
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/src/cryo_sbi/inference/models/__init__.py
@@ -0,0 +1 @@
+
diff --git a/src/cryo_sbi/inference/models/build_models.py b/src/cryo_sbi/inference/models/build_models.py
new file mode 100644
index 0000000..f3e1bd5
--- /dev/null
+++ b/src/cryo_sbi/inference/models/build_models.py
@@ -0,0 +1,59 @@
+import torch.nn as nn
+from functools import partial
+import zuko
+import lampe
+import cryo_sbi.inference.models.estimator_models as estimator_models
+from cryo_sbi.inference.models.embedding_nets import EMBEDDING_NETS
+
+
+def build_npe_flow_model(config: dict, **embedding_kwargs) -> nn.Module:
+ """
+ Function to build NPE estimator with embedding net
+ from config_file
+
+ Args:
+ config (dict): config file
+ embedding_kwargs (dict): kwargs for embedding net
+
+ Returns:
+ estimator (nn.Module): NPE estimator
+ """
+
+ if config["MODEL"] == "MAF":
+ model = zuko.flows.MAF
+ elif config["MODEL"] == "NSF":
+ model = zuko.flows.NSF
+ elif config["MODEL"] == "SOSPF":
+ model = zuko.flows.SOSPF
+ else:
+ raise NotImplementedError(
+ f"Model : {config['MODEL']} has not been implemented yet!"
+ )
+
+ try:
+ embedding = partial(
+ EMBEDDING_NETS[config["EMBEDDING"]], config["OUT_DIM"], **embedding_kwargs
+ )
+ except KeyError:
+ raise NotImplementedError(
+ f"Model : {config['EMBEDDING']} has not been implemented yet! \
+The following embeddings are implemented : {[key for key in EMBEDDING_NETS.keys()]}"
+ )
+
+ estimator = estimator_models.NPEWithEmbedding(
+ embedding_net=embedding,
+ output_embedding_dim=config["OUT_DIM"],
+ num_transforms=config["NUM_TRANSFORM"],
+ num_hidden_flow=config["NUM_HIDDEN_FLOW"],
+ hidden_flow_dim=config["HIDDEN_DIM_FLOW"],
+ flow=model,
+ theta_shift=config["THETA_SHIFT"],
+ theta_scale=config["THETA_SCALE"],
+ **{"activation": partial(nn.LeakyReLU, 0.1)},
+ )
+
+ return estimator
+
+
+def build_nre_classifier_model(config: dict, **embedding_kwargs) -> nn.Module:
+ raise NotImplementedError("NRE classifier model has not been implemented yet!")
diff --git a/src/cryo_sbi/inference/models/embedding_nets.py b/src/cryo_sbi/inference/models/embedding_nets.py
new file mode 100644
index 0000000..2d41234
--- /dev/null
+++ b/src/cryo_sbi/inference/models/embedding_nets.py
@@ -0,0 +1,404 @@
+import torch
+import torch.nn as nn
+import torchvision.models as models
+import torchvision.transforms as transforms
+
+from cryo_sbi.utils.image_utils import LowPassFilter, Mask
+
+
+EMBEDDING_NETS = {}
+
+
+def add_embedding(name):
+ """
+ Add embedding net to EMBEDDING_NETS dict
+
+ Args:
+ name (str): name of embedding net
+
+ Returns:
+ add (function): function to add embedding net to EMBEDDING_NETS dict
+ """
+
+ def add(class_):
+ EMBEDDING_NETS[name] = class_
+ return class_
+
+ return add
+
+
+@add_embedding("RESNET18")
+class ResNet18_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet18_Encoder, self).__init__()
+ self.resnet = models.resnet18()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("RESNET50")
+class ResNet50_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet50_Encoder, self).__init__()
+
+ self.resnet = models.resnet50()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.linear = nn.Linear(1000, output_dimension)
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ x = self.linear(nn.functional.relu(x))
+ return x
+
+
+@add_embedding("RESNET101")
+class ResNet101_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet101_Encoder, self).__init__()
+
+ self.resnet = models.resnet101()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.linear = nn.Linear(1000, output_dimension)
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ x = self.linear(nn.functional.relu(x))
+ return x
+
+
+@add_embedding("CONVNET")
+class ConvNet_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ConvNet_Encoder, self).__init__()
+
+ self.convnet = models.convnext_tiny()
+ self.convnet.features[0][0] = nn.Conv2d(
+ 1, 96, kernel_size=(4, 4), stride=(4, 4)
+ )
+ self.convnet.classifier[2] = nn.Linear(
+ in_features=768, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.convnet(x)
+ return x
+
+
+@add_embedding("CONVNET")
+class RegNetX_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(RegNetX_Encoder, self).__init__()
+
+ self.regnetx = models.regnet_x_3_2gf()
+ self.regnetx.stem[0] = nn.Conv2d(
+ 1, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False
+ )
+ self.regnetx.fc = nn.Linear(
+ in_features=1008, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.regnetx(x)
+ return x
+
+
+@add_embedding("EFFICIENT")
+class EfficientNet_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(EfficientNet_Encoder, self).__init__()
+
+ self.efficient_net = models.efficientnet_b3().features
+ self.efficient_net[0][0] = nn.Conv2d(
+ 1, 40, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False
+ )
+ self.avg_pool = nn.AdaptiveAvgPool2d(output_size=1)
+ self.leakyrelu = nn.LeakyReLU()
+ self.linear = nn.Linear(1536, output_dimension)
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.efficient_net(x)
+ x = self.avg_pool(x).flatten(start_dim=1)
+ x = self.leakyrelu(self.linear(x))
+ return x
+
+
+@add_embedding("SWINS")
+class SwinTransformerS_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(SwinTransformerS_Encoder, self).__init__()
+
+ self.swin_transformer = models.swin_t()
+ self.swin_transformer.features[0][0] = nn.Conv2d(
+ 1, 96, kernel_size=(4, 4), stride=(4, 4)
+ )
+ self.swin_transformer.head = nn.Linear(
+ in_features=768, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.swin_transformer(x)
+ return x
+
+
+@add_embedding("WIDERES50")
+class WideResnet50_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(WideResnet50_Encoder, self).__init__()
+
+ self.wideresnet = models.wide_resnet50_2()
+ self.wideresnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.linear = nn.Linear(1000, output_dimension)
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.wideresnet(x)
+ x = self.linear(nn.functional.relu(x))
+ return x
+
+
+@add_embedding("WIDERES101")
+class WideResnet101_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(WideResnet101_Encoder, self).__init__()
+
+ self.wideresnet = models.wide_resnet101_2()
+ self.wideresnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.linear = nn.Linear(1000, output_dimension)
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.wideresnet(x)
+ x = self.linear(nn.functional.relu(x))
+ return x
+
+
+@add_embedding("REGNETY")
+class RegNetY_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(RegNetY_Encoder, self).__init__()
+
+ self.regnety = models.regnet_y_1_6gf()
+ self.regnety.stem[0] = nn.Conv2d(
+ 1, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False
+ )
+ self.regnety.fc = nn.Linear(
+ in_features=888, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.regnety(x)
+ return x
+
+
+@add_embedding("SHUFFLENET")
+class ShuffleNet_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ShuffleNet_Encoder, self).__init__()
+
+ self.shuffle_net = models.shufflenet_v2_x0_5()
+ self.shuffle_net.conv1[0] = nn.Conv2d(
+ 1, 24, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False
+ )
+ self.shuffle_net.fc = nn.Linear(
+ in_features=1024, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ x = x.unsqueeze(1)
+ x = self.shuffle_net(x)
+ return x
+
+
+@add_embedding("RESNET18_FFT_FILTER")
+class ResNet18_FFT_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet18_FFT_Encoder, self).__init__()
+ self.resnet = models.resnet18()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+
+ self._fft_filter = LowPassFilter(128, 25)
+
+ def forward(self, x):
+ # Low pass filter images
+ x = self._fft_filter(x)
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("RESNET18_FFT_FILTER_132")
+class ResNet18_FFT_Encoder_132(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet18_FFT_Encoder_132, self).__init__()
+ self.resnet = models.resnet18()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+
+ self._fft_filter = LowPassFilter(132, 25)
+
+ def forward(self, x):
+ # Low pass filter images
+ x = self._fft_filter(x)
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("RESNET18_FFT_FILTER_224")
+class ResNet18_FFT_Encoder_224(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet18_FFT_Encoder_224, self).__init__()
+ self.resnet = models.resnet18()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+
+ self._fft_filter = LowPassFilter(224, 25)
+
+ def forward(self, x):
+ # Low pass filter images
+ x = self._fft_filter(x)
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("RESNET18_FFT_FILTER_256")
+class ResNet18_FFT_Encoder_256(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet18_FFT_Encoder_256, self).__init__()
+ self.resnet = models.resnet18()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+
+ self._fft_filter = LowPassFilter(256, 10)
+
+ def forward(self, x):
+ # Low pass filter images
+ x = self._fft_filter(x)
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("RESNET34")
+class ResNet34_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet34_Encoder, self).__init__()
+ self.resnet = models.resnet34()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+
+ def forward(self, x):
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("RESNET34_256_LP")
+class ResNet34_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(ResNet34_Encoder, self).__init__()
+ self.resnet = models.resnet34()
+ self.resnet.conv1 = nn.Conv2d(
+ 1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False
+ )
+ self.resnet.fc = nn.Linear(
+ in_features=512, out_features=output_dimension, bias=True
+ )
+ self._fft_filter = LowPassFilter(256, 50)
+
+ def forward(self, x):
+ # Low pass filter images
+ x = self._fft_filter(x)
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.resnet(x)
+ return x
+
+
+@add_embedding("VGG19")
+class VGG19_Encoder(nn.Module):
+ def __init__(self, output_dimension: int):
+ super(VGG19_Encoder, self).__init__()
+
+ self.vgg19 = models.vgg19_bn().features
+ self.vgg19[0] = nn.Conv2d(
+ 1, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)
+ )
+
+ self.avgpool = nn.AdaptiveAvgPool2d(output_size=(7, 7))
+
+ self.feedforward = nn.Sequential(
+ *[
+ nn.Linear(in_features=25088, out_features=4096),
+ nn.ReLU(inplace=True),
+ nn.Linear(in_features=4096, out_features=output_dimension, bias=True),
+ nn.ReLU(inplace=True),
+ ]
+ )
+
+ # self._fft_filter = LowPassFilter(256, 50)
+
+ def forward(self, x):
+ # Low pass filter images
+ # x = self._fft_filter(x)
+ # Proceed as normal
+ x = x.unsqueeze(1)
+ x = self.vgg19(x)
+ x = self.avgpool(x).flatten(start_dim=1)
+ x = self.feedforward(x)
+ return x
+
+
+if __name__ == "__main__":
+ pass
diff --git a/src/cryo_sbi/inference/models/estimator_models.py b/src/cryo_sbi/inference/models/estimator_models.py
new file mode 100644
index 0000000..a1ff0fe
--- /dev/null
+++ b/src/cryo_sbi/inference/models/estimator_models.py
@@ -0,0 +1,147 @@
+import torch
+import torch.nn as nn
+import zuko
+from lampe.inference import NPE, NRE
+
+
+class Standardize(nn.Module):
+ """
+ Module to standardize inputs and retransform them to the original space
+
+ Args:
+ mean (torch.Tensor): mean of the data
+ std (torch.Tensor): standard deviation of the data
+
+ Returns:
+ standardized (torch.Tensor): standardized data
+ """
+
+ # Code adapted from :https://github.com/mackelab/sbi/blob/main/sbi/utils/sbiutils.py
+ def __init__(self, mean: float, std: float) -> None:
+ super(Standardize, self).__init__()
+ mean, std = map(torch.as_tensor, (mean, std))
+ self.mean = mean
+ self.std = std
+ self.register_buffer("_mean", mean)
+ self.register_buffer("_std", std)
+
+ def forward(self, tensor: torch.Tensor) -> torch.Tensor:
+ """
+ Standardize the input tensor
+
+ Args:
+ tensor (torch.Tensor): input tensor
+
+ Returns:
+ standardized (torch.Tensor): standardized tensor
+ """
+
+ return (tensor - self._mean) / self._std
+
+ def transform(self, tensor: torch.Tensor) -> torch.Tensor:
+ """
+ Transform the standardized tensor back to the original space
+
+ Args:
+ tensor (torch.Tensor): input tensor
+
+ Returns:
+ retransformed (torch.Tensor): retransformed tensor
+ """
+
+ return (tensor * self._std) + self._mean
+
+
+class NPEWithEmbedding(nn.Module):
+ """Neural Posterior Estimation with embedding net
+
+ Attributes:
+ npe (NPE): NPE model
+ embedding (nn.Module): embedding net
+ standardize (Standardize): standardization module
+ """
+
+ def __init__(
+ self,
+ embedding_net: nn.Module,
+ output_embedding_dim: int,
+ num_transforms: int = 4,
+ num_hidden_flow: int = 2,
+ hidden_flow_dim: int = 128,
+ flow: nn.Module = zuko.flows.MAF,
+ theta_shift: float = 0.0,
+ theta_scale: float = 1.0,
+ **kwargs,
+ ) -> None:
+ """
+ Neural Posterior Estimation with embedding net.
+
+ Args:
+ embedding_net (nn.Module): embedding net
+ output_embedding_dim (int): output embedding dimension
+ num_transforms (int, optional): number of transforms. Defaults to 4.
+ num_hidden_flow (int, optional): number of hidden layers in flow. Defaults to 2.
+ hidden_flow_dim (int, optional): hidden dimension in flow. Defaults to 128.
+ flow (nn.Module, optional): flow. Defaults to zuko.flows.MAF.
+ theta_shift (float, optional): Shift of the theta for standardization. Defaults to 0.0.
+ theta_scale (float, optional): Scale of the theta for standardization. Defaults to 1.0.
+ kwargs: additional arguments for the flow
+
+ Returns:
+ None
+ """
+
+ super().__init__()
+
+ self.npe = NPE(
+ 1,
+ output_embedding_dim,
+ transforms=num_transforms,
+ build=flow,
+ hidden_features=[*[hidden_flow_dim] * num_hidden_flow, 128, 64],
+ **kwargs,
+ )
+
+ self.embedding = embedding_net()
+ self.standardize = Standardize(theta_shift, theta_scale)
+
+ def forward(self, theta: torch.Tensor, x: torch.Tensor) -> torch.Tensor:
+ """
+ Forward pass of the NPE model
+
+ Args:
+ theta (torch.Tensor): Conformational parameters.
+ x (torch.Tensor): Image to condition the posterior on.
+
+ Returns:
+ torch.Tensor: Log probability of the posterior.
+ """
+
+ return self.npe(self.standardize(theta), self.embedding(x))
+
+ def flow(self, x: torch.Tensor):
+ """
+ Conditions the posterior on an image.
+
+ Args:
+ x (torch.Tensor): Image to condition the posterior on.
+
+ Returns:
+ zuko.flows.Flow: The posterior distribution.
+ """
+ return self.npe.flow(self.embedding(x))
+
+ def sample(self, x: torch.Tensor, shape=(1,)) -> torch.Tensor:
+ """
+ Generate samples from the posterior distribution.
+
+ Args:
+ x (torch.Tensor): Image to condition the posterior on.
+ shape (tuple, optional): Shape of the samples. Defaults to (1,).
+
+ Returns:
+ torch.Tensor: Samples from the posterior distribution.
+ """
+
+ samples_standardized = self.flow(x).sample(shape)
+ return self.standardize.transform(samples_standardized)
diff --git a/src/cryo_sbi/inference/priors.py b/src/cryo_sbi/inference/priors.py
new file mode 100644
index 0000000..6ceabaa
--- /dev/null
+++ b/src/cryo_sbi/inference/priors.py
@@ -0,0 +1,215 @@
+import torch
+import zuko
+from torch.distributions.distribution import Distribution
+from torch.utils.data import DataLoader, Dataset, IterableDataset
+
+
+def gen_quat() -> torch.Tensor:
+ """
+ Generate a random quaternion.
+
+ Returns:
+ quat (np.ndarray): Random quaternion
+
+ """
+ count = 0
+ while count < 1:
+ quat = 2 * torch.rand(size=(4,)) - 1
+ norm = torch.sqrt(torch.sum(quat ** 2))
+ if 0.2 <= norm <= 1.0:
+ quat /= norm
+ count += 1
+
+ return quat
+
+
+def get_image_priors(
+ max_index, image_config: dict, device="cuda"
+) -> zuko.distributions.BoxUniform:
+ """
+ Return uniform prior in 1d from 0 to 19
+
+ Args:
+ max_index (int): max index of the 1d prior
+
+ Returns:
+ zuko.distributions.BoxUniform: prior
+ """
+ if isinstance(image_config["SIGMA"], list) and len(image_config["SIGMA"]) == 2:
+ lower = torch.tensor(
+ [[image_config["SIGMA"][0]]], dtype=torch.float32, device=device
+ )
+ upper = torch.tensor(
+ [[image_config["SIGMA"][1]]], dtype=torch.float32, device=device
+ )
+
+ assert lower <= upper, "Lower bound must be smaller or equal than upper bound."
+
+ sigma_prior = zuko.distributions.BoxUniform(lower=lower, upper=upper, ndims=1)
+
+ shift_prior = zuko.distributions.BoxUniform(
+ lower=torch.tensor(
+ [-image_config["SHIFT"], -image_config["SHIFT"]],
+ dtype=torch.float32,
+ device=device,
+ ),
+ upper=torch.tensor(
+ [image_config["SHIFT"], image_config["SHIFT"]],
+ dtype=torch.float32,
+ device=device,
+ ),
+ ndims=1,
+ )
+
+ if isinstance(image_config["DEFOCUS"], list) and len(image_config["DEFOCUS"]) == 2:
+ lower = torch.tensor(
+ [[image_config["DEFOCUS"][0]]], dtype=torch.float32, device=device
+ )
+ upper = torch.tensor(
+ [[image_config["DEFOCUS"][1]]], dtype=torch.float32, device=device
+ )
+
+ assert lower > 0.0, "The lower bound for DEFOCUS must be positive."
+ assert lower <= upper, "Lower bound must be smaller or equal than upper bound."
+
+ defocus_prior = zuko.distributions.BoxUniform(lower=lower, upper=upper, ndims=1)
+
+ if (
+ isinstance(image_config["B_FACTOR"], list)
+ and len(image_config["B_FACTOR"]) == 2
+ ):
+ lower = torch.tensor(
+ [[image_config["B_FACTOR"][0]]], dtype=torch.float32, device=device
+ )
+ upper = torch.tensor(
+ [[image_config["B_FACTOR"][1]]], dtype=torch.float32, device=device
+ )
+
+ assert lower > 0.0, "The lower bound for B_FACTOR must be positive."
+ assert lower <= upper, "Lower bound must be smaller or equal than upper bound."
+
+ b_factor_prior = zuko.distributions.BoxUniform(lower=lower, upper=upper, ndims=1)
+
+ if isinstance(image_config["SNR"], list) and len(image_config["SNR"]) == 2:
+ lower = torch.tensor(
+ [[image_config["SNR"][0]]], dtype=torch.float32, device=device
+ ).log10()
+ upper = torch.tensor(
+ [[image_config["SNR"][1]]], dtype=torch.float32, device=device
+ ).log10()
+
+ assert lower <= upper, "Lower bound must be smaller or equal than upper bound."
+
+ snr_prior = zuko.distributions.BoxUniform(lower=lower, upper=upper, ndims=1)
+
+ amp_prior = zuko.distributions.BoxUniform(
+ lower=torch.tensor([[image_config["AMP"]]], dtype=torch.float32, device=device),
+ upper=torch.tensor([[image_config["AMP"]]], dtype=torch.float32, device=device),
+ ndims=1,
+ )
+
+ index_prior = zuko.distributions.BoxUniform(
+ lower=torch.tensor([0], dtype=torch.float32, device=device),
+ upper=torch.tensor([max_index], dtype=torch.float32, device=device),
+ )
+ quaternion_prior = QuaternionPrior(device)
+ if (
+ image_config.get("ROTATIONS")
+ and isinstance(image_config["ROTATIONS"], list)
+ and len(image_config["ROTATIONS"]) == 4
+ ):
+ test_quat = image_config["ROTATIONS"]
+ quaternion_prior = QuaternionTestPrior(test_quat, device)
+
+ return ImagePrior(
+ index_prior,
+ quaternion_prior,
+ sigma_prior,
+ shift_prior,
+ defocus_prior,
+ b_factor_prior,
+ amp_prior,
+ snr_prior,
+ device=device,
+ )
+
+
+class QuaternionPrior:
+ def __init__(self, device) -> None:
+ self.device = device
+
+ def sample(self, shape) -> torch.Tensor:
+ quats = torch.stack(
+ [gen_quat().to(self.device) for _ in range(shape[0])], dim=0
+ )
+ return quats
+
+
+class QuaternionTestPrior:
+ def __init__(self, quat, device) -> None:
+ self.device = device
+ self.quat = torch.tensor(quat, device=device)
+
+ def sample(self, shape) -> torch.Tensor:
+ quats = torch.stack([self.quat for _ in range(shape[0])], dim=0)
+ return quats
+
+
+class ImagePrior:
+ def __init__(
+ self,
+ index_prior,
+ quaternion_prior,
+ sigma_prior,
+ shift_prior,
+ defocus_prior,
+ b_factor_prior,
+ amp_prior,
+ snr_prior,
+ device,
+ ) -> None:
+ self.priors = [
+ index_prior,
+ quaternion_prior,
+ sigma_prior,
+ shift_prior,
+ defocus_prior,
+ b_factor_prior,
+ amp_prior,
+ snr_prior,
+ ]
+
+ def sample(self, shape) -> torch.Tensor:
+ samples = [prior.sample(shape) for prior in self.priors]
+ return samples
+
+
+class PriorDataset(IterableDataset):
+ def __init__(
+ self,
+ prior: Distribution,
+ batch_shape: torch.Size = (),
+ ):
+ super().__init__()
+
+ self.prior = prior
+ self.batch_shape = batch_shape
+
+ def __iter__(self):
+ while True:
+ theta = self.prior.sample(self.batch_shape)
+ yield theta
+
+
+class PriorLoader(DataLoader):
+ def __init__(
+ self,
+ prior: Distribution,
+ batch_size: int = 2 ** 8, # 256
+ **kwargs,
+ ):
+ super().__init__(
+ PriorDataset(prior, batch_shape=(batch_size,)),
+ batch_size=None,
+ **kwargs,
+ )
diff --git a/src/cryo_sbi/inference/train_npe_model.py b/src/cryo_sbi/inference/train_npe_model.py
new file mode 100644
index 0000000..612f990
--- /dev/null
+++ b/src/cryo_sbi/inference/train_npe_model.py
@@ -0,0 +1,175 @@
+from typing import Union
+import json
+import torch
+import numpy as np
+import torch.optim as optim
+from torch.utils.data import TensorDataset
+from torchvision import transforms
+from tqdm import tqdm
+from lampe.data import JointLoader, H5Dataset
+from lampe.inference import NPELoss
+from lampe.utils import GDStep
+from itertools import islice
+
+from cryo_sbi.inference.priors import get_image_priors, PriorLoader
+from cryo_sbi.inference.models.build_models import build_npe_flow_model
+from cryo_sbi.inference.validate_train_config import check_train_params
+from cryo_sbi.wpa_simulator.cryo_em_simulator import cryo_em_simulator
+from cryo_sbi.wpa_simulator.validate_image_config import check_image_params
+from cryo_sbi.inference.validate_train_config import check_train_params
+import cryo_sbi.utils.image_utils as img_utils
+
+
+def load_model(
+ train_config: str, model_state_dict: str, device: str, train_from_checkpoint: bool
+) -> torch.nn.Module:
+ """
+ Load model from checkpoint or from scratch.
+
+ Args:
+ train_config (str): path to train config file
+ model_state_dict (str): path to model state dict
+ device (str): device to load model to
+ train_from_checkpoint (bool): whether to load model from checkpoint or from scratch
+ """
+
+ check_train_params(train_config)
+ estimator = build_npe_flow_model(train_config)
+ if train_from_checkpoint:
+ if not isinstance(model_state_dict, str):
+ raise Warning("No model state dict specified! --model_state_dict is empty")
+ print(f"Loading model parameters from {model_state_dict}")
+ estimator.load_state_dict(torch.load(model_state_dict))
+ estimator.to(device=device)
+ return estimator
+
+
+def npe_train_no_saving(
+ image_config: str,
+ train_config: str,
+ epochs: int,
+ estimator_file: str,
+ loss_file: str,
+ train_from_checkpoint: bool = False,
+ model_state_dict: Union[str, None] = None,
+ n_workers: int = 1,
+ device: str = "cpu",
+ saving_frequency: int = 20,
+ simulation_batch_size: int = 1024,
+) -> None:
+ """
+ Train NPE model by simulating training data on the fly.
+ Saves model and loss to disk.
+
+ Args:
+ image_config (str): path to image config file
+ train_config (str): path to train config file
+ epochs (int): number of epochs
+ estimator_file (str): path to estimator file
+ loss_file (str): path to loss file
+ train_from_checkpoint (bool, optional): train from checkpoint. Defaults to False.
+ model_state_dict (str, optional): path to pretrained model state dict. Defaults to None.
+ n_workers (int, optional): number of workers. Defaults to 1.
+ device (str, optional): training device. Defaults to "cpu".
+ saving_frequency (int, optional): frequency of saving model. Defaults to 20.
+ whiten_filter (Union[None, str], optional): path to whiten filter. Defaults to None.
+
+ Raises:
+ Warning: No model state dict specified! --model_state_dict is empty
+
+ Returns:
+ None
+ """
+
+ train_config = json.load(open(train_config))
+ check_train_params(train_config)
+ image_config = json.load(open(image_config))
+
+ assert simulation_batch_size >= train_config["BATCH_SIZE"]
+ assert simulation_batch_size % train_config["BATCH_SIZE"] == 0
+
+ if image_config["MODEL_FILE"].endswith("npy"):
+ models = (
+ torch.from_numpy(
+ np.load(image_config["MODEL_FILE"]),
+ )
+ .to(device)
+ .to(torch.float32)
+ )
+ else:
+ models = torch.load(
+ image_config["MODEL_FILE"]).to(device).to(torch.float32)
+
+ image_prior = get_image_priors(len(models) - 1, image_config, device="cpu")
+ prior_loader = PriorLoader(
+ image_prior, batch_size=simulation_batch_size, num_workers=n_workers
+ )
+
+ num_pixels = torch.tensor(
+ image_config["N_PIXELS"], dtype=torch.float32, device=device
+ )
+ pixel_size = torch.tensor(
+ image_config["PIXEL_SIZE"], dtype=torch.float32, device=device
+ )
+
+ estimator = load_model(
+ train_config, model_state_dict, device, train_from_checkpoint
+ )
+
+ loss = NPELoss(estimator)
+ optimizer = optim.AdamW(
+ estimator.parameters(), lr=train_config["LEARNING_RATE"], weight_decay=0.001
+ )
+ step = GDStep(optimizer, clip=train_config["CLIP_GRADIENT"])
+ mean_loss = []
+
+ print("Training neural netowrk:")
+ estimator.train()
+ with tqdm(range(epochs), unit="epoch") as tq:
+ for epoch in tq:
+ losses = []
+ for parameters in islice(prior_loader, 100):
+ (
+ indices,
+ quaternions,
+ res,
+ shift,
+ defocus,
+ b_factor,
+ amp,
+ snr,
+ ) = parameters
+ images = cryo_em_simulator(
+ models,
+ indices.to(device, non_blocking=True),
+ quaternions.to(device, non_blocking=True),
+ res.to(device, non_blocking=True),
+ shift.to(device, non_blocking=True),
+ defocus.to(device, non_blocking=True),
+ b_factor.to(device, non_blocking=True),
+ amp.to(device, non_blocking=True),
+ snr.to(device, non_blocking=True),
+ num_pixels,
+ pixel_size,
+ )
+ for _indices, _images in zip(
+ indices.split(train_config["BATCH_SIZE"]),
+ images.split(train_config["BATCH_SIZE"]),
+ ):
+ losses.append(
+ step(
+ loss(
+ _indices.to(device, non_blocking=True),
+ _images.to(device, non_blocking=True),
+ )
+ )
+ )
+ losses = torch.stack(losses)
+
+ tq.set_postfix(loss=losses.mean().item())
+ mean_loss.append(losses.mean().item())
+ if epoch % saving_frequency == 0:
+ torch.save(estimator.state_dict(), estimator_file + f"_epoch={epoch}")
+
+ torch.save(estimator.state_dict(), estimator_file)
+ torch.save(torch.tensor(mean_loss), loss_file)
diff --git a/src/cryo_sbi/inference/validate_train_config.py b/src/cryo_sbi/inference/validate_train_config.py
new file mode 100644
index 0000000..76a8c9b
--- /dev/null
+++ b/src/cryo_sbi/inference/validate_train_config.py
@@ -0,0 +1,29 @@
+def check_train_params(config: dict) -> None:
+ """
+ Checks if all necessary parameters are provided.
+
+ Args:
+ config (dict): Dictionary containing training parameters.
+
+ Returns:
+ None
+ """
+
+ needed_keys = [
+ "EMBEDDING",
+ "OUT_DIM",
+ "NUM_TRANSFORM",
+ "NUM_HIDDEN_FLOW",
+ "HIDDEN_DIM_FLOW",
+ "MODEL",
+ "LEARNING_RATE",
+ "CLIP_GRADIENT",
+ "BATCH_SIZE",
+ "THETA_SHIFT",
+ "THETA_SCALE",
+ ]
+
+ for key in needed_keys:
+ assert key in config.keys(), f"Please provide a value for {key}"
+
+ return
diff --git a/cryo_em_sbi/embedding_nets/__init__.py b/src/cryo_sbi/utils/__init__.py
similarity index 100%
rename from cryo_em_sbi/embedding_nets/__init__.py
rename to src/cryo_sbi/utils/__init__.py
diff --git a/src/cryo_sbi/utils/estimator_utils.py b/src/cryo_sbi/utils/estimator_utils.py
new file mode 100644
index 0000000..ce565a1
--- /dev/null
+++ b/src/cryo_sbi/utils/estimator_utils.py
@@ -0,0 +1,144 @@
+import torch
+import json
+from cryo_sbi.inference.models import build_models
+
+
+@torch.no_grad()
+def evaluate_log_prob(
+ estimator: torch.nn.Module,
+ images: torch.Tensor,
+ theta: torch.Tensor,
+ batch_size: int = 0,
+ device: str = "cpu",
+) -> torch.Tensor:
+
+ # batching images if necessary
+ if images.shape[0] > batch_size and batch_size > 0:
+ images = torch.split(images, split_size_or_sections=batch_size, dim=0)
+ else:
+ batch_size = images.shape[0]
+ images = [images]
+
+ # theta dimensions [num_eval, num_images, 1]
+ if theta.ndim == 3:
+ num_eval = theta.shape[0]
+ num_images = images.shape[0]
+ assert theta.shape == torch.Size([num_eval, num_images, 1])
+
+ elif theta.ndim == 2:
+ raise IndexError("theta must have 3 dimensions [num_eval, num_images, 1]")
+
+ elif theta.ndim == 1:
+ theta = theta.reshape(-1, 1, 1).repeat(1, batch_size, 1)
+
+ log_probs = []
+ for image_batch in images:
+ posterior = estimator.flow(image_batch.to(device))
+ log_probs.append(
+ posterior.log_prob(
+ estimator.standardize(theta.to(device))
+ )
+ )
+
+ log_probs = torch.cat(log_probs, dim=1)
+ return log_probs
+
+
+@torch.no_grad()
+def sample_posterior(
+ estimator: torch.nn.Module,
+ images: torch.Tensor,
+ num_samples: int,
+ batch_size: int = 100,
+ device: str = "cpu",
+) -> torch.Tensor:
+ """
+ Samples from the posterior distribution
+
+ Args:
+ estimator (torch.nn.Module): The posterior to use for sampling.
+ images (torch.Tensor): The images used to condition the posterio.
+ num_samples (int): The number of samples to draw
+ batch_size (int, optional): The batch size for sampling. Defaults to 100.
+ device (str, optional): The device to use. Defaults to "cpu".
+
+ Returns:
+ torch.Tensor: The posterior samples
+ """
+
+ theta_samples = []
+
+ if images.shape[0] > batch_size and batch_size > 0:
+ images = torch.split(images, split_size_or_sections=batch_size, dim=0)
+ else:
+ batch_size = images.shape[0]
+ images = [images]
+
+ for image_batch in images:
+ samples = estimator.sample(
+ image_batch.to(device, non_blocking=True), shape=(num_samples,)
+ ).cpu()
+ theta_samples.append(samples.reshape(-1, image_batch.shape[0]))
+
+ return torch.cat(theta_samples, dim=1)
+
+
+@torch.no_grad()
+def compute_latent_repr(
+ estimator: torch.nn.Module,
+ images: torch.Tensor,
+ batch_size: int = 100,
+ device: str = "cpu",
+) -> torch.Tensor:
+ """
+ Computes the latent representation of images.
+
+ Args:
+ estimator (torch.nn.Module): Posterior model for which to compute the latent representation.
+ images (torch.Tensor): The images to compute the latent representation for.
+ batch_size (int, optional): The batch size to use. Defaults to 100.
+ device (str, optional): The device to use. Defaults to "cpu".
+
+ Returns:
+ torch.Tensor: The latent representation of the images.
+ """
+
+ latent_space_samples = []
+
+ if images.shape[0] > batch_size and batch_size > 0:
+ images = torch.split(images, split_size_or_sections=batch_size, dim=0)
+ else:
+ batch_size = images.shape[0]
+ images = [images]
+
+ for image_batch in images:
+ samples = estimator.embedding(image_batch.to(device, non_blocking=True)).cpu()
+ latent_space_samples.append(samples.reshape(image_batch.shape[0], -1))
+
+ return torch.cat(latent_space_samples, dim=0)
+
+
+def load_estimator(
+ config_file_path: str, estimator_path: str, device: str = "cpu"
+) -> torch.nn.Module:
+ """
+ Loads a trained estimator.
+
+ Args:
+ config_file_path (str): Path to the config file used to train the estimator.
+ estimator_path (str): Path to the estimator.
+ device (str, optional): The device to use. Defaults to "cpu".
+
+ Returns:
+ torch.nn.Module: The loaded estimator.
+ """
+
+ train_config = json.load(open(config_file_path))
+ estimator = build_models.build_npe_flow_model(train_config)
+ estimator.load_state_dict(
+ torch.load(estimator_path, map_location=torch.device(device))
+ )
+ estimator.to(device)
+ estimator.eval()
+
+ return estimator
diff --git a/src/cryo_sbi/utils/generate_models.py b/src/cryo_sbi/utils/generate_models.py
new file mode 100644
index 0000000..28b7026
--- /dev/null
+++ b/src/cryo_sbi/utils/generate_models.py
@@ -0,0 +1,129 @@
+import MDAnalysis as mda
+from MDAnalysis.analysis import align
+import torch
+
+
+def pdb_parser_(fname: str) -> torch.tensor:
+ """
+ Parses a pdb file and returns a coarsed grained atomic model of the protein.
+ The atomic model is a 5xN array, where N is the number of residues in the protein.
+ The first three rows are the x, y, z coordinates of the alpha carbons.
+
+ Parameters
+ ----------
+ fname : str
+ The path to the pdb file.
+
+ Returns
+ -------
+ atomic_model : torch.tensor
+ The coarse grained atomic model of the protein.
+ """
+
+
+ univ = mda.Universe(fname)
+ univ.atoms.translate(-univ.atoms.center_of_mass())
+
+ model = torch.from_numpy(univ.select_atoms("name CA").positions.T)
+
+ return model
+
+
+def pdb_parser(file_formatter, n_pdbs, output_file, start_index=1):
+ """
+ Parses multiple pdb files and returns an coarsed grained model of the protein. The atomic model is a 5xN array, where N is the number of atoms or residues in the protein. The first three rows are the x, y, z coordinates of the atoms or residues. The fourth row is the atomic number of the atoms or the density of the residues. The fifth row is the variance of the atoms or residues, which is the resolution of the cryo-EM map divided by pi squared.
+
+ Parameters
+ ----------
+ file_formatter : str
+ The path to the pdb file. The path must contain the placeholder {} for the pdb index. For example, if the path is "data/pdb/{}.pdb", then the placeholder is {}.
+ n_pdbs : int
+ The number of pdb files to parse.
+ output_file : str
+ The path to the output file. The output file must be a .pt file.
+ mode : str
+ The mode of the atomic model. Either "resid" or "all atom". Resid mode returns a coarse grained atomic model of the protein. All atom mode returns an all atom atomic model of the protein.
+ """
+
+ models = pdb_parser_(file_formatter.format(start_index))
+ models = torch.zeros((n_pdbs, *models.shape))
+
+ for i in range(0, n_pdbs):
+ models[i] = pdb_parser_(file_formatter.format(start_index+i))
+
+
+ if output_file.endswith("pt"):
+ torch.save(models, output_file)
+
+ else:
+ raise ValueError("Model file format not supported. Please use .pt.")
+
+ return
+
+
+def traj_parser_(top_file: str, traj_file: str) -> torch.tensor:
+ """
+ Parses a traj file and returns a coarsed grained atomic model of the protein.
+ The atomic model is a Mx3xN array, where M is the number of frames in the trajectory,
+ and N is the number of residues in the protein. The first three rows in axis 1 are the x, y, z coordinates of the alpha carbons.
+
+ Parameters
+ ----------
+ top_file : str
+ The path to the traj file.
+
+ Returns
+ -------
+ atomic_model : torch.tensor
+ The coarse grained atomic model of the protein.
+ """
+
+ ref = mda.Universe(top_file)
+ ref.atoms.translate(-ref.atoms.center_of_mass())
+
+ mobile = mda.Universe(top_file, traj_file)
+ align.AlignTraj(mobile, ref, select="name CA", in_memory=True).run()
+
+ atomic_models = torch.zeros(
+ (mobile.trajectory.n_frames, 3, mobile.select_atoms("name CA").n_atoms)
+ )
+
+ for i in range(mobile.trajectory.n_frames):
+ mobile.trajectory[i]
+
+ atomic_models[i, 0:3, :] = torch.from_numpy(
+ mobile.select_atoms("name CA").positions.T
+ )
+
+ return atomic_models
+
+
+def traj_parser(top_file: str, traj_file: str, output_file: str) -> None:
+ """
+ Parses a traj file and returns an atomic model of the protein. The atomic model is a Mx5xN array, where M is the number of frames in the trajectory, and N is the number of atoms in the protein. The first three rows in axis 1 are the x, y, z coordinates of the atoms. The fourth row is the atomic number of the atoms. The fifth row is the variance of the atoms before the resolution is applied.
+
+ Parameters
+ ----------
+ top_file : str
+ The path to the topology file.
+ traj_file : str
+ The path to the trajectory file.
+ output_file : str
+ The path to the output file. Must be a .pt file.
+ mode : str
+ The mode of the atomic model. Either "resid" or "all-atom". Resid mode returns a coarse grained atomic model of the protein. All atom mode returns an all atom atomic model of the protein.
+
+ Returns
+ -------
+ None
+ """
+
+ atomic_models = traj_parser_(top_file, traj_file)
+
+ if output_file.endswith("pt"):
+ torch.save(atomic_models, output_file)
+
+ else:
+ raise ValueError("Model file format not supported. Please use .pt.")
+
+ return
\ No newline at end of file
diff --git a/src/cryo_sbi/utils/image_utils.py b/src/cryo_sbi/utils/image_utils.py
new file mode 100644
index 0000000..07211a0
--- /dev/null
+++ b/src/cryo_sbi/utils/image_utils.py
@@ -0,0 +1,358 @@
+import math
+from typing import List, Union
+import numpy as np
+import torch
+import torchvision.transforms as transforms
+import torch.distributions as d
+import mrcfile
+from tqdm import tqdm
+
+
+def circular_mask(n_pixels: int, radius: int, inside: bool = True) -> torch.Tensor:
+ """
+ Create a circular mask for a given image size and radius.
+
+ Args:
+ n_pixels (int): Side length of the image in pixels.
+ radius (int): Radius of the circle.
+ inside (bool, optional): If True, the mask will be True inside the circle. Defaults to True.
+
+ Returns:
+ mask (torch.Tensor): Mask of shape (n_pixels, n_pixels).
+ """
+
+ grid = torch.linspace(-0.5 * (n_pixels - 1), 0.5 * (n_pixels - 1), n_pixels)
+ r_2d = grid[None, :] ** 2 + grid[:, None] ** 2
+
+ if inside is True:
+ mask = r_2d < radius ** 2
+ else:
+ mask = r_2d > radius ** 2
+
+ return mask
+
+
+class Mask:
+ """
+ Mask a circular region in an image.
+
+ Args:
+ image_size (int): Number of pixels in the image.
+ radius (int): Radius of the circle.
+ inside (bool, optional): If True, the mask will be True inside the circle. Defaults to True.
+ """
+
+ def __init__(self, image_size: int, radius: int, inside: bool = False) -> None:
+ self.image_size = image_size
+ self.n_pixels = radius
+ self.mask = circular_mask(image_size, radius, inside=inside)
+
+ def __call__(self, image: torch.Tensor) -> torch.Tensor:
+ """Mask a circular region in an image.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels) or (n_channels, n_pixels, n_pixels).
+
+ Returns:
+ image (torch.Tensor): Image with masked region equal to zero.
+ """
+
+ if len(image.shape) == 2:
+ image[self.mask] = 0
+ elif len(image.shape) == 3:
+ image[:, self.mask] = 0
+ else:
+ raise NotImplementedError
+
+ return image
+
+
+def fourier_down_sample(
+ image: torch.Tensor, image_size: int, n_pixels: int
+) -> torch.Tensor:
+ """
+ Downsample an image by removing the outer frequencies.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels) or (n_channels, n_pixels, n_pixels).
+ image_size (int): Side length of the image in pixels.
+ n_pixels (int): Number of pixels to remove from each side.
+
+ Returns:
+ reconstructed (torch.Tensor): Downsampled image.
+ """
+
+ fft_image = torch.fft.fft2(image)
+ fft_image = torch.fft.fftshift(fft_image)
+
+ if len(image.shape) == 2:
+ fft_image = fft_image[
+ n_pixels : image_size - n_pixels,
+ n_pixels : image_size - n_pixels,
+ ]
+ elif len(image.shape) == 3:
+ fft_image = fft_image[
+ :,
+ n_pixels : image_size - n_pixels,
+ n_pixels : image_size - n_pixels,
+ ]
+ else:
+ raise NotImplementedError
+
+ fft_image = torch.fft.fftshift(fft_image)
+ reconstructed = torch.fft.ifft2(fft_image).real
+ return reconstructed
+
+
+class FourierDownSample:
+ """
+ Downsample an image by removing the outer frequencies.
+
+ Args:
+ image_size (int): Size of image in pixels.
+ down_sampled_size (int): Size of downsampled image in pixels.
+ """
+
+ def __init__(self, image_size: int, down_sampled_size: int) -> None:
+ self._image_size = image_size
+ self._n_pixels = (image_size - down_sampled_size) // 2
+
+ def __call__(self, image: torch.Tensor) -> torch.Tensor:
+ """Downsample an image by removing the outer frequencies.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels) or (n_channels, n_pixels, n_pixels).
+
+ Returns:
+ down_sampled (torch.Tensor): Downsampled image.
+ """
+
+ down_sampled = fourier_down_sample(
+ image, image_size=self._image_size, n_pixels=self._n_pixels
+ )
+
+ return down_sampled
+
+
+class LowPassFilter:
+ """
+ Low pass filter an image by removing the outer frequencies.
+
+ Args:
+ image_size (int): Side length of the image in pixels.
+ frequency_cutoff (int): Frequency cutoff.
+ """
+
+ def __init__(self, image_size: int, frequency_cutoff: int):
+ self.mask = circular_mask(image_size, frequency_cutoff, inside=False)
+
+ def __call__(self, image: torch.Tensor) -> torch.Tensor:
+ """
+ Low pass filter an image by removing the outer frequencies.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels) or (n_channels, n_pixels, n_pixels).
+
+ Returns:
+ reconstructed (torch.Tensor): Low pass filtered image.
+ """
+ fft_image = torch.fft.fft2(image)
+ fft_image = torch.fft.fftshift(fft_image)
+
+ if len(image.shape) == 2:
+ fft_image[self.mask] = 0 + 0j
+ elif len(image.shape) == 3:
+ fft_image[:, self.mask] = 0 + 0j
+ else:
+ raise NotImplementedError
+
+ fft_image = torch.fft.fftshift(fft_image)
+ reconstructed = torch.fft.ifft2(fft_image).real
+ return reconstructed
+
+
+class NormalizeIndividual:
+ """
+ Normalize an image by subtracting the mean and dividing by the standard deviation.
+ """
+
+ def __init__(self) -> None:
+ pass
+
+ def __call__(self, images: torch.Tensor) -> torch.Tensor:
+ """
+ Normalize an image by subtracting the mean and dividing by the standard deviation.
+
+ Args:
+ images (torch.Tensor): Image of shape (n_channels, n_pixels, n_pixels).
+
+ Returns:
+ normalized (torch.Tensor): Normalized image.
+ """
+ if len(images.shape) == 2:
+ mean = images.mean()
+ std = images.std()
+ images = images.unsqueeze(0)
+ elif len(images.shape) == 3:
+ mean = images.mean(dim=[1, 2])
+ std = images.std(dim=[1, 2])
+ else:
+ raise NotImplementedError
+
+ return transforms.functional.normalize(images, mean=mean, std=std)
+
+
+def mrc_to_tensor(image_path: str) -> torch.Tensor:
+ """
+ Convert an MRC file to a tensor.
+
+ Args:
+ image_path (str): Path to the MRC file.
+
+ Returns:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels).
+ """
+
+ assert isinstance(image_path, str), "image path needs to be a string"
+ with mrcfile.open(image_path) as mrc:
+ image = mrc.data
+ return torch.from_numpy(image)
+
+
+class MRCtoTensor:
+ """
+ Convert an MRC file to a tensor.
+ """
+
+ def __init__(self) -> None:
+ pass
+
+ def __call__(self, image_path: str) -> torch.Tensor:
+ """
+ Convert an MRC file to a tensor.
+
+ Args:
+ image_path (str): Path to the MRC file.
+
+ Returns:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels).
+ """
+
+ return mrc_to_tensor(image_path)
+
+
+class WhitenImage:
+ """
+ Whiten an image by dividing by the noise PSD.
+
+ Args:
+ noise_psd (torch.Tensor): Noise PSD of shape (n_pixels, n_pixels).
+ """
+
+ def __init__(self, noise_psd: torch.Tensor) -> None:
+ self._noise_psd = noise_psd
+
+ def __call__(self, image: torch.Tensor) -> torch.Tensor:
+ """
+ Whiten an image by dividing by the noise PSD.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels).
+
+ Returns:
+ reconstructed (torch.Tensor): Whiten image.
+ """
+
+ fft_image = torch.fft.fft2(image)
+ if image.ndim == 3:
+ fft_image = fft_image / torch.sqrt(self._noise_psd.unsqueeze(0))
+ elif image.ndim == 2:
+ fft_image = fft_image / torch.sqrt(self._noise_psd)
+ reconstructed = torch.fft.ifft2(fft_image).real
+
+ return reconstructed
+
+
+class MRCdataset:
+ """
+ Creates a dataset of MRC files.
+ Each MRC file is converted to a tensor and has a unique index.
+
+ Args:
+ image_paths (list[str]): List of paths to MRC files.
+
+ Methods:
+ build_index_map: Builds a map of indices to file paths and file indices.
+ getitem: Returns a at the given global index.
+ __getitem__: Returns tensor of the MRC file at the given index.
+ """
+
+ def __init__(self, image_paths: List[str]):
+ super().__init__()
+ self.paths = image_paths
+ self._num_paths = len(image_paths)
+ self._index_map = None
+
+ def __len__(self):
+ return self._num_paths
+
+ def __getitem__(self, idx):
+ return idx, mrc_to_tensor(self.paths[idx])
+
+ def _extract_num_particles(self, path):
+ future_mrc = mrcfile.open_async(path)
+ mrc = future_mrc.result()
+ data_shape = mrc.data.shape
+ #img_stack = mrc.is_image_stack()
+ num_images = data_shape[0] if len(data_shape) > 2 else 1
+ return num_images
+
+ def build_index_map(self):
+ """
+ Builds a map of image indices to file paths and file indices.
+ """
+ if self._index_map is not None:
+ print("Index map already built.")
+ return
+
+ self._path_index = []
+ self._file_index = []
+ print("Initalizing indexing...")
+ for idx, path in tqdm(enumerate(self.paths), total=self._num_paths):
+ num_images = self._extract_num_particles(path)
+ self._path_index += [idx] * num_images
+ self._file_index += list(range(num_images))
+ self._index_map = True
+
+ def get_image(self, idx: Union[int, list]):
+ """
+ Returns the image at the given global index.
+
+ Args:
+ idx (int, List): Global index of the image.
+ """
+ assert (
+ self._index_map is not None
+ ), "Index map not built. First call build_index_map()"
+ if isinstance(idx, int):
+ image = mrc_to_tensor(self.paths[self._path_index[idx]])
+ if image.ndim > 2:
+ return image[self._file_index[idx]]
+ if isinstance(idx, (list, np.ndarray, torch.Tensor)):
+ return [
+ mrc_to_tensor(self.paths[self._path_index[i]])[self._file_index[i]]
+ for i in idx
+ ]
+
+
+class MRCloader(torch.utils.data.DataLoader):
+ """
+ Creates a dataloader of MRC files.
+
+ Args:
+ image_paths (list[str]): List of paths to MRC files.
+ **kwargs: Keyword arguments passed to torch.utils.data.DataLoader.
+ """
+
+ def __init__(self, image_paths: List[str], **kwargs):
+ super().__init__(MRCdataset(image_paths), batch_size=None, **kwargs)
diff --git a/src/cryo_sbi/utils/micrograph_utils.py b/src/cryo_sbi/utils/micrograph_utils.py
new file mode 100644
index 0000000..428c72d
--- /dev/null
+++ b/src/cryo_sbi/utils/micrograph_utils.py
@@ -0,0 +1,101 @@
+import random
+from typing import Optional, Union, List
+from cryo_sbi.utils.image_utils import mrc_to_tensor
+import torch
+import torchvision.transforms as transforms
+import torchvision.transforms.functional as TF
+
+
+class RandomMicrographPatches:
+ """
+ Iterator that returns random patches from a list of micrographs.
+
+ Args:
+ micro_graphs (List[Union[str, torch.Tensor]]): List of micrographs.
+ transform (Union[None, transforms.Compose]): Transform to apply to the patches.
+ patch_size (int): Size of the patches.
+ batch_size (int, optional): Batch size. Defaults to 1.
+ """
+
+ def __init__(
+ self,
+ micro_graphs: List[Union[str, torch.Tensor]],
+ transform: Union[None, transforms.Compose],
+ patch_size: int,
+ max_iter: Optional[int] = 1000,
+ ) -> None:
+ if all(map(isinstance, micro_graphs, [str] * len(micro_graphs))):
+ self._micro_graphs = [mrc_to_tensor(path) for path in micro_graphs]
+ else:
+ self._micro_graphs = micro_graphs
+
+ self._transform = transform
+ self._patch_size = patch_size
+ self._max_iter = max_iter
+ self._current_iter = 0
+
+ def __iter__(self) -> "RandomMicrographPatches":
+ return self
+
+ def __next__(self) -> torch.Tensor:
+ if self._current_iter == self._max_iter:
+ self._current_iter = 0
+ raise StopIteration
+ random_micrograph = random.choice(self._micro_graphs)
+ assert random_micrograph.ndim == 2, "Micrograph should be 2D"
+ x = random.randint(0, random_micrograph.shape[0] - self._patch_size)
+ y = random.randint(0, random_micrograph.shape[1] - self._patch_size)
+ patch = TF.crop(
+ random_micrograph,
+ top=y,
+ left=x,
+ height=self._patch_size,
+ width=self._patch_size,
+ )
+ if self._transform is not None:
+ patch = self._transform(patch)
+ else:
+ patch = patch.unsqueeze(0)
+ self._current_iter += 1
+ return patch
+
+ def __len__(self) -> int:
+ return self._max_iter
+
+ @property
+ def shape(self) -> torch.Size:
+ """
+ Shape of the transformed patches.
+
+ Returns:
+ torch.Size: Shape of the transformed patches.
+ """
+ return self.__next__().shape
+
+
+def compute_average_psd(
+ images: Union[torch.Tensor, RandomMicrographPatches],
+ device: str = "cpu",
+) -> torch.Tensor:
+ """
+ Compute the average PSD of a set of images.
+
+ Args:
+ images (Union[torch.Tensor, RandomMicrographPatches]): Images to compute the average PSD of.
+ device (str, optional): Device to compute the PSD on. Defaults to "cpu".
+
+ Returns:
+ avg_psd (torch.Tensor): Average PSD of the images.
+ """
+
+ if isinstance(images, RandomMicrographPatches):
+ avg_psd = torch.zeros(images.shape[1:], device=device)
+ for image in images: # TODO add progress bar with tqdm
+ fft_image = torch.fft.fft2(image[0].to(device, non_blocking=True))
+ psd = torch.abs(fft_image) ** 2
+ avg_psd += psd / len(images)
+ # add convergence check
+ elif isinstance(images, torch.Tensor):
+ fft_images = torch.fft.fft2(images.to(device=device), dim=(-2, -1))
+ avg_psd = torch.mean(torch.abs(fft_images) ** 2, dim=0)
+ return avg_psd.cpu()
diff --git a/src/cryo_sbi/wpa_simulator/__init__.py b/src/cryo_sbi/wpa_simulator/__init__.py
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/__init__.py
@@ -0,0 +1 @@
+
diff --git a/src/cryo_sbi/wpa_simulator/cryo_em_simulator.py b/src/cryo_sbi/wpa_simulator/cryo_em_simulator.py
new file mode 100644
index 0000000..742ce37
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/cryo_em_simulator.py
@@ -0,0 +1,181 @@
+from typing import Union, Callable
+import json
+import numpy as np
+import torch
+
+from cryo_sbi.wpa_simulator.ctf import apply_ctf
+from cryo_sbi.wpa_simulator.image_generation import project_density
+from cryo_sbi.wpa_simulator.noise import add_noise
+from cryo_sbi.wpa_simulator.normalization import gaussian_normalize_image
+from cryo_sbi.inference.priors import get_image_priors
+from cryo_sbi.wpa_simulator.validate_image_config import check_image_params
+
+
+def cryo_em_simulator(
+ models,
+ index,
+ quaternion,
+ sigma,
+ shift,
+ defocus,
+ b_factor,
+ amp,
+ snr,
+ num_pixels,
+ pixel_size,
+):
+ """
+ Simulates a bacth of cryo-electron microscopy (cryo-EM) images of a set of given coars-grained models.
+
+ Args:
+ models (torch.Tensor): A tensor of coars grained models (num_models, 3, num_beads).
+ index (torch.Tensor): A tensor of indices to select the models to simulate.
+ quaternion (torch.Tensor): A tensor of quaternions to rotate the models.
+ sigma (float): The standard deviation of the Gaussian kernel used to project the density.
+ shift (torch.Tensor): A tensor of shifts to apply to the models.
+ defocus (float): The defocus value of the contrast transfer function (CTF).
+ b_factor (float): The B-factor of the CTF.
+ amp (float): The amplitude contrast of the CTF.
+ snr (float): The signal-to-noise ratio of the simulated image.
+ num_pixels (int): The number of pixels in the simulated image.
+ pixel_size (float): The size of each pixel in the simulated image.
+
+ Returns:
+ torch.Tensor: A tensor of the simulated cryo-EM image.
+ """
+ models_selected = models[index.round().long().flatten()]
+ image = project_density(
+ models_selected,
+ quaternion,
+ sigma,
+ shift,
+ num_pixels,
+ pixel_size,
+ )
+ image = apply_ctf(image, defocus, b_factor, amp, pixel_size)
+ image = add_noise(image, snr)
+ image = gaussian_normalize_image(image)
+ return image
+
+
+class CryoEmSimulator:
+ def __init__(self, config_fname: str, device: str = "cpu"):
+ self._device = device
+ self._load_params(config_fname)
+ self._load_models()
+ self._priors = get_image_priors(self.max_index, self._config, device=device)
+ self._num_pixels = torch.tensor(
+ self._config["N_PIXELS"], dtype=torch.float32, device=device
+ )
+ self._pixel_size = torch.tensor(
+ self._config["PIXEL_SIZE"], dtype=torch.float32, device=device
+ )
+
+ def _load_params(self, config_fname: str) -> None:
+ """
+ Loads the parameters from the config file into a dictionary.
+
+ Args:
+ config_fname (str): Path to the configuration file.
+
+ Returns:
+ None
+ """
+
+ config = json.load(open(config_fname))
+ check_image_params(config)
+ self._config = config
+
+ def _load_models(self) -> None:
+ """
+ Loads the models from the model file specified in the config file.
+
+ Returns:
+ None
+
+ """
+ if self._config["MODEL_FILE"].endswith("npy"):
+ models = (
+ torch.from_numpy(
+ np.load(self._config["MODEL_FILE"]),
+ )
+ .to(self._device)
+ .to(torch.float32)
+ )
+ elif self._config["MODEL_FILE"].endswith("pt"):
+ models = (
+ torch.load(self._config["MODEL_FILE"])
+ .to(self._device)
+ .to(torch.float32)
+ )
+
+ else:
+ raise NotImplementedError(
+ "Model file format not supported. Please use .npy or .pt."
+ )
+
+ self._models = models
+
+ assert self._models.ndim == 3, "Models are not of shape (models, 3, atoms)."
+ assert self._models.shape[1] == 3, "Models are not of shape (models, 3, atoms)."
+
+ @property
+ def max_index(self) -> int:
+ """
+ Returns the maximum index of the model file.
+
+ Returns:
+ int: Maximum index of the model file.
+ """
+ return len(self._models) - 1
+
+ def simulate(self, num_sim, indices=None, return_parameters=False, batch_size=None):
+ """
+ Simulate cryo-EM images using the specified models and prior distributions.
+
+ Args:
+ num_sim (int): The number of images to simulate.
+ indices (torch.Tensor, optional): The indices of the images to simulate. If None, all images are simulated.
+ return_parameters (bool, optional): Whether to return the sampled parameters used for simulation.
+ batch_size (int, optional): The batch size to use for simulation. If None, all images are simulated in a single batch.
+
+ Returns:
+ torch.Tensor or tuple: The simulated images as a tensor of shape (num_sim, num_pixels, num_pixels),
+ and optionally the sampled parameters as a tuple of tensors.
+ """
+
+ parameters = self._priors.sample((num_sim,))
+ indices = parameters[0] if indices is None else indices
+ if indices is not None:
+ assert isinstance(
+ indices, torch.Tensor
+ ), "Indices are not a torch.tensor, converting to torch.tensor."
+ assert (
+ indices.dtype == torch.float32
+ ), "Indices are not a torch.float32, converting to torch.float32."
+ assert (
+ indices.ndim == 2
+ ), "Indices are not a 2D tensor, converting to 2D tensor. With shape (batch_size, 1)."
+ indices = torch.tensor(indices, dtype=torch.float32)
+
+ images = []
+ if batch_size is None:
+ batch_size = num_sim
+ for i in range(0, num_sim, batch_size):
+ batch_indices = indices[i:i+batch_size]
+ batch_parameters = [param[i:i+batch_size] for param in parameters[1:]]
+ batch_images = cryo_em_simulator(
+ self._models,
+ batch_indices,
+ *batch_parameters,
+ self._num_pixels,
+ self._pixel_size,
+ )
+ images.append(batch_images.cpu())
+
+ images = torch.cat(images, dim=0)
+
+ if return_parameters:
+ return images.cpu(), parameters
+ else:
+ return images.cpu()
\ No newline at end of file
diff --git a/src/cryo_sbi/wpa_simulator/ctf.py b/src/cryo_sbi/wpa_simulator/ctf.py
new file mode 100644
index 0000000..9717e67
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/ctf.py
@@ -0,0 +1,41 @@
+import numpy as np
+import torch
+
+
+def apply_ctf(image: torch.Tensor, defocus, b_factor, amp, pixel_size) -> torch.Tensor:
+ """
+ Applies the CTF to the image.
+
+ Args:
+ image (torch.Tensor): The image to apply the CTF to.
+ defocus (torch.Tensor): The defocus value.
+ b_factor (torch.Tensor): The B-factor value.
+ amp (torch.Tensor): The amplitude value.
+ pixel_size (torch.Tensor): The pixel size value.
+
+ Returns:
+ torch.Tensor: The image with the CTF applied.
+ """
+
+ num_batch, num_pixels, _ = image.shape
+ freq_pix_1d = torch.fft.fftfreq(num_pixels, d=pixel_size, device=image.device)
+ x, y = torch.meshgrid(freq_pix_1d, freq_pix_1d, indexing="ij")
+
+ freq2_2d = x ** 2 + y ** 2
+ freq2_2d = freq2_2d.expand(num_batch, -1, -1)
+ imag = torch.zeros_like(freq2_2d, device=image.device) * 1j
+
+ env = torch.exp(-b_factor * freq2_2d * 0.5)
+ phase = defocus * torch.pi * 2.0 * 10000 * 0.019866 # hardcoded 0.019866 for 300kV
+
+ ctf = (
+ -amp * torch.cos(phase * freq2_2d * 0.5)
+ - torch.sqrt(1 - amp ** 2) * torch.sin(phase * freq2_2d * 0.5)
+ + imag
+ )
+ ctf = ctf * env / amp
+
+ conv_image_ctf = torch.fft.fft2(image) * ctf
+ image_ctf = torch.fft.ifft2(conv_image_ctf).real
+
+ return image_ctf
diff --git a/src/cryo_sbi/wpa_simulator/image_generation.py b/src/cryo_sbi/wpa_simulator/image_generation.py
new file mode 100644
index 0000000..c4f46ec
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/image_generation.py
@@ -0,0 +1,152 @@
+import numpy as np
+import torch
+
+
+def gen_quat() -> torch.Tensor:
+ """
+ Generate a random quaternion.
+
+ Returns:
+ quat (np.ndarray): Random quaternion
+
+ """
+ count = 0
+ while count < 1:
+ quat = 2 * torch.rand(size=(4,)) - 1
+ norm = torch.sqrt(torch.sum(quat ** 2))
+ if 0.2 <= norm <= 1.0:
+ quat /= norm
+ count += 1
+
+ return quat
+
+
+def gen_rot_matrix(quats: torch.Tensor) -> torch.Tensor:
+ # TODO add docstring explaining the quaternion convention qr, qx, qy, qz
+ """
+ Generate a rotation matrix from a quaternion.
+
+ Args:
+ quat (torch.Tensor): Quaternion (n_batch, 4)
+
+ Returns:
+ rot_matrix (torch.Tensor): Rotation matrix
+ """
+
+ rot_matrix = torch.zeros((quats.shape[0], 3, 3), device=quats.device)
+
+ rot_matrix[:, 0, 0] = 1 - 2 * (quats[:, 2] ** 2 + quats[:, 3] ** 2)
+ rot_matrix[:, 0, 1] = 2 * (quats[:, 1] * quats[:, 2] - quats[:, 3] * quats[:, 0])
+ rot_matrix[:, 0, 2] = 2 * (quats[:, 1] * quats[:, 3] + quats[:, 2] * quats[:, 0])
+
+ rot_matrix[:, 1, 0] = 2 * (quats[:, 1] * quats[:, 2] + quats[:, 3] * quats[:, 0])
+ rot_matrix[:, 1, 1] = 1 - 2 * (quats[:, 1] ** 2 + quats[:, 3] ** 2)
+ rot_matrix[:, 1, 2] = 2 * (quats[:, 2] * quats[:, 3] - quats[:, 1] * quats[:, 0])
+
+ rot_matrix[:, 2, 0] = 2 * (quats[:, 1] * quats[:, 3] - quats[:, 2] * quats[:, 0])
+ rot_matrix[:, 2, 1] = 2 * (quats[:, 2] * quats[:, 3] + quats[:, 1] * quats[:, 0])
+ rot_matrix[:, 2, 2] = 1 - 2 * (quats[:, 1] ** 2 + quats[:, 2] ** 2)
+
+ return rot_matrix
+
+
+def project_density(
+ coords: torch.Tensor,
+ quats: torch.Tensor,
+ sigma: torch.Tensor,
+ shift: torch.Tensor,
+ num_pixels: int,
+ pixel_size: float,
+) -> torch.Tensor:
+ """
+ Generate a 2D projections from a set of coordinates.
+
+ Args:
+ coords (torch.Tensor): Coordinates of the atoms in the images
+ sigma (float): Standard deviation of the Gaussian function used to model electron density.
+ num_pixels (int): Number of pixels along one image size.
+ pixel_size (float): Pixel size in Angstrom
+
+ Returns:
+ image (torch.Tensor): Images generated from the coordinates
+ """
+
+ num_batch, _, num_atoms = coords.shape
+ norm = 1 / (2 * torch.pi * sigma**2 * num_atoms)
+
+ grid_min = -pixel_size * num_pixels * 0.5
+ grid_max = pixel_size * num_pixels * 0.5
+
+ rot_matrix = gen_rot_matrix(quats)
+ grid = torch.arange(grid_min, grid_max, pixel_size, device=coords.device)[0:num_pixels.long()].repeat(
+ num_batch, 1
+ ) # [0: num_pixels.long()] is needed due to single precision error in some cases
+
+ coords_rot = torch.bmm(rot_matrix, coords)
+ coords_rot[:, :2, :] += shift.unsqueeze(-1)
+
+ gauss_x = torch.exp_(
+ -0.5 * (((grid.unsqueeze(-1) - coords_rot[:, 0, :].unsqueeze(1)) / sigma) ** 2)
+ )
+ gauss_y = torch.exp_(
+ -0.5 * (((grid.unsqueeze(-1) - coords_rot[:, 1, :].unsqueeze(1)) / sigma) ** 2)
+ ).transpose(1, 2)
+
+ image = torch.bmm(gauss_x, gauss_y) * norm.reshape(-1, 1, 1)
+
+ return image
+
+
+'''def project_density(
+ atomic_model: torch.Tensor,
+ quats: torch.Tensor,
+ delta_sigma: torch.Tensor,
+ shift: torch.Tensor,
+ num_pixels: int,
+ pixel_size: float,
+) -> torch.Tensor:
+ """
+ Generate a 2D projections from a set of coordinates.
+
+ Args:
+ atomic_model (torch.Tensor): Coordinates of the atoms in the images
+ res (float): resolution of the images in Angstrom
+ num_pixels (int): Number of pixels along one image size.
+ pixel_size (float): Pixel size in Angstrom
+
+ Returns:
+ image (torch.Tensor): Images generated from the coordinates
+ """
+
+ num_batch, _, num_atoms = atomic_model.shape
+
+ variances = atomic_model[:, 4, :] * delta_sigma[:, 0]
+ amplitudes = atomic_model[:, 3, :] / torch.sqrt((2 * torch.pi * variances))
+
+ grid_min = -pixel_size * num_pixels * 0.5
+ grid_max = pixel_size * num_pixels * 0.5
+
+ rot_matrix = gen_rot_matrix(quats)
+ grid = torch.arange(grid_min, grid_max, pixel_size, device=atomic_model.device)[
+ 0 : num_pixels.long()
+ ].repeat(
+ num_batch, 1
+ ) # [0: num_pixels.long()] is needed due to single precision error in some cases
+
+ coords_rot = torch.bmm(rot_matrix, atomic_model[:, :3, :])
+ coords_rot[:, :2, :] += shift.unsqueeze(-1)
+
+ gauss_x = torch.exp_(
+ -((grid.unsqueeze(-1) - coords_rot[:, 0, :].unsqueeze(1)) ** 2)
+ / variances.unsqueeze(1)
+ ) * amplitudes.unsqueeze(1)
+
+ gauss_y = torch.exp(
+ -((grid.unsqueeze(-1) - coords_rot[:, 1, :].unsqueeze(1)) ** 2)
+ / variances.unsqueeze(1)
+ ) * amplitudes.unsqueeze(1)
+
+ image = torch.bmm(gauss_x, gauss_y.transpose(1, 2)) # * norms
+ image /= torch.norm(image, dim=[-2, -1]).reshape(-1, 1, 1) # do we need this normalization?
+
+ return image'''
diff --git a/src/cryo_sbi/wpa_simulator/noise.py b/src/cryo_sbi/wpa_simulator/noise.py
new file mode 100644
index 0000000..1a8539c
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/noise.py
@@ -0,0 +1,66 @@
+from typing import Union
+import numpy as np
+import torch
+
+
+def circular_mask(n_pixels: int, radius: int, device: str = "cpu") -> torch.Tensor:
+ """
+ Creates a circular mask of radius RADIUS_MASK centered in the image
+
+ Args:
+ n_pixels (int): Number of pixels along image side.
+ radius (int): Radius of the mask.
+
+ Returns:
+ mask (torch.Tensor): Mask of shape (n_pixels, n_pixels).
+ """
+
+ grid = torch.linspace(
+ -0.5 * (n_pixels - 1), 0.5 * (n_pixels - 1), n_pixels, device=device
+ )
+ r_2d = grid[None, :] ** 2 + grid[:, None] ** 2
+ mask = r_2d < radius ** 2
+
+ return mask
+
+
+def get_snr(images, snr):
+ """
+ Computes the SNR of the images
+ """
+ mask = circular_mask(
+ n_pixels=images.shape[-1],
+ radius=images.shape[-1] // 2, # TODO: make this a parameter
+ device=images.device,
+ )
+ signal_power = torch.std(
+ images[:, mask], dim=[-2, -1]
+ ) # images are not centered at 0, so std is not the same as power
+ noise_power = signal_power / torch.sqrt(torch.pow(10, snr))
+
+ return noise_power
+
+
+def add_noise(image: torch.Tensor, snr, seed=None) -> torch.Tensor:
+ """
+ Adds noise to image.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels).
+ image_params (dict): Dictionary with image parameters.
+ seed (int, optional): Seed for random number generator. Defaults to None.
+
+ Returns:
+ image_noise (torch.Tensor): Image with noise of shape (n_pixels, n_pixels) or (n_channels, n_pixels, n_pixels).
+ """
+
+ if seed is not None:
+ torch.manual_seed(seed) #
+
+ noise_power = get_snr(image, snr)
+ noise = torch.randn_like(image, device=image.device)
+ noise = noise * noise_power.reshape(-1, 1, 1)
+
+ image_noise = image + noise
+
+ return image_noise
diff --git a/src/cryo_sbi/wpa_simulator/normalization.py b/src/cryo_sbi/wpa_simulator/normalization.py
new file mode 100644
index 0000000..220efe8
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/normalization.py
@@ -0,0 +1,19 @@
+import torch
+import torchvision.transforms as transforms
+
+
+def gaussian_normalize_image(images: torch.Tensor) -> torch.Tensor:
+ """
+ Normalize an images by subtracting the mean and dividing by the standard deviation.
+
+ Args:
+ image (torch.Tensor): Image of shape (n_pixels, n_pixels) or (n_channels, n_pixels, n_pixels).
+
+ Returns:
+ normalized (torch.Tensor): Normalized image.
+ """
+
+ mean = images.mean(dim=[1, 2])
+ std = images.std(dim=[1, 2])
+
+ return transforms.functional.normalize(images, mean=mean, std=std)
diff --git a/src/cryo_sbi/wpa_simulator/validate_image_config.py b/src/cryo_sbi/wpa_simulator/validate_image_config.py
new file mode 100644
index 0000000..8f25dbb
--- /dev/null
+++ b/src/cryo_sbi/wpa_simulator/validate_image_config.py
@@ -0,0 +1,27 @@
+def check_image_params(config: dict) -> None:
+ """
+ Checks if all necessary parameters are provided.
+
+ Args:
+ config (dict): Dictionary containing image parameters.
+
+ Returns:
+ None
+ """
+
+ needed_keys = [
+ "N_PIXELS",
+ "PIXEL_SIZE",
+ "SIGMA",
+ "SHIFT",
+ "DEFOCUS",
+ "SNR",
+ "MODEL_FILE",
+ "AMP",
+ "B_FACTOR",
+ ]
+
+ for key in needed_keys:
+ assert key in config.keys(), f"Please provide a value for {key}"
+
+ return None
diff --git a/tests/config_files/image_params_testing.json b/tests/config_files/image_params_testing.json
new file mode 100644
index 0000000..90832ef
--- /dev/null
+++ b/tests/config_files/image_params_testing.json
@@ -0,0 +1,11 @@
+{
+ "N_PIXELS": 128,
+ "PIXEL_SIZE": 2.06,
+ "SIGMA": [0.5, 5.0],
+ "MODEL_FILE": "../models/hemagglutinin_models.pt",
+ "SHIFT": 20.0,
+ "DEFOCUS": [1.5, 3.5],
+ "SNR": [0.05, 0.05],
+ "AMP": 0.1,
+ "B_FACTOR": [1.0, 100.0]
+}
diff --git a/tests/config_files/training_params_npe_testing.json b/tests/config_files/training_params_npe_testing.json
new file mode 100644
index 0000000..130349b
--- /dev/null
+++ b/tests/config_files/training_params_npe_testing.json
@@ -0,0 +1,13 @@
+{
+ "EMBEDDING": "RESNET18",
+ "OUT_DIM": 256,
+ "NUM_TRANSFORM": 5,
+ "NUM_HIDDEN_FLOW": 10,
+ "HIDDEN_DIM_FLOW": 256,
+ "MODEL": "NSF",
+ "LEARNING_RATE": 0.0003,
+ "CLIP_GRADIENT": 5.0,
+ "THETA_SHIFT": 25,
+ "THETA_SCALE": 25,
+ "BATCH_SIZE": 256
+}
diff --git a/tests/data/test.mrc b/tests/data/test.mrc
new file mode 100644
index 0000000..aa0bf21
Binary files /dev/null and b/tests/data/test.mrc differ
diff --git a/tests/models/hsp90_models.pt b/tests/models/hsp90_models.pt
new file mode 100644
index 0000000..1cce5ce
Binary files /dev/null and b/tests/models/hsp90_models.pt differ
diff --git a/tests/test_embeddings.py b/tests/test_embeddings.py
new file mode 100644
index 0000000..719386d
--- /dev/null
+++ b/tests/test_embeddings.py
@@ -0,0 +1,18 @@
+import pytest
+import torch
+from itertools import product
+
+from cryo_sbi.inference.models.embedding_nets import EMBEDDING_NETS
+
+embedding_networks = list(EMBEDDING_NETS.keys())
+num_images_to_test = [1, 5]
+out_dims_to_test = [10, 100]
+cases_to_test = list(product(embedding_networks, num_images_to_test, out_dims_to_test))
+
+
+@pytest.mark.parametrize(("embedding_name", "num_images", "out_dim"), cases_to_test)
+def test_embedding(embedding_name, num_images, out_dim):
+ test_images = torch.randn(num_images, 128, 128)
+ embedding = EMBEDDING_NETS[embedding_name](out_dim)
+ out = embedding(test_images).shape
+ assert out == torch.Size([num_images, out_dim]), embedding_name
diff --git a/tests/test_estimator_utils.py b/tests/test_estimator_utils.py
new file mode 100644
index 0000000..6cbb2f7
--- /dev/null
+++ b/tests/test_estimator_utils.py
@@ -0,0 +1,85 @@
+import pytest
+import os
+import torch
+import numpy as np
+import json
+
+from cryo_sbi.inference.models import build_models
+from cryo_sbi.inference.models.estimator_models import NPEWithEmbedding
+from cryo_sbi.inference.validate_train_config import check_train_params
+from cryo_sbi.utils.estimator_utils import (
+ sample_posterior,
+ compute_latent_repr,
+ evaluate_log_prob,
+ load_estimator
+)
+
+
+@pytest.fixture
+def train_params():
+ config = json.load(open("tests/config_files/training_params_npe_testing.json"))
+ check_train_params(config)
+ return config
+
+
+@pytest.fixture
+def train_config_path():
+ return "tests/config_files/training_params_npe_testing.json"
+
+
+@pytest.mark.parametrize(
+ ("num_images", "num_samples", "batch_size"),
+ [(1, 1, 1), (2, 10, 2), (5, 1000, 5), (100, 2, 100)],
+)
+def test_sampling(train_params, num_images, num_samples, batch_size):
+ estimator = build_models.build_npe_flow_model(train_params)
+ estimator.eval()
+ images = torch.randn((num_images, 128, 128))
+ samples = sample_posterior(
+ estimator, images, num_samples=num_samples, batch_size=batch_size
+ )
+ assert samples.shape == torch.Size(
+ [num_samples, num_images]
+ ), f"Failed with: num_images: {num_images}, num_samles:{num_samples}, batch_size:{batch_size}"
+
+
+@pytest.mark.parametrize(
+ ("num_images", "batch_size"), [(1, 1), (2, 2), (1, 5), (100, 10)]
+)
+def test_latent_extraction(train_params, num_images, batch_size):
+ estimator = build_models.build_npe_flow_model(train_params)
+ estimator.eval()
+
+ latent_dim = train_params["OUT_DIM"]
+ images = torch.randn((num_images, 128, 128))
+ samples = compute_latent_repr(estimator, images, batch_size=batch_size)
+ assert samples.shape == torch.Size(
+ [num_images, latent_dim]
+ ), f"Failed with: num_images: {num_images}, batch_size:{batch_size}"
+
+
+@pytest.mark.parametrize(
+ ("num_images", "num_eval", "batch_size"),
+ [(1, 1, 1), (2, 10, 2), (5, 1000, 5), (100, 2, 100)],
+)
+def test_logprob_eval(train_params, num_images, num_eval, batch_size):
+ estimator = build_models.build_npe_flow_model(train_params)
+ estimator.eval()
+ images = torch.randn((num_images, 128, 128))
+ theta = torch.linspace(0, 25, num_eval)
+ samples = evaluate_log_prob(
+ estimator, images, theta, batch_size=batch_size
+ )
+ assert samples.shape == torch.Size(
+ [num_eval, num_images]
+ ), f"Failed with: num_images: {num_images}, num_eval:{num_eval}, batch_size:{batch_size}"
+
+
+def test_load_estimator(train_params, train_config_path):
+ estimator = build_models.build_npe_flow_model(train_params)
+ torch.save(estimator.state_dict(), "tests/config_files/test_estimator.estimator")
+ estimator = load_estimator(
+ train_config_path, "tests/config_files/test_estimator.estimator"
+ )
+ assert isinstance(estimator, NPEWithEmbedding)
+ os.remove("tests/config_files/test_estimator.estimator")
diff --git a/tests/test_image_utils.py b/tests/test_image_utils.py
new file mode 100644
index 0000000..ddea493
--- /dev/null
+++ b/tests/test_image_utils.py
@@ -0,0 +1,98 @@
+import pytest
+import torch
+from cryo_sbi.utils import image_utils as iu
+
+
+def test_circular_mask():
+ n_pixels = 100
+ radius = 30
+ inside_mask = iu.circular_mask(n_pixels, radius, inside=True)
+ outside_mask = iu.circular_mask(n_pixels, radius, inside=False)
+
+ assert inside_mask.shape == (n_pixels, n_pixels)
+ assert outside_mask.shape == (n_pixels, n_pixels)
+ assert inside_mask.sum().item() == pytest.approx(radius ** 2 * 3.14159, abs=10)
+ assert outside_mask.sum().item() == pytest.approx(
+ n_pixels ** 2 - radius ** 2 * 3.14159, abs=10
+ )
+
+
+def test_mask_class():
+ image_size = 100
+ radius = 30
+ inside = True
+ mask = iu.Mask(image_size, radius, inside=inside)
+ image = torch.ones((image_size, image_size))
+
+ masked_image = mask(image)
+ assert masked_image.shape == (image_size, image_size)
+ assert masked_image[inside].sum().item() == pytest.approx(
+ image_size ** 2 - radius ** 2 * 3.14159, abs=10
+ )
+
+
+def test_fourier_down_sample():
+ image_size = 100
+ n_pixels = 30
+ image = torch.ones((image_size, image_size))
+
+ downsampled_image = iu.fourier_down_sample(image, image_size, n_pixels)
+ assert downsampled_image.shape == (
+ image_size - 2 * n_pixels,
+ image_size - 2 * n_pixels,
+ )
+
+
+def test_fourier_down_sample_class():
+ image_size = 100
+ down_sampled_size = 40
+ down_sampler = iu.FourierDownSample(image_size, down_sampled_size)
+ image = torch.ones((image_size, image_size))
+
+ down_sampled_image = down_sampler(image)
+ assert down_sampled_image.shape == (
+ image_size - 2 * down_sampler._n_pixels,
+ image_size - 2 * down_sampler._n_pixels,
+ )
+
+
+def test_low_pass_filter():
+ image_size = 100
+ frequency_cutoff = 30
+ low_pass_filter = iu.LowPassFilter(image_size, frequency_cutoff)
+ image = torch.ones((image_size, image_size))
+
+ filtered_image = low_pass_filter(image)
+ assert filtered_image.shape == (image_size, image_size)
+
+
+def test_normalize_individual():
+ normalize_individual = iu.NormalizeIndividual()
+ image = torch.randn((3, 100, 100))
+
+ normalized_image = normalize_individual(image)
+ assert normalized_image.shape == (3, 100, 100)
+ assert normalized_image.mean().item() == pytest.approx(0.0, abs=1e-1)
+ assert normalized_image.std().item() == pytest.approx(1.0, abs=1e-1)
+
+
+def test_mrc_to_tensor():
+ image_path = "tests/data/test.mrc"
+ image = iu.mrc_to_tensor(image_path)
+
+ assert isinstance(image, torch.Tensor)
+ assert image.shape == (5, 5)
+
+
+def test_image_whithening():
+ whitening_transform = iu.WhitenImage(torch.randn((100, 100)))
+ images = torch.randn((100, 100))
+ images_whitened = whitening_transform(images)
+ assert images_whitened.shape == (100, 100)
+
+
+def test_image_whithening_batched():
+ whitening_transform = iu.WhitenImage(torch.randn((100, 100)))
+ images = torch.randn((10, 100, 100))
+ images_whitened = whitening_transform(images)
+ assert images_whitened.shape == (10, 100, 100)
diff --git a/tests/test_micrograph_utils.py b/tests/test_micrograph_utils.py
new file mode 100644
index 0000000..413a7ac
--- /dev/null
+++ b/tests/test_micrograph_utils.py
@@ -0,0 +1,40 @@
+import pytest
+import torch
+import torchvision.transforms as transforms
+from cryo_sbi.utils.image_utils import NormalizeIndividual
+from cryo_sbi.utils import micrograph_utils as mu
+
+
+def test_random_micrograph_patches_fail():
+ micrograph = torch.randn(2, 128, 128)
+ random_patches = mu.RandomMicrographPatches(
+ micro_graphs=[micrograph], patch_size=10, transform=None
+ )
+ with pytest.raises(AssertionError):
+ patch = next(random_patches)
+
+
+@pytest.mark.parametrize(
+ ("micrograph_size", "patch_size", "max_iter"), [(128, 12, 100), (128, 90, 1000)]
+)
+def test_random_micrograph_patches(micrograph_size, patch_size, max_iter):
+ micrograph = torch.randn(micrograph_size, micrograph_size)
+ random_patches = mu.RandomMicrographPatches(
+ micro_graphs=[micrograph],
+ patch_size=patch_size,
+ transform=None,
+ max_iter=max_iter,
+ )
+ patch = next(random_patches)
+ assert patch.shape == torch.Size([1, patch_size, patch_size])
+ assert len(random_patches) == max_iter
+
+
+def test_compute_average_psd():
+ micrograph = torch.randn(128, 128)
+ transform = transforms.Compose([NormalizeIndividual()])
+ random_patches = mu.RandomMicrographPatches(
+ micro_graphs=[micrograph], patch_size=10, transform=transform, max_iter=100
+ )
+ avg_psd = mu.compute_average_psd(random_patches)
+ assert avg_psd.shape == torch.Size([10, 10])
diff --git a/tests/test_posterior_models.py b/tests/test_posterior_models.py
new file mode 100644
index 0000000..37c4a4d
--- /dev/null
+++ b/tests/test_posterior_models.py
@@ -0,0 +1,28 @@
+import pytest
+import json
+import torch
+from cryo_sbi.inference.models import build_models
+from cryo_sbi.inference.models import estimator_models
+from cryo_sbi.inference.validate_train_config import check_train_params
+
+
+@pytest.fixture
+def train_params():
+ config = json.load(open("tests/config_files/training_params_npe_testing.json"))
+ check_train_params(config)
+ return config
+
+
+def test_build_npe_model(train_params):
+ posterior_model = build_models.build_npe_flow_model(train_params)
+ assert isinstance(posterior_model, estimator_models.NPEWithEmbedding)
+
+
+@pytest.mark.parametrize(
+ ("batch_size", "sample_size"), [(1, 1), (2, 10), (5, 1000), (100, 2)]
+)
+def test_sample_npe_model(train_params, batch_size, sample_size):
+ posterior_model = build_models.build_npe_flow_model(train_params)
+ test_image = torch.randn((batch_size, 128, 128))
+ samples = posterior_model.sample(test_image, shape=(sample_size,))
+ assert samples.shape == torch.Size([sample_size, batch_size, 1])
diff --git a/tests/test_simulator.py b/tests/test_simulator.py
new file mode 100644
index 0000000..a6f3195
--- /dev/null
+++ b/tests/test_simulator.py
@@ -0,0 +1,57 @@
+import pytest
+import torch
+import numpy as np
+import json
+
+from cryo_sbi.wpa_simulator.cryo_em_simulator import cryo_em_simulator
+from cryo_sbi.wpa_simulator.ctf import apply_ctf
+from cryo_sbi.wpa_simulator.image_generation import project_density, gen_quat, gen_rot_matrix
+from cryo_sbi.wpa_simulator.noise import add_noise, circular_mask, get_snr
+from cryo_sbi.wpa_simulator.normalization import gaussian_normalize_image
+from cryo_sbi.inference.priors import get_image_priors
+
+
+def test_apply_ctf():
+ # Create a test image
+ image = torch.randn(1, 64, 64)
+
+ # Set test parameters
+ defocus = torch.tensor([1.0])
+ b_factor = torch.tensor([100.0])
+ amp = torch.tensor([0.5])
+ pixel_size = torch.tensor(1.0)
+
+ # Apply CTF to the test image
+ image_ctf = apply_ctf(image, defocus, b_factor, amp, pixel_size)
+
+ assert image_ctf.shape == image.shape
+ assert isinstance(image_ctf, torch.Tensor)
+ assert not torch.allclose(image_ctf, image)
+
+
+def test_gen_rot_matrix():
+ # Create a test quaternion
+ quat = torch.tensor([[1.0, 0.0, 0.0, 0.0]])
+
+ # Generate a rotation matrix from the quaternion
+ rot_matrix = gen_rot_matrix(quat)
+
+ assert rot_matrix.shape == torch.Size([1, 3, 3])
+ assert isinstance(rot_matrix, torch.Tensor)
+ assert torch.allclose(rot_matrix, torch.eye(3).unsqueeze(0))
+
+
+def test_gen_rot_matrix_batched():
+ # Create a test quaternions with batche size 3
+ quat = torch.tensor([
+ [1.0, 0.0, 0.0, 0.0],
+ [1.0, 0.0, 0.0, 0.0],
+ [1.0, 0.0, 0.0, 0.0]
+ ])
+
+ # Generate a rotation matrix from the quaternion
+ rot_matrix = gen_rot_matrix(quat)
+
+ assert rot_matrix.shape == torch.Size([3, 3, 3])
+ assert isinstance(rot_matrix, torch.Tensor)
+ assert torch.allclose(rot_matrix, torch.eye(3).repeat(3, 1, 1))
\ No newline at end of file
diff --git a/tests/vis_image_gen.ipynb b/tests/vis_image_gen.ipynb
deleted file mode 100644
index b138e74..0000000
--- a/tests/vis_image_gen.ipynb
+++ /dev/null
@@ -1,456 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import torch\n",
- "import cryo_em_sbi\n",
- "import matplotlib.pyplot as plt"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 117,
- "metadata": {},
- "outputs": [],
- "source": [
- "model = torch.tensor(np.load(\"../models/hsp90_models.npy\")[0, 0])\n",
- "\n",
- "config = {\n",
- " \"IMAGES\": {\"N_PIXELS\": 128, \"PIXEL_SIZE\": 1.0, \"SIGMA\": 2.0},\n",
- " \"SIMULATION\": {\n",
- " \"N_SIMULATIONS\": 100,\n",
- " \"MODEL_FILE\": \"../../models/hsp90_models.npy\",\n",
- " \"DEVICE\": \"cpu\",\n",
- " \"ROTATIONS\": \"QUAT_576\",\n",
- " },\n",
- " \"PREPROCESSING\": {\n",
- " \"SHIFT\": True,\n",
- " \"CTF\": True,\n",
- " \"NOISE\": True,\n",
- " \"DEFOCUS\": 1.5,\n",
- " \"SNR\": 0.1,\n",
- " },\n",
- " \"TRAINING\": {\n",
- " \"MODEL\": \"maf\",\n",
- " \"HIDDEN_FEATURES\": 100,\n",
- " \"NUM_TRANSFORMS\": 4,\n",
- " \"DEVICE\": \"cpu\",\n",
- " \"BATCH_SIZE\": 1000,\n",
- " \"POSTERIOR_NAME\": \"posterior_all_effects_noise_01.pkl\",\n",
- " },\n",
- "}"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {},
- "outputs": [],
- "source": [
- "def gen_img(coord, image_params, dtype):\n",
- "\n",
- " n_atoms = coord.shape[1]\n",
- " norm = 1 / (2 * torch.pi * image_params[\"SIGMA\"] ** 2 * n_atoms)\n",
- "\n",
- " grid_min = -image_params[\"PIXEL_SIZE\"] * (image_params[\"N_PIXELS\"] - 1) * 0.5\n",
- " grid_max = (\n",
- " image_params[\"PIXEL_SIZE\"] * (image_params[\"N_PIXELS\"] - 1) * 0.5\n",
- " + image_params[\"PIXEL_SIZE\"]\n",
- " )\n",
- "\n",
- " grid = torch.arange(grid_min, grid_max, image_params[\"PIXEL_SIZE\"], dtype=dtype)\n",
- " gauss_x = torch.zeros((image_params[\"N_PIXELS\"], n_atoms), dtype=dtype)\n",
- " gauss_y = torch.zeros((image_params[\"N_PIXELS\"], n_atoms), dtype=dtype)\n",
- "\n",
- " gauss_x[:, :] = torch.exp(\n",
- " -0.5 * (((grid[:, None] - coord[0, :]) / image_params[\"SIGMA\"]) ** 2)\n",
- " )\n",
- "\n",
- " gauss_y[:, :] = torch.exp(\n",
- " -0.5 * (((grid[:, None] - coord[1, :]) / image_params[\"SIGMA\"]) ** 2)\n",
- " )\n",
- "\n",
- " image = torch.matmul(gauss_x, gauss_y.T) * norm\n",
- "\n",
- " return image"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 80,
- "metadata": {},
- "outputs": [],
- "source": [
- "def apply_ctf(image, image_params, preproc_params):\n",
- " def calc_ctf(n_pixels, amp, phase, b_factor):\n",
- "\n",
- " ctf = torch.zeros((n_pixels, n_pixels), dtype=torch.complex64)\n",
- "\n",
- " freq_pix_1d = torch.fft.fftfreq(n_pixels, d=image_params[\"PIXEL_SIZE\"])\n",
- "\n",
- " x, y = torch.meshgrid(freq_pix_1d, freq_pix_1d)\n",
- "\n",
- " freq2_2d = x**2 + y**2\n",
- " imag = torch.zeros_like(freq2_2d) * 1j\n",
- "\n",
- " env = torch.exp(-b_factor * freq2_2d * 0.5)\n",
- " ctf = (\n",
- " amp * torch.cos(phase * freq2_2d * 0.5)\n",
- " - np.sqrt(1 - amp**2) * torch.sin(phase * freq2_2d * 0.5)\n",
- " + imag\n",
- " )\n",
- "\n",
- " return ctf * env / amp\n",
- "\n",
- " b_factor = 0.0 # no\n",
- " amp = 0.1 # no\n",
- "\n",
- " elecwavel = 0.019866\n",
- " phase = preproc_params[\"DEFOCUS\"] * torch.pi * 2.0 * 10000 * elecwavel\n",
- "\n",
- " ctf = calc_ctf(image.shape[0], amp, phase, b_factor)\n",
- "\n",
- " conv_image_ctf = torch.fft.fft2(image) * ctf\n",
- "\n",
- " image_ctf = torch.fft.ifft2(conv_image_ctf).real\n",
- "\n",
- " return image_ctf"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 134,
- "metadata": {},
- "outputs": [],
- "source": [
- "def add_noise(img, preproc_params):\n",
- "\n",
- " mean_image = torch.mean(img)\n",
- " std_image = torch.std(img)\n",
- "\n",
- " mask = torch.logical_or(\n",
- " img >= mean_image + 0.5 * std_image, img <= mean_image - 0.5 * std_image\n",
- " )\n",
- "\n",
- " signal_std = torch.std(img[mask])\n",
- "\n",
- " noise_mean = torch.mean(img[mask])\n",
- " noise_std = signal_std / np.sqrt(preproc_params[\"SNR\"])\n",
- "\n",
- " print(\"Old Method: \", noise_std)\n",
- "\n",
- " noise = torch.normal(mean=noise_mean, std=noise_std, size=img.shape)\n",
- "\n",
- " img_noise = img + noise\n",
- "\n",
- " return img_noise"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 140,
- "metadata": {},
- "outputs": [],
- "source": [
- "def circular_mask(n_pixels, radius):\n",
- "\n",
- " grid = torch.linspace(-0.5 * (n_pixels - 1), 0.5 * (n_pixels - 1), n_pixels)\n",
- " r_2d = grid[None, :] ** 2 + grid[:, None] ** 2\n",
- " mask = r_2d < radius**2\n",
- "\n",
- " return mask\n",
- "\n",
- "\n",
- "def add_noise_torch_batch(img, snr):\n",
- "\n",
- " n_pixels = img.shape[1]\n",
- " radius = n_pixels * 0.4\n",
- " mask = circular_mask(n_pixels, radius)\n",
- " image_noise = torch.empty_like(img, device=\"cpu\")\n",
- "\n",
- " for i, image in enumerate(img):\n",
- "\n",
- " image_masked = image[mask]\n",
- " signal_std = image_masked.pow(2).mean().sqrt()\n",
- " noise_std = signal_std / np.sqrt(snr)\n",
- " noise = torch.distributions.normal.Normal(0, noise_std).sample(image.shape)\n",
- " image_noise[i] = image + noise\n",
- "\n",
- " return image_noise"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 165,
- "metadata": {},
- "outputs": [],
- "source": [
- "def add_noise_new(img, preproc_params, radius_coef):\n",
- "\n",
- " mask = circular_mask(n_pixels=img.shape[0], radius=img.shape[0] * radius_coef)\n",
- "\n",
- " signal_std = img[mask].pow(2).mean().sqrt()\n",
- " noise_std = signal_std / np.sqrt(preproc_params[\"SNR\"])\n",
- "\n",
- " img_noise = img + torch.distributions.normal.Normal(0, noise_std).sample(img.shape)\n",
- "\n",
- " print(\"New Method: \", noise_std)\n",
- " # return noise_std\n",
- " return img_noise"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 152,
- "metadata": {},
- "outputs": [],
- "source": [
- "rad = np.linspace(0.1, 0.9, 100)\n",
- "noises = np.zeros_like(rad)\n",
- "\n",
- "for i in range(rad.shape[0]):\n",
- "\n",
- " noises[i] = add_noise_new(ctf_img_db, config[\"PREPROCESSING\"], rad[i])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 153,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 153,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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bAERkEbASGCEipSIyx2nrESAOeENE1ovIE621FQqKy44TExnGwL4xXofSZteNT6P8eB3vfXLI61CMMR5ztXScqr4CvNKs7Gd+2zXAjac49h7gnhbKZ52i/vDTxNFiW6Gg+NBxMhJjg3rOqVO5fEQKCb0j+etHe7h8ZIrX4RhjPBS0A+HdTfGh4wxLDq2uqSZREWFcOzaV1wv2c7TmpNfhGGM8ZEkjAE42NLKrojrkxjP8TR+fTm19I69+vN/rUIwxHrKkEQCllSeob1Qyk0Lrdlt/5wxJICOxN3/9qNTrUIwxHrKkEQDFzu22oXylISJcNz6NVUUV7Dl8wutwjDEesaQRAEVlvtttQ+0Zjeamj/c9gP/SRyHzeIwxppNZ0giA4kPHSegdSb/YKK9D6ZChibGcO7Qff/toj00rYkwPZUkjAEJtzqnTmT4+jcKDxyjYW+V1KMYYD1jSCICisu6TNK4dm0pkuPA366IypkeypNHFjtfWs7+qJuTHM5ok9I7i8hEp5G3YS71NK2JMj2NJo4uVlDfNORW6t9s2N318GmVHa/lgR7nXoRhjAsySRhcL1YkKT+fykSnExURYF5UxPZAljS5W7Nxum5HU2+NIOk9MZDjXjEnltU37OV5b3/oBxphuw5JGFys+dJzU+Bh6R7maGzJkTB+fxomTDbyx+YDXoRhjAsiSRhfbvK+K4SndZzyjyYSM/qQl9LIuKmN6GEsaXehAVQ1b9x/l/DMSvQ6l04WFCbnjBrHikzL2HbFpRYzpKSxpdKF3t5cBcNmZ3XMNipkThqDAs6t2eR2KMSZAXCUNEZkiIttEpFBE5rWwP1pEnnf2rxaRDL99dzrl20TkKr/yp0XkoIhsatbWjSJSICKNIpLjV54hIiec1fw+XdEvmL27vYyUuGjOSo3zOpQuMSSxN5NHDuC5NbuoORkyiygaYzqg1aQhIuHAo8BUIBuYJSLZzarNASqdVfceBO5zjs3Gt6b4KGAK8JjTHsACp6y5TcD1wPIW9u1Q1XHO69bWYvdSfUMjK7aXcemZyYiE3mp9bn3jwgwqjtfx8oa9XodijAkAN1caE4FCVS1S1TpgMZDbrE4usNDZfhGYLL5vylxgsarWqmoxUOi0h6ouByqan0xVt6jqtnZ9miCyofQwVTX1XDoi2etQutQFZyRy5oA+LPigxCYxNKYHcJM00oDdfu9LnbIW66hqPXAESHR5bFtkishHIvKuiFzcUgURmSsi+SKSX1ZW1oFTdcw728oIE7h4ePdOGiLCLRdkUrC3irUllV6HY4zpYqE0EL4PGKKq44E7gOdEpG/zSqr6pKrmqGpOcrJ3X9jvbi9j/JB+xPeO9CyGQJk+Po34XpEs+KDY61CMMV3MTdLYAwz2e5/ulLVYR0QigHig3OWxrjhdXOXO9jpgB3Bme9rqDCfqGvhFXgFvtvBw26FjtWwsPcJlZ3bvq4wmvaLCmTlxMEsLDlBaWe11OMaYLuQmaawFskQkU0Si8A1s5zWrkwfMdrZnAMvU18GdB8x07q7KBLKANe0JVESSmwbRRWSY01ZRe9rqqGO19dzyxzUs+KCEuc/k80L+7n/Zv+ITX7dYdx/P8Df7/AwE+MMKu9owpjtrNWk4YxS3A0uBLcASVS0QkbtFZJpTbT6QKCKF+LqO5jnHFgBLgM3Aa8BtqtoAICKLgJXACBEpFZE5Tvl0ESkFzgf+KSJLnXNcAmwUkfX4BttvVdXPDaR3taqak3x9/mryd1Zy/w1juXB4Ej9+cSNPv1fMyYZGCvYe4a8f7iGpTxSjB8UHOjzPDEroRe64NJ5fu5vK43Veh2OM6SLSne94ycnJ0fz8/E5rr6FRuf7xD9i89wgPzzqHKaMHUlvfwPcXree1gv1ERYRRV+9bY+Lr5w/l7tzRnXbuUPDJgaN84cHl/ODKLH5wpWc9h8aYDhKRdaqa09K+7jWLXhfbvLeKDbsP86vrRjNl9EAAoiPCeeQr43ni3R0cOXGSMekJjE2LZ2hi95nV1q2sAXFceVYKCz8oYe4lw7rdJI3GGEsabbK2xNcbNvmsf50WJCI8jNuvyPIipKBz66VnMOOJlSxZu5tbLsz0OhxjTCcLpVtuPbe2pIL0fr1Ije/ldShBKyejPxMy+vHUCt8YjzGme7Gk4ZKqsrakkgkZ/b0OJej922XD2XP4BL95PeQf7DfGNGNJw6Wd5dUcOlZLTkY/r0MJepePTOHm84bw+3eLbE4qY7oZSxourXHGMybalYYrP//SKHKG9uMnL25k894qr8MxxnQSSxou5ZdUkNA7kjOSu98qfF0hKiKMx756DvG9Ipn7TD6HjtV6HZIxphNY0nApv6SSnKH9CAvrvtOcd7aUuBie+Nq5HDpWy01PrGTPYVvhz5hQZ0nDhbKjtRQdOm6D4O0wbnACz8w5j7Jjtdz4+AcUlR3zOiRjTAdY0nBh3U7feEaOJY12mZDRn8VzJ1Fb38iNT6zk5Q17qbfbcY0JSZY0XFhTXEl0RBhj0nrOXFKdbdSgeF649Xz6x0bxvUUfccX/vsszq3ZytOak16EZY9rAkoYL+TsrGDc4gagI+3F1xLDkPiz9wSU88dVz6RcbxU9f2sQ5v3yDr81fzYL3izl4tMbrEI0xrbBpRFpxvLaegr1VfPfSM7wOpVsICxOmjB7IVaMG8OGuw7xesJ83thzgFy9v5lf/3MIXsgfwlfOGcOEZSXbTgTFByJJGK3aUHaOhURltXVOdSkQ4d2g/zh3ajzuvPovCg8dYkr+bF/J38+qm/Zw9OIF7rx/DWamfW5zRGOMh629pxc5y30p0GUk9b9baQBqe0of/uvosVt45mftnjKW0opovPfweDyzdSs3JBq/DM8Y4XCUNEZkiIttEpFBE5rWwP1pEnnf2rxaRDL99dzrl20TkKr/yp0XkoIhsatbWjSJSICKNIpLTbF+LbXWlXRW+pDGkvyWNQIiJDOemnMG8ecel5I5L49G3d/D1+WuorbfEYUwwaDVpOEusPgpMBbKBWSKS3azaHKBSVYcDDwL3Ocdm41sedhQwBXisaclWYIFT1twm4HpgebM4TtdWl9lZfpzkuGhbGyLA+sVG8b83nc1vvzyONSUV/NdfN9GdFwwzJlS4udKYCBSqapGq1gGLgdxmdXKBhc72i8BkERGnfLGq1qpqMVDotIeqLgc+t1yrqm5R1ZamRz1lW11pZ3m1XWV46Lrxafzgyiz+8mEpj7+7w+twjOnx3CSNNGC33/tSp6zFOs6a4keARJfHuuWqLRGZKyL5IpJfVlbWzlN9ZndFNUMtaXjq+5OzmHb2IO5/bRuvbdrvdTjG9GjdbiBcVZ9U1RxVzUlOTu5QW7X1DeyrqmFID1y6NZiICPfPGMvZgxP48QsbbA4rYzzkJmnsAQb7vU93ylqsIyIRQDxQ7vJYtzqzLVd2V5xAlR653newiYkM55FZ42lU5YdL1tPYaOMbxnjBTdJYC2SJSKaIROEbjM5rVicPmO1szwCWqW/UMg+Y6dxdlQlkAWvaGWtntuXKrorjAAzpH9uVpzEuDe7fm59PG8Wqogrmv1fsdTjG9EitJg1njOJ2YCmwBViiqgUicreITHOqzQcSRaQQuAOY5xxbACwBNgOvAbepagOAiCwCVgIjRKRUROY45dNFpBQ4H/iniCxtra2u0vSMhl1pBI8bz03ni9kDeGDpNrbut8WdjAk06c63Mebk5Gh+fn67j//vlwt4fu1uCv77Knw3g5lgUH6slqt+u4KkPlHk3X6RzQlmTCcTkXWqmtPSPvvfdhq7nNttLWEEl8Q+0dx7/Ri27j/KI28Xeh2OMT2KJY3T2FlRbV1TQerK7AFcPz6Nx94uZNOeI16HY0yPYUnjFBoblV0V1QxNtEHwYPWzL2XTLzaKH72wgbp6W9TJmECwpHEKB47WUFffaE+DB7GE3lH8erqvm+rhZZ94HY4xPYIljVPYVW4TFYaCK7MHcP05aTy8rJDH39lh81MZ08VsFr5T2Flht9uGinuvH0t9g3Lfa1s5dKyWu64+67QLODU0KjvKjlGw9wib91axs7yaswcnMPmsFEYMiLMbH4w5DUsap7CrvJrwMGFQQi+vQzGtiIoI47dfHkf/2Cjmv1fMzvJqbsxJ54IzEomLieRwdR0bSo/w0a5K1u2sZP2uwxytrf/02NT4GF7ffIAHlm4jLaEXv5o+mstHpHj8qYwJTpY0TmFnRTVpCb2IDLcevFAQFib8/EvZDIyP4aG3PuHNLQcIDxMG9o35dK4qERgxII5p4wZxzpB+jEmPZ1hSLBHhYRyoquHtrQdZ8EEJ31qYz303jGXGuekefypjgo8ljVPYVX7cuqZCjIhw66Vn8M0LM/lwVyXLt5exs6Kar5w3hPGDExiTHk9cTGSLxw7oG8PMiUO4Zmwq3/3zh/zohQ0cqKrh3y47w7qrjPFjSeMUdlVUM3VMqtdhmHaIighj0rBEJg1LbPOxcTGRPH3LBH784gYeWLqNmpMN/PCLI7ogSmNCkyWNFlTVnKSy+qSto9FDRUWE8eBN4+gVGc7Dywrp1zuKb16U6XVYxgQFSxot2GUTFfZ4YWHCPdPHcLj6JHf/YzP9YiOZPt7GOIyxUd4WpPSN5pe5ozh7cILXoRgPhYcJv5s1jgvOSORHL2xkxScdXwnSmFBnSaMFKXExfO38DFLj7Xbbni46Ipwnv57DsKRY5v3lY447t+oa01NZ0jCmFX2iI/j19WPYc/gEv31zu9fhGOMpSxrGuJCT0Z9ZE4fw9PslNquu6dFcJQ0RmSIi20SkUETmtbA/WkSed/avFpEMv313OuXbROQqv/KnReSgiGxq1lZ/EXlDRD5x/uznlF8mIkdEZL3z+lm7P7Ux7TBvykj69Y7krr99TIOtUW56qFaThoiEA48CU4FsYJaIZDerNgeoVNXhwIPAfc6x2fjWFB8FTAEec9oDWOCUNTcPeEtVs4C3nPdNVqjqOOd1t7uPaEzniO8dyU+vzWZD6RGeXb3T63CM8YSbK42JQKGqFqlqHbAYyG1WJxdY6Gy/CEwW32O0ucBiVa1V1WKg0GkPVV0OVLRwPv+2FgLXuf84xnStaWcP4vxhifz2zU84WnPS63CMCTg3SSMN2O33vtQpa7GOqtYDR4BEl8c2N0BV9znb+4EBfvvOF5ENIvKqiIxq6WARmSsi+SKSX1Zmt0iaziUi3Hn1SCqO1/HU8iKvwzEm4IJ6IFx9iyM0dR5/CAxV1bOBh4GXTnHMk6qao6o5ycnJgQnU9Chj0xO4dmwqT60o5uDRGq/DMSag3CSNPcBgv/fpTlmLdUQkAogHyl0e29wBEUl12koFDgKoapWqHnO2XwEiRSTJRfzGdLoffXEEJxsaeegtWzHQ9CxuksZaIEtEMkUkCt/Adl6zOnnAbGd7BrDMuUrIA2Y6d1dlAlnAmlbO59/WbODvACIy0BknQUQmOrGXu4jfmE6XkRTLV84bwqI1uykqO+Z1OMYETKtJwxmjuB1YCmwBlqhqgYjcLSLTnGrzgUQRKQTuwLnjSVULgCXAZuA14DZVbQAQkUXASmCEiJSKyBynrXuBL4jIJ8CVznvwJaNNIrIBeAiYqba2p/HQ967IIiYijP99wx74Mz2HdOfv3ZycHM3Pz/c6DNON/WbpNh55u5DXfnAxIwf29TocYzqFiKxT1ZyW9gX1QLgxwe5bF2cSFx3B7960sQ3TM1jSMKYDEnpH8Y2LMnl1034K9tr0Iqb7s6RhTAfNuSiTuBi72jA9gyUNYzoovlck37poGK9vPmCTGZpuz5KGMZ3gGxdl0Dcmgl+/uoXufHOJMZY0jOkEfWMi+fFVI3i/sJzn1uzyOhxjuowlDWM6yc3nDeXC4Ync888t7K6o9jocY7qEJQ1jOklYmHD/jLMJE+FHL2yg0dbcMN2QJQ1jOlFaQi9+eu1ZrC6uYMEHJV6HY0yns6RhTCe7KWcwV4xM4d5Xt7Kx9LDX4RjTqSxpGNPJRITf3Hg2yXHRfPfPH1J5vM7rkIzpNJY0jOkC/WOjeOzmcyg7Wsv3n19va4qbbsOShjFd5OzBCfzsS9ks317Gb9+0mXBN9xDhdQDGdGc3nzeEDbsP8/CyQuoblZ9cNQJnWRhjQpIlDWO6kIhw7w1jiQgP4/F3dlB+rJb/mT6GiHC7yDehydW/XBGZIiLbRKRQROa1sD9aRJ539q8WkQy/fXc65dtE5Cq/8qdF5KCIbGrWVn8ReUNEPnH+7OeUi4g85LS1UUTOafenNiaAwsOE/5k+mn+fnMWS/FLmPrOOqpqTXodlTLu0mjREJBx4FJgKZAOzRCS7WbU5QKWqDgceBO5zjs3GtzzsKGAK8JjTHsACp6y5ecBbqpoFvOW8xzl/lvOaCzzu7iMa4z0R4Y4vnMmvrhvN8u1lTHv4Pbbsq/I6LGPazM2VxkSgUFWLVLUOWAzkNquTCyx0tl8EJjvreecCi1W1VlWLgUKnPVR1OVDRwvn821oIXOdX/if1WQUkiEiqi/iNCRpfnTSURXMnUV3XwPTH3ucv60q9DsmYNnGTNNKA3X7vS52yFus4a4ofARJdHtvcAFXd52zvBwa0IQ5EZK6I5ItIfllZWSunMibwJmT055//fjHjBifwwxc28IcVRV6HZIxrQT0ap745ptt0g7uqPqmqOaqak5yc3EWRGdMxyXHRPDPnPKaOHsiv/rmFJ97d4XVIxrjiJmnsAQb7vU93ylqsIyIRQDxQ7vLY5g40dTs5fx5sQxzGhIzI8DAemjWea8emcu+rW3lkma38Z4Kfm6SxFsgSkUwRicI3sJ3XrE4eMNvZngEsc64S8oCZzt1VmfgGsde0cj7/tmYDf/cr/7pzF9Uk4IhfN5YxISkyPIzffnkc140bxG9e385Cm+TQBLlWn9NQ1XoRuR1YCoQDT6tqgYjcDeSrah4wH3hGRArxDW7PdI4tEJElwGagHrhNVRsARGQRcBmQJCKlwM9VdT5wL7BEROYAO4GbnFBeAa7GN5heDXyjM34AxngtIjyM39x4NsdqG/jFywWkxEUzdYzd42GCk3TnpSlzcnI0Pz/f6zCMceVEXQM3/2EVm/ZW8ec55zExs7/XIZkeSkTWqWpOS/uCeiDcmJ6kV1Q482dPYHC/Xnxr4VoK9h7xOiRjPseShjFBpF9sFAu/OZG4mEi++ofVbN1vDwCa4GJJw5ggk96vN899+zyiI8K5+anVbD9w1OuQjPmUJQ1jgtDQxFgWzZ1EeJjwladWUXjQEocJDpY0jAlSmUmxPPftSYAw88nVfGJXHCYIWNIwJogNT+nD4rmTAJj1lCUO4z1LGsYEuabEIQKznlplg+PGU5Y0jAkBw1P6sOjbvjGOm55YSX5JSxNEG9P1LGkYEyKGp/ThL9+9gKQ+0Xx1/mqWbT3gdUimB7KkYUwISe/XmxduPZ+slDi+/ad1PLNqJ915VgcTfCxpGBNiEvtEs2juJC7JSuKnL23ihy9s4ERdg9dhmR7CkoYxIahPdATzZ0/gP648k799tIfpj73PzvLjXodlegBLGsaEqLAw4ftXZvHHWyaw70gN1z78Hm9stnEO07UsaRgT4i4bkcI/vncRGYmxfPtP+dz/2lbqGxq9Dst0U5Y0jOkGBvf3DZDPmjiEx97ZwU2/X0lR2TGvwzLdkKukISJTRGSbiBSKyLwW9keLyPPO/tUikuG3706nfJuIXNVamyJyhYh8KCKbRGShs3wsInKZiBwRkfXO62cd+uTGdDMxkeH8+vox/G7mOHaUHWfq71Yw/71iGhvt7irTeVpNGiISDjwKTAWygVkikt2s2hygUlWHAw8C9znHZuNbxW8UMAV4TETCT9WmiIQBC4GZqjoa38p9s/3Os0JVxzmvu9v9qY3pxnLHpfH6f1zCRcOT+OU/NjP7j2s4XF3ndVimm3BzpTERKFTVIlWtAxYDuc3q5OL7sgd4EZgsIuKUL1bVWlUtxrdU68TTtJkI1KnqdqetN4Ab2v/xjOmZBvSN4Q+zc/j19WNYXVRB7qPvs22/zVtlOs5N0kgDdvu9L3XKWqyjqvXAEXwJ4FTHnqr8EBAhIk3LDM4ABvvVO19ENojIqyIyykXsxvRYIsKsiUNYNHcSJ+oamP7Y+7z00R57GNB0SFANhKvvX/NM4EERWQMcBZqeWvoQGKqqZwMPAy+11IaIzBWRfBHJLysrC0DUxgS3c4f24+XvXcTIgXH84Pn1Numh6RA3SWMP//rbfrpT1mIdZ+A6Hig/zbGnbFNVV6rqxao6EVgObHfKq1T1mLP9ChApIknNg1XVJ1U1R1VzkpOTXXw8Y7q/AX1jeOHWC7hn+mi27j/KNQ+9xy//sZnqunqvQzMhxk3SWAtkiUimiEThuxLIa1Ynj88GrGcAy5yrhjxgpnN3VSaQBaw5XZsikuL8GQ38J/CE836gM06CiEx0Yi9v38c2pucJDxNuPm8ob//wMr48YTDz3ytmym9X8MGOQ16HZkJIq0nDGaO4HVgKbAGWqGqBiNwtItOcavOBRBEpBO4A5jnHFgBLgM3Aa8Btqtpwqjadtn4sIluAjcDLqrrMKZ8BbBKRDcBD+O6wss5ZY9qoX2wU/zN9zKdrdHzlqdX8+IUN7K6o9jo0EwKkO3/v5uTkaH5+vtdhGBO0TtQ18OCb21nwfgkNqlw3Lo3brxhOZlKs16EZD4nIOlXNaXGfJQ1jzIGqGn7/bhHPrt5JfaNyU85gvj85i4HxMV6HZjxgScMY40rZ0VoefbuQZ1fvJEyE2Rdk8LVJQxncv7fXoZkAsqRhjGmTXeXV/N8b28jbsBcFLj0zma9NGsrlI1IICxOvwzNdzJKGMaZd9h4+weI1u1i8djcHj9ZyRnIs37nkDHLHDyI6Itzr8EwXsaRhjOmQkw2NvPLxPn7/bhGb91WRHBfNtWNTuXbsIM4ZkoBzN7zpJixpGGM6haryXuEhnlm5k3e2l1FX30haQi+uGz+I6ePTGZ7Sx+sQTSewpGGM6XRVNSd5o+AAeRv2suKTMhoVzk6P56rRA7nyrAFkpfSxK5AQZUnDGNOlDlbVkLdhLy+t38OmPb55rQb378WkzETOHdqPc4f244zkPjaIHiIsaRhjAmb/kRqWbT3I29sOsm5nJRXHfWt59OsdycTM/pyXmciIgXGk9+tFanwvoiKCat5UgyUNr8MwpsdSVYoPHSe/pJLVxRWsLi6ntPLEp/tFICMxllGD+jI6LZ4h/XuT0CuS+N6R9I+Non9slN2l5YHTJY2IQAdjjOk5RIRhyX0YltyHmyb4Jrbed+QEJYeqKa2sZnflCbbtr+KjXYf5x8Z9LbYRFxNB35hIwsOEiHAhTATr5GrdZSOSueua5ousdpwlDWNMQKXG+7qlfOu0feZwdR0Hqmo5XF1HZfVJKqvrKD9Wy6FjdRyrraehUTnZ0EhjN+4d6UwD+nbNFDCWNIwxQSGhdxQJvaO8DsO0wkagjDHGuGZJwxhjjGuWNIwxxrjmKmmIyBQR2SYihSIyr4X90SLyvLN/tYhk+O270ynfJiJXtdamiFwhIh+KyCYRWeisOY74POTU3ygi53TokxtjjGmzVpOGiIQDjwJTgWxglog0v49rDlCpqsOBB4H7nGOz8a3/PQqYAjwmIuGnalNEwoCF+JZyHQ3s5LO1x6fiW2M8C5gLPN7uT22MMaZd3FxpTAQKVbVIVeuAxUBuszq5+L7sAV4EJotv0plcYLGq1qpqMVDotHeqNhOBOlXd7rT1BnCD3zn+pD6rgAQRSW3HZzbGGNNObpJGGrDb732pU9ZiHVWtB47gSwCnOvZU5YeACBFpehJxBjC4DXEgInNFJF9E8svKylx8PGOMMW4F1UC4+uY0mQk8KCJrgKNAQxvbeFJVc1Q1Jzk5uSvCNMaYHsvNw317+Oy3fYB0p6ylOqXOwHU8UN7KsS2Wq+pK4GIAEfkicGYb4vgX69atOyQiO09XpxVJ+K5+go3F1TYWV9tYXG3THeMaeso9qnraF77EUgRkAlHABmBUszq3AU842zOBJc72KKd+tHN8ERB+ujaBFOfPaOAt4Arn/TXAq4AAk4A1rcXe0ReQ39XnsLgsrmB7WVwW1+lerV5pqGq9iNwOLHW+8J9W1QIRudsJKg+YDzwjIoVAhZM4cOotATYD9cBtqtoA0FKbzil/LCLX4us6e1xVlznlrwBX4xtMrwa+0VrsxhhjOle3nhq9o0QkX08xPbCXLK62sbjaxuJqm54WV1ANhAehJ70O4BQsrraxuNrG4mqbHhWXXWkYY4xxza40jDHGuGZJwxhjjGs9Pmm4mIzxEmcCxXoRmRFEcd0hIpudyRvfEpFT31cd2LhuFZGPRWS9iLzXwjxlnsTlV+8GEVG/WQc8jUtEbhGRMufntV5EvhUMcTl1bnL+jRWIyHOBiMtNbCLyoN/Pa7uIHA6SuIaIyNsi8pHz//LqIIlrqPMdsVFE3hGR9A6d0Ot7iT2+jzkc2AEM47PnRbKb1ckAxgJ/AmYEUVyXA72d7e8CzwdJXH39tqcBrwVDXE69OGA5sArICYa4gFuARwLx76qNcWUBHwH9nPcpwRJbs/rfw3fLvudx4Rt4/q6znQ2UBElcLwCzne0rgGc6cs6efqXR6mSMqlqiqhuBxiCL621VrXbersL3hHwwxFXl9zYWCMSdFm4m1QT4Jb4ZmGsCEFNb4go0N3F9G3hUVSsBVPVgEMXmbxawKEjiUqCvsx0P7A2SuLKBpufd3m5hf5v09KThahJED7Q1rjn4npbvam4njbxNRHYA9wP/HgxxOeuvDFbVfwYgHtdxOW5wug5eFJHBLez3Iq4zgTNF5H0RWSUiUwIQl9vYAF+3C75ZJZa1tN+DuH4BfFVESvE9jPy9IIlrA3C9sz0diBORxPaesKcnjZAnIl8FcoAHvI6liao+qqpnAP8J/D+v43HWafk/4Idex9KCl4EMVR2LbymAha3UD5QIfF1Ul+H7bf4pEUnwMqAWzAReVGeWiSAwC1igqun4Zq94xvm357UfAZeKyEfApfjm7Gv3zywYPpCX2jwJYoC4iktErgTuAqapam2wxOVnMXBdVwbkaC2uOGA08I6IlOCbuywvAIPhrf68VLXc7+/uD8C5XRyTq7jw/caap6on1bcWznZ8SSQYYmsyk8B0TYG7uOYAS+DTiVdj8E0a6GlcqrpXVa9X1fH4vi9Q1cPtPmNXD9QE8wsXkzH61V1A4AbC3UwSOR7fAFhWMP28/OMBvkQAJnNry9+jU/8dAjMQ7ubnleq3PR1YFSRxTQEWOttJ+LpAEoMhNqfeSKAE5wHlYIgLXxfxLc72WfjGNLo0PpdxJQFhzvY9wN0dOmcgfuDB/MJ3Gbnd+QK+yym7G99v7wAT8P3WdRzfdO8FQRLXm8ABYL3zyguSuH4HFDgxvX26L+9AxtWsbkCShsuf16+dn9cG5+c1MkjiEnxdepuBj/Etwdzlcbn9u8Q3fnBvoGJy+TPLBt53/i7XA18MkrhmAJ84df4ARHfkfDaNiDHGGNd6+piGMcaYNrCkYYwxxjVLGsYYY1yzpGGMMcY1SxrGGGNcs6RhjDHGNUsaxhhjXPv/ZXM+dLHhxqQAAAAASUVORK5CYII=",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.plot(rad, noises)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 95,
- "metadata": {},
- "outputs": [],
- "source": [
- "img_db = gen_img(model, config[\"IMAGES\"], torch.float64)\n",
- "img_ft = gen_img(model, config[\"IMAGES\"], torch.float32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 96,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 96,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(img_db.numpy(), cmap=\"Greys_r\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 97,
- "metadata": {},
- "outputs": [],
- "source": [
- "ctf_img_db = apply_ctf(img_db, config[\"IMAGES\"], config[\"PREPROCESSING\"])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 98,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 98,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(ctf_img_db.numpy(), cmap=\"Greys_r\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 166,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Old Method: tensor(0.0013, dtype=torch.float64)\n",
- "New Method: tensor(0.0011, dtype=torch.float64)\n",
- "New Method: tensor(0.0009, dtype=torch.float64)\n"
- ]
- }
- ],
- "source": [
- "noise_ctf_img_db = add_noise(ctf_img_db, config[\"PREPROCESSING\"])\n",
- "noise_ctf_img_db1 = add_noise_new(ctf_img_db, config[\"PREPROCESSING\"], 0.4)\n",
- "noise_ctf_img_db2 = add_noise_new(ctf_img_db, config[\"PREPROCESSING\"], 1.0)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 163,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 163,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
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- ],
- "source": [
- "plt.imshow(noise_ctf_img_db1.numpy(), cmap=\"Greys\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 164,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 164,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(noise_ctf_img_db2.numpy(), cmap=\"Greys\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3.10.4 ('sbi_env')",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.10.4"
- },
- "orig_nbformat": 4,
- "vscode": {
- "interpreter": {
- "hash": "8b03f34d7658f43f9a4f07ae898b2559b89b151c4d450d9141533f3396306ac8"
- }
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/tutorials/.gitignore b/tutorials/.gitignore
new file mode 100644
index 0000000..d45e02a
--- /dev/null
+++ b/tutorials/.gitignore
@@ -0,0 +1,2 @@
+*.h5
+*.tp
\ No newline at end of file
diff --git a/tutorials/empty.txt b/tutorials/empty.txt
deleted file mode 100644
index e69de29..0000000
diff --git a/tutorials/first_tutorial.ipynb b/tutorials/first_tutorial.ipynb
new file mode 100644
index 0000000..66bdbd7
--- /dev/null
+++ b/tutorials/first_tutorial.ipynb
@@ -0,0 +1,149 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Data/Packages/Utilities/miniconda3/envs/cryosbi_env/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+ " from .autonotebook import tqdm as notebook_tqdm\n"
+ ]
+ }
+ ],
+ "source": [
+ "import torch\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "from cryo_sbi import CryoEmSimulator\n",
+ "from cryo_sbi import gen_training_set\n",
+ "from cryo_sbi.inference.NPE_train_from_disk import npe_train_from_disk\n",
+ "from cryo_sbi.inference.NPE_train_without_saving import npe_train_no_saving"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Creating particles and then training with them"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "hsp90_models.npy\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "100%|██████████| 10000/10000 [01:13<00:00, 136.60pair/s]\n",
+ "100%|██████████| 100/100 [00:00<00:00, 4779.94pair/s]\n"
+ ]
+ }
+ ],
+ "source": [
+ "gen_training_set(\n",
+ " config_file=\"config_file.json\",\n",
+ " num_train_samples=10000,\n",
+ " num_val_samples=100,\n",
+ " file_name=\"tut_imgs\",\n",
+ " save_as_tensor=False,\n",
+ " n_workers=2,\n",
+ " batch_size=100,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Training neural netowrk:\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "100%|██████████| 30/30 [04:44<00:00, 9.48s/epoch, train_loss=-.981, val_loss=0.108] \n"
+ ]
+ }
+ ],
+ "source": [
+ "npe_train_from_disk(\n",
+ " train_config=\"resnet18_encoder.json\",\n",
+ " epochs=30,\n",
+ " train_data_dir=\"tut_imgs_train.h5\",\n",
+ " val_data_dir=\"tut_imgs_valid.h5\",\n",
+ " estimator_file=\"tut_estimator\",\n",
+ " loss_file=\"tut_loss\",\n",
+ " train_from_checkpoint=False,\n",
+ " model_state_dict=None,\n",
+ " n_workers=2,\n",
+ ")"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Training without saving images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "npe_train_no_saving(\n",
+ " image_config=\"image_params_snr01_128.json\",\n",
+ " train_config=\"resnet18_encoder.json\",\n",
+ " epochs=350,\n",
+ " estimator_file=\"resnet18_encoder.estimator\",\n",
+ " loss_file=\"resnet18_encoder.estimator\",\n",
+ " n_workers=2, # CHANGE\n",
+ ")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cryosbi_env",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.16"
+ },
+ "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tutorials/hsp90/QUAT_576 b/tutorials/hsp90/QUAT_576
deleted file mode 100644
index 9600e95..0000000
--- a/tutorials/hsp90/QUAT_576
+++ /dev/null
@@ -1,577 +0,0 @@
-576
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--0.15623012 0.37717212 -0.00000012 0.91287112
--0.24852612 0.32388512 -0.23626812 0.88176612
--0.32388512 0.24852612 -0.45643512 0.79056912
--0.37717212 0.15623012 -0.64549712 0.64549712
--0.40475612 0.05328712 -0.79056912 0.45643512
-0.40475612 0.05328712 0.45643512 -0.79056912
-0.37717212 0.15623012 0.64549712 -0.64549712
-0.32388512 0.24852612 0.79056912 -0.45643512
-0.24852612 0.32388512 0.88176612 -0.23626812
-0.15623012 0.37717212 0.91287112 0.00000012
-0.05328712 0.40475612 0.88176612 0.23626812
--0.05328712 0.40475612 0.79056912 0.45643512
--0.15623012 0.37717212 0.64549712 0.64549712
--0.24852612 0.32388512 0.45643512 0.79056912
--0.32388512 0.24852612 0.23626812 0.88176612
--0.37717212 0.15623012 0.00000012 0.91287112
--0.40475612 0.05328712 -0.23626812 0.88176612
-0.57241112 0.07535912 0.64777012 -0.49705212
-0.53340212 0.22094212 0.75434412 -0.31246012
-0.45804312 0.35146912 0.80951112 -0.10657412
-0.35146912 0.45804312 0.80951112 0.10657412
-0.22094212 0.53340212 0.75434412 0.31246012
-0.07535912 0.57241112 0.64777012 0.49705212
--0.07535912 0.57241112 0.49705212 0.64777012
--0.22094212 0.53340212 0.31246012 0.75434512
--0.35146912 0.45804312 0.10657412 0.80951112
--0.45804312 0.35146912 -0.10657412 0.80951112
--0.53340212 0.22094212 -0.31246012 0.75434512
--0.57241112 0.07535912 -0.49705212 0.64777012
diff --git a/tutorials/hsp90/config.json b/tutorials/hsp90/config.json
deleted file mode 100644
index 8b7cb30..0000000
--- a/tutorials/hsp90/config.json
+++ /dev/null
@@ -1,28 +0,0 @@
-{
- "IMAGES": {
- "N_PIXELS": 64,
- "PIXEL_SIZE": 2.0,
- "SIGMA": 2.0
- },
- "SIMULATION": {
- "N_SIMULATIONS": 100,
- "MODEL_FILE": "../../models/hsp90_models.npy",
- "DEVICE": "cpu",
- "ROTATIONS": "QUAT_576"
- },
- "PREPROCESSING": {
- "SHIFT": true,
- "CTF": true,
- "NOISE": true,
- "DEFOCUS": 1.5,
- "SNR": 1
- },
- "TRAINING": {
- "MODEL": "maf",
- "HIDDEN_FEATURES": 100,
- "NUM_TRANSFORMS": 4,
- "DEVICE": "cpu",
- "BATCH_SIZE": 1000,
- "POSTERIOR_NAME": "posterior_all_effects_noise_01.pkl"
- }
-}
\ No newline at end of file
diff --git a/tutorials/hsp90/launch_gen_data_sbi.job b/tutorials/hsp90/launch_gen_data_sbi.job
deleted file mode 100755
index 67212ad..0000000
--- a/tutorials/hsp90/launch_gen_data_sbi.job
+++ /dev/null
@@ -1,34 +0,0 @@
-#!/bin/bash -l
-
-# Standard output and error:
-#SBATCH -o ./sbi_data_gen.out.%j
-#SBATCH -e ./sbi_data_gen.err.%j
-# Initial working directory:
-#SBATCH -D ./
-# Job Name:
-#SBATCH -J SBI_Data_Gen
-#
-# Queue (Partition):
-#SBATCH --constraint=rome
-#SBATCH --partition=ccm
-#
-# Request 2 node(s)
-#SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=1
-#SBATCH --time=24:00:00
-
-module purge
-module load gcc/7
-module load python
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env/bin/activate
-
-CONFIG_NAME="config.json"
-
-python3 - << EOF
-from cryo_em_sbi import CryoEmSbi
-
-cryosbi = CryoEmSbi("$CONFIG_NAME")
-_, __ = cryosbi.simulate(num_workers=$SLURM_CPUS_PER_TASK)
-
-EOF
diff --git a/tutorials/hsp90/launch_preprocessing.job b/tutorials/hsp90/launch_preprocessing.job
deleted file mode 100755
index cac06d3..0000000
--- a/tutorials/hsp90/launch_preprocessing.job
+++ /dev/null
@@ -1,41 +0,0 @@
-#!/bin/bash -l
-
-# Standard output and error:
-#SBATCH -o ./sbi_preprocess.out.%j
-#SBATCH -e ./sbi_preprocess.err.%j
-# Initial working directory:
-#SBATCH -D ./
-# Job Name:
-#SBATCH -J SBI_Data_Gen
-#
-# Queue (Partition):
-#SBATCH --constraint=rome
-#SBATCH --partition=ccm
-#
-# Request 2 node(s)
-#SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=1
-#SBATCH --time=24:00:00
-
-module purge
-module load gcc/7
-module load python
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env/bin/activate
-
-CONFIG_NAME="config.json"
-
-python3 - << EOF
-import torch
-from cryo_em_sbi import CryoEmSbi
-
-indices = torch.load("indices.pt")
-images = torch.load("images.pt")
-
-num_workers = 1
-batch_size = int(images.shape[0] / num_workers)
-cryosbi = CryoEmSbi("$CONFIG_NAME")
-
-_, __ = cryosbi.preprocess(indices, images, num_workers=num_workers, batch_size=batch_size)
-
-EOF
diff --git a/tutorials/hsp90/launch_train_post_sbi_cpu.job b/tutorials/hsp90/launch_train_post_sbi_cpu.job
deleted file mode 100644
index 4ed4e3f..0000000
--- a/tutorials/hsp90/launch_train_post_sbi_cpu.job
+++ /dev/null
@@ -1,81 +0,0 @@
-#!/bin/bash -l
-
-# Standard output and error:
-#SBATCH -o ./sbi_train_post_cpu.out.%j
-#SBATCH -e ./sbi_train_post_cpu.err.%j
-#
-# Initial working directory:
-#SBATCH -D ./
-# Job Name:
-#SBATCH -J sbi_train_posterior_cpu
-#
-# Queue (Partition):
-#SBATCH --partition=ccm
-#SBATCH --constraint=rome
-#
-# Request 124 node(s)
-#SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=120
-#SBATCH --time=24:00:00
-
-module purge
-module load gcc/7
-module load python
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env/bin/activate
-
-CONFIG_NAME="config.json"
-
-python3 - << EOF
-import torch
-import numpy as np
-from cryo_em_sbi import CryoEmSbi
-import torch.nn as nn
-import torch.nn.functional as F
-
-class CNN(nn.Module):
- def __init__(self):
- super(CNN, self).__init__()
-
- self.conv1 = nn.Conv2d(
- in_channels=1,
- out_channels=6,
- kernel_size=8
- )
- self.pool1 = nn.MaxPool2d(kernel_size=2, stride=2)
- self.conv2 = nn.Conv2d(
- in_channels=6,
- out_channels=6,
- kernel_size=8
- )
- self.pool2 = nn.MaxPool2d(kernel_size=2, stride=2)
-
-
- def forward(self, x):
-
- x = x.view(-1, 1, 64, 64)
-
- x = F.relu(self.conv1(x))
- x = self.pool1(x)
- x = F.relu(self.conv2(x))
- x = self.pool2(x)
-
- return x.view(-1, 600)
-
-embedding_net = CNN()
-
-cryosbi = CryoEmSbi("$CONFIG_NAME")
-
-indices = torch.load("indices_training.pt")
-images = torch.load("images_training.pt")
-
-# random_selector = np.arange(0, cryosbi.config["SIMULATION"]["N_SIMULATIONS"], 1)
-# np.random.shuffle(random_selector)
-# random_selector = random_selector[0:100000]
-
-# indices = indices[random_selector]
-# images = images[random_selector]
-
-_ = cryosbi.train_posterior(indices, images, $SLURM_CPUS_PER_TASK)#, embedding_net)
-
-EOF
diff --git a/tutorials/hsp90/tutorial_cluster.ipynb b/tutorials/hsp90/tutorial_cluster.ipynb
deleted file mode 100644
index 5b2dd8f..0000000
--- a/tutorials/hsp90/tutorial_cluster.ipynb
+++ /dev/null
@@ -1,1155 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "from cryo_em_sbi import CryoEmSbi\n",
- "import sbi\n",
- "import torch\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "from tqdm import tqdm"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 1. Configure your config file\n",
- "\n",
- "Go to your config file and set all the parameters."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 2. Run the script to generate images\n",
- "\n",
- "Run `launch_gen_data.job`. The clean images and the indices will be saved automatically after the run as \"images.pt\" and \"indices.pt\". Alternatively you can edit this line in the .job file `_, __ = cryosbi.simulate($SLURM_CPUS_PER_TASK)` for something like `_, __ = cryosbi.simulate($SLURM_CPUS_PER_TASK, fname_indices=fname_for_indices.pt, fname_images=fname_for_images.pt)` if you want different names or you want to specify a path for the clean images."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 3. Load generated images and preprocess them LOCALLY\n",
- "\n",
- "Check again the parameters you set for preprocessing in the config file!!"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/mnt/home/dsilvasanchez/virtual_envs/sbi_env_try/lib/python3.8/site-packages/sbi/utils/torchutils.py:27: UserWarning: GPU was selected as a device for training the neural network. Note that we expect **no** significant speed ups in training for the default architectures we provide. Using the GPU will be effective only for large neural networks with operations that are fast on the GPU, e.g., for a CNN or RNN `embedding_net`.\n",
- " warnings.warn(\n"
- ]
- }
- ],
- "source": [
- "#cryosbi_no_shift = CryoEmSbi(\"config_no_shift.json\")\n",
- "cryosbi_all = CryoEmSbi(\"config_all.json\")\n",
- "cryosbi_all_noise01 = CryoEmSbi(\"config_all_noise01.json\")\n",
- "# Edit the filename if you used something else!\n",
- "\n",
- "#indices = torch.load(\"indices.pt\")\n",
- "#images = torch.load(\"images.pt\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "8408244a8f3846bca95c31bdbf9b9980",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Running 10 simulations.: 0%| | 0/10 [00:00"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "# Let's check how the images look for peace of mind\n",
- "\n",
- "plt.imshow(images[2].reshape(64, 64))\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 4. Preprocessing\n",
- "To properly simulate CryoEM we need to add noise, apply CTF effects, and shift the images randomly. We do not generate images directly with this effects, as it would be expensive to generate new datasets for each combination of effects. Instead we create raw images, and then apply a desired combination of filters before training.\n",
- "\n",
- "The function below automatically saves indices and images as \"indices_training.pt\" and \"images_training.pt\".\n",
- "\n",
- "You DON'T need to use a GPU here. I set it so the preprocessing uses the same device as the simulation. If you generated data with a CPU, you preprocess with a CPU. If you generated data with a GPU, then you do need a GPU for preprocessing.\n",
- "\n",
- "Alternatively if you don't want to use a GPU for preprocessing, you should edit your config file to have a simulating device = \"cpu\" and load the indices/images in step 3 as\n",
- "\n",
- "```\n",
- "indices = torch.load(\"indices.pt\").to(\"cpu\")\n",
- "images = torch.load(\"images.pt\").to(\"cpu\")\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "66f44f1b2e294814b6cca431ebd0ed02",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Running 1000000 simulations in 8 batches.: 0%| | 0/8 [00:00"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(images_training[100].reshape(64, 64),cmap=\"Greys_r\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 5. Training the posterior\n",
- "\n",
- "Since you did the preprocessing here, you don't need to do it in the .job file. PLEASE be careful when you load the indices and the images in the .job files. Be sure that you are loading the files you want to train with."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 6. Loading posterior and checking how everything turned out"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "import torch.nn as nn \n",
- "import torch.nn.functional as F \n",
- "\n",
- "class CNN(nn.Module):\n",
- " def __init__(self):\n",
- " super(CNN, self).__init__()\n",
- " \n",
- " self.conv1 = nn.Conv2d(\n",
- " in_channels=1,\n",
- " out_channels=6,\n",
- " kernel_size=8\n",
- " )\n",
- " self.pool1 = nn.MaxPool2d(kernel_size=2, stride=2)\n",
- " self.conv2 = nn.Conv2d(\n",
- " in_channels=6,\n",
- " out_channels=6,\n",
- " kernel_size=8\n",
- " )\n",
- " self.pool2 = nn.MaxPool2d(kernel_size=2, stride=2)\n",
- " \n",
- " \n",
- " def forward(self, x):\n",
- " \n",
- " x = x.view(-1, 1, 64, 64)\n",
- "\n",
- " x = F.relu(self.conv1(x))\n",
- " x = self.pool1(x)\n",
- " x = F.relu(self.conv2(x))\n",
- " x = self.pool2(x)\n",
- "\n",
- " return x.view(-1, 600)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# embedding_net = SummaryNet()\n",
- "\n",
- "# posterior = cryosbi.train_posterior(indices_training, images_training, num_workers=32, embedding_net=embedding_net)\n",
- "\n",
- "# del indices_training, images_training"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "import pickle\n",
- "\n",
- "# Be careful here! If the name of your posterior is different to the one you have in your config file, replace \n",
- "# cryosbi.config[\"TRAINING\"][\"POSTERIOR_NAME\"] for \"name_of_posterior_file.pkl\"\n",
- "\n",
- "\n",
- "#torch.loading_context(map_location='cuda')\n",
- "with open(\"posterior_all_effects.pkl\", \"rb\") as handle:\n",
- " posterior_all = pickle.load(handle)\n",
- "\n",
- "# with open(\"posterior_no_shift.pkl\", \"rb\") as handle:\n",
- "# posterior_no_shift = pickle.load(handle)\n",
- "\n",
- "with open(\"posterior_all_effects_cnn.pkl\", \"rb\") as handle:\n",
- " posterior_all_cnn = pickle.load(handle)\n",
- "\n",
- "# with open(\"posterior_no_shift_cnn.pkl\", \"rb\") as handle:\n",
- "# posterior_no_shift_cnn = pickle.load(handle)\n",
- "\n",
- "\n",
- "with open(\"posterior_all_effects_noise_01_cnn.pkl\", \"rb\") as handle:\n",
- " posterior_noisy = pickle.load(handle)\n",
- "\n",
- "with open(\"posterior_all_effects_cnn_1e5images.pkl\", \"rb\") as handle:\n",
- " posterior_few_images = pickle.load(handle)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "torch.save(posterior_all, \"posterior_all_effects.pt\")\n",
- "torch.save(posterior_all_cnn, \"posterior_all_effects_cnn.pt\")\n",
- "torch.save(posterior_noisy, \"posterior_all_effects_noise_01_cnn.pt\")\n",
- "torch.save(posterior_few_images, \"posterior_all_effects_cnn_1e5images.pt\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "posterior_all = torch.load(\"posterior_all_effects.pt\", map_location=\"cuda\")\n",
- "posterior_all_cnn = torch.load(\"posterior_all_effects_cnn.pt\", map_location=\"cuda\")\n",
- "posterior_noisy = torch.load(\"posterior_all_effects_noise_01_cnn.pt\", map_location=\"cuda\")\n",
- "posterior_few_images = torch.load(\"posterior_all_effects_cnn_1e5images.pt\", map_location=\"cuda\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "with open(\"posterior_cuda.pkl\", \"wb\") as handle:\n",
- " pickle.dump(posterior, handle)\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 5. Checking if the posterior works\n",
- "\n",
- "We can check that the posterior works by generating new images, and checking if it can pinpoint the model they were generated from."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "cryosbi_all.quaternions = np.loadtxt(\"QUAT_576\", skiprows=1)[0:1, :]\n",
- "\n",
- "cryosbi_all_noise01.quaternions = np.loadtxt(\"QUAT_576\", skiprows=1)[0:1, :]\n",
- "#cryosbi_no_shift.quaternions = cryosbi_no_shift.quaternions[0:1, :]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [],
- "source": [
- "torch.set_num_threads(32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "38eee96cbc004b4cbb8d44e0efa882f5",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Running 20 simulations.: 0%| | 0/20 [00:00"
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(true_images_all_noise01[4].reshape(64, 64).to(\"cpu\"), cmap=\"Greys_r\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [],
- "source": [
- "n_samples = 10000\n",
- "\n",
- "samples_all = torch.zeros(20, n_samples, 1, device=\"cpu\")\n",
- "samples_all_cnn = torch.zeros(20, n_samples, 1, device=\"cpu\")\n",
- "samples_all_noisy = torch.zeros(20, n_samples, 1, device=\"cpu\")\n",
- "samples_few_images = torch.zeros(20, n_samples, 1, device=\"cpu\")\n",
- "\n",
- "#samples_no_shifts = torch.zeros(20, n_samples, 1, device=\"cpu\")\n",
- "\n",
- "#samples_no_shifts_cnn = torch.zeros(20, n_samples, 1, device=\"cpu\")\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "100%|██████████| 20/20 [00:00<00:00, 130.07it/s]\n"
- ]
- }
- ],
- "source": [
- "for i in tqdm(range(20)):\n",
- " \n",
- " #samples_all[i] = posterior_all.sample((n_samples,), x=true_images_all[i], show_progress_bars=False) \n",
- " #samples_all_cnn[i] = posterior_all_cnn.sample((n_samples,), x=true_images_all[i], show_progress_bars=False) \n",
- " samples_all_noisy[i] = posterior_noisy.sample((n_samples,), x=true_images_all_noise01[i], show_progress_bars=False) \n",
- " #samples_few_images[i] = posterior_few_images.sample((n_samples,), x=true_images_all[i], show_progress_bars=False) \n",
- " \n",
- " #samples_no_shifts_cnn[i] = posterior_no_shift_cnn.sample((n_samples,), x=true_images_no_shift[i], show_progress_bars=False) \n",
- " #samples_no_shifts[i] = posterior_no_shift.sample((n_samples,), x=true_images_no_shift[i], show_progress_bars=False) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
- "outputs": [],
- "source": [
- "torch.save(samples_all, \"samples/samples_all.pt\")\n",
- "torch.save(samples_no_shifts, \"samples/samples_no_shift.pt\")\n",
- "\n",
- "torch.save(samples_all_cnn, \"samples/samples_all_cnn.pt\")\n",
- "torch.save(samples_no_shifts_cnn, \"samples/samples_no_shift_cnn.pt\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, axes = plt.subplots(4, 5, figsize=(20, 20), sharex=True)\n",
- "# fig.suptitle(f\"N_IMAGES: {cryosbi.config['SIMULATION']['N_SIMULATIONS']}, SNR:{cryosbi.config['PREPROCESSING']['SNR']}, Rotations\\nMAF\")\n",
- "\n",
- "for i in range(4):\n",
- " for j in range(5):\n",
- "\n",
- " axes[i,j].hist(samples_all_noisy[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"blue\", label=\"all\")\n",
- "\n",
- " #axes[i,j].hist(samples_all_cnn[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"blue\", label=\"all\")\n",
- "\n",
- " #axes[i,j].hist(samples_few_images[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"blue\", label=\"all\")\n",
- "\n",
- "\n",
- " #axes[i,j].hist(samples_no_shifts[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"black\", label=\"no_shifts\")\n",
- "\n",
- "\n",
- " axes[i,j].axvline(x=i*5 + j, color=\"red\", ls=\":\")\n",
- " axes[i,j].set_title(f\"index = {i*5 + j}\")\n",
- " axes[i,j].set_yticks([])\n",
- " axes[i,j].set_xticks(range(0, 19, 4))\n",
- "\n",
- "axes[0,0].legend()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, axes = plt.subplots(4, 5, figsize=(20, 20), sharex=True)\n",
- "# fig.suptitle(f\"N_IMAGES: {cryosbi.config['SIMULATION']['N_SIMULATIONS']}, SNR:{cryosbi.config['PREPROCESSING']['SNR']}, Rotations\\nMAF\")\n",
- "\n",
- "for i in range(4):\n",
- " for j in range(5):\n",
- "\n",
- " axes[i,j].hist(samples_all_cnn[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"blue\", label=\"all\")\n",
- " axes[i,j].hist(samples_no_shifts_cnn[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"black\", label=\"no_shifts\")\n",
- " axes[i,j].axvline(x=i*5 + j, color=\"red\", ls=\":\")\n",
- " axes[i,j].set_title(f\"index = {i*5 + j}\")\n",
- " axes[i,j].set_yticks([])\n",
- " axes[i,j].set_xticks(range(0, 19, 4))\n",
- "\n",
- "axes[0,0].legend()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, axes = plt.subplots(4, 5, figsize=(20, 20), sharex=True)\n",
- "# fig.suptitle(f\"N_IMAGES: {cryosbi.config['SIMULATION']['N_SIMULATIONS']}, SNR:{cryosbi.config['PREPROCESSING']['SNR']}, Rotations\\nMAF\")\n",
- "\n",
- "for i in range(4):\n",
- " for j in range(5):\n",
- "\n",
- " axes[i,j].hist(samples_all[i*5 + j].numpy().flatten(), bins=30, histtype=\"stfig, axes = plt.subplots(4, 5, figsize=(20, 20), sharex=True)\n",
- "# fig.suptitle(f\"N_IMAGES: {cryosbi.config['SIMULATION']['N_SIMULATIONS']}, SNR:{cryosbi.config['PREPROCESSING']['SNR']}, Rotations\\nMAF\")\n",
- "\n",
- "for i in range(4):\n",
- " for j in range(5):\n",
- "\n",
- " axes[i,j].hist(samples_all_cnn[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"blue\", label=\"all\")\n",
- " axes[i,j].hist(samples_no_shifts_cnn[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"black\", label=\"no_shifts\")\n",
- " axes[i,j].axvline(x=i*5 + j, color=\"red\", ls=\":\")\n",
- " axes[i,j].set_title(f\"index = {i*5 + j}\")\n",
- " axes[i,j].set_yticks([])\n",
- " axes[i,j].set_xticks(range(0, 19, 4))\n",
- "\n",
- "axes[0,0].legend()ep\", color=\"blue\", label=\"No CNN\")\n",
- " axes[i,j].hist(samples_all_cnn[i*5 + j].numpy().flatten(), bins=30, histtype=\"step\", color=\"black\", label=\"With CNN\")\n",
- " axes[i,j].axvline(x=i*5 + j, color=\"red\", ls=\":\")\n",
- " axes[i,j].set_title(f\"index = {i*5 + j}\")\n",
- " axes[i,j].set_yticks([])\n",
- " axes[i,j].set_xticks(range(0, 19, 4))\n",
- "\n",
- "axes[0,0].legend()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [],
- "source": [
- "del images_training, indices_training"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 6. Recovering Distriutions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 80,
- "metadata": {},
- "outputs": [],
- "source": [
- "\n",
- "# If you want to use an uniform distribution\n",
- "#true_indices_fe = cryosbi.prior_analysis.sample((20000,))\n",
- "\n",
- "# Example for a 2-well distribution\n",
- "\n",
- "\n",
- "import torch.distributions as D\n",
- "\n",
- "mix = D.Categorical(torch.ones(2,))\n",
- "comp = D.Normal(torch.tensor([3., 14.]), torch.tensor([1., 1.]))\n",
- "double_well_distribution = D.MixtureSameFamily(mix, comp)\n",
- "\n",
- "true_indices_fe = double_well_distribution.sample((5000,))\n",
- "\n",
- "# Erase non-valid elementes (<0 or >19)\n",
- "\n",
- "true_indices_fe = true_indices_fe[true_indices_fe.round() <= 19.]\n",
- "true_indices_fe = true_indices_fe[true_indices_fe.round() >= 0]\n",
- "\n",
- "true_indices_fe = true_indices_fe.reshape(-1, 1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "torch.Size([5000, 1])"
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "true_indices.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 81,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "8aa5321f20af40339f60bd6100b2a486",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Running 4998 simulations in 4998 batches.: 0%| | 0/4998 [00:00"
- ]
- },
- "execution_count": 82,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(true_images_fe_all[0].reshape(64, 64).cpu().numpy(), cmap=\"Greys_r\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 83,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- " 0%| | 0/4998 [00:00\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0msamples_all_fe\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mposterior_all\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrue_images_fe_all\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshow_progress_bars\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0msamples_no_shifts_fe\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mposterior_no_shift\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrue_images_fe_no_shift\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshow_progress_bars\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0msamples_all_fe_cnn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mposterior_all_cnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrue_images_fe_all\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshow_progress_bars\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mNameError\u001b[0m: name 'posterior_no_shift' is not defined"
- ]
- }
- ],
- "source": [
- "n_samples = 1000\n",
- "\n",
- "samples_all_fe = torch.zeros(true_indices_fe.shape[0], n_samples, 1, device=\"cpu\")\n",
- "samples_no_shifts_fe = torch.zeros(true_indices_fe.shape[0], n_samples, 1, device=\"cpu\")\n",
- "\n",
- "samples_all_fe_cnn = torch.zeros(true_indices_fe.shape[0], n_samples, 1, device=\"cpu\")\n",
- "samples_no_shifts_fe_cnn = torch.zeros(true_indices_fe.shape[0], n_samples, 1, device=\"cpu\")\n",
- "\n",
- "for i in tqdm(range(true_indices_fe.shape[0])):\n",
- " \n",
- " samples_all_fe[i] = posterior_all.sample((n_samples,), x=true_images_fe_all[i], show_progress_bars=False) \n",
- " samples_no_shifts_fe[i] = posterior_no_shift.sample((n_samples,), x=true_images_fe_no_shift[i], show_progress_bars=False) \n",
- "\n",
- " samples_all_fe_cnn[i] = posterior_all_cnn.sample((n_samples,), x=true_images_fe_all[i], show_progress_bars=False) \n",
- " samples_no_shifts_fe_cnn[i] = posterior_no_shift_cnn.sample((n_samples,), x=true_images_fe_no_shift[i], show_progress_bars=False) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 85,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "100%|██████████| 4998/4998 [00:29<00:00, 170.78it/s]\n"
- ]
- }
- ],
- "source": [
- "n_samples = 1000\n",
- "\n",
- "samples_noise = torch.zeros(true_indices_fe.shape[0], n_samples, 1, device=\"cpu\")\n",
- "\n",
- "\n",
- "\n",
- "for i in tqdm(range(true_indices_fe.shape[0])):\n",
- " \n",
- " samples_noise[i] = posterior_noisy.sample((n_samples,), x=true_images_fe_all[i], show_progress_bars=False) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {},
- "outputs": [],
- "source": [
- "torch.save(samples_all_fe, \"samples/samples_all_fe.pt\")\n",
- "torch.save(samples_no_shifts_fe, \"samples/samples_no_shift_fe.pt\")\n",
- "\n",
- "torch.save(samples_all_fe_cnn, \"samples/samples_all_fe_cnn.pt\")\n",
- "torch.save(samples_no_shifts_fe_cnn, \"samples/samples_no_shift_fe_cnn.pt\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 88,
- "metadata": {},
- "outputs": [],
- "source": [
- "samples_noise_mean = torch.mean(samples_noise, axis=1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 90,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.0625"
- ]
- },
- "execution_count": 90,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "1/16"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 89,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 89,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "import seaborn as sns\n",
- "sns.set_context(\"talk\")\n",
- "\n",
- "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
- "\n",
- "ax.hist(true_indices_fe.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"blue\", label=\"true\", density=True);\n",
- "\n",
- "#ax.hist(samples_all_fe.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"black\", label=\"all effects\", density=True);\n",
- "\n",
- "#ax.hist(samples_no_shifts_fe.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"red\", label=\"no shifts\", density=True);\n",
- "\n",
- "ax.hist(samples_noise_mean.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"black\", label=\"all effects\", density=True);\n",
- "\n",
- "ax.set_xticks(np.arange(0, 20, 2));\n",
- "ax.set_xticks(np.arange(0, 20, 2));\n",
- "\n",
- "ax.legend()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "import seaborn as sns\n",
- "sns.set_context(\"talk\")\n",
- "\n",
- "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
- "\n",
- "ax.hist(true_indices_fe.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"blue\", label=\"true\", density=True);\n",
- "\n",
- "ax.hist(samples_all_fe_cnn.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"black\", label=\"all effects\", density=True);\n",
- "\n",
- "ax.hist(samples_no_shifts_fe_cnn.cpu().numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"step\", color=\"red\", label=\"no shifts\", density=True);\n",
- "\n",
- "\n",
- "ax.set_xticks(np.arange(0, 20, 2));\n",
- "ax.set_xticks(np.arange(0, 20, 2));\n",
- "\n",
- "ax.legend()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "tensor([6.1620]) tensor([5.6875]) tensor([5.])\n"
- ]
- }
- ],
- "source": [
- "meand = torch.empty(true_indices.shape[0],1)\n",
- "maxd = torch.empty(true_indices.shape[0],1)\n",
- "bins = torch.arange(21)\n",
- "\n",
- "\n",
- "f = open(\"Pwm.txt\", \"w\")\n",
- "f2 = open(\"true_plus.txt\",\"w\")\n",
- "\n",
- "for i in range(true_indices.shape[0]):\n",
- " f.write(str(i))\n",
- " f2.write(str(i))\n",
- " meand[i]=torch.mean(samples[i],axis=0)\n",
- " hist,bin_ed=torch.histogram(samples[i],bins=20, range=(0., 20.))\n",
- " maxd[i]=torch.argmax(hist)\n",
- " f2.write(' '+ str(true_indices[i].numpy().flatten())+ ' '+ str(meand[i].numpy().flatten())+ ' '+ str(maxd[i].numpy().flatten()))\n",
- " for j in range(20):\n",
- " f.write(' ' + str(hist[j].numpy().flatten()))\n",
- " f.write('\\n')\n",
- " f2.write('\\n')\n",
- "\n",
- "f2.close()\n",
- "f.close()\n",
- "\n",
- "print(true_indices[2],meand[2],maxd[2])\n",
- "\n",
- "all_sam = samples.cpu().numpy().flatten()\n",
- "\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [],
- "source": [
- "histall,bin_ed=np.histogram(all_sam,bins=20, range=(0., 20.))\n",
- "histmax,bin_ed=torch.histogram(meand,bins=20, range=(0., 20.))\n",
- "histmean,bin_ed=torch.histogram(maxd,bins=20, range=(0., 20.))\n",
- "histtrue,bin_ed=np.histogram(true_indices,bins=20, range=(0., 20.))\n",
- "\n",
- "\n",
- "f3 = open(\"histos.txt\", \"w\")\n",
- "\n",
- "for j in range(20):\n",
- " f3.write(' ' + str(histtrue[j]) + ' ' + str(histall[j])+ ' ' + str(histmax[j].numpy().flatten())+' ' + str(histmean[j].numpy().flatten()))\n",
- " f3.write('\\n')\n",
- " \n",
- "f3.close()\n",
- "\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "#plt.title(f\"MODEL_FILE:{simulation_params['MODEL_FILE']}, N_IMAGES: {simulation_params['N_SIMULATIONS']}, SNR:{image_params['SNR']}, With Rotations\")\n",
- "\n",
- "plt.hist(true_indices.cpu().numpy().flatten(), bins=bins, histtype=\"step\", linewidth=1.5,label='True', density = 'true')\n",
- "\n",
- "plt.hist(meand.cpu().numpy().flatten(), bins=bins, histtype=\"step\", linewidth=2.0, label = 'Mean', density = 'true')\n",
- "\n",
- "plt.hist(maxd.cpu().numpy().flatten(), bins=bins, histtype=\"step\", linewidth=1.5, label = 'Max', density = 'true')\n",
- "\n",
- "plt.hist(all_sam, bins=bins, histtype=\"step\", linewidth=1.5, label = 'All', density = 'true')\n",
- "plt.legend()\n",
- "\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3.8.12 ('sbi_env_try')",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.12"
- },
- "vscode": {
- "interpreter": {
- "hash": "4c2a1af4c67af5391b40e9df2dd79293a2163069b42db13e0a4e4857b53919cf"
- }
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/tutorials/hsp90_analysis.ipynb b/tutorials/hsp90_analysis.ipynb
new file mode 100644
index 0000000..180acd3
--- /dev/null
+++ b/tutorials/hsp90_analysis.ipynb
@@ -0,0 +1,562 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "c11d3bbe-f081-467b-9a51-f993cd7dea8a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import torch\n",
+ "import json\n",
+ "from multiprocessing import Pool\n",
+ "from lampe.data import JointLoader\n",
+ "from itertools import islice\n",
+ "from tqdm import tqdm\n",
+ "from lampe.diagnostics import expected_coverage_mc\n",
+ "from lampe.plots import coverage_plot\n",
+ "\n",
+ "from cryo_sbi.inference.models import build_models\n",
+ "from cryo_sbi import CryoEmSimulator\n",
+ "from cryo_sbi.inference import priors"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "bed3b97c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "file_name = \"23_03_09_results\" # File name\n",
+ "data_dir = \"raw_data/\"\n",
+ "plot_dir = \"plots/\"\n",
+ "num_samples_stats = 2000 # Number of simulations for computing posterior stats\n",
+ "num_samples_SBC = 1000 # Number of simulations for SBC\n",
+ "num_posterior_samples_SBC = 4096 # Number of posterior samples for each SBC simulation\n",
+ "num_samples_posterior = 5000 # Number of samples to draw from posterior\n",
+ "batch_size_sampling = 100 # Batch size for sampling posterior\n",
+ "num_workers = 24 # Number of CPU cores\n",
+ "device = \"cuda\" # Device for computations\n",
+ "save_figures = False"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1f1226dd-53f1-40db-82a7-657c60a8e104",
+ "metadata": {},
+ "source": [
+ "## Load cryo-em simulator and posterior with correct config"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "f2eb23c1-3229-48a7-a965-deb74277e0a8",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "hsp90_models.npy\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/mnt/sw/nix/store/z6v265ivx5w6xbajay41vdfc0la8gla5-python-3.9.12-view/lib/python3.9/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /dev/shm/nix-build-py-torch-1.11.0.drv-0/nixbld1/spack-stage-py-torch-1.11.0-1nz745m2yd6q5pzmdri0jhmiqb7dl200/spack-src/aten/src/ATen/native/TensorShape.cpp:2227.)\n",
+ " return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]\n",
+ "/mnt/ceph/users/dsilvasanchez/projects/new_sbi/cryo_em_SBI/src/cryo_sbi/wpa_simulator/ctf.py:36: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
+ " env = torch.exp(torch.tensor(-image_params[\"B_FACTOR\"] * freq2_2d * 0.5))\n",
+ "/mnt/ceph/users/dsilvasanchez/projects/new_sbi/cryo_em_SBI/src/cryo_sbi/wpa_simulator/ctf.py:38: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
+ " image_params[\"AMP\"] * torch.tensor(phase * freq2_2d * 0.5).cos()\n",
+ "/mnt/ceph/users/dsilvasanchez/projects/new_sbi/cryo_em_SBI/src/cryo_sbi/wpa_simulator/ctf.py:40: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
+ " * torch.tensor(phase * freq2_2d * 0.5).sin()\n"
+ ]
+ }
+ ],
+ "source": [
+ "cryosbi = CryoEmSimulator(\"image_params_snr01_128.json\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "269ee74f-9a78-4c27-bd7f-14ec441de8ba",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "train_config = json.load(open(\"resnet18_encoder.json\"))\n",
+ "estimator = build_models.build_npe_flow_model(train_config)\n",
+ "estimator.load_state_dict(torch.load(\"resnet18_encoder_snr01.estimator\"))\n",
+ "estimator.cuda()\n",
+ "estimator.eval();"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "id": "488a4635-ea67-4728-b016-a9ecebe23e4a",
+ "metadata": {},
+ "source": [
+ "## Testing posterior on single images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "872d28d3-0ec6-4928-b825-216f071740d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "indices = torch.tensor(np.arange(0, cryosbi.max_index + 1, 1), dtype=float)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "00403aef",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "images = []\n",
+ "quats = []\n",
+ "\n",
+ "for index in indices:\n",
+ " image, quat = cryosbi.simulator(index)\n",
+ " images.append(image)\n",
+ " quats.append(torch.tensor(quat))\n",
+ "\n",
+ "images = torch.stack(images, dim=0)\n",
+ "quats = torch.stack(quats)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "fb0f924d-8f2c-4c32-b15d-f23d2b805a23",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "theta_samples = []\n",
+ "with torch.no_grad():\n",
+ " for batched_images in torch.split(\n",
+ " images, split_size_or_sections=batch_size_sampling, dim=0\n",
+ " ):\n",
+ " samples = estimator.sample(\n",
+ " batched_images.cuda(non_blocking=True), shape=(num_samples_posterior,)\n",
+ " ).cpu()\n",
+ " theta_samples.append(samples)\n",
+ " samples = torch.cat(theta_samples, dim=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "3b4133ac-b50e-4d37-8b78-2732d6ebeb01",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8))\n",
+ "for idx, ax in enumerate(axes.reshape(-1)):\n",
+ " ax.imshow(images[idx], vmax=5, vmin=-5)\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks([])\n",
+ " ax.text(10, 20, str(int(indices[idx].item())))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "2add5831-d35d-4a19-b422-e0c4f03b98ef",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8), sharex=True)\n",
+ "for idx, ax in enumerate(axes.reshape(1, -1)[0]):\n",
+ " ax.hist(\n",
+ " samples[:, idx].numpy(),\n",
+ " bins=np.arange(0, 20, 0.5),\n",
+ " histtype=\"step\",\n",
+ " color=\"blue\",\n",
+ " label=\"all\",\n",
+ " )\n",
+ " ax.set_yticks([])\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks(range(0, 20, 4))\n",
+ " ax.axvline(indices[idx], color=\"red\")"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "id": "a7213a4a-3a5d-4e04-9edd-d1906ff02818",
+ "metadata": {},
+ "source": [
+ "## Generate images from prior and evaluate posterior for statistical analysis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "0d40097c-43b3-41a4-b01a-0216c6ec6465",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "indices = priors.get_uniform_prior_1d(cryosbi.max_index).sample((num_samples_stats,))\n",
+ "images = torch.stack([cryosbi.simulator(index) for index in indices], dim=0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "f1c977bb-673d-4b08-94c0-39d93c52c63b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "theta_samples = []\n",
+ "with torch.no_grad():\n",
+ " for batched_images in torch.split(\n",
+ " images, split_size_or_sections=batch_size_sampling, dim=0\n",
+ " ):\n",
+ " samples = estimator.sample(\n",
+ " batched_images.cuda(non_blocking=True), shape=(num_samples_posterior,)\n",
+ " ).cpu()\n",
+ " theta_samples.append(samples.reshape(-1, batch_size_sampling))\n",
+ " samples = torch.cat(theta_samples, dim=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "ec3aae2c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mean_distance = (samples.mean(dim=0) - indices.reshape(-1)).numpy()\n",
+ "posterior_quantiles = np.quantile(samples.numpy(), [0.025, 0.975], axis=0)\n",
+ "confidence_widths = (posterior_quantiles[1] - posterior_quantiles[0]).flatten()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "82c9029e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "_ = plt.hist(mean_distance)\n",
+ "_ = plt.xlabel(\"Posterior Mean - True index\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "a4346841",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "_ = plt.hist(confidence_widths)\n",
+ "_ = plt.xlabel(\"95\\% confidence width\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a890dc7a-5881-46fa-9ac2-c5a9379d7834",
+ "metadata": {},
+ "source": [
+ "## Compute posterior calibration"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "id": "5bfb7150-5ed0-4d17-a31a-54be434b2ff9",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "1000pair [00:29, 33.43pair/s]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "loader = JointLoader(\n",
+ " priors.get_uniform_prior_1d(cryosbi.max_index),\n",
+ " cryosbi.simulator,\n",
+ " vectorized=False,\n",
+ " batch_size=1,\n",
+ " num_workers=num_workers,\n",
+ " prefetch_factor=1,\n",
+ ")\n",
+ "\n",
+ "levels, coverages = expected_coverage_mc(\n",
+ " estimator.flow,\n",
+ " (\n",
+ " (estimator.standardize(theta.cuda()), x.cuda())\n",
+ " for theta, x in islice(loader, num_samples_SBC)\n",
+ " ),\n",
+ " n=num_posterior_samples_SBC,\n",
+ ")\n",
+ "\n",
+ "fig = coverage_plot(levels, coverages, legend=\"NPE\")\n",
+ "\n",
+ "if save_figures:\n",
+ " fig.savefig(f\"{plot_dir}{file_name}_SBC.pdf\", dpi=400)"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "id": "5050ccaa-fcff-4e37-8255-ed65a172e6a1",
+ "metadata": {},
+ "source": [
+ "## Generate images from index 10 with known quaternion"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "id": "beda7e80-e8ed-41ff-beb1-50c66ceca824",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "quats = torch.from_numpy(np.load(\"quaternion_list.npy\"))[:5000]\n",
+ "num_simulations = len(quats)\n",
+ "indices = 10 * torch.ones(num_simulations).reshape(-1, 1)\n",
+ "parameters = torch.cat((indices, quats), dim=1)\n",
+ "images = torch.stack(\n",
+ " [cryosbi._simulator_with_quat(param) for param in parameters], dim=0\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "998ed401-01d7-4bbc-a9bc-c942eea26cb5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "theta_samples = []\n",
+ "with torch.no_grad():\n",
+ " for batched_images in torch.split(\n",
+ " images, split_size_or_sections=batch_size_sampling, dim=0\n",
+ " ):\n",
+ " samples = estimator.sample(\n",
+ " batched_images.cuda(non_blocking=True), shape=(num_samples_posterior,)\n",
+ " ).cpu()\n",
+ " theta_samples.append(samples.reshape(-1, batch_size_sampling))\n",
+ "samples = torch.cat(theta_samples, dim=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "efe3e5d9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mean_distance = (samples.mean(dim=0) - indices.reshape(-1)).numpy()\n",
+ "posterior_quantiles = np.quantile(samples.numpy(), [0.025, 0.975], axis=0)\n",
+ "confidence_widths = (posterior_quantiles[1] - posterior_quantiles[0]).flatten()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "id": "62d855e4",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/tmp/ipykernel_49433/3633206100.py:55: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all axes decorations.\n",
+ " plt.tight_layout()\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "from matplotlib import cm, colors\n",
+ "from mpl_toolkits.mplot3d import Axes3D\n",
+ "import numpy as np\n",
+ "from scipy.spatial.transform import Rotation\n",
+ "\n",
+ "# Create a sphere\n",
+ "r = 1\n",
+ "pi = np.pi\n",
+ "cos = np.cos\n",
+ "sin = np.sin\n",
+ "phi, theta = np.mgrid[0.0:pi:100j, 0.0 : 2.0 * pi : 100j]\n",
+ "x = r * sin(phi) * cos(theta)\n",
+ "y = r * sin(phi) * sin(theta)\n",
+ "z = r * cos(phi)\n",
+ "\n",
+ "unit_vecotr = np.array([0, 0, 1])\n",
+ "points = []\n",
+ "for i in range(len(quats)):\n",
+ " rot_mat = Rotation.from_quat(quats[i]).as_matrix()\n",
+ " coord = np.matmul(rot_mat, unit_vecotr)\n",
+ " points.append(coord)\n",
+ "points = np.array(points)\n",
+ "\n",
+ "xx = points[:, 0]\n",
+ "yy = points[:, 1]\n",
+ "zz = points[:, 2]\n",
+ "\n",
+ "# Set colours and render\n",
+ "fig = plt.figure()\n",
+ "ax = fig.add_subplot(111, projection=\"3d\")\n",
+ "\n",
+ "# ax.plot_surface(\n",
+ "# x, y, z, rstride=1, cstride=1, color='c', alpha=0.3, linewidth=0)\n",
+ "\n",
+ "im = ax.scatter(xx, yy, zz, s=confidence_widths, c=confidence_widths)\n",
+ "\n",
+ "ax.set_xlabel(\"x\")\n",
+ "ax.set_ylabel(\"y\")\n",
+ "# ax.set_zlabel('z')\n",
+ "ax.set_xticklabels([])\n",
+ "ax.set_yticklabels([])\n",
+ "ax.set_zticklabels([])\n",
+ "\n",
+ "ax.azim = -40\n",
+ "ax.elev = 30\n",
+ "ax.dist = 10\n",
+ "\n",
+ "fig.colorbar(im)\n",
+ "\n",
+ "ax.set_xlim([-1, 1])\n",
+ "ax.set_ylim([-1, 1])\n",
+ "ax.set_zlim([-1, 1])\n",
+ "ax.set_aspect(\"auto\")\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ef72d57c",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cryo_sbi",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.0 (default, Mar 3 2022, 09:58:08) [GCC 7.5.0]"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "1391d301e9aa4dc24331c4a52095d8473e5107d84c03241f78234deb9fd2437e"
+ }
+ },
+ "widgets": {
+ "application/vnd.jupyter.widget-state+json": {
+ "state": {},
+ "version_major": 2,
+ "version_minor": 0
+ }
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/models/hsp90_models.npy b/tutorials/hsp90_models.npy
similarity index 100%
rename from models/hsp90_models.npy
rename to tutorials/hsp90_models.npy
diff --git a/tutorials/image_anim.npy b/tutorials/image_anim.npy
new file mode 100644
index 0000000..08036e4
Binary files /dev/null and b/tutorials/image_anim.npy differ
diff --git a/tutorials/image_params_snr01_128.json b/tutorials/image_params_snr01_128.json
new file mode 100644
index 0000000..290d57f
--- /dev/null
+++ b/tutorials/image_params_snr01_128.json
@@ -0,0 +1,15 @@
+{"N_PIXELS": 128,
+"PIXEL_SIZE": 1.5,
+"SIGMA": 4.0,
+"MODEL_FILE": "hsp90_models.npy",
+"ROTATIONS": true,
+"SHIFT": true,
+"CTF": true,
+"NOISE": true,
+"DEFOCUS": 1.5,
+"SNR": 0.1,
+"RADIUS_MASK": 64,
+"AMP": 0.1,
+"B_FACTOR": 1,
+"ELECWAVE": 0.019866
+}
\ No newline at end of file
diff --git a/tutorials/quaternion_list.npy b/tutorials/quaternion_list.npy
new file mode 100644
index 0000000..0427858
Binary files /dev/null and b/tutorials/quaternion_list.npy differ
diff --git a/tutorials/resnet18_encoder.json b/tutorials/resnet18_encoder.json
new file mode 100644
index 0000000..a7084ba
--- /dev/null
+++ b/tutorials/resnet18_encoder.json
@@ -0,0 +1,12 @@
+{"EMBEDDING": "RESNET18",
+"OUT_DIM": 256,
+"NUM_TRANSFORM": 5,
+"NUM_HIDDEN_FLOW": 10,
+"HIDDEN_DIM_FLOW": 256,
+"MODEL": "NSF",
+"LEARNING_RATE": 0.0003,
+"CLIP_GRADIENT": 5.0,
+"THETA_SHIFT": 9.5,
+"THETA_SCALE": 9.5,
+"BATCH_SIZE": 512
+}
diff --git a/tutorials/square/config_square.json b/tutorials/square/config_square.json
deleted file mode 100644
index 3ac2a55..0000000
--- a/tutorials/square/config_square.json
+++ /dev/null
@@ -1,28 +0,0 @@
-{
- "IMAGES": {
- "N_PIXELS": 32,
- "PIXEL_SIZE": 2.0,
- "SIGMA": 2.0
- },
- "SIMULATION": {
- "N_SIMULATIONS": 10000,
- "MODEL_FILE": "../../models/square_models.npy",
- "DEVICE": "cpu",
- "ROTATIONS": false
- },
- "PREPROCESSING": {
- "SHIFT": true,
- "CTF": false,
- "NOISE": false,
- "DEFOCUS": 1.5,
- "SNR": 0.1
- },
- "TRAINING": {
- "MODEL": "maf",
- "HIDDEN_FEATURES": 10,
- "NUM_TRANSFORMS": 4,
- "DEVICE": "cpu",
- "BATCH_SIZE": 50,
- "POSTERIOR_NAME": "posterior.pkl"
- }
-}
\ No newline at end of file
diff --git a/tutorials/square/launch_gen_data_sbi.job b/tutorials/square/launch_gen_data_sbi.job
deleted file mode 100755
index 4c7ddb5..0000000
--- a/tutorials/square/launch_gen_data_sbi.job
+++ /dev/null
@@ -1,34 +0,0 @@
-#!/bin/bash -l
-
-# Standard output and error:
-#SBATCH -o ./sbi_data_gen.out.%j
-#SBATCH -e ./sbi_data_gen.err.%j
-# Initial working directory:
-#SBATCH -D ./
-# Job Name:
-#SBATCH -J SBI_Data_Gen
-#
-# Queue (Partition):
-#SBATCH --constraint=rome
-#SBATCH --partition=ccm
-#
-# Request 2 node(s)
-#SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=124
-#SBATCH --time=24:00:00
-
-module purge
-module load gcc/7
-module load python
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env_try/bin/activate
-
-CONFIG_NAME="config_square.json"
-
-python3 - << EOF
-from cryo_em_sbi import CryoEmSbi
-
-cryosbi = CryoEmSbi("$CONFIG_NAME")
-_, __ = cryosbi.simulate($SLURM_CPUS_PER_TASK)
-
-EOF
diff --git a/tutorials/square/launch_train_post_sbi_cpu.job b/tutorials/square/launch_train_post_sbi_cpu.job
deleted file mode 100644
index ab17f4d..0000000
--- a/tutorials/square/launch_train_post_sbi_cpu.job
+++ /dev/null
@@ -1,40 +0,0 @@
-#!/bin/bash -l
-
-# Standard output and error:
-#SBATCH -o ./sbi_train_post_cpu.out.%j
-#SBATCH -e ./sbi_train_post_cpu.err.%j
-#
-# Initial working directory:
-#SBATCH -D ./
-# Job Name:
-#SBATCH -J sbi_train_posterior_cpu
-#
-# Queue (Partition):
-#SBATCH --partition=ccm
-#SBATCH --constraint=rome
-#
-# Request 124 node(s)
-#SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=120
-#SBATCH --time=24:00:00
-
-module purge
-module load gcc/7
-module load python
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env_try/bin/activate
-
-CONFIG_NAME="config_square.json"
-
-python3 - << EOF
-import torch
-from cryo_em_sbi import CryoEmSbi
-
-cryosbi = CryoEmSbi("$CONFIG_NAME")
-
-indices = torch.load(NAME_OF_FILE_PREPROCESSED_INDICES)
-images = torch.load(NAME_OF_FILE_PREPROCESSED_IMAGES)
-
-_ = cryosbi.train_posterior(indices, images, $SLURM_CPUS_PER_TASK)
-
-EOF
diff --git a/tutorials/square/launch_train_post_sbi_gpu.job b/tutorials/square/launch_train_post_sbi_gpu.job
deleted file mode 100644
index e457a28..0000000
--- a/tutorials/square/launch_train_post_sbi_gpu.job
+++ /dev/null
@@ -1,42 +0,0 @@
-#!/bin/bash -l
-
-# Standard output and error:
-#SBATCH -o ./sbi_train_post_gpu.out.%j
-#SBATCH -e ./sbi_train_post_gpu.err.%j
-
-# Initial working directory:
-#SBATCH -D ./
-# Job Name:
-#SBATCH -J sbi_train_posterior
-#
-# Queue (Partition):
-#SBATCH --partition=gpu
-#SBATCH --constraint=a100,sxm4
-#
-# Request 124 node(s)
-#SBATCH --nodes=1
-#SBATCH --gpus-per-node=a100-40gb:4
-#SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=64
-#SBATCH --time=24:00:00
-
-module purge
-module load gcc/7
-module load python
-module load cuda
-source /mnt/home/dsilvasanchez/virtual_envs/sbi_env_try/bin/activate
-
-CONFIG_NAME="config_square.json"
-
-python3 - << EOF
-import torch
-from cryo_em_sbi import CryoEmSbi
-
-cryosbi = CryoEmSbi("$CONFIG_NAME")
-
-indices = torch.load(NAME_OF_FILE_PREPROCESSED_INDICES)
-images = torch.load(NAME_OF_FILE_PREPROCESSED_IMAGES)
-
-_ = cryosbi.train_posterior(indices, images, $SLURM_CPUS_PER_TASK)
-
-EOF
diff --git a/tutorials/square/tutorial.ipynb b/tutorials/square/tutorial.ipynb
deleted file mode 100644
index 676415b..0000000
--- a/tutorials/square/tutorial.ipynb
+++ /dev/null
@@ -1,440 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "from cryo_em_sbi import CryoEmSbi\n",
- "import torch\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "\n",
- "import sbi\n",
- "from tqdm import tqdm"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Introduction\n",
- "\n",
- "In this tutorial I will show you how to generate synthetic images, preprocess them (apply ctf, noise, and shifts), and train a posterior probability function using SBI. I will also show how to check if the posterior trained work how it's intended to work."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 1. The CryoEMSbi class\n",
- "\n",
- "This class takes an input file (config_square.json) at sets up everything required to do SBI using CryoEM data "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "cryosbi = CryoEmSbi(\"config_square.json\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2. Simulate\n",
- "\n",
- "In this step we are going to generate synthetic cryoEM images based on the values on the config file. The images are generated from 20 discrete models, and each model has equal probability to be used. The indices and images are automatically saved as `indices.pt` and `images.pt`. You can change this names by passing your desired names to the function below.\n",
- "\n",
- "If you want to use slurm to generate data, just launch `launch_gen_data.job` (Found in this same folder)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "60e65f61a4f242f6b09d4d8c276c5aca",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Running 10000 simulations in 10000 batches.: 0%| | 0/10000 [00:00"
- ]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "# Let's check how the images look\n",
- "indices = torch.load(\"indices.pt\")\n",
- "images = torch.load(\"images.pt\")\n",
- "\n",
- "plt.imshow(images[1].reshape(32, 32))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 3. Preprocessing\n",
- "To properly simulate CryoEM we need to add noise, apply CTF effects, and shift the images randomly. We do not generate images directly with this effects, as it would be expensive to generate new datasets for each combination of effects. Instead we create raw images, and then apply a desired combination of filters before training.\n",
- "\n",
- "The function below automatically saves indices and images as \"indices_training.pt\" and \"images_training.pt\".\n",
- "\n",
- "Additionally, if you use a cpu to generate images, but a gpu to train the posterior, the function below automatically changes everything to the required device.\n",
- "\n",
- "If you want to use slurm to run the preprocessing and the training just launch `launch_train_post_sbi_DEVICE.job`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "indices_training, images_training = cryosbi.preprocess(indices, images)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
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- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.imshow(images_training[350].reshape(32, 32))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 4. Training the posterior\n",
- "\n",
- "We use SBI to train the posterior. You can modify the type of model and the hyperparameters in the config file.\n",
- "\n",
- "If you want to use slurm to run the preprocessing and the training just launch `launch_train_post_sbi_DEVICE.job`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/mnt/home/dsilvasanchez/virtual_envs/sbi_env_try/lib/python3.8/site-packages/sbi/neural_nets/flow.py:141: UserWarning: In one-dimensional output space, this flow is limited to Gaussians\n",
- " warn(\"In one-dimensional output space, this flow is limited to Gaussians\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " Neural network successfully converged after 43 epochs."
- ]
- }
- ],
- "source": [
- "posterior = cryosbi.train_posterior(num_workers=32)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "If you already trained a network, or you trained it with slurm, you can load it with:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "ename": "FileNotFoundError",
- "evalue": "[Errno 2] No such file or directory: 'posterior.pkl'",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m/tmp/ipykernel_2169896/1753470154.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcryosbi\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"TRAINING\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"POSTERIOR_NAME\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mhandle\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mposterior\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'posterior.pkl'"
- ]
- }
- ],
- "source": [
- "import pickle\n",
- "\n",
- "with open(cryosbi.config[\"TRAINING\"][\"POSTERIOR_NAME\"], \"rb\") as handle:\n",
- " posterior = pickle.load(handle)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 5. Checking if the posterior works\n",
- "\n",
- "We can check that the posterior works by generating new images, and checking if it can pinpoint the model they were generated from."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "true_indices = torch.tensor(np.arange(0.0, 20.0, 1.0).reshape(20, 1))\n",
- "true_images = sbi.simulators.simutils.simulate_in_batches(\n",
- " cryosbi.simulator_analysis, true_indices, num_workers=1\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "plt.imshow(true_images[0].reshape(32, 32))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "n_samples = 10000\n",
- "samples = torch.zeros(20, n_samples, 1)\n",
- "\n",
- "for i in range(20):\n",
- "\n",
- " samples[i] = posterior.sample(\n",
- " (n_samples,), x=true_images[i], show_progress_bars=False\n",
- " )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, axes = plt.subplots(4, 5, figsize=(20, 20), sharex=True)\n",
- "fig.suptitle(\n",
- " f\"N_IMAGES: {cryosbi.config['SIMULATION']['N_SIMULATIONS']}, SNR:{cryosbi.config['PREPROCESSING']['SNR']}, Rotations\\nMAF\"\n",
- ")\n",
- "\n",
- "for i in range(4):\n",
- " for j in range(5):\n",
- "\n",
- " axes[i, j].hist(samples[i * 5 + j].numpy().flatten(), bins=30, histtype=\"step\")\n",
- " axes[i, j].axvline(x=i * 5 + j, color=\"red\")\n",
- " axes[i, j].set_title(f\"index = {i*5 + j}\")\n",
- " axes[i, j].set_yticks([])\n",
- " axes[i, j].set_xticks(range(0, 19, 4))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Recovering distributions"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Define your distribution"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# If you want to use an uniform distribution\n",
- "true_indices = cryosbi.prior_analysis.sample((5000,))\n",
- "\n",
- "# Example for a 2-well distribution\n",
- "\n",
- "\"\"\"\n",
- "import torch.distributions as D\n",
- "\n",
- "mix = D.Categorical(torch.ones(2,))\n",
- "comp = D.Normal(torch.tensor([7., 14.]), torch.tensor([2., 2.]))\n",
- "double_well_distribution = D.MixtureSameFamily(mix, comp)\n",
- "\n",
- "true_indices = double_well_distribution.sample((5000,))\n",
- "\n",
- "# Erase non-valid elementes (<0 or >19)\n",
- "\n",
- "true_indices = torch.round(true_indices)\n",
- "\n",
- "true_indices = true_indices[true_indices.round() <= 19.]\n",
- "true_indices = true_indices[true_indices.round() >= 0]\n",
- "\"\"\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_workers = 8\n",
- "batch_size = int(true_indices.shape[0] / num_workers)\n",
- "\n",
- "true_images = sbi.simulators.simutils.simulate_in_batches(\n",
- " cryosbi.simulator_analysis, true_indices, num_workers=32\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "n_samples = 1000\n",
- "samples = torch.zeros(true_indices.shape[0], n_samples, 1)\n",
- "\n",
- "for i in tqdm(range(true_indices.shape[0])):\n",
- " samples[i] = posterior.sample(\n",
- " (n_samples,), x=true_images[i], show_progress_bars=False\n",
- " )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "fig, ax = plt.subplots(1, 2, figsize=(15, 5))\n",
- "\n",
- "ax[0].hist(\n",
- " true_indices.numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"bar\", rwidth=0.8\n",
- ")\n",
- "ax[0].set_title(\"true distribution\")\n",
- "\n",
- "ax[1].hist(\n",
- " samples.numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"bar\", rwidth=0.8\n",
- ")\n",
- "ax[1].set_title(\"estimated distribution\")\n",
- "\n",
- "ax[0].set_xticks(np.arange(0, 20, 2))\n",
- "ax[1].set_xticks(np.arange(0, 20, 2));"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3.8.12 ('sbi_env_try')",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.12"
- },
- "orig_nbformat": 4,
- "vscode": {
- "interpreter": {
- "hash": "4c2a1af4c67af5391b40e9df2dd79293a2163069b42db13e0a4e4857b53919cf"
- }
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/tutorials/square/tutorial_cluster.ipynb b/tutorials/square/tutorial_cluster.ipynb
deleted file mode 100644
index 5247813..0000000
--- a/tutorials/square/tutorial_cluster.ipynb
+++ /dev/null
@@ -1,405 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "from cryo_em_sbi import CryoEmSbi\n",
- "import sbi\n",
- "import torch\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import tqdm"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 1. Configure your config file\n",
- "\n",
- "Go to your config file and set all the parameters."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 2. Run the script to generate images\n",
- "\n",
- "Run `launch_gen_data.job`. The clean images and the indices will be saved automatically after the run as \"images.pt\" and \"indices.pt\". Alternatively you can edit this line in the .job file `_, __ = cryosbi.simulate($SLURM_CPUS_PER_TASK)` for something like `_, __ = cryosbi.simulate($SLURM_CPUS_PER_TASK, fname_indices=fname_for_indices.pt, fname_images=fname_for_images.pt)` if you want different names or you want to specify a path for the clean images."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 3. Load generated images and preprocess them LOCALLY\n",
- "\n",
- "Check again the parameters you set for preprocessing in the config file!!"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "cryosbi = CryoEmSbi(\"config_square.json\")\n",
- "\n",
- "# Edit the filename if you used something else!\n",
- "indices = torch.load(\"indices.pt\")\n",
- "images = torch.load(\"images.pt\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
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- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "# Let's check how the images look for peace of mind\n",
- "\n",
- "plt.imshow(images[1].reshape(32, 32))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 4. Preprocessing\n",
- "To properly simulate CryoEM we need to add noise, apply CTF effects, and shift the images randomly. We do not generate images directly with this effects, as it would be expensive to generate new datasets for each combination of effects. Instead we create raw images, and then apply a desired combination of filters before training.\n",
- "\n",
- "The function below automatically saves indices and images as \"indices_training.pt\" and \"images_training.pt\".\n",
- "\n",
- "You DON'T need to use a GPU here. I set it so the preprocessing uses the same device as the simulation. If you generated data with a CPU, you preprocess with a CPU. If you generated data with a GPU, then you do need a GPU for preprocessing.\n",
- "\n",
- "Alternatively if you don't want to use a GPU for preprocessing, you should edit your config file to have a simulating device = \"cpu\" and load the indices/images in step 3 as\n",
- "\n",
- "```\n",
- "indices = torch.load(\"indices.pt\").to(\"cpu\")\n",
- "images = torch.load(\"images.pt\").to(\"cpu\")\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "ename": "NameError",
- "evalue": "name 'cryosbi' is not defined",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m/tmp/ipykernel_2460446/201047471.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mindices_training\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimages_training\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcryosbi\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpreprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindices\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimages\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;31m# You can set different names for the preprocessed indices and images\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m# indices_training, images_training = cryosbi.preprocess(\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mNameError\u001b[0m: name 'cryosbi' is not defined"
- ]
- }
- ],
- "source": [
- "num_workers = 4\n",
- "batch_size = int(images.shape[0] / num_workers)\n",
- "\n",
- "indices_training, images_training = cryosbi.preprocess(\n",
- " indices, images, num_workers=num_workers, batch_size=batch_size\n",
- ")\n",
- "\n",
- "# You can set different names for the preprocessed indices and images\n",
- "\n",
- "# indices_training, images_training = cryosbi.preprocess(\n",
- "# indices,\n",
- "# images,\n",
- "# fname_output_indices=fname_for_indices.pt,\n",
- "# fname_output_images=fname_for_images.pt\n",
- "# )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
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- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "# Again, check images for peace of mind\n",
- "\n",
- "plt.imshow(images_training[1].reshape(32, 32))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 5. Training the posterior\n",
- "\n",
- "Since you did the preprocessing here, you don't need to do it in the .job file. PLEASE be careful when you load the indices and the images in the .job files. Be sure that you are loading the files you want to train with."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 6. Loading posterior and checking how everything turned out"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "import pickle\n",
- "\n",
- "# Be careful here! If the name of your posterior is different to the one you have in your config file, replace\n",
- "# cryosbi.config[\"TRAINING\"][\"POSTERIOR_NAME\"] for \"name_of_posterior_file.pkl\"\n",
- "\n",
- "with open(cryosbi.config[\"TRAINING\"][\"POSTERIOR_NAME\"], \"rb\") as handle:\n",
- " posterior = pickle.load(handle)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 5. Checking if the posterior works\n",
- "\n",
- "We can check that the posterior works by generating new images, and checking if it can pinpoint the model they were generated from."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "true_indices = torch.tensor(np.arange(0.0, 20.0, 1.0).reshape(20, 1))\n",
- "true_images = sbi.simulators.simutils.simulate_in_batches(\n",
- " cryosbi.simulator_analysis, true_indices, num_workers=1\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "plt.imshow(true_images[0].reshape(32, 32))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "n_samples = 10000\n",
- "samples = torch.zeros(20, n_samples, 1)\n",
- "\n",
- "for i in range(20):\n",
- "\n",
- " samples[i] = posterior.sample(\n",
- " (n_samples,), x=true_images[i], show_progress_bars=False\n",
- " )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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AAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0OYWquqOqHnfCx/5gVT19thUBid6EXulN6I++hD7pTS4R2pxCa+0RrbVbh65jFqrqk6vqd6vqXVX1i1X1sKFrgpNalt6sqnNV9eKqulhV7aRv3NCLJerNT6iq/1xVb6mqN1bVi6rqrwxdF5zEEvXlR1fVbVX11unlF6rqo4euC05qWXrzsKr6puln2k8ZupZFIrQhVXVTkh9P8g1JPjDJbUleMGhRwCUvT/KFSd4wdCHAX/iAJN+T5HyShyV5e5IfGLIgIK9P8g8z+Sx7U5KXJPmxQSsC/kJVfXgmPfpHQ9eyaIQ2pzA9+v0p05+fVlUvrKrnVtXbp8PZHnvovh9TVbdPb3tBkhsv29anVdWvV9W4qn6lqh41vf4JVfWaqnrQ9PfHV9UbquohM3wqn53kjtbai1prf5bkaUkeXVX/ywz3AXOzLL3ZWrurtfbM1trLk9wzq+3CUJaoN39m+p75p621dyV5dpKtWW0f5mmJ+nLcWrvYWmtJKpP3zY+Y1fZh3palNw95dpJ/meSuM9j2UhPazNZnZJLob2SS7j87mUxxSPKfkjwvk/T/RUk+59KDquqWJN+f5MuTPDjJc5K8pKru21p7QZJXJHlWVT04yfcleXJr7Y1XKmDaiFe77Fyl7kck+Y1Lv7TW3pnk96fXwzJY1N6EZbcsvflJSe443lOHbi10X1bVOMmfJfn3SZ5xspcAurSwvVlV/yjJXa21l53qFVhRQpvZenlr7WWttXsyaZpHT6//hCT3SfLM1tp7WmsvTvLKQ4/70iTPaa39WmvtntbaDyV59/RxSfKVSbaT3Jrkp1prP321AlprG9e4jK7ysAckedtl170tyQOP/Myhb4vam7DsFr43p0crvzHJ1x/rmUO/FrovW2sbSd4/yVcl+f+O+dyhZwvZm1X1gEwC1K856RNfdUKb2Tq85sS7ktxYVWtJHppkfzpc85LXHvr5YUm+7nBSmeRDpo9La22cSWL6yCTfdgZ1vyPJgy677kGZzNGHZbCovQnLbqF7s6o+IsnPJPnq1tovn9V+YM4Wui+n+3pnku9O8tyq+qCz3BfM0aL25r9O8rzW2h+cwbZXgtBmPv4oyWZV1aHrbj708x8m+ebLksr7tdaenyRV9ZgkX5Lk+Umeda0dVdU7rnF56lUedkfem9Smqu6f5MNjqDfLr/fehFXVfW/W5CyLv5Dk37bWnneypwkLpfu+vMz7Jblfks0j3h8WVe+9+clJnlKTtXLekElg9MKq+pcne7qrR2gzH69Icncm/7GuVdVnJ/m4Q7d/b5J/VlUfXxP3r6oLVfXAqroxyQ8neWqSL86kIb/iajtqrT3gGperzev9iSSPrKrPme7vG5P8Zmvtd2fw3KFnvfdmquq+030lybmquvGyN2VYRl33ZlVtJtlN8h2tte+e0XOG3vXel3+3Joux3lCTRVX/nyRvTfI7s3n60K2uezOT0OaRSR4zvbw+k/V1vuN0T3t1CG3moLV2VyZnaPqiTN48npDJKbYv3X5bJnMNnz29/fem902Sb0nyutbad7XW3p3JqX+fXlUfOcP63pjJYlXfPN3/xyf5vFltH3rVe29OvTrJQSZHCn9u+vPDZrwP6MoC9OaTk3xYkm86fJRxhtuH7ixAX25kMlLgbZmcUOMjkvy9NjkzKiyt3nuztfbm1tobLl0yObPbW1tr3jePqO499Q0AAACAHhhpAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDAAAA0KG149z5pptuaufPn7/yja9+9eTfhz/8lCVBn171qle9qbX2kKHruJJr9uZR6WEWVK+9OZO+PCr9S4f05hHpX+ZMb86Q/mWGrtabxwptzp8/n9tuu+3KNz7ucZN/b731uLXBQqiq1w5dw9VcszePSg+zoHrtzZn05VHpXzqkN49I/zJnenOG9C8zdLXeND0KAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDZxLanN956VlsFjhjv/qaNw9dAnACt985zu13jocuAzih2+8cZ2u0O3QZwAn4/MxZWxu6AADgdO66+56hSwBO4a6778n++GDoMgDokOlRwL040gcAANCHMwttfPGDxXL7neOcW7vBkT4AAIBOnFlo44sfLJa77r4nt9y8MXQZAAAATM08tNka7WZzY33WmwUAAABYKTMPbfbHB9nb2Z71ZgEAYOlcmp4MAFdiIWIAABiI6cmwuG6/czx0CawAoQ0AAAAc011335Nzazc4CQ9nSmgDAAAAJ3DLzRtOwsOZEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2QLZGu043CgAA0BmhDZD98YHTjQIAAHRGaAMAAADQIaENAAAAQIeENgCwwKxJBQCwvIQ2ALDArEkFALC8hDYAAAAAHRLaAAAAAHRIaAMAAADQoTMLbTY31rM12j2rzQMAwEKzkDgA13Nmoc3eznb2xwdntXkAAFhoFhIH4HpMjwIAAADokNAGAAAAoENCGwAAAIAOCW2Ae7GIOAAAQB+ENsC9WEQcAACuzdnfmBehDQAsgXNrNxglBwBz4uxvzMtMQ5vb7xxnc2N9lpsEAI7glps3jJIDAFgyMw1t7rr7nuztbM9ykwAAAAAryfQoAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAAA4oc2N9WyNdocugyUltAEAAIAT2tvZzv74YOgyWFJCGwAAAIAOCW0AAAAAOiS0AYAFtTXazebG+tBlAABwRoQ2ALCg9scH2dvZHroMAADOiNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAAa2ubGerdHu0GUA0BmhDQAADGxvZzv744OhywCgM0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltgPfhtKMAAADDE9oA78NpRwEAAIYntAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAlsTmxnq2RrtDlwEAwIwIbQBgSeztbGd/fDB0GQAAzIjQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOnWlos7mxnq3R7lnuAgAAAGApnWlos7eznf3xwVnuAgAAAGApmR4FAAAAp2CWCWdFaAMAAACnYJYJZ0VoAwAAANAhoQ0AAABAh4Q2sOK2RrvZ3FgfugwAAAAuI7SBFbc/PsjezvbQZQDHJHAFAFh+a0MXAAAc3/74IBdHF4YuAwCAM2SkDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAHRgc2M9W6PdocsAoCNCGwAA6MDeznb2xwdDlwFAR4Q2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENACyRzY31bI12hy4DAIAZENoAwBLZ29nO/vhg6DIAYGltjXazubE+dBmsCKENAADMmS99sLj2xwfZ29keugxWhNAGAADmzJc+AI5CaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDaywrdFuNjfWhy4DAACAK1gbugBgOPvjg1wcXRi6DAAAAK7ASBsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ2ce2mxurGdrtHvWuwEAAABYKmce2uztbGd/fHDWuwEAAABYKqZHAVdklBz0a2u0m82N9aHLAADgjAltgCsySg76tT8+yN7O9tBlAABwxoQ2AADQCSNdAThMaAMAAJ0w0hWAw4Q2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAABHsDXazebG+tBlsELWhi4AAAAAFsH++CAXRxeGLoMVYqQNAAAAQIeENgAAAAAdEtoAwJLZ3FjP1mh36DKAq7AmBgBHJbSBFeUDIyyvvZ3t7I8Phi4DuIr98UH2draHLgOABWAhYlhRFlEDAADom5E2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAABwSpsb69ka7Q5dBktGaAMAAACntLeznf3xwdBlsGSENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDXNXmxnq2RrtDlwEAALCShDbAVe3tbGd/fDB0GQAAACtJaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAMB1bI12s7mxPnQZrJi1oQsAAACA3u2PD3JxdGHoMlgxRtoAAAAAdGguoc3mxnq2Rrvz2BUAAADAUphLaLO3s5398cE8dgUAAACwFEyPAgAAAOiQ0AYAAObE2WcAOA5njwIAgDlx9hkAjsNIGwAAAIAOCW0AAAAAOiS0AYAltLmxnq3R7tBlAABwCkIbAFhCezvb2R8fDF0GAACnILQBAAAA6JDQBgAAAGbA9GRmTWgDAAAAM2B6MrMmtAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAFsjWaDebG+tDlwEAwBysDV0AAHB0++ODXBxdGLoMAADmwEgbAAAAgA4JbQAAAAA6JLQBAICObG6sZ2u0O3QZAHRAaAMAAB3Z29nO/vhg6DIA6IDQBlaQs88AAAD0z9mjYAU5+wwAAED/jLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAGAJbW5sZ6t0e7QZQBTzt4IwHEJbQBgSe3tbGd/fDB0GcDU/vggezvbQ5cBwAKZW2jjaB8sJr0LAABH5/MzszS30MbRPlhMehcAAI7O52dmyfQoAAAAgA4JbQAAAAA6JLQBAAAA6JDQBlaM043C4tK/AACrZW3oAoD52h8f5OLowtBlACegfwEAVouRNgAAAAAdEtoAAEBnNjfWszXaHboMAAYmtAEAgM7s7Wxnf3wwdBkADExoAwAAANfgZAAMxULEAAAAcA1OBsBQjLQBAAAA6JDQBrguiyECAADMn9AGuC6LIQIAAMyf0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBgAWwNdrN5sb60GUAADBHcw1tnIEGAE5mf3yQvZ3tocsAAGCO5hraOAMNAAAAi8RoV4ZkehQAAHTIKHXog9GuDEloAwAAHTJKHQChDXAkjvbBYtK7AACLS2gDHImjfbCY9C70wZoYsFocNGFWhDYAAHDGrIkBq8VBE2ZFaAMrxFE+AAA4Op+fGdra0AUA87M/PsjF0YWhywCOyQdGABiGz88Mbe4jbcztA4DjMa0CFttpglefnQFW29xDG3P7YBiO1MPq8qUPhnWa4NVnZ1hc3n+ZBWvawIpwpB4W0ywCV1/6AGD+vP8yC0Ib4MgcLYD5E7gCAKyuQUIbX/xgvmY1NerSF0f9C4vHey8Mw/RkAE5jkNDGFz+Yr1keqde/MD+z/LKnd2EYs3gPFrrC/G2NdnN+56Wnfh/Wv5xWtdaOfueqNyZ57TXuclOSN522qBlT09Go6foe1lp7yNBFXInenBk1HU1vNXXZm0foy6S/1zJR01Gp6fr05myp6Wh6q6m3ehK9OWtqOpreauqtnuQqvXms0OZ6quq21tpjZ7bBGVDT0ahpufX4WqrpaNS03Hp8LdV0NGpabj2+lmo6mt5q6q2eRdfj66mmo+mtpt7quRYLEQMAAAB0SGgDAAAA0KFZhzbfM+PtzYKajkZNy63H11JNR6Om5dbja6mmo1HTcuvxtVTT0fRWU2/1LLoeX081HU1vNfVWz1XNdE0bAAAAAGbD9CgAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktDmFqrqjqh53wsf+YFU9fbYVAYnehF7pTeiPvoQ+6U0uEdqcQmvtEa21W4eu47Sq6nxVtap6x6HLNwxdF5zUsvRmklTV/arqO6vqTVX1tqr6paFrgpNalt6sqi+47D3zXdP30Y8dujY4rmXpyySpqs+tqt+pqrdX1X+vqs8cuiY4qSXrzSdX1e9N3zN/tqoeOnRNi0Row2EbrbUHTC//duhigCTJ9yT5wCQfNf33fx+2HKC19iOH3i8fkOQrkrwmye0DlwYrq6o2k/xwkq9N8qAkX5/kR6vqgwYtDFZcVf3tJM9I8g8y+Sz7B0meP2hRC0ZocwpVdbGqPmX689Oq6oVV9dxpun9HVT320H0/pqpun972giQ3XratT6uqX6+qcVX9SlU9anr9E6rqNVX1oOnvj6+qN1TVQ+b4VGGhLEtvVtXDk3xGki9rrb2xtXZPa+1Vs9o+zNuy9OYVPCnJc1tr7Qz3AWdiifryg5OMW2s/0yZemuSdST58hvuAuVmi3vz0JC9qrd3RWrsryb9N8klVpTePSGgzW5+R5MeSbCR5SZJnJ0lVnUvyn5I8L5N08UVJPufSg6rqliTfn+TLkzw4yXOSvKSq7ttae0GSVyR5VlU9OMn3JXlya+2NVypg2ohXu+xcp/7XVtXrquoHquqmE74G0KNF7c2PT/LaJP+6JtOjfquqPucq94VFtKi9efjxD0vySUmee5IXADq0qH15W5LfqarPqKobajI16t1JfvMUrwX0ZFF7s6aXw78nySOP+wKsKqHNbL28tfay1to9mTTNo6fXf0KS+yR5ZmvtPa21Fyd55aHHfWmS57TWfm16JP2HMnmT+YTp7V+ZZDvJrUl+qrX201croLW2cY3L6CoPe1OSv57kYUk+NskDk/zICZ4/9GpRe/ODM3lDe1uShyb5qiQ/VFUfdYLXAHq0qL152BOT/HJr7Q+O8byhZwvZl9N6n5vkR6f7/dEkX95ae+fJXgbozkL2ZpKXJfncqnpUVa0n+cYkLcn9TvIirCKhzWy94dDP70pyY1WtZfJla/+yYdOvPfTzw5J83eGkMsmHTB+X1to4k8T0kUm+bdZFt9be0Vq7rbV2d2vtjzP5Yvipl4bJwRJYyN5McpDkPUme3lq7q7X2X5P8YpJPPYN9wRAWtTcPe2KSHzrjfcA8LWRfTqeRfGuSxyU5l+RvJ/kPVfWYWe8LBrKQvdla+y9JvinJf5zWdTHJ25O8btb7WlZCm/n4oySbVXV4WNjNh37+wyTffFlSeb/W2vOTZPpm8yWZLNj0rGvtqO59NovLL089Yr2XGr6ueS9YfL33piHdrKree/PSY7cy+dD74uM/RVg4vfflY5L80vRA5J+31l6Z5NeSfMqJni0sjt57M62172itfWRr7YMyCW/Wkvz2iZ7tChLazMcrktyd5ClVtVZVn53k4w7d/r1J/llVfXxN3L+qLlTVA6vqxkxWwn9qki/OpCG/4mo7aofOZnGFyzOu9Jjpfh9eVe83ncv4rCS3ttbeNqPnD73qujeT/FKSO5P8q2l9W5kcQfy5Uz9z6FvvvXnJk5L8x9ba20/1bGEx9N6Xr0zyiZdG1lTVxyT5xDgAwvLrujer6saqeuR03zdncmbU/7e19tYZPf+lJ7SZgzZZJfuzk3xRkrcmeUKSHz90+22ZzDV89vT235veN0m+JcnrWmvf1Vp7d5IvTPL0qvrIGZb4YUl+NpNhar+dyRzHz5/h9qFLvfdma+09mZwe8e9nsq7N9yZ5Ymvtd2e1D+hR772ZTD6EJvncmBrFiui9L6dTiJ+W5MVV9fZMjuY/o7X287PaB/So997M5ExWP5rkHUn+WyYh0zfMcPtLr5qzUwIAAAB0x0gbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDa8e580033dTOnz9/RqUM5NWvnvz78IcPWwfde9WrXvWm1tpDhq7jSpayN49KD6+8XntzpfvyqPTvUtObS07/Liy9if7t09V681ihzfnz53PbbbfNrqoePO5xk39vvXXIKlgAVfXaoWu4mqXszaPSwyuv195c6b48Kv271PTmktO/C0tvon/7dLXeND0KAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDKx/a3H7nOLffOR66DOAUbr9znK3R7tBlAKewNdrVx7BgfvU1bx66BOCEfH5eHGtDFzC0u+6+Z+gSgFO66+57sj8+GLoM4BT0MADMj8/Pi2OlR9psjXZzbu2GocsAAAAAeB8rHdrsjw9yy80bQ5cBAAAA8D5WOrQBAABOzpoYAGdLaAMAAJyINTFgcW1urAteF4DQBgAAAFbM3s624HUBCG0AAAAAOiS0ARba7XeOnQUOAABYSkIbYKHddfc9zgIHAAAsJaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAMamu0m82N9aHLAADojtAmybm1G7I12h26DABYSfvjg+ztbA9dBnACmxvrPkcDnCGhTZJbbt7I/vhg6DIAAGCh7O1s+xwNcIaENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAwLHcfuc459ZuGLoMgKUntAEAAI7lrrvvyS03bwxdBsDSE9oAS2FzYz1bo92hywAAAJgZoQ2wFPZ2trM/Phi6DOAUhK8AAPcmtAEAuiB8BQC4N6ENAAAAQIeENgAAAAAdEtoAAIO5/c5xNjfWhy4DAKBLQhsAYDB33X1P9na2hy4DOAWLiAOcHaENAABwYhYRh8Vy+53jnFu7YegyOCKhDQAAAKyIu+6+J7fcvDF0GRyR0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6NDKhjZbo91sbqwPXQYAAADAFa1saLM/PsjezvbQZQAAAABc0cqGNgAAAAA9E9oAAAAAdEhoAwAAANAhoQ2wsLZGuzm3dsPQZQAAAJwJoQ2wsPbHB7nl5o2hywAAADgTQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAA4MicvRFgfoQ2AADAkTl7I8D8CG0AAABgBW1urGdrtDt0GVyD0AYAAABW0N7OdvbHB0OXwTUIbYCl4UgBAACwTIQ2wNJwpAAAAFgmQhsAAACADgltAAAAADoktAEAAADokNAGAOiGBcUBAN5LaAMAdMOC4gAA7yW0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAABYAVuj3Zxbu2HoMjgGoQ2wkLZGu9ncWB+6DOAUbr9z7IMjAMzR/vggt9y8MXQZHIPQBlhI++OD7O1sD10GcAp33X2PD44AANcgtAEAAADo0EqGNqZVAAAAAL1bG7qAIeyPD3JxdGHoMgAAAACuaiVH2gAAAAD0TmgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENlObG+vZGu0OXQYAAABAEqHNX9jb2c7++GDoMgAAAACSCG0AAAAAuiS0AQAAAOiQ0AYAAACgQ0IbAAAAWFFOytM3oQ0AAACsKCfl6ZvQBlgqjhQAAADLQmgDLBVHCgAAgGUhtAEAAADokNAGAAAAoENCGwAAAIAOCW0AAIAj2RrtZnNjfegyAFaG0AYAADiS/fFB9na2hy4DYGUIbQAAAAA6JLQBALqyubGerdHu0GUAAAxOaAMAdGVvZzv744OhywAAGJzQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAABOZXNjPVuj3aHLAFg6QhsAAOBU9na2sz8+GLoMgKUjtAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0OcSq9wAAAEAvVi602RrtZnNj/Yq3WfUeFsO1+hgAAGBZrA1dwLztjw9ycXRh6DKAU9DHAADAKli5kTYAAAAAi0BoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAS2dzYz1bo92hywAAADgVoQ2wdPZ2trM/Phi6DAAAgFMR2gAAAAB0SGgDAAAA0CGhDQAAACy5rdFuNjfWhy6DYxLaAADdsaA4AMzW/vggezvbQ5fBMQltAIDuWFAcAEBoAwAAANAloQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAzN3WaDfn1m4YugwAgK4JbQCAudsfH+SWmzeGLgOYoc2N9WyNdocuA2CpCG0AAIBT29vZzv74YOgyAJaK0AYAAACgQ0KbyxjWCQAAwCrxPbhfQpvLGNYJAADAKvE9uF9CGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhtgKW1urGdrtDt0GQAAACcmtAGW0t7OdvbHB0OXAQAAcGJCGwAA4Lq2RrvZ3FgfugyAlbI2dAEAAED/9scHuTi6MHQZACvFSBsAAABYYkbKLS4jbQAAAGCJGSm3uIy0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwBgrrZGu9ncWB+6DACA7q1UaONDIiw+fQyLb398kL2d7aHLAAAO2dxYz9Zod+gyuMxKhTY+JMLi08cAADB7ezvb2R8fDF0Gl1mp0AYAAABgUQhtAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAALimrdFuNjfWhy4DYOWsDV0AAADQt/3xQS6OLgxdBnACQtfFJrQBAACAJSV0XWymRwEAAAB0SGgDAHRpc2M9W6PdocsAABiM0AYA6NLeznb2xwdDlwEAMJiVCW0svgQAAAAskpVZiNjiSwAAAMAiWZmRNgAAwNmyFhXAbAltAACAmbAWFcBsCW2uwBEC6JO1qWDx6WMA6Jfvwv0R2lyBIwTQp/3xQfZ2tocuAzgFfQwA/fJduD9CGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAALgqC4gDDEdoAywtq98DwOlZQBxgOEIbYGlZ/R4AAFhkQhsAoFtGzAEAq0xoAwB0y4g5AGCVCW0AAAAAOiS0AQAAZsa0RoDZWYnQ5iSnKfRmA31xulFYfPoYVoNpjQCzsxKhzUlOU+jNBvridKOw+PQxAMDxrERoAwAAALBohDbAUjPVEQAAWFRCG2CpmeoIAMCqsp7c4hPaAABdM2IOAE7GenKLT2gDAHTNiDkAmB8HS/oitAEAAGbKlz5YXA6W9EVoA3TPXFwAWCy+9AHMxtrQBQBcz/74IBdHF4YuAwAAYK6MtAGWniHaAHAyRrvC4tK/y2HpQxv/oQKGaAPAyTjzDCyu0/Svg579WPrQxhsNLDbBKywHvQwAi8NBz34sfWhzGtJFGN6sglf9DMNyEAUWj7AVYHhLHdqc9o3m0odLX/Rg8elnGM4svvgJXmH+Thu26lsYjtB1eSzl2aO2RrvZHx9kc2P91Ef19na2szXazfmdl85ke8D1XerhJDN9s7nUz1ujXb0MZ+zyPp7l+/Gstglc2eHP0qehb2EYl8LS0/bb5sa678EdqNba0e9c9cYkr73GXW5K8qbTFjVjajoaNV3fw1prDxm6iCvRmzOjpqPpraYue/MIfZn091omajoqNV2f3pwtNR1NbzX1Vk+iN2dNTUfTW0291ZNcpTePFdpcT1Xd1lp77Mw2OANqOho1LbceX0s1HY2alluPr6WajkZNy63H11JNR9NbTb3Vs+h6fD3VdDS91dRbPdey1GvaAAAAACwqoQ0AAABAh2Yd2nzPjLc3C2o6GjUttx5fSzUdjZqWW4+vpZqORk3LrcfXUk1H01tNvdWz6Hp8PdV0NL3V1Fs9VzXTNW0AAAAAmA3TowAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQ5hqq6o6oed8LH/mBVPX22FQGJ3oRe6U3ok96EPulNrkRocwyttUe01m4duo7TqqpzVfXiqrpYVe3y/zHUxL+rqjdPL99aVTVMtXB9K9Sbf6eqfrGq3lZVFwcpEo5hhXrz66vqt6vq7VX1B1X19cNUCkezQr35NVX1mqr606p6fVV9e1WtDVMtXN+q9OZl9/vdqnrdfCtcLEKb1fXyJF+Y5A1XuO3LknxmkkcneVSST0vy5XOrDFbbtXrznUm+P4kvhDB/1+rNSvLEJB+Q5O8l+aqq+rw51gar7Fq9+VNJbmmtPSjJIzP5bPuUOdYGq+xavXnJ1yf5k/mUs7iENscwTQo/Zfrz06rqhVX13OmRtTuq6rGH7vsxVXX79LYXJLnxsm19WlX9elWNq+pXqupR0+ufMD0i8KDp74+vqjdU1UNm9Txaa3e11p7ZWnt5knuucJcnJfm21trrWmv7Sb4tyRfNav8wa6vSm621/9Zae16S18xqn3CWVqg3v7W1dntr7e7W2quT/GSSrVntH2ZthXrz91tr40ulJvnzJB8xq/3DrK1Kb073+6GZhDrfMqv9Liuhzel8RpIfS7KR5CVJnp1Mhnkl+U9JnpfkA5O8KMnnXHpQVd2SydHyL0/y4CTPSfKSqrpva+0FSV6R5FlV9eAk35fkya21N16pgGkTXu2yc8Ln9Ygkv3Ho99+YXgeLYll7Exbd0vdmVVWST0xyx2m3BXO0tL1ZVf+4qv40yZsyGWnznJNuCwawtL2Z5N8neWqSg1NsYyUIbU7n5a21l7XW7smkYR49vf4TktwnyTNba+9prb04ySsPPe5LkzyntfZrrbV7Wms/lOTd08clyVcm2U5ya5Kfaq399NUKaK1tXOMyOuHzekCStx36/W1JHjD9IAqLYFl7ExbdKvTm0zL5fPUDM9gWzMvS9mZr7Uen06P+apLvTvLHJ90WDGApe7OqPivJWmvtJ07y+FUjtDmdw/Pz3pXkxposbvbQJPuttXbo9tce+vlhSb7ucEqZ5EOmj8t0GOeLMpl7+21nV/5VvSPJgw79/qAk77js+UDPlrU3YdEtdW9W1VdlsrbNhdbau4eqA05gqXtzWsv/zGQE3HcOWQcc09L1ZlXdP8m3Jvnn89zvIhPanI0/SrJ52ciUmw/9/IdJvvmylPJ+rbXnJ0lVPSbJlyR5fpJnXWtHVfWOa1yeesL678h7U9xMfzbMm2Ww6L0Jy2rhe7OqviTJTpJPbq05CwbLYuF78zJrST58RtuCIS1yb35kkvNJfrmq3pDkx5P8lZqsq3P+BNtbekKbs/GKJHcneUpVrVXVZyf5uEO3f2+Sf1ZVH18T96+qC1X1wKq6MckPZzK/74szacavuNqOWmsPuMblGVd7XFXdd7qvJDlXVTceavrnJvnaqtqsqocm+bokP3jC1wJ6stC9WVXvN73tPpNf68aazGmGRbfovfkFSZ6R5O+21iwUzjJZ9N58clV90PTnj07yr5L8l5O/HNCNRe7N385k1M9jppcnZzJt8TGZhE1cRmhzBlprdyX57EzOuPTWJE/IJEG8dPttmcwzfPb09t/Le8/O9C1JXtda+67p0OovTPL0qvrIGZf56kwWfdpM8nPTnx82ve05mZwi8bcyaaqXxqJtLIEl6M1Pmv7+skyOphwk+fkZ7x/mbgl68+mZLPT4ykNHH797xvuHuVuC3txK8ltV9c5M3jtflskXVVhoi9ybbXKmxTdcuiR5S5I/n/5+xTNNrbqyTAkAAABAf4y0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6NDace580003tfPnz59RKRzbq189+ffhDx+2jhXxqle96k2ttYcMXceV6M0FpH9nptfe1JdLTP8eid6kS/pXb7K4lrx/r9abxwptzp8/n9tuu212VXE6j3vc5N9bbx2yipVRVa8duoar0ZsLSP/OTK+9qS+XmP49Er1Jl/Sv3mRxLXn/Xq03TY8CAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0GYJbI12szXaHboM4Ii2Rru5/c7x0GUAJ6B/YXHpX1hst985XskeXhu6AE5vf3wwdAnAMeyPD3LX3fcMXQZwAvoXFpf+hcW2qv1rpA0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDAHAM59ZuWMmFEAGA+RPaAAAcwy03b6zsYogAwHwJbQAAAAA6JLQBAAAA6JDQBgAAAOjW1mg359ZuGLqMQQhtAOZoa7SbzY31ocsAAICFsT8+yC03bwxdxiCENgvu9jvHvgDCAtkfH2RvZ3voMgAAgAUgtFlwd919jy+AAAAAsISENgAAAAAdEtosic2N9WyNdocuAwAAAJgRoc2S2NvZzv74YOgyAAAAgBkR2gAAACvh3NoNuf3O8dBlAByZ0AYAAFgJt9y8kbvuvmfoMgCOTGgDAAAA0CGhDcAADM8GAACuR2gDMADDswEAgOsR2gAAAAB0SGgDAHBM59ZuyNZod+gyAIAlJ7QBADimW27eyP74YOgygCPaGu1mc2N96DIAjk1oAwAALLX98UH2draHLgM4pVUc6Sq0AQAAALq3iiNdhTYL7PY7xzm3dsPQZQAAAABnQGizwO66+57ccvPG0GUAAAAAZ0BoAzAnFkEEAACOY23oAgBWxf74IBdHF4YuAwAAWBBG2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAwMo4t3ZDtka7Q5cBcCRCGwAAYGXccvNG9scHQ5cBcCRCGwAAAIAOCW0AAI5ga7SbzY31ocsAAFaI0AYA4Aj2xwfZ29keugwAYIUIbQAAAAA6JLQBAAAAurTq05OFNgAAAECXVn16stBmiWxurGdrtDt0GQAAAMAMCG2WyN7OdvbHB0OXAQAAAMyA0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBmAg59ZucMY3AADgqoQ2AAO55eYNZ3wDAACuSmgDAAAA0CGhDQAAsLS2RrvZ3FgfugyAE1kbugAAAICzsj8+yMXRhaHLADgRI20AAAAAOiS0AQAAAOiQ0AYAAABYCJsb69ka7Q5dxtwIbQAAAICFsLeznf3xwdBlzI3QBgAAAKBDQhuAOXC6UQAA4Lic8htgDpxuFAAAOC4jbQAAAAA6JLQBAAAA6JDQZkFtjXZzbu2GocsAAAAAzojQZkHtjw9yy80bQ5cBAAAAnBGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhos2Q2N9azNdodugwAAADglIQ2S2ZvZzv744OhywAAAABOSWgDAAAA0CGhDQAAAECHhDYAANexNdrN5sb60GUAACtmbegCAAB6tz8+yMXRhaHLAICV4qCJ0AYAAADokIMmpkcBAAAAdEloAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAAB0SGgDMKDNjfVsjXaHLgMAAOiQ0AZgQHs729kfHwxdBgAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwBwApsb69ka7Q5dBgCwxIQ2AAAnsLeznf3xwdBlAABLTGgDAAAALIxVGu0qtFlAW6PdbG6sD10GAAAAzN0qjXYV2iyg/fFB9na2hy4DOCJBKwAAcBJrQxcAsOz2xwe5OLowdBkAAMCCMdIGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAABWyubGerZGu0OXAXBdQhsAAGCl7O1sZ398MHQZANcltAEAAADokNAGAAAAoENCGwCAa9ga7WZzY33oMgCAFbQ2dAEAAD3bHx/k4ujC0GUAACvISBsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAa2ubGerdHu0GUAAACdEdoADGxvZzv744OhywCApbM12s3mxvrQZQCc2NrQBQAAAJyF/fFBLo4uDF0GwIkZabNgHC0AAACA1WCkzYJxtAAAAABWg5E2AAAnZCFxAOAsCW0AAE7IQuIAwFkS2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAnKGt0W42N9aHLgMAAFhAa0MXALDM9scHuTi6MHQZAADAAjLSBgAAWDmbG+vZGu0OXQbANQltAACAlbO3s5398cHQZQBck9AGAAAAoENCmyVkqCcAAAAsPqHNEjLUEwAAABaf0AYAAACgQ0IbAAAAgA4JbQAAAICubI12s7mxPnQZg1sbugAAAACAw/bHB7k4ujB0GYMz0gYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAACApbM12s3mxvrQZQCcytrQBQAAAMza/vggF0cXhi4D4FSMtAEAAADokNAGAOAUNjfWszXaHboMAGAJCW0WiHm5ANCfvZ3t7I8Phi4DAFhC1rRZIOblAgAAwOow0gagA6ZXAADA0a3K52ehDUAHTK8AAICjW5XPz0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW2W1ObGerZGu0OXAQAAAJyQ0GZJ7e1sZ398MHQZAAAAwAkJbQAArmJrtJvNjfWhywCAleL9973Whi4AAKBX++ODXBxdGLoMAFgp3n/fy0gbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCmwWxNdrN5sb60GUAAAAAc7I2dAEczf74IBdHF4YuAwAAAJgTI20AOrG5sZ6t0e7QZQAAwEJYhc/PQhuATuztbGd/fDB0GQAAsBBW4fOz0AYAAFhJq3CUHlhsQhsAAGAlrcJRemCxCW0AzoizvgEAAKchtFlihnvCsPbHB9nb2R66DAAAYEEJbZaY4Z4AAACwuIQ2AAAAAB0S2gAAAABdsC7kva0NXQAAQI98aASA+dsfH+Ti6MLQZXRDaAMAcAU+NAIAQzM9CgAAAKBDQhsAAGCpmN4ILAvTowAAgKVieiOwLIy0AQA4pc2N9WyNdocuAwBYMkIbAIBT2tvZzv74YOgyAGDlLPuBE6ENAAAAsJCW/cCJ0AagI8t+pAAAeuO9F+iZ0GbJeROCxbLsRwoAoDfee4GeCW2WnDchAAAAWExCG4AzsDXazebG+tBlAAAAC2xt6AIAltH++CAXRxeGLgM4IcErANADoc0C8MERAOZL8AqLy2dnYJmYHrUA9scH2dvZHroMAOAaLP4PffDZGVgmQhsAgBmw+D8ADGOZD5wIbQA6s8xvOgDQI++9sNiW+cCJ0GYFeBOC+TrtXPplftMBgB557wV6JbRZAd6EYL7MpQcAAGZBaAMAcIgzz8Di0r/AshHaAAAccprRcqYkw7CMdoXFJnh9X0KbzvmPFgAWhynJAHBygtf3tTZ0AVzb/vggF0cXhi4DAAAAzowBC1dmpE3HZvkfreHaMB/ebAAA4PhOO8pmWb/zCm06NsuhYZe2s4z/EUNPZtW3y/qmA70TvMLq8t4Li21ZpygLbTp1Fh8aBTdwtmbZt8v6pgM9u/T+eNrg1Rc/mL+t0W7O77z0VO/DPivDcGb1OXoZ34OrtXb0O1e9Mclrr3GXm5K86bRFzZiajkZN1/ew1tpDhi7iSvTmzKjpaHqrqcvePEJfJv29lomajkpN16c3Z0tNR9NbTb3Vk+jNWVPT0fRWU2/1JFfpzWOFNtdTVbe11h47sw3OgJqORk3LrcfXUk1Ho6bl1uNrqaajUdNy6/G1VNPR9FZTb/Usuh5fTzUdTW819VbPtZgeBQAAANAhoQ0AAABAh2Yd2nzPjLc3C2o6GjUttx5fSzUdjZqWW4+vpZqORk3LrcfXUk1H01tNvdWz6Hp8PdV0NL3V1Fs9VzXTNW0AAAAAmA3TowAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQ5hiq6o6qetwJH/uDVfX02VYEJHoTeqU3oU96E/qkN7kSoc0xtNYe0Vq7deg6TquqzlXVi6vqYlW1y//HUFVPq6r3VNU7Dl0+bJhq4fpWpTen97mlqn5p2pd/XFVfPf9K4WhWpTer6mcue8+8q6p+a5hq4fpWqDfvW1XfPX2/fEtV/VRVbQ5TLVzfCvXmRlX9UFX9yfTytEEKXRBCm9X18iRfmOQNV7n9Ba21Bxy6vGaOtcEqu2pvVtVNSX42yXOSPDjJRyT5+blWB6vrqr3ZWnv84ffMJL+S5EXzLhBW1LU+0351kr+R5FFJHppknOTfz60yWG3X6s1vT3K/JOeTfFySf1JVXzy/0haL0OYYpknhp0x/flpVvbCqnltVb58OZXvsoft+TFXdPr3tBUluvGxbn1ZVv15V46r6lap61PT6J1TVa6rqQdPfH19Vb6iqh8zqebTW7mqtPbO19vIk98xquzCUFerNr03yc621H2mtvbu19vbW2u/Mav8wayvUm4frPJ/kE5M8b1b7h1lbod780EzeN/+4tfZnSX4sySNmtX+YtRXqzU9P8q2ttXe11i4m+b4kXzKr/S8boc3pfEYm//PfSPKSJM9OJsPBkvynTD6wfWAmR9s+59KDquqWJN+f5MszOVr+nCQvqar7ttZekOQVSZ5VVQ/O5D/gJ7fW3nilAqZNeLXLzime26fXZBjpHVX1v51iOzCEZe3NT0jylukb75/UZJj3zSfcFgxhWXvzsCcm+eXW2h/MYFswL8vam9+XZKuqHlpV90vyBUl+5oTbgiEsa28mSV328yNPsa2lJrQ5nZe31l7WWrsnk4Z59PT6T0hynyTPbK29p7X24iSvPPS4L03ynNbar7XW7mmt/VCSd08flyRfmWQ7ya1Jfqq19tNXK6C1tnGNy+iEz+uFST4qyUOmtX5jVX3+CbcFQ1jW3vzgJE/KZLj3zUn+IMnzT7gtGMKy9uZhT0zygzPYDszTsvbm/0hyZ5L9JH+ayefbf3PCbcEQlrU3fzbJTlU9sKo+IpNRNvc74baWntDmdA7Pz3tXkhurai2TObP7rbV26PbXHvr5YUm+7nBKmeRDpo9La22cSVr6yCTfdnblX1lr7b+31l4/bfBfSfL/JvmH864DTmEpezPJQZKfaK29cjrM+18n+ZtV9f4D1AInsay9mSSpqr+V5C8nefFQNcAJLWtvflcmU0YenOT+SX48RtqwWJa1N5+Syefa/5nkJzM5CPm6AepYCEKbs/FHSTar6vCQr8NTGP4wyTdfllLer7X2/CSpqsdkkjY+P8mzrrWjuvfZKi6/PHVGz6fl3sPXYFEtem/+Zib9eMmln/Uni27Re/OSJyX58dbaO065HejFovfmo5P8YGvtLa21d2eyCPHH1WRhf1hkC92b0578gtbaX26tPSKTXOK/nWRbq0BoczZekeTuJE+pqrWq+uxMVsW+5HuT/LOq+viauH9VXZgOD7sxyQ8neWqSL86kGb/iajtq9z7D0+WXZ1ztcTU5BeKlxarOVdWNl5q+qv5BVX3AtLaPyyQJ/cnTvCDQiYXuzSQ/kOSzquoxVXWfJN+QybDZ8QlfD+jFovdmqmo9yT+KqVEsl0XvzVcmeWJVvf/0ffMrkry+tfamk74g0ImF7s2q+vCqenBV3VBVj0/yZUmefpoXZJkJbc5Aa+2uJJ+d5IuSvDXJEzIZjnnp9tsymWf47Ontvze9b5J8S5LXtda+a3pE4AuTPL2qPnLGZb46kyFpm0l+bvrzw6a3fd60prcneW6SfzedBwkLbdF7s7W2m8kb7EuT/Ekmp/z+xzPeP8zdovfm1GcmeVuSX5zxfmEwS9Cb/yLJn2UyBeONSf5+ks+a8f5h7pagNz82yW9l8n3zW5J8QWvtjhnvf2nUvafBAQAAANADI20AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA6tHefON910Uzt//vwZlcLKePWrJ/8+/OHD1nFMr3rVq97UWnvI0HVcid5kbjrs3157U1/SnTn3r96EGZph/+pNmLMj9u/VevNYoc358+dz2223Hech8L4e97jJv7feOmQVx1ZVrx26hqvRm8xNh/3ba2/qS7oz5/7VmzBDM+xfvQlzdsT+vVpvmh4FAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2zNXWaDe33zkeugzgBPQvLL5ffc2bhy4BOIXzOy8dugTgOrZGu9ka7c5se2sz2xIcwf74IHfdfc/QZQAnoH8BAODa9scHM92ekTYAAAAAp7Q12s3mxvpMtym0AQAAADil/fFB9na2Z7pNoQ0AAABAh4Q2AFzXWQz1BACOzskAYDUJbQC4rrMY6gkAHJ2TAcBqEtowN5eO1J9bu8GRAgAAALgOoQ1zc+lI/S03bzhSAABz5oAJACweoQ0AwApwwAQAFo/QBgAAAKBDQhsAjsyaVLDYzq3dkK3R7tBlAABHJLQB4MisSQWL7ZabN7I/Phi6DOCYbr9znHNrNwxdBjAAoQ0AAEDH7rr7ntxy88bQZQADENoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAC2BzY90Z4GDFCG0AAAAWwN7OtjPAwYoR2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAMzILM/0JrQBAAAAOIWt0W42N9aTzPZMb2sz2QoAAADAitofH+Ti6MLMt2ukDQAAAECHhDYM4tzaDTOb4wcAAADLSGjDIG65eWNmc/wAAABgGQltALimw4uqAQAA8yO0AeCa9scH2dvZHroMYEZmeRpSAOBsCW0AAFbILE9DCgCcLaENAMCS2xrt5tzaDUOXAQAck9AGAGDJ7Y8PcsvNG0OXAQAck9CGubCQKSyPc2s35PzOS62JAQAAZ0xow1xYyBSWxy03b+Ti6II1MQAA4IwJbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAFsTmxrozOMIKEdoAAAAsiL2dbWdwhAUwq4BVaAMAANCprdFuzq3dMHQZwDHNKmAV2gAAAHRqf3yQW27eGLoMYCBCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAAOKGt0W42N9bPZNtrZ7JVAAAAgBWwPz7IxdGFM9m2kTYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gAAAADM2ObGem6/c3yqbQhtALiqrdFuNjfWhy4DAAAWzt7Odu66+55TbWNtRrUAsIT2xwe5OLowdBkAALCSjLQBAAAA6JDQBgAAAKBDQhsAAACADgltAACW2JUWFN/cWM/WaHegigCAoxLaAAAssf3xQfZ2tu913d7OdvbHBwNVBAAcldAGgBNxpB4AAM6W0AaAE3GkHgAAzpbQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQAAAAA6JLQBAAAA6JDQBgAAAKBDQhsAAACADgltAAAAADoktAEAAADokNAGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQC4oq3RbjY31ocuAwAAVtba0AUA0Kf98UEuji4MXQYAAKwsI20AAAAAOiS0AQAAAOiQ0AYAAADgBM56HUhr2gAAAACcwFmvA2mkDQAAAECHhDYAAAAAHRLaAAAAdOis18oA+ie0YTCbG+vZGu0OXQYAAHRpf3yQvZ3tocsABiS0YTB7O9vZHx8MXQYAACwUBz9hdQhtAAAAFoiDn7A6hDYAAAAAHRLaAAAAAJyBc2s35PY7xyd+vNAGAAAA4AzccvNG7rr7nhM/XmgDwIlZCBEAAM6O0AaAE7MQIgAAnB2hDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENpy5rdFuNjfWhy4DADhkc2M9W6PdocsAAK5BaMOZ2x8fZG9ne+gyAIBD9na2sz8+GLoMAOAahDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAMe0NdrN5sb6me5j7Uy3DgAAALCE9scHuTi6cKb7MNIGAAAAoENCGwAAAIAOCW0AAAAAOiS0AQAAAOiQ0AYAAKAz8zgrDdA/Z48C4F62RrvZHx/4oAgAA5rHWWmA/gltALgXHxIBAKAPpkcBAAAsmM2N9WyNdocuAzhjQhsAAIAFs7eznf3xwdBlAGdMaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoA8CpOHsFAACcDaENAKfi7BUAAHA2hDYMyhF6AAAAuDKhDYNyhB4AAACuTGgDAAAAcAxbo91sbqyf+X7WznwPAAAAAEtkf3yQi6MLZ74fI20AAAAAOiS04UzNa8gYAAAALBvTozhT8xoyBgAAAMvGSBsAAACADgltAAAAADoktAEAWFLWlgOAxWZNGwCAJWVtOQBYbEbaAAAAAHRIaAMAAADQIaENAAAAQIeENgAAAAAdEtoAAAAAdEhoAwAAANAhoQ0AAABAh4Q2AAAAAB0S2gDwF7ZGu9ncWB+6DADgCDY31rM12h26DOAMCW0A+Av744Ps7WwPXQYAcAR7O9vZHx8MXQZwhoQ2AAAAAB0S2gAAAAB0SGgDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAMAAADQIaENAKe2ubGerdHu0GUAAMBSEdoAcGp7O9vZHx8MXQYAACwVoQ0AAABAh4Q2DM60CgAAAHhfQhsGZ1oFAAAAvC+hDQAAAECHhDYAAAAAHRLaAAAAAHRIaMOZ2RrtZnNjfegyAGAleR8GgMW3NnQBLK/98UEuji4MXQYArCTvwwBwNuZ5YERoAwAAAHBE8zwwYnoUAMCK2txYz9Zod+gyAICrENoAAKyovZ3t7I8Phi4DALgKoQ0AAEBHLCQOXGJNGwAAgI5YSBy4xEgbAJI4qgcAAL0x0gaAJI7qAQBAb4y0AQAAAOiQ0AYAAACgQ0IbAAAAgA4JbQCYic2N9WyNdocuAwAAlobQBoCZ2NvZzv74YOgyAABgaQhtAAAAADoktAEAAADokNCGLlgLAwAAAO5NaEMXrIUBAABA77ZGu9ncWJ/b/tbmticAAOZi3h8oAWBV7I8PcnF0YW77E9pwJnxYBIDhzPsDJQBwNkyP4kzsjw+yt7M9dBkAwHVYVw76ctyDn3oYlpvQBgBghVlXDvpy3IOfehiWm9AGAAAAoENCGwCsQwUAAB2yEDEAFi0FAIAOGWkDAAAA0CGhDQAAAECHhDYAAAAAHRLaAAAAAHRIaAPAzGxurGdrtDt0GQAAsBSENgDMzN7OdvbHB0OXAQArxUETWF5CGwAAgAXmoAksL6ENAMCKc5QeAPoktAEAWHGO0gPA9W2NdrO5sT7Xfa7NdW8AAAAAC2h/fJCLowtz3aeRNgArbogjBgAAwPUZaQOw4oY4YgAAAFyfkTYAzJQFTQEAYDaENnTDFz1YDhY0BYCTMWUZ+jVUfwpt6IYvegAArLL98UH2draHLgO4gqH6U2gDAAAA0CGhDTNnWCcsDv0Ky0dfA8DycPYoZs6ZaGBxnFW/bm6s5/zOS7O5sW6YN8yZ92FYTAJX6NeQ/WmkDV2xGDEsh72d7VwcXbBOFQAc0WnXy/A5Gs7OkOtNCW2YqdMmkBYjhvlxRA+Wz2n62hc+GM4s3pN9joblJLRhpmaRQPrQCPMxjyMG+hnm6zR9felxehbmz1mjoF9DH+gU2jAzs/qP2YdGODtbo92c33npX6w3c9b0M8zHpd6exZH6S9sDgFV26b01yaCharXWjn7nqjcmee017nJTkjedtqgZU9PRqOn6HtZae8jQRVyJ3pwZNR1NbzV12ZtH6Mukv9cyUdNRqen69OZsqeloequpt3oSvTlrajqa3mrqrZ7kKr15rNDmeqrqttbaY2e2wRlQ09Goabn1+Fqq6WjUtNx6fC3VdDRqWm49vpZqOpreauqtnkXX4+uppqPprabe6rkW06MAAAAAOiS04f9v715erCwDOI5/fyhSRpDQKifIIAMTVxVStMhaGIltiwKhVkEXWnSR/oGoFi4KQkJmUSgSJhFECkFtyqILpXRBKmwqsAjaBJX0tDiHmGTGc3uY9zlnvp/deRlefryc7+ZhzjmSJEmSJKlBtQ9t9le+Xw1uGo6bZluLz9JNw3HTbGvxWbppOG6abS0+SzcNp7VNre2Zdi0+TzcNp7VNre1ZVtXvtJEkSZIkSVIdfjxKkiRJkiSpQdUObZLsTPJ1ktNJnqp130klWZPk0yRvdr0FIMljSU4lOZnkYJKLOthwIMnZJCcXXXsuyVdJPk/yepLLutzTv/5w/z11KsmzK7Vn1rTYpl0uu8M2VxHbHKyFNlvrcrlN/eu2WYFtDmabw2/qX7fNCbXYJdjmMhtss7IqhzZJ1gAvAncAW4B7kmypce8KHgW+7HoEQJKNwCPA9aWUrcAa4O4OpswDO8+7dhzYWkrZBnwD7O1yT5JbgbuAbaWU64DnV3DPzGi4Tbtc2jy2uSrY5mANtTlPW10uuck267DNwWxztE22ObmGuwTbXMo8tllVrf+0uRE4XUr5tpTyF3CI3gPoVJI54E7g5a63LLIWuDjJWmA98NNKDyilvAf8dt61Y6WUc/2XHwBzXe4BHgSeKaX82f+bsyu1Z8Y016ZdLs82VxXbHE7nbbbW5XKbsM1abHM4tjnkJmyzhua6BNtcjm3WV+vQZiPww6LXC/1rXdsHPAH80/EOAEopP9I7wTsD/Az8Xko51u2qJd0PvNXxhs3ALUlOJHk3yQ0d75lWLba5D7scl23ODtscYIrabKFLsM1abHMA2xyZbU6uxS7BNsdlmyOqdWiTJa51+rNUSXYBZ0spH3e5Y7EkG+idCm8CrgAuSXJft6v+L8nTwDng1Y6nrAU2ANuBx4HDSZZ6n+nCmmrTLsdnmzPHNgeYhjYb6hJssxbbHMA2R2abk2uqS7DNcdnmeGod2iwAVy56PUdHHy9Y5GZgd5Lv6f0L3Y4kr3Q7iduB70opv5RS/gaOADd1vOk/SfYAu4B7S/e/Bb8AHCk9H9I7wb68403TqLU27XIMtjmTbHOwpttsrEuwzVpsczDbHI1tTq61LsE2R2ab46t1aPMRcE2STUnW0fvCozcq3XsspZS9pZS5UspV/T3vlFK6Pmk8A2xPsr5/incb7Xxx1U7gSWB3KeWPrvcAR4EdAEk2A+uAX7scNKWaatMuR2ebM8s2B2u2zQa7BNusxTYHs83RHMU2J9VUl2Cbo7LNyVQ5tOl/qdBDwNv03hiHSymnatx7lpRSTgCvAZ8AX9B7/vtXekeSg8D7wLVJFpI8ALwAXAocT/JZkpc63nMAuDq9n2U7BOxp5ER2qtjmYK10Cba5mtjmYK202VqXF9hkmxXY5mC2OfIm25yQXQ7HNkfeNDVtptFdkiRJkiRJq1qtj0dJkiRJkiSpIg9tJEmSJEmSGuShjSRJkiRJUoM8tJEkSZIkSWqQhzaSJEmSJEkN8tBGkiRJkiSpQR7aSJIkSZIkNchDG0mSJEmSpAb9CwMjqsfTsKTmAAAAAElFTkSuQmCC",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, axes = plt.subplots(4, 5, figsize=(20, 20), sharex=True)\n",
- "fig.suptitle(\n",
- " f\"N_IMAGES: {cryosbi.config['SIMULATION']['N_SIMULATIONS']}, SNR:{cryosbi.config['PREPROCESSING']['SNR']}, Rotations\\nMAF\"\n",
- ")\n",
- "\n",
- "for i in range(4):\n",
- " for j in range(5):\n",
- "\n",
- " axes[i, j].hist(samples[i * 5 + j].numpy().flatten(), bins=30, histtype=\"step\")\n",
- " axes[i, j].axvline(x=i * 5 + j, color=\"red\")\n",
- " axes[i, j].set_title(f\"index = {i*5 + j}\")\n",
- " axes[i, j].set_yticks([])\n",
- " axes[i, j].set_xticks(range(0, 19, 4))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 6. Recovering Distriutions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# If you want to use an uniform distribution\n",
- "true_indices = cryosbi.prior_analysis.sample((5000,))\n",
- "\n",
- "# Example for a 2-well distribution\n",
- "\n",
- "\"\"\"\n",
- "import torch.distributions as D\n",
- "\n",
- "mix = D.Categorical(torch.ones(2,))\n",
- "comp = D.Normal(torch.tensor([7., 14.]), torch.tensor([2., 2.]))\n",
- "double_well_distribution = D.MixtureSameFamily(mix, comp)\n",
- "\n",
- "true_indices = double_well_distribution.sample((5000,))\n",
- "\n",
- "# Erase non-valid elementes (<0 or >19)\n",
- "\n",
- "true_indices = torch.round(true_indices)\n",
- "\n",
- "true_indices = true_indices[true_indices.round() <= 19.]\n",
- "true_indices = true_indices[true_indices.round() >= 0]\n",
- "\"\"\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "num_workers = 8\n",
- "batch_size = int(true_indices.shape[0] / num_workers)\n",
- "\n",
- "true_images = sbi.simulators.simutils.simulate_in_batches(\n",
- " cryosbi.simulator_analysis, true_indices, num_workers=32\n",
- ")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "n_samples = 1000\n",
- "samples = torch.zeros(true_indices.shape[0], n_samples, 1)\n",
- "\n",
- "for i in tqdm(range(true_indices.shape[0])):\n",
- " samples[i] = posterior.sample(\n",
- " (n_samples,), x=true_images[i], show_progress_bars=False\n",
- " )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "fig, ax = plt.subplots(1, 2, figsize=(15, 5))\n",
- "\n",
- "ax[0].hist(\n",
- " true_indices.numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"bar\", rwidth=0.8\n",
- ")\n",
- "ax[0].set_title(\"true distribution\")\n",
- "\n",
- "ax[1].hist(\n",
- " samples.numpy().flatten(), bins=np.arange(0, 20, 1), histtype=\"bar\", rwidth=0.8\n",
- ")\n",
- "ax[1].set_title(\"estimated distribution\")\n",
- "\n",
- "ax[0].set_xticks(np.arange(0, 20, 2))\n",
- "ax[1].set_xticks(np.arange(0, 20, 2));"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3.8.12 ('sbi_env_try')",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.12"
- },
- "orig_nbformat": 4,
- "vscode": {
- "interpreter": {
- "hash": "4c2a1af4c67af5391b40e9df2dd79293a2163069b42db13e0a4e4857b53919cf"
- }
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/tutorials/tutorial_experimetal_images.ipynb b/tutorials/tutorial_experimetal_images.ipynb
new file mode 100644
index 0000000..dc60699
--- /dev/null
+++ b/tutorials/tutorial_experimetal_images.ipynb
@@ -0,0 +1,549 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import torch\n",
+ "import torchvision.transforms as transforms\n",
+ "import json\n",
+ "import mrcfile\n",
+ "import umap\n",
+ "\n",
+ "from cryo_sbi.inference.models import build_models\n",
+ "from cryo_sbi import CryoEmSimulator\n",
+ "from cryo_sbi.inference import priors\n",
+ "import cryo_sbi.utils.estimator_utils as est_utils\n",
+ "from cryo_sbi.utils.image_utils import (\n",
+ " LowPassFilter,\n",
+ " NormalizeIndividual,\n",
+ " MRCtoTensor,\n",
+ " FourierDownSample,\n",
+ " Mask,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Load posterior surrogate"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "posterior_config_file = (\n",
+ " \"../experiments/6wxb/resnet18_fft_encoder.json\" # \"PATH_TO_NN_CONFIG\"\n",
+ ")\n",
+ "posterior_weights_file = (\n",
+ " \"../experiments/6wxb/posterior_6wxb_mixed.estimator\" # \"PATH_TO_NN_WEIGHTS\"\n",
+ ")\n",
+ "\n",
+ "estimator = est_utils.load_estimator(\n",
+ " posterior_config_file, posterior_weights_file, device=device\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Test posterior with simulated images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "../data/protein_models/6wxb_mixed_models.npy\n"
+ ]
+ }
+ ],
+ "source": [
+ "image_config_file = \"../experiments/6wxb/image_params_mixed_training.json\"\n",
+ "cryo_em = CryoEmSimulator(image_config_file)\n",
+ "cryo_em.config[\"SNR\"] = 0.01 # Fixing the SNR, set range with [lower, upper]\n",
+ "cryo_em.config[\"SIGMA\"] = 1.0 # Fixing the Sigma, set range with [lower, upper]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Simulate a single image and infer the conformation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "synthetic_image = cryo_em.simulator(torch.tensor([50.0]))\n",
+ "samples = est_utils.sample_posterior(\n",
+ " estimator, synthetic_image.unsqueeze(0), num_samples=10000, device=device\n",
+ ") # we need to use unsqueeze becase we are using a single image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
+ "_ = ax[0].imshow(synthetic_image)\n",
+ "_ = ax[1].hist(samples.flatten(), bins=np.linspace(0, cryo_em.max_index, 100))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Test posterior on 20 images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "indices = torch.tensor(np.arange(0, cryo_em.max_index + 1, 5), dtype=float).reshape(\n",
+ " -1, 1\n",
+ ")\n",
+ "images = torch.stack([cryo_em.simulator(index) for index in indices], dim=0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "samples = est_utils.sample_posterior(\n",
+ " estimator, images, num_samples=10000, device=device\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8))\n",
+ "for idx, ax in enumerate(axes.reshape(-1)):\n",
+ " ax.imshow(images[idx], vmax=4, vmin=-4, cmap=\"binary\")\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks([])\n",
+ " ax.text(10, 20, str(int(indices[idx].item())))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8), sharex=True)\n",
+ "for idx, ax in enumerate(axes.reshape(1, -1)[0]):\n",
+ " ax.hist(\n",
+ " samples[:, idx].flatten().numpy(),\n",
+ " bins=np.arange(0, 100, 1),\n",
+ " histtype=\"step\",\n",
+ " color=\"blue\",\n",
+ " label=\"all\",\n",
+ " )\n",
+ " ax.set_yticks([])\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks(range(0, 100, 20))\n",
+ " ax.axvline(indices[idx], color=\"red\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### If you want we can also test the posterior with SBCC (This may take a while)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from lampe.data import JointLoader\n",
+ "from lampe.diagnostics import expected_coverage_mc\n",
+ "from lampe.plots import coverage_plot\n",
+ "from cryo_sbi.inference import priors\n",
+ "from itertools import islice"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "49pair [00:06, 7.33pair/s]\n"
+ ]
+ },
+ {
+ "ename": "KeyboardInterrupt",
+ "evalue": "",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [28], line 10\u001b[0m\n\u001b[1;32m 1\u001b[0m loader \u001b[38;5;241m=\u001b[39m JointLoader(\n\u001b[1;32m 2\u001b[0m priors\u001b[38;5;241m.\u001b[39mget_uniform_prior_1d(cryo_em\u001b[38;5;241m.\u001b[39mmax_index),\n\u001b[1;32m 3\u001b[0m cryo_em\u001b[38;5;241m.\u001b[39msimulator,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 7\u001b[0m prefetch_factor\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m,\n\u001b[1;32m 8\u001b[0m )\n\u001b[0;32m---> 10\u001b[0m levels, coverages \u001b[38;5;241m=\u001b[39m expected_coverage_mc(\n\u001b[1;32m 11\u001b[0m estimator\u001b[38;5;241m.\u001b[39mflow,\n\u001b[1;32m 12\u001b[0m (\n\u001b[1;32m 13\u001b[0m (estimator\u001b[38;5;241m.\u001b[39mstandardize(theta\u001b[38;5;241m.\u001b[39mcuda()), x\u001b[38;5;241m.\u001b[39mcuda())\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m theta, x \u001b[38;5;129;01min\u001b[39;00m islice(loader, \u001b[38;5;241m500\u001b[39m)\n\u001b[1;32m 15\u001b[0m ), \u001b[38;5;66;03m# We use here just 500 samples, this is not really accurate but gives us an idea\u001b[39;00m\n\u001b[1;32m 16\u001b[0m )\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/lampe/diagnostics.py:65\u001b[0m, in \u001b[0;36mexpected_coverage_mc\u001b[0;34m(posterior, pairs, n)\u001b[0m\n\u001b[1;32m 62\u001b[0m dist \u001b[38;5;241m=\u001b[39m posterior(x)\n\u001b[1;32m 64\u001b[0m samples \u001b[38;5;241m=\u001b[39m dist\u001b[38;5;241m.\u001b[39msample((n,))\n\u001b[0;32m---> 65\u001b[0m mask \u001b[38;5;241m=\u001b[39m dist\u001b[38;5;241m.\u001b[39mlog_prob(theta) \u001b[38;5;241m<\u001b[39m \u001b[43mdist\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43msamples\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 66\u001b[0m rank \u001b[38;5;241m=\u001b[39m mask\u001b[38;5;241m.\u001b[39msum() \u001b[38;5;241m/\u001b[39m mask\u001b[38;5;241m.\u001b[39mnumel()\n\u001b[1;32m 68\u001b[0m ranks\u001b[38;5;241m.\u001b[39mappend(rank)\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/zuko/distributions.py:110\u001b[0m, in \u001b[0;36mNormalizingFlow.log_prob\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 109\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlog_prob\u001b[39m(\u001b[38;5;28mself\u001b[39m, x: Tensor) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tensor:\n\u001b[0;32m--> 110\u001b[0m z, ladj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtransform\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_and_ladj\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 111\u001b[0m ladj \u001b[38;5;241m=\u001b[39m _sum_rightmost(ladj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreinterpreted)\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbase\u001b[38;5;241m.\u001b[39mlog_prob(z) \u001b[38;5;241m+\u001b[39m ladj\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/zuko/transforms.py:136\u001b[0m, in \u001b[0;36mComposedTransform.call_and_ladj\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 133\u001b[0m acc \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtransforms:\n\u001b[0;32m--> 136\u001b[0m x, ladj \u001b[38;5;241m=\u001b[39m \u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_and_ladj\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 137\u001b[0m acc \u001b[38;5;241m=\u001b[39m acc \u001b[38;5;241m+\u001b[39m _sum_rightmost(ladj, event_dim \u001b[38;5;241m-\u001b[39m t\u001b[38;5;241m.\u001b[39mdomain\u001b[38;5;241m.\u001b[39mevent_dim)\n\u001b[1;32m 138\u001b[0m event_dim \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m t\u001b[38;5;241m.\u001b[39mcodomain\u001b[38;5;241m.\u001b[39mevent_dim \u001b[38;5;241m-\u001b[39m t\u001b[38;5;241m.\u001b[39mdomain\u001b[38;5;241m.\u001b[39mevent_dim\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/zuko/transforms.py:725\u001b[0m, in \u001b[0;36mAutoregressiveTransform.call_and_ladj\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 724\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcall_and_ladj\u001b[39m(\u001b[38;5;28mself\u001b[39m, x: Tensor) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[Tensor, Tensor]:\n\u001b[0;32m--> 725\u001b[0m y, ladj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmeta\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mcall_and_ladj(x)\n\u001b[1;32m 726\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m y, ladj\u001b[38;5;241m.\u001b[39msum(dim\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/zuko/flows.py:316\u001b[0m, in \u001b[0;36mMaskedAutoregressiveTransform.meta\u001b[0;34m(self, y, x)\u001b[0m\n\u001b[1;32m 313\u001b[0m phi \u001b[38;5;241m=\u001b[39m (p\u001b[38;5;241m.\u001b[39munflatten(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, s \u001b[38;5;241m+\u001b[39m (\u001b[38;5;241m1\u001b[39m,)) \u001b[38;5;28;01mfor\u001b[39;00m p, s \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(phi, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mshapes))\n\u001b[1;32m 314\u001b[0m phi \u001b[38;5;241m=\u001b[39m (p\u001b[38;5;241m.\u001b[39msqueeze(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m p \u001b[38;5;129;01min\u001b[39;00m phi)\n\u001b[0;32m--> 316\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munivariate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mphi\u001b[49m\u001b[43m)\u001b[49m\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/zuko/transforms.py:352\u001b[0m, in \u001b[0;36mMonotonicRQSTransform.__init__\u001b[0;34m(self, widths, heights, derivatives, bound, slope, **kwargs)\u001b[0m\n\u001b[1;32m 341\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 342\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 343\u001b[0m widths: Tensor,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 348\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 349\u001b[0m ):\n\u001b[1;32m 350\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 352\u001b[0m widths \u001b[38;5;241m=\u001b[39m widths \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28;43mabs\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mwidths\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mmath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog\u001b[49m\u001b[43m(\u001b[49m\u001b[43mslope\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 353\u001b[0m heights \u001b[38;5;241m=\u001b[39m heights \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mabs\u001b[39m(\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m heights \u001b[38;5;241m/\u001b[39m math\u001b[38;5;241m.\u001b[39mlog(slope)))\n\u001b[1;32m 354\u001b[0m derivatives \u001b[38;5;241m=\u001b[39m derivatives \u001b[38;5;241m/\u001b[39m (\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mabs\u001b[39m(derivatives \u001b[38;5;241m/\u001b[39m math\u001b[38;5;241m.\u001b[39mlog(slope)))\n",
+ "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+ ]
+ }
+ ],
+ "source": [
+ "loader = JointLoader(\n",
+ " priors.get_uniform_prior_1d(cryo_em.max_index),\n",
+ " cryo_em.simulator,\n",
+ " vectorized=False,\n",
+ " batch_size=1,\n",
+ " num_workers=24, # You might wanna change this\n",
+ " prefetch_factor=1,\n",
+ ")\n",
+ "\n",
+ "levels, coverages = expected_coverage_mc(\n",
+ " estimator.flow,\n",
+ " (\n",
+ " (estimator.standardize(theta.cuda()), x.cuda())\n",
+ " for theta, x in islice(loader, 500)\n",
+ " ), # We use here just 500 samples, this is not really accurate but gives us an idea\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "coverage_plot(levels, coverages);"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Now let's look at experimental images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# We use parts of the torchvision module to take care of imigae processing\n",
+ "# We can build a transformation which modify our images in a predefined pipline\n",
+ "transform = transforms.Compose(\n",
+ " [\n",
+ " MRCtoTensor(), # Load mrc file (str) and construct pytorch tensor\n",
+ " transforms.Resize(size=(128, 128)), # Resize image to given size\n",
+ " NormalizeIndividual(), # Normalize image\n",
+ " ]\n",
+ ")\n",
+ "\n",
+ "# Example transformation, we can do more then just normalization\n",
+ "transform_test = transforms.Compose(\n",
+ " [\n",
+ " MRCtoTensor(),\n",
+ " FourierDownSample(256, 128),\n",
+ " NormalizeIndividual(),\n",
+ " Mask(128, 45),\n",
+ " LowPassFilter(128, 80),\n",
+ " ]\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "You can download the particles directly here : https://www.ebi.ac.uk/empiar/EMPIAR-10532/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "FileNotFoundError",
+ "evalue": "[Errno 2] No such file or directory: '../../6wxb/particles/particles_01.mrc'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[0;32mIn [30], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m experimental_images \u001b[38;5;241m=\u001b[39m transform(\n\u001b[1;32m 2\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../../6wxb/particles/particles_01.mrc\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 3\u001b[0m )\n",
+ "File \u001b[0;32m/mnt/sw/nix/store/b4q5asj8flwlgmaijgj1r6wbmnls5x8k-python-3.9.15-view/lib/python3.9/site-packages/torchvision/transforms/transforms.py:95\u001b[0m, in \u001b[0;36mCompose.__call__\u001b[0;34m(self, img)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, img):\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtransforms:\n\u001b[0;32m---> 95\u001b[0m img \u001b[38;5;241m=\u001b[39m \u001b[43mt\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m img\n",
+ "File \u001b[0;32m~/cryo_em_SBI/src/cryo_sbi/utils/image_utils.py:241\u001b[0m, in \u001b[0;36mMRCtoTensor.__call__\u001b[0;34m(self, image_path)\u001b[0m\n\u001b[1;32m 230\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, image_path: \u001b[38;5;28mstr\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m torch\u001b[38;5;241m.\u001b[39mTensor:\n\u001b[1;32m 231\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 232\u001b[0m \u001b[38;5;124;03m Convert an MRC file to a tensor.\u001b[39;00m\n\u001b[1;32m 233\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 238\u001b[0m \u001b[38;5;124;03m image (torch.Tensor): Image of shape (n_pixels, n_pixels).\u001b[39;00m\n\u001b[1;32m 239\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 241\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmrc_to_tensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage_path\u001b[49m\u001b[43m)\u001b[49m\n",
+ "File \u001b[0;32m~/cryo_em_SBI/src/cryo_sbi/utils/image_utils.py:217\u001b[0m, in \u001b[0;36mmrc_to_tensor\u001b[0;34m(image_path)\u001b[0m\n\u001b[1;32m 206\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 207\u001b[0m \u001b[38;5;124;03mConvert an MRC file to a tensor.\u001b[39;00m\n\u001b[1;32m 208\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;124;03m image (torch.Tensor): Image of shape (n_pixels, n_pixels).\u001b[39;00m\n\u001b[1;32m 214\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(image_path, \u001b[38;5;28mstr\u001b[39m), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage path needs to be a string\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 217\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mmrcfile\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage_path\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m mrc:\n\u001b[1;32m 218\u001b[0m image \u001b[38;5;241m=\u001b[39m mrc\u001b[38;5;241m.\u001b[39mdata\n\u001b[1;32m 219\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mfrom_numpy(image)\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/mrcfile/load_functions.py:139\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(name, mode, permissive, header_only)\u001b[0m\n\u001b[1;32m 137\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m start[:\u001b[38;5;241m2\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBZ\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 138\u001b[0m NewMrc \u001b[38;5;241m=\u001b[39m Bzip2MrcFile\n\u001b[0;32m--> 139\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mNewMrc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpermissive\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpermissive\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 140\u001b[0m \u001b[43m \u001b[49m\u001b[43mheader_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheader_only\u001b[49m\u001b[43m)\u001b[49m\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/mrcfile/mrcfile.py:109\u001b[0m, in \u001b[0;36mMrcFile.__init__\u001b[0;34m(self, name, mode, overwrite, permissive, header_only, **kwargs)\u001b[0m\n\u001b[1;32m 106\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m=\u001b[39m mode\n\u001b[1;32m 107\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_read_only \u001b[38;5;241m=\u001b[39m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 109\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_open_file\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 112\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01min\u001b[39;00m mode:\n",
+ "File \u001b[0;32m~/cryo_sbi_env/lib/python3.9/site-packages/mrcfile/mrcfile.py:126\u001b[0m, in \u001b[0;36mMrcFile._open_file\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_open_file\u001b[39m(\u001b[38;5;28mself\u001b[39m, name):\n\u001b[1;32m 125\u001b[0m \u001b[38;5;124;03m\"\"\"Open a file object to use as the I/O stream.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 126\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iostream \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_mode\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mb\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
+ "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../../6wxb/particles/particles_01.mrc'"
+ ]
+ }
+ ],
+ "source": [
+ "experimental_images = transform(\n",
+ " \"../../6wxb/particles/particles_01.mrc\"\n",
+ ") # Here the images are loaded, resized and normalized"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# In case you want to load more than just one mrc file\n",
+ "experimental_images = []\n",
+ "for i in range(1, 17):\n",
+ " if i < 10:\n",
+ " img_file = f\"../../6wxb/particles/particles_0{i}.mrc\"\n",
+ " else:\n",
+ " img_file = f\"../../6wxb/particles/particles_{i}.mrc\"\n",
+ " tmp_images = transform(img_file)\n",
+ " experimental_images.append(tmp_images)\n",
+ "\n",
+ "experimental_images = torch.cat(experimental_images, dim=0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8))\n",
+ "for idx, ax in enumerate(axes.reshape(-1)):\n",
+ " ax.imshow(experimental_images[idx], vmax=4, vmin=-4, cmap=\"binary\")\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks([])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Finally we test the posterior on the real images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "samples_exp = est_utils.sample_posterior(\n",
+ " estimator, experimental_images, num_samples=10000, device=device\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8), sharex=True)\n",
+ "for idx, ax in enumerate(axes.reshape(1, -1)[0]):\n",
+ " ax.hist(\n",
+ " samples_exp[:, idx].flatten().numpy(),\n",
+ " bins=np.arange(0, 100, 1),\n",
+ " histtype=\"step\",\n",
+ " color=\"blue\",\n",
+ " label=\"all\",\n",
+ " )\n",
+ " ax.set_yticks([])\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks(range(0, 100, 20))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "##### Since we can look at all posteriors, lets look at all the posterior means"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "posterior_mean = samples_exp.mean(axis=0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "_ = plt.hist(posterior_mean)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "##### Some of the posterior might be to wide, so lets exclude them "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "posterior_quantiles = np.quantile(samples_exp.numpy(), [0.025, 0.975], axis=0)\n",
+ "confidence_widths = (posterior_quantiles[1] - posterior_quantiles[0]).flatten()\n",
+ "condition = (\n",
+ " confidence_widths < 50\n",
+ ") # Select posterior with a 95% confidence intervall less the 50 indices\n",
+ "posterior_idx = np.where(condition)[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "fig, axes = plt.subplots(4, 5, figsize=(10, 8), sharex=True)\n",
+ "for idx, ax in enumerate(axes.reshape(1, -1)[0]):\n",
+ " ax.hist(\n",
+ " samples_exp[:, posterior_idx[idx]].flatten().numpy(),\n",
+ " bins=np.arange(0, 100, 1),\n",
+ " histtype=\"step\",\n",
+ " color=\"blue\",\n",
+ " label=\"all\",\n",
+ " )\n",
+ " ax.set_yticks([])\n",
+ " ax.set_yticks([])\n",
+ " ax.set_xticks(range(0, 100, 20))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "posterior_mean = samples_exp[:, posterior_idx].mean(axis=0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "_ = plt.hist(posterior_mean)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cryo_sbi_env",
+ "language": "python",
+ "name": "cryo_sbi_env"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "1391d301e9aa4dc24331c4a52095d8473e5107d84c03241f78234deb9fd2437e"
+ }
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}