diff --git a/gpudrive_vbd_sample_11671609ebfa3185.pkl b/gpudrive_vbd_sample_11671609ebfa3185.pkl
deleted file mode 100644
index 021e4a4c..00000000
Binary files a/gpudrive_vbd_sample_11671609ebfa3185.pkl and /dev/null differ
diff --git a/notebooks/00_align_simulators_vbd.ipynb b/notebooks/00_align_simulators_vbd.ipynb
index 339b9bda..3068c36a 100644
--- a/notebooks/00_align_simulators_vbd.ipynb
+++ b/notebooks/00_align_simulators_vbd.ipynb
@@ -45,13 +45,13 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "2024-11-04 13:57:58.242989: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
- "2024-11-04 13:57:58.249867: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
- "2024-11-04 13:57:58.256749: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
- "2024-11-04 13:57:58.258845: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
- "2024-11-04 13:57:58.265316: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+ "2024-11-04 14:47:08.762921: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+ "2024-11-04 14:47:08.769846: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+ "2024-11-04 14:47:08.776862: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+ "2024-11-04 14:47:08.778953: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+ "2024-11-04 14:47:08.785416: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
"To enable the following instructions: AVX2 AVX512F AVX512_VNNI AVX512_BF16 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
- "2024-11-04 13:57:58.703728: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+ "2024-11-04 14:47:09.216740: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
]
}
],
@@ -105,56 +105,6 @@
"warnings.filterwarnings(\"ignore\")"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Helper functions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "def plot_batch_distributions(batch, timestep, title, dist_type='hist'):\n",
- "\n",
- " num_keys = len(batch.keys())\n",
- " num_cols = 4\n",
- " num_rows = math.ceil(num_keys / num_cols)\n",
- "\n",
- " fig, axes = plt.subplots(num_rows, num_cols, figsize=(11, num_rows * 2))\n",
- " fig.suptitle(f\"{title} | Scenario id: {SCENARIO_ID} | t = {timestep}\", y=1.02)\n",
- " axes = axes.flatten()\n",
- "\n",
- " for i, key in enumerate(batch.keys()):\n",
- " data = batch[key].flatten()\n",
- " \n",
- " if dist_type == 'hist':\n",
- " axes[i].hist(batch[key].flatten(), bins=30)\n",
- " elif dist_type == 'box_plot':\n",
- " \n",
- " sns.boxplot(data=data, ax=axes[i], width=0.3)\n",
- " # Add a strip plot to visualize individual data points\n",
- " sns.stripplot(data=data, ax=axes[i], color='k', size=3, jitter=True)\n",
- " \n",
- " max_value = data.max()\n",
- " min_value = data.min()\n",
- " axes[i].set_title(f\"{key}: Min={min_value:.2f}, Max={max_value:.2f}\", fontsize=8)\n",
- "\n",
- " # Hide any unused subplots\n",
- " for j in range(i + 1, len(axes)):\n",
- " axes[j].axis('off')\n",
- "\n",
- " # Adjust layout for better readability\n",
- " plt.tight_layout()\n",
- " plt.show()\n",
- " \n",
- " # Save as pdf\n",
- " fig.savefig(f'{title}_{SCENARIO_ID}_t{timestep}_{dist_type}.png', format='png', bbox_inches='tight')"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -164,7 +114,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
@@ -188,7 +138,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
@@ -223,7 +173,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
@@ -278,7 +228,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 12,
"metadata": {},
"outputs": [
{
@@ -317,7 +267,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
@@ -333,7 +283,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "Diffusion: 100%|██████████| 50/50 [00:01<00:00, 32.13it/s]\n"
+ "Diffusion: 100%|██████████| 50/50 [00:01<00:00, 31.60it/s]\n"
]
}
],
@@ -401,13 +351,13 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
- "
|
"
+ " |
"
],
"text/plain": [
""
@@ -421,6 +371,15 @@
"mediapy.show_video(vbd_waymax_imgs, codec='gif', fps=FPS)"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#mediapy.write_video(\"vbd_waymax_trajs.gif\", vbd_waymax_imgs, codec='gif', fps=FPS)"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -430,28 +389,9 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Steps remaining: 79\n"
- ]
- },
- {
- "ename": "",
- "evalue": "",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
- "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
- "\u001b[1;31mClick here for more info. \n",
- "\u001b[1;31mView Jupyter log for further details."
- ]
- }
- ],
+ "outputs": [],
"source": [
"init_state = waymax_env.reset(scenario)\n",
"\n",
@@ -486,7 +426,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -531,7 +471,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
@@ -563,7 +503,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
@@ -594,7 +534,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 22,
"metadata": {},
"outputs": [
{
@@ -608,7 +548,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "Diffusion: 100%|██████████| 50/50 [00:01<00:00, 31.17it/s]\n"
+ "Diffusion: 100%|██████████| 50/50 [00:01<00:00, 30.26it/s]\n"
]
}
],
@@ -632,7 +572,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 23,
"metadata": {},
"outputs": [
{
@@ -680,7 +620,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 24,
"metadata": {},
"outputs": [
{
@@ -688,7 +628,7 @@
"text/html": [
"\n",
" \n",
- " GPUDrive with VBD-trajs |
"
+ " GPUDrive with VBD-trajs
"
],
"text/plain": [
""
@@ -704,11 +644,11 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
- "mediapy.write_video(\"vbd_gpudrive_trajs_before_yaw_fix.gif\", frames, codec='gif', fps=FPS)"
+ "mediapy.write_video(\"vbd_gpudrive_trajs.gif\", frames, codec='gif', fps=FPS)"
]
},
{
@@ -720,7 +660,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
@@ -735,16 +675,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [],
- "source": [
- "#plot_batch_distributions(gpudrive_sample_batch_np, title='GPUDrive', timestep=INIT_STEPS, dist_type='box_plot')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
+ "execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
@@ -792,32 +723,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Meaning of each type is aligned with Waymax. Note that GPUDrive is missing some road information.\n",
- "\n",
- "```\n",
- "LANE_UNDEFINED = 0\n",
- "LANE_FREEWAY = 1\n",
- "LANE_SURFACE_STREET = 2\n",
- "LANE_BIKE_LANE = 3\n",
- "# Original definition skips 4.\n",
- "ROAD_LINE_UNKNOWN = 5\n",
- "ROAD_LINE_BROKEN_SINGLE_WHITE = 6\n",
- "ROAD_LINE_SOLID_SINGLE_WHITE = 7\n",
- "ROAD_LINE_SOLID_DOUBLE_WHITE = 8\n",
- "ROAD_LINE_BROKEN_SINGLE_YELLOW = 9\n",
- "ROAD_LINE_BROKEN_DOUBLE_YELLOW = 10\n",
- "ROAD_LINE_SOLID_SINGLE_YELLOW = 11\n",
- "ROAD_LINE_SOLID_DOUBLE_YELLOW = 12\n",
- "ROAD_LINE_PASSING_DOUBLE_YELLOW = 13\n",
- "ROAD_EDGE_UNKNOWN = 14\n",
- "ROAD_EDGE_BOUNDARY = 15\n",
- "ROAD_EDGE_MEDIAN = 16\n",
- "STOP_SIGN = 17\n",
- "CROSSWALK = 18\n",
- "SPEED_BUMP = 19\n",
- "DRIVEWAY = 20 # New datatype in v1.2.0: Driveway entrances\n",
- "UNKNOWN = -1\n",
- "```"
+ "Meaning of each type is aligned with Waymax (seed data_utils/datatypes.py). Note that GPUDrive is missing some road information.\n"
]
}
],
diff --git a/notebooks/01_features_deepdive.ipynb b/notebooks/01_features_deepdive.ipynb
index de08b1ec..96038a4a 100644
--- a/notebooks/01_features_deepdive.ipynb
+++ b/notebooks/01_features_deepdive.ipynb
@@ -2,20 +2,18 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 102,
+ "execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
- "import torch\n",
"import pickle\n",
"import warnings\n",
"from pathlib import Path\n",
- "import jax.numpy as jnp\n",
"import numpy as np\n",
- "import pandas as pd\n",
+ "import math\n",
"\n",
"# GPUDrive dependencies\n",
"working_dir = Path.cwd()\n",
@@ -41,7 +39,7 @@
},
{
"cell_type": "code",
- "execution_count": 103,
+ "execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
@@ -62,7 +60,7 @@
},
{
"cell_type": "code",
- "execution_count": 329,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
@@ -82,10 +80,46 @@
},
{
"cell_type": "code",
- "execution_count": 330,
+ "execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
+ "def plot_batch_distributions(batch, timestep, title, dist_type='hist'):\n",
+ "\n",
+ " num_keys = len(batch.keys())\n",
+ " num_cols = 4\n",
+ " num_rows = math.ceil(num_keys / num_cols)\n",
+ "\n",
+ " fig, axes = plt.subplots(num_rows, num_cols, figsize=(11, num_rows * 2))\n",
+ " fig.suptitle(f\"{title} | Scenario id: {SCENARIO_ID} | t = {timestep}\", y=1.02)\n",
+ " axes = axes.flatten()\n",
+ "\n",
+ " for i, key in enumerate(batch.keys()):\n",
+ " data = batch[key].flatten()\n",
+ " \n",
+ " if dist_type == 'hist':\n",
+ " axes[i].hist(batch[key].flatten(), bins=30)\n",
+ " elif dist_type == 'box_plot':\n",
+ " \n",
+ " sns.boxplot(data=data, ax=axes[i], width=0.3)\n",
+ " # Add a strip plot to visualize individual data points\n",
+ " sns.stripplot(data=data, ax=axes[i], color='k', size=3, jitter=True)\n",
+ " \n",
+ " max_value = data.max()\n",
+ " min_value = data.min()\n",
+ " axes[i].set_title(f\"{key}: Min={min_value:.2f}, Max={max_value:.2f}\", fontsize=8)\n",
+ "\n",
+ " # Hide any unused subplots\n",
+ " for j in range(i + 1, len(axes)):\n",
+ " axes[j].axis('off')\n",
+ "\n",
+ " # Adjust layout for better readability\n",
+ " plt.tight_layout()\n",
+ " plt.show()\n",
+ " \n",
+ " # Save as pdf\n",
+ " fig.savefig(f'{title}_{SCENARIO_ID}_t{timestep}_{dist_type}.png', format='png', bbox_inches='tight')\n",
+ " \n",
"def make_heatmaps(waymax_vbd_data, gpudrive_vbd_data, array_name, index, feature_name, \n",
" share_axes=True, share_color_scale=True, x_label=\"Time step\", y_label=\"Agent index\"):\n",
" \n",
@@ -123,7 +157,7 @@
" gpudrive_vbd_data[array_name].squeeze(0)[:, :, index], cmap=cmap, center=center, linewidth=.5,\n",
" vmin=vmin, vmax=vmax, cbar=False, annot=False, ax=axs[1]\n",
" )\n",
- " axs[1].set_title(f\"GPUDrive VBD data [min: {gpudrive_vbd_data[array_name].squeeze(0)[:, :, index].min()}, max: {gpudrive_vbd_data[array_name].squeeze(0)[:, :, index].max():.2}]\")\n",
+ " axs[1].set_title(f\"GPUDrive VBD data [min: {gpudrive_vbd_data[array_name].squeeze(0)[:, :, index].min():.2}, max: {gpudrive_vbd_data[array_name].squeeze(0)[:, :, index].max():.2}]\")\n",
" axs[1].set_xlabel(x_label)\n",
"\n",
" # Add separate color bars if axes and color scales are not shared\n",
@@ -151,7 +185,7 @@
},
{
"cell_type": "code",
- "execution_count": 331,
+ "execution_count": 27,
"metadata": {},
"outputs": [
{
@@ -160,7 +194,7 @@
"dict_keys(['agents_history', 'agents_interested', 'agents_type', 'agents_future', 'traffic_light_points', 'polylines', 'polylines_valid', 'relations', 'agents_id', 'anchors'])"
]
},
- "execution_count": 331,
+ "execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
@@ -171,7 +205,7 @@
},
{
"cell_type": "code",
- "execution_count": 332,
+ "execution_count": 28,
"metadata": {},
"outputs": [
{
@@ -180,7 +214,7 @@
"dict_keys(['agents_history', 'agents_interested', 'agents_type', 'agents_future', 'traffic_light_points', 'polylines', 'polylines_valid', 'relations', 'agents_id', 'anchors'])"
]
},
- "execution_count": 332,
+ "execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
@@ -226,7 +260,7 @@
},
{
"cell_type": "code",
- "execution_count": 333,
+ "execution_count": 29,
"metadata": {},
"outputs": [
{
@@ -235,7 +269,7 @@
"((32, 12, 8), (32, 12, 8))"
]
},
- "execution_count": 333,
+ "execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
@@ -246,7 +280,7 @@
},
{
"cell_type": "code",
- "execution_count": 334,
+ "execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
@@ -255,7 +289,7 @@
},
{
"cell_type": "code",
- "execution_count": 335,
+ "execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
@@ -268,7 +302,7 @@
" 5: \"vehicle_length\",\n",
" 6: \"vehicle_width\",\n",
" 7: \"vehicle_height\"\n",
- "}\n"
+ "}"
]
},
{
@@ -280,169 +314,7 @@
},
{
"cell_type": "code",
- "execution_count": 344,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": 342,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array([[[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 1.72722168e+01, 3.23500977e+01, 3.07467318e+00,\n",
- " -6.65283203e+00, -2.44140625e-02, 4.55015659e+00,\n",
- " 2.01722050e+00, 1.00000000e+00],\n",
- " [ 1.15910645e+01, 2.77480469e+01, 3.61526704e+00,\n",
- " -1.95312500e-02, 2.92968750e-02, 4.48535204e+00,\n",
- " 2.01758647e+00, 1.00000000e+00],\n",
- " [ 1.17468262e+01, 2.38881836e+01, 3.69327211e+00,\n",
- " -1.46484375e-02, 9.76562500e-03, 4.64210320e+00,\n",
- " 2.02009487e+00, 1.00000000e+00],\n",
- " [ 4.18652344e+01, 2.45576172e+01, 2.38069510e+00,\n",
- " 4.15039062e-02, 3.90625000e-02, 4.62185097e+00,\n",
- " 2.09067822e+00, 1.00000000e+00],\n",
- " [ 6.36328125e+00, 4.32124023e+01, 5.35535431e+00,\n",
- " -2.31933594e-01, 1.07421875e-01, 4.78441858e+00,\n",
- " 2.14586616e+00, 1.00000000e+00],\n",
- " [ 4.84711914e+01, 1.89599609e+01, 2.35442495e+00,\n",
- " 1.17187500e-01, -7.32421875e-02, 4.45077229e+00,\n",
- " 2.09260201e+00, 1.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 6.42285156e+00, 2.05205078e+01, 3.71484089e+00,\n",
- " -1.97753906e-01, -1.17187500e-01, 4.53792238e+00,\n",
- " 1.99590814e+00, 1.00000000e+00],\n",
- " [ 6.23632812e+00, 2.48793945e+01, 3.68895793e+00,\n",
- " -9.27734375e-02, 9.76562500e-03, 4.57543802e+00,\n",
- " 2.03280234e+00, 1.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 7.28271484e-01, 1.70991211e+01, 3.70230317e+00,\n",
- " -2.00195312e-01, -1.07421875e-01, 4.86705685e+00,\n",
- " 2.14276004e+00, 1.00000000e+00],\n",
- " [ 7.51774902e+01, -7.38183594e+00, 2.39556694e+00,\n",
- " -6.35009766e+00, 5.76171875e+00, 4.56218481e+00,\n",
- " 2.08000016e+00, 1.00000000e+00],\n",
- " [-6.59179688e-02, 2.03515625e+01, 3.70129633e+00,\n",
- " 7.08007812e-02, 2.44140625e-02, 4.56809950e+00,\n",
- " 1.99587429e+00, 1.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 3.63391113e+01, 2.94892578e+01, 2.37194300e+00,\n",
- " -7.42739183e-04, -1.62165612e-04, 5.28599977e+00,\n",
- " 2.33200002e+00, 1.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00],\n",
- " [ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n",
- " 0.00000000e+00, 0.00000000e+00]]], dtype=float32)"
- ]
- },
- "execution_count": 342,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "gpudrive_vbd_data['agents_history'][:, :, 2]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 336,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(-7.381836, 75.17749)"
- ]
- },
- "execution_count": 336,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "gpudrive_vbd_data['agents_history'][:, :, 2], gpudrive_vbd_data['agents_history'][:, :, 2].max()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 341,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "75.17749"
- ]
- },
- "execution_count": 341,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "gpudrive_vbd_data['agents_history'][:, :, 2].max()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 337,
+ "execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
@@ -451,12 +323,12 @@
},
{
"cell_type": "code",
- "execution_count": 338,
+ "execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
"