reorganize and delete a lot of bloat

CompositeEnvironment.py

@@ -5,6 +5,7 @@
 from Terrain import generator
 import matplotlib.pyplot as plt
 from DNoise.dnoise import EncoderDecoder as ed
+from Terrain.timer import FunctionTimer
 import torch
 from torch import nn
 
@@ -81,7 +82,14 @@ def dNoiseVis(self, inputpic):
         inputpic = torch.tensor(inputpic, dtype=torch.float32).view(1, 1, 256, 256)
         inputpic = inputpic.type(torch.cuda.FloatTensor)
 
+        de_noise_timer = FunctionTimer("De-Noising")
+        de_noise_timer.start()
+
         de_noised_image = model(inputpic)
+
+        de_noise_timer.stop()
+        de_noise_timer.print()
+
         loss = loss_fn(de_noised_image, inputpic)
 
         loss = (1 - loss.item()) * 100
@@ -154,5 +162,4 @@ def thresholdDNoise(input, x):
     masked = ev.generate()
 
     vi = Visualizer("./DNoise/models/synthnav-model-0.pth", pic)
-
     vi.dNoiseVis(masked)

DNoise/array2img.py

@@ -7,30 +7,30 @@
 import threading
 from Terrain import generator
 import math
-from Terrain import timers
+from Terrain import timer
 import os
 
 
 def array2image(x, y, octaves, weight, seed: int = 0, iD: int = 0):
-    timer = timers.FunctionTimer("Clean - Generate")
+    timer = timer.FunctionTimer("Clean - Generate")
     array = generator.generateClean(x, y, octaves, seed)
     timer.stop()
     bool_array = np.array(array, dtype=bool)
-    timer = timers.FunctionTimer("Clean - To Image")
+    timer = timer.FunctionTimer("Clean - To Image")
     img = PIL.Image.fromarray(bool_array)
     print(img)
     timer.stop()
-    timer = timers.FunctionTimer("Clean - Image Save")
+    timer = timer.FunctionTimer("Clean - Image Save")
     img.save("./val_images/clean/" + str(iD) + "_clean.jpeg", bits=1, optimize=True)
     timer.stop()
-    timer = timers.FunctionTimer("Noisy - Generate")
+    timer = timer.FunctionTimer("Noisy - Generate")
     array = generator.generateNoise(x, y, octaves, weight, seed)
     timer.stop()
     bool_array = np.array(array, dtype=bool)
-    timer = timers.FunctionTimer("Noisy - To Image")
+    timer = timer.FunctionTimer("Noisy - To Image")
     img = PIL.Image.fromarray(bool_array)
     timer.stop()
-    timer = timers.FunctionTimer("Noisy - Image Save")
+    timer = timer.FunctionTimer("Noisy - Image Save")
     img.save("./val_images/noisy/" + str(iD) + "_noisy.jpeg", bits=1, optimize=True)
     timer.stop()
 

Pathfinding/astar.py

@@ -4,7 +4,7 @@
 
 import random
 
-from Terrain.timers import FunctionTimer
+from Terrain.timer import FunctionTimer
 from CompositeEnvironment import Visualizer, Environment
 from Terrain import pathcheck, generator
 

Terrain/border.py

@@ -1,7 +1,7 @@
 import copy
 
 import Terrain.terraingen as terraingen
-from Terrain.timers import FunctionTimer
+from Terrain.timer import FunctionTimer
 from typing import Union
 import numpy as np
 

Terrain/helpers.py

@@ -0,0 +1,13 @@
+"""
+A series of helper functions used throughout the course.
+
+If a function gets defined once and could be used over and over, it'll go in here.
+"""
+
+from math import floor, log10
+
+def round_sig(x, sig=2):
+    """
+    Rounds `x` to `sig` significant figures.
+    """
+    return round(x, sig - int(floor(log10(abs(x)))) - 1)

Terrain/pathcheck.py

@@ -2,7 +2,7 @@
 import sys
 
 import Terrain.terraingen as terraingen
-from Terrain.timers import FunctionTimer
+from Terrain.timer import FunctionTimer
 
 
 def path(x: int, y: int, octaves: int, progress: bool = False, setseed: int = 0):