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UNI_Python
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07/01/2023

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Jan-Niclas Loosen 9 months ago
parent ec66e7d14c
commit 8e3db2af40
6 changed files with 180 additions and 27 deletions
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11
.idea/UNI_Python.iml
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<?xml version="1.0" encoding="UTF-8"?>
<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$">
<excludeFolder url="file://$MODULE_DIR$/Virtualenv" />
</content>
<orderEntry type="jdk" jdkName="C:\ProgramData\anaconda3" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" />
<module version="4">
<component name="PyDocumentationSettings">
<option name="format" value="GOOGLE" />
<option name="myDocStringFormat" value="Google" />
</component>
</module>

2
.idea/misc.xml
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectRootManager" version="2" project-jdk-name="C:\ProgramData\anaconda3" project-jdk-type="Python SDK" />
<component name="ProjectRootManager" version="2" project-jdk-name="C:\Users\janni\anaconda3" project-jdk-type="Python SDK" />
</project>

8
.idea/modules.xml
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/.idea/UNI_Python.iml" filepath="$PROJECT_DIR$/.idea/UNI_Python.iml" />
</modules>
</component>
</project>

70
7.0.0
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17
ha_07/loosen_janniclas_1540907_08.py
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@ -62,7 +62,7 @@ def mysterious_transformation_parallel(data, stripes=16):
i += 1
return np.concatenate(data_new_stripes)
3
img = Image.open("lokomotive.png")
pixels = np.asarray(img, dtype=np.uint8)
@ -82,12 +82,19 @@ end_time_parallel = time.time()
execution_time_parallel = end_time_parallel - start_time_parallel
print("Execution time for parallel method:", execution_time_parallel, "seconds")
# Each time one pixel is different - don't know the reason? But this difference is negligible
num_different_pixels = np.count_nonzero(np.sum(data_new_normal != data_new_parallel, axis=-1))
print("Number of different pixels:", num_different_pixels)
img_new_normal = Image.fromarray(data_new_normal, 'RGB')
img_new_normal.save("new_normal_lokomotive.png")
img_new_parallel = Image.fromarray(data_new_normal, 'RGB')
img_new_parallel.save("new_parallel_lokomotive.png")
img1 = Image.open("new_normal_lokomotive.png")
img2 = Image.open("new_parallel_lokomotive.png")
diff_count = 0
for x in range(img1.width):
for y in range(img1.height):
if img1.getpixel((x, y)) != img2.getpixel((x, y)):
diff_count += 1
print(diff_count)

99
ha_08/loosen_janniclas_1540907_09.py
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@ -1,10 +1,9 @@
import requests
import colorsys
import plotly.graph_objects as go
from PIL import Image
import numpy as np
from io import BytesIO
from matplotlib import pyplot as plt
import plotly.graph_objects as go
import time
def apply_convolution_operator(operator, image):
@ -94,5 +93,93 @@ else:
"""
class Simulation:
class Heatmap_Simulator:
k = 1
h = 2
delta_f = 0.005
cookie_size = 0.5
def __init__(self, y_size=28, x_size=28, tmp_min=0, tmp_max=1):
init_heatmap = np.zeros((y_size, x_size))
self.x_size = x_size
self.y_size = y_size
self.tmp_min = tmp_min
self.tmp_max = tmp_max
size = self.cookie_size / 2
for y in range(int(y_size * (0.5 - size)), int(y_size * (0.5 + size))):
for x in range(int(x_size * (0.5 - size)), int(x_size * (0.5 + size))):
init_heatmap[y][x] = 1
self.heatmap = init_heatmap
def simulate(self, cycles=1):
for c in range(cycles):
new_heatmap = np.zeros((self.y_size, self.x_size))
for y in range(self.y_size):
for x in range(self.x_size):
u = self.heatmap[y, x]
value = u + self.delta_f * (self.k / (1 ** 2)) * self._consider_convolution(x, y)
value = max(self.tmp_min, min(self.tmp_max, value))
new_heatmap[y][x] = value
self.heatmap = new_heatmap
def _consider_convolution(self, x, y):
top = self.heatmap[y - 1, x] if y > 0 else 0
bottom = self.heatmap[y + 1, x] if y < self.heatmap.shape[0] - 1 else 0
left = self.heatmap[y, x - 1] if x > 0 else 0
right = self.heatmap[y, x + 1] if x < self.heatmap.shape[1] - 1 else 0
center = self.heatmap[y, x]
return top + bottom + left + right + center * (-4)
def export(self):
if self.heatmap is not None:
return Heatmap_Image(self.heatmap, 0, 1)
else:
AttributeError("Heatmap is not initialized.")
class Visual_Heatmap_Simulator(Heatmap_Simulator):
def __init__(self, y_size=28, x_size=28, tmp_min=0, tmp_max=1, delay=0.5):
super().__init__(y_size, x_size, tmp_min, tmp_max)
self.delay = delay
def simulate_visual(self, cycles=100, skip=5):
for c in range(cycles):
if c != 0:
self.simulate(1)
if c % skip == 0:
self._update_plot()
print(f"Figure updated: {c}.")
def _update_plot(self):
plt.imshow(self.heatmap, cmap='viridis', interpolation='nearest')
plt.draw()
plt.pause(self.delay)
simulator = Visual_Heatmap_Simulator(28, 28, -0.5, 1)
simulator.simulate_visual(10000, 50)
class Heatmap_Image:
def __init__(self, heatmap, min_val, max_val):
self.min_val = min_val
self.max_val = max_val
x_size, y_size = heatmap.shape
colormap = np.zeros((y_size, x_size, 3), dtype=np.uint8)
for y in range(y_size):
for x in range(x_size):
colormap[y][x] = self._val_to_color(heatmap[y][x])
self.image = Image.fromarray(colormap, 'RGB')
def _val_to_color(self, value):
normalized_value = (value - self.min_val) / (self.max_val - self.min_val)
hsv_color = (0.66 - 0.66 * normalized_value, 1.0, 1.0) # Blue to Red
rgb_color = colorsys.hsv_to_rgb(*hsv_color)
scaled_rgb_color = tuple(int(c * 255) for c in rgb_color)
return scaled_rgb_color
def show(self):
self.image.show()
def save(self, file):
self.image.save(file)

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