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.gitignore

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+install/
+.cproject
+.project
+bin/
+.settings
+*.aux
+*.log
+*.out
+*.toc
+*.o
+*.so
+.*
+build/
+RELEASE.txt
+Testing/
+
+ctbDict.cpp
+ctbDict.h
+
+wheelhouse/
+dist/
+
+*.pyc
+*/__pycache__/*
+

play.py

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+import matplotlib.pyplot as plt
+plt.ion()
+import numpy as np
+
+
+from simple_eta import gaussian_2d, plot_gaussian
+from simple_eta import generate
+
+sigma_um = 12
+resolution = 200
+grid_size = 3
+pixel_size = 25
+
+
+pos = (37.5,37.5) #x,y
+t = gaussian_2d(mx=pos[0], my = pos[1], sigma = sigma_um, res = resolution, grid_size = grid_size, pixel_size = pixel_size)
+
+fig, ax = plot_gaussian(t, pixel_size=pixel_size, grid_size = grid_size)
+plt.show()
+
+res = generate.sum_pixels(t, grid_size)
+
+
+fig,ax = plt.subplots()
+im = ax.imshow(res, origin = 'lower')

simple_eta/__init__.py

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+from .generate import gaussian_2d
+from .plotting import plot_gaussian

simple_eta/generate.py

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+import torch
+import math
+import numpy as np
+
+def gaussian_2d(mx, my, sigma = 1, res=100, pixel_size = 25, grid_size = 2):
+    """
+    Generate a 2D gaussian as position mx, my, with sigma=sigma. 
+    The gaussian is placed on a grid_size x grid_size pixel matrix with resolution 
+    res in one dimesion.
+    """
+    x = torch.linspace(0, pixel_size*grid_size, res)
+    x,y = torch.meshgrid(x,x, indexing="ij")
+    return 1 / (2*math.pi*sigma**2) * \
+      torch.exp(-((x - my)**2 / (2*sigma**2) + (y - mx)**2 / (2*sigma**2)))
+
+
+def sum_pixels(t, grid):
+    resolution = t.shape[0]
+    pixels = np.zeros((grid,grid))
+
+    step = resolution//grid
+    for i in range(grid):
+        for j in range(grid):
+            print(f'[{i*step}:{(i+1)*step}, {j*step}:{(j+1)*step}]')
+            pixels[i,j] = t[i*step:(i+1)*step, j*step:(j+1)*step].sum()
+
+    # pixels[0,0] = t[0:resolution//2, 0:resolution//2].sum()
+    # pixels[0,1] = t[0:resolution//2, resolution//2:].sum()
+    # pixels[1,0] = t[resolution//2:, 0:resolution//2].sum()
+    # pixels[1,1] = t[resolution//2:, resolution//2:].sum()
+    return pixels
+
+def sum_pixels2(t, grid):
+    resolution = t.shape[0]
+    pixels = np.zeros((grid,grid))
+    pixels[0,0] = t[0:resolution//2, 0:resolution//2].sum()
+    pixels[0,1] = t[0:resolution//2, resolution//2:].sum()
+    pixels[1,0] = t[resolution//2:, 0:resolution//2].sum()
+    pixels[1,1] = t[resolution//2:, resolution//2:].sum()
+    return pixels

simple_eta/plotting.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+def plot_gaussian(t, pixel_size, grid_size):
+    print(f'{t.shape=}')
+
+    resolution = t.shape[0]
+    xa = np.linspace(0,grid_size*pixel_size,resolution)
+    ticks = [tick for tick in range(0,pixel_size*grid_size+1, pixel_size)]
+
+    fig, ax = plt.subplots(figsize = (7,7))
+    ax.pcolormesh(xa,xa, t)
+    ax.set_xticks(ticks)
+    ax.set_yticks(ticks)
+    ax.set_xlim(0,grid_size*pixel_size)
+    ax.set_ylim(0,grid_size*pixel_size)
+    
+    ax.grid()
+
+    ax.set_xlabel(r'Position x [$\mu$m]')
+    ax.set_ylabel(r'Position y [$\mu$m]')
+    return fig, ax