#59: Save rmss for futher investigations

For instance to plot a fair comparison, see [issues/59#issuecomment-1732](#59 (comment)).

datasets/raise/extract_noise.py

@@ -4,7 +4,7 @@ import numpy as np
 import os
 from tqdm import tqdm
 import csv
-from utils import Color, denoise, iterativeMean, isARawImage, escapeFilePath, getColorChannel
+from utils import Color, denoise, iterativeMean, isARawImage, escapeFilePath, getColorChannel, saveNpArray
 import matplotlib.pyplot as plt
 from scipy.ndimage import gaussian_filter
 
@@ -95,10 +95,6 @@ if (minColor is None or maxColor is None) and denoiser != 'mean':
     print(f'{minColor=}')
     print(f'{maxColor=}')
 
-def saveNpArray(fileName, npArray):
-    with open(f'{fileName}.npy', 'wb') as f:
-        np.save(f, npArray)
-
 if denoiser == 'mean':
     means = {}
     for color in colors:

datasets/raise/split_and_compare_prnus_of_subgroups.py

@@ -56,5 +56,6 @@ plt.title(f'RMS between both subgroups estimated PRNUs with {DENOISER} denoiser
 plt.xlabel('Number of images of each subgroup')
 plt.ylabel('RMS between both subgroups estimated PRNUs')
 plt.plot(rmss)
+saveNpArray('{setting}_rmss', rmss)
 plt.savefig(f'{setting}_rms_between_estimated_prnu_of_2_subgroups.svg')
 #plt.show()

datasets/raise/utils.py

@@ -119,4 +119,8 @@ def mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelImages
                 newX, newY = [getNewIndex(index, offset) for index, offset in [(x, offsetX), (y, offsetY)]]
 
                 multipleColorsImage[newX, newY] = pixel
-    return multipleColorsImage
+    return multipleColorsImage
+
+def saveNpArray(fileName, npArray):
+    with open(f'{fileName}.npy', 'wb') as f:
+        np.save(f, npArray)