# HG changeset patch
# User luca_milaz
# Date 1722783991 0
# Node ID 85e5a73eb6d2ef5e5e9bd0bde18bcf3f36ca0ecf
# Parent  28de43f27623afcd3b80889b1d8f4aa048f9ca6e
Uploaded

diff -r 28de43f27623 -r 85e5a73eb6d2 marea_2/flux_to_map.py
--- a/marea_2/flux_to_map.py	Sun Aug 04 14:51:03 2024 +0000
+++ b/marea_2/flux_to_map.py	Sun Aug 04 15:06:31 2024 +0000
@@ -819,8 +819,8 @@
     return '#{:02x}{:02x}{:02x}'.format(int(rgba[0] * 255), int(rgba[1] * 255), int(rgba[2] * 255))
 
 def reds_cmap(value):
-    """Map normalized value to RGB color using the Reds colormap."""
-    # The `Reds` colormap starts with white and transitions to red
+    """Map a normalized value to RGB color using the Reds colormap."""
+    # Assumi che 'value' sia scalare e tra 0 e 1
     r = value
     g = 0
     b = 0
@@ -830,9 +830,6 @@
 
     metabMap_mean = copy.deepcopy(metabMap)
     metabMap_median = copy.deepcopy(metabMap)
-
-    #class_pat 462 * cellule
-
     
     medians = {}
     means = {}
@@ -843,21 +840,22 @@
         medians[key] = median
         means[key] = mean
 
-
     max_flux_medians = max(np.max(np.abs(arr)) for arr in medians.values())
     max_flux_means = max(np.max(np.abs(arr)) for arr in means.values())
 
+    # Normalizzazione dei medians e means
     for key, value in medians.items():
         medians[key] = medians[key] / max_flux_medians
     
     for key, value in means.items():
         means[key] = means[key] / max_flux_means
 
-    colors_median_rgb = {k: reds_cmap(v) for k, v in medians.items()}
-    colors_median = {k: rgba_to_hex(c) for k, c in colors_median_rgb.items()}
+    # Mappatura dei colori, applica reds_cmap a ogni elemento
+    colors_median_rgb = {k: [reds_cmap(v) for v in arr] for k, arr in medians.items()}
+    colors_median = {k: rgba_to_hex(np.mean(c, axis=0)) for k, c in colors_median_rgb.items()}
 
-    colors_mean_rgb = {k: reds_cmap(v) for k, v in means.items()}
-    colors_mean = {k: rgba_to_hex(c) for k, c in colors_mean_rgb.items()}
+    colors_mean_rgb = {k: [reds_cmap(v) for v in arr] for k, arr in means.items()}
+    colors_mean = {k: rgba_to_hex(np.mean(c, axis=0)) for k, c in colors_mean_rgb.items()}
 
     for rxn_id in ids:
         arrow = Arrow(width=5, col=colors_median[rxn_id])
@@ -865,7 +863,6 @@
 
     svgFilePath = utils.FilePath(details = "SVG Map median", ext = utils.FileFormat.SVG, prefix="result")
     utils.writeSvg(svgFilePath, metabMap_median)
-    pass
 
     
 ############################ MAIN #############################################