# HG changeset patch
# User luca_milaz
# Date 1722798763 0
# Node ID e4d02f9b41a1c1821e16b59f2be007a35c48aa0e
# Parent  b501ac3585a1b414361ce7539c750d4d998e7818
Uploaded

diff -r b501ac3585a1 -r e4d02f9b41a1 marea_2/flux_to_map.py
--- a/marea_2/flux_to_map.py	Sun Aug 04 19:00:56 2024 +0000
+++ b/marea_2/flux_to_map.py	Sun Aug 04 19:12:43 2024 +0000
@@ -851,6 +851,57 @@
     # Convert RGB values (0-1 range) to hexadecimal format
     rgb = (rgb * 255).astype(int)
     return '#{:02x}{:02x}{:02x}'.format(rgb[0], rgb[1], rgb[2])
+
+def jet_colormap(value):
+    """
+    Generate an RGB color based on a single numeric value using a colormap similar to MATLAB's 'jet'.
+
+    Args:
+        value (float): A numeric value to be mapped to a color.
+
+    Returns:
+        tuple: An (R, G, B) tuple with color components in the range [0, 255].
+    """
+    # Normalize value to range [0, 1]
+    value = np.clip(value, 0, 1)
+    
+    # Define the red, green, and blue color components
+    red = np.clip(1.5 - np.abs(4 * (value - 0.75)), 0, 1)
+    green = np.clip(1.5 - np.abs(4 * (value - 0.5)), 0, 1)
+    blue = np.clip(1.5 - np.abs(4 * (value - 0.25)), 0, 1)
+    
+    # Convert to 0-255 range
+    return int(red * 255), int(green * 255), int(blue * 255)
+
+def save_colormap_image(min_value:float, max_value:float, path:str):
+    """
+    Create and save an image of the colormap showing the gradient and its range.
+
+    Args:
+        min_value (float): The minimum value of the colormap range.
+        max_value (float): The maximum value of the colormap range.
+        filename (str): The filename for saving the image.
+    """
+    # Define image size and create a new image
+    width = 256
+    height = 50
+    image = Image.new('RGB', (width, height), color='white')
+    draw = ImageDraw.Draw(image)
+    
+    # Create the gradient
+    for x in range(width):
+        value = (x / (width - 1)) * (max_value - min_value) + min_value
+        color = jet_colormap((value - min_value) / (max_value - min_value))
+        draw.line([(x, 0), (x, height)], fill=color)
+    
+    # Add text for min and max values
+    font = ImageFont.load_default()
+    draw.text((10, height - 20), f'{min_value:.2f}', fill='black', font=font)
+    draw.text((width - 50, height - 20), f'{max_value:.2f}', fill='black', font=font)
+    
+    # Save the image
+    image.save(path.show())
+    pass
     
 
 def computeEnrichmentMeanMedian(metabMap: ET.ElementTree, class_pat: Dict[str, List[List[float]]], ids: List[str]) -> None:
@@ -878,9 +929,15 @@
     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())
 
+    min_flux_medians = min(np.min(np.abs(arr)) for arr in medians.values())
+    min_flux_means = min(np.min(np.abs(arr)) for arr in means.values())
+
     medians = {key: median / max_flux_medians for key, median in medians.items()}
     means = {key: mean / max_flux_means for key, mean in means.items()}
 
+    save_colormap_image(min_flux_medians, max_flux_medians, utils.FilePath("Color map median", ext=utils.FileFormat.PNG, prefix="result"))
+    save_colormap_image(min_flux_means, max_flux_means, utils.FilePath("Color map mean", ext=utils.FileFormat.PNG, prefix="result"))
+
     for key in class_pat:
         # Create color mappings for median and mean
         colors_median = {rxn_id: rgb_to_hex(jet_colormap(medians[key][i])) for i, rxn_id in enumerate(ids)}
@@ -937,6 +994,8 @@
     if not ARGS.generate_svg:
         os.remove(svgFilePath.show())
 
+
+
     
 ############################ MAIN #############################################
 def main() -> None: