pep8 coding style

catalog/C10_Catalog.py

@@ -312,7 +312,7 @@ class Catalog(CatalogBase):
             param['diskmass'] = gals['diskmass'][igals]
 
             np.random.seed(int(pix_id)+cat_id+igals)
-            param['size'] = (gals['size'][igals] *((1.+gals['redshift'][igals])**(0.4))) *np.random.uniform(0.7, 1.3)
+            param['size'] = (gals['size'][igals] * ((1.+gals['redshift'][igals])**(0.4))) * np.random.uniform(0.7, 1.3)
             if param['size'] > self.max_size:
                 self.max_size = param['size']
 

tools/imgCropping.py

-import os,sys
+import os
+import sys
 import numpy as np
 from astropy.io import fits
 
@@ -6,12 +7,13 @@ PRESCAN_X, IMAGE_X, OVERSCAN_X = 27, 1152, 71
 PRESCAN_Y, IMAGE_Y, OVERSCAN_Y = 0, 4616, 84
 BLOCK_WIDTH = PRESCAN_X + IMAGE_X + OVERSCAN_X
 
+
 def process_single_file(filename):
     with fits.open(filename) as hdul:
         data = hdul[1].data
 
-    data = data[PRESCAN_Y : PRESCAN_Y + IMAGE_Y, :]
-    blocks = [data[:, i * BLOCK_WIDTH + PRESCAN_X : (i + 1) * BLOCK_WIDTH - OVERSCAN_X] for i in range(16)]
+    data = data[PRESCAN_Y:PRESCAN_Y + IMAGE_Y, :]
+    blocks = [data[:, i * BLOCK_WIDTH + PRESCAN_X:(i + 1) * BLOCK_WIDTH - OVERSCAN_X] for i in range(16)]
 
     blocks_a = np.concatenate(blocks[:4], axis=1)
     blocks_b = np.concatenate([np.fliplr(b) for b in blocks[4:8]], axis=1)
@@ -26,6 +28,7 @@ def process_single_file(filename):
     fits.writeto(output_path, blocks_final, overwrite=True)
     print(f"OK:{output_path}")
 
+
 if __name__ == "__main__":
     if len(sys.argv) > 1:
         fn = sys.argv[1]