update module-crosstalk

observation_sim/sim_steps/readout_output.py

@@ -44,7 +44,7 @@ def add_crosstalk(self, chip, filt, tel, pointing, catalog, obs_param):
     crosstalk[15, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1.])
 
     # 2*8 -> 1*16
-    img = formatOutput(chip.img)
+    img = chip_utils.formatOutput(chip.img)
     ny, nx = img.array.shape
     nsecy = 1
     nsecx = 16
@@ -57,7 +57,7 @@ def add_crosstalk(self, chip, filt, tel, pointing, catalog, obs_param):
             newimg.array[:, int(i*dx):int(i*dx+dx)] += crosstalk[i, j]*img.array[:, int(j*dx):int(j*dx+dx)]
 
     # 1*16 -> 2*8
-    newimg = formatRevert(newimg)
+    newimg = chip_utils.formatRevert(newimg)
     chip.img.array[:, :] = newimg.array[:, :]
 
     return chip, filt, tel, pointing

tests/test_crosstalk.py

+import unittest
+
+import sys
+import os
+import math
+from itertools import islice
+import numpy as np
+import copy
+import ctypes
+import galsim
+import yaml
+from astropy.io import fits
+
+from observation_sim.instruments.chip import chip_utils
+import matplotlib.pyplot as plt
+
+
+# test FUNCTION --- START #
+def add_crosstalk(GSimg):
+    crosstalk = np.zeros([16, 16])
+    crosstalk[0, :] = np.array([1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[1, :] = np.array([1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[2, :] = np.array([0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[3, :] = np.array([0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[4, :] = np.array([0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[5, :] = np.array([0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[6, :] = np.array([0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[7, :] = np.array([0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0., 0., 0.])
+    crosstalk[8, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0., 0., 0.])
+    crosstalk[9, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0., 0., 0.])
+    crosstalk[10, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0., 0., 0.])
+    crosstalk[11, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0., 0., 0.])
+    crosstalk[12, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4, 0., 0.])
+    crosstalk[13, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1., 0., 0.])
+    crosstalk[14, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1e-4])
+    crosstalk[15, :] = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1e-4, 1.])
+
+    # 2*8 -> 1*16
+    img = chip_utils.formatOutput(GSimg)
+    ny, nx = img.array.shape
+    nsecy = 1
+    nsecx = 16
+    dy = int(ny/nsecy)
+    dx = int(nx/nsecx)
+
+    newimg = galsim.Image(nx, ny, init_value=0)
+    for i in range(16):
+        for j in range(16):
+            newimg.array[:, int(i*dx):int(i*dx+dx)] += crosstalk[i, j]*img.array[:, int(j*dx):int(j*dx+dx)]
+
+    # 1*16 -> 2*8
+    newimg = chip_utils.formatRevert(newimg)
+
+    return newimg 
+# test FUNCTION --- END #
+
+
+class detModule_coverage(unittest.TestCase):
+    def __init__(self, methodName='runTest'):
+        super(detModule_coverage, self).__init__(methodName)
+        self.dataPath = os.path.join(
+            os.getenv('UNIT_TEST_DATA_ROOT'), 'csst_msc_sim/csst_fz_msc')
+
+    def test_add_crosstalk(self):
+        nsecy = 2
+        nsecx = 8
+        ny, nx = 1024,1024
+        dy = int(ny/nsecy)
+        dx = int(nx/nsecx)
+        mapclip = np.zeros([dy, int(nsecx*nsecy*dx)])
+        for i in range(int(nsecx*nsecy)):
+            mapclip[:, i*dx:dx+i*dx] = np.random.randint(10)+np.random.rand(int(dy*dx)).reshape([dy, dx])
+        mapclip = galsim.ImageF(mapclip)
+
+        nsecy = 1
+        nsecx = 16
+        ny,nx = mapclip.array.shape
+        dy = int(ny/nsecy)
+        dx = int(nx/nsecx)
+        for i in range(int(nsecy*nsecx)):
+            gal = galsim.Gaussian(sigma=0.2, flux=500000).drawImage(nx=32, ny=32).array
+            py = np.random.randint(450)+10
+            mapclip.array[py:py+32, int(i*dx)+10:int(i*dx)+42] += gal
+        
+        tmap = chip_utils.formatRevert(mapclip, nsecy=1, nsecx=16)  # 1*16 -> 2*8
+        temp = add_crosstalk(tmap)
+
+        fig = plt.figure(figsize=(20,60))
+        ax = plt.subplot(311)
+        plt.imshow(np.log10(mapclip.array+1), origin='lower', cmap='gray')
+        ax = plt.subplot(312)
+        plt.imshow(np.log10(temp.array+1), origin='lower', cmap='gray')
+        ax = plt.subplot(313)
+        plt.imshow(np.log10(temp.array-tmap.array+1), origin='lower', cmap='gray')
+        plt.savefig(os.path.join(self.dataPath, "./test_crosstalk.png"), dpi=300, bbox_inches='tight')
+        self.assertTrue(True)
+
+
+if __name__ == '__main__':
+    unittest.main()