Loading observation_sim/mock_objects/Galaxy.py +3 −3 Original line number Diff line number Diff line Loading @@ -375,7 +375,7 @@ class Galaxy(MockObject): 1, origin_star[1] + galImg.array.shape[1] - 1] if gal_origin[1] < grating_split_pos_chip < gal_end[1]: subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1) subSlitPos = int(grating_split_pos_chip - gal_origin[1]) # part img disperse star_p1s=[] Loading Loading @@ -407,12 +407,12 @@ class Galaxy(MockObject): for galImg in galImg_List: subImg_p2 = galImg.array[:, subSlitPos + 1:galImg.array.shape[1]] subSlitPos:galImg.array.shape[1]] star_p2 = galsim.Image(subImg_p2) star_p2.setOrigin(0, 0) star_p2s.append(star_p2) origin_p2 = [origin_star[0], grating_split_pos_chip] xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0 xcenter_p2 = max(x_nominal, grating_split_pos_chip) - 0 ycenter_p2 = y_nominal - 0 sdp_p2 = SpecDisperser(orig_img=star_p2s, xcenter=xcenter_p2, Loading observation_sim/mock_objects/MockObject.py +3 −3 Original line number Diff line number Diff line Loading @@ -477,7 +477,7 @@ class MockObject(object): gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1] if gal_origin[1] < grating_split_pos_chip < gal_end[1]: subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1) subSlitPos = int(grating_split_pos_chip - gal_origin[1]) # part img disperse star_p1s=[] for starImg in starImg_List: Loading Loading @@ -508,12 +508,12 @@ class MockObject(object): for starImg in starImg_List: subImg_p2 = starImg.array[:, subSlitPos + 1:starImg.array.shape[1]] subSlitPos:starImg.array.shape[1]] star_p2 = galsim.Image(subImg_p2) star_p2.setOrigin(0, 0) star_p2s.append(star_p2) origin_p2 = [origin_star[0], grating_split_pos_chip] xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0 xcenter_p2 = max(x_nominal, grating_split_pos_chip) - 0 ycenter_p2 = y_nominal - 0 sdp_p2 = SpecDisperser(orig_img=star_p2s, xcenter=xcenter_p2, Loading observation_sim/sim_steps/readout_output.py +1 −0 Original line number Diff line number Diff line Loading @@ -44,6 +44,7 @@ def apply_gain(self, chip, filt, tel, pointing, catalog, obs_param): seed=self.overall_config["random_seeds"]["seed_gainNonUniform"]+chip.chipID) elif obs_param["gain_16channel"] == False: chip.img /= chip.gain chip.gain_channel = np.ones(chip.nsecy*chip.nsecx)*chip.gain return chip, filt, tel, pointing Loading Loading
observation_sim/mock_objects/Galaxy.py +3 −3 Original line number Diff line number Diff line Loading @@ -375,7 +375,7 @@ class Galaxy(MockObject): 1, origin_star[1] + galImg.array.shape[1] - 1] if gal_origin[1] < grating_split_pos_chip < gal_end[1]: subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1) subSlitPos = int(grating_split_pos_chip - gal_origin[1]) # part img disperse star_p1s=[] Loading Loading @@ -407,12 +407,12 @@ class Galaxy(MockObject): for galImg in galImg_List: subImg_p2 = galImg.array[:, subSlitPos + 1:galImg.array.shape[1]] subSlitPos:galImg.array.shape[1]] star_p2 = galsim.Image(subImg_p2) star_p2.setOrigin(0, 0) star_p2s.append(star_p2) origin_p2 = [origin_star[0], grating_split_pos_chip] xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0 xcenter_p2 = max(x_nominal, grating_split_pos_chip) - 0 ycenter_p2 = y_nominal - 0 sdp_p2 = SpecDisperser(orig_img=star_p2s, xcenter=xcenter_p2, Loading
observation_sim/mock_objects/MockObject.py +3 −3 Original line number Diff line number Diff line Loading @@ -477,7 +477,7 @@ class MockObject(object): gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1] if gal_origin[1] < grating_split_pos_chip < gal_end[1]: subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1) subSlitPos = int(grating_split_pos_chip - gal_origin[1]) # part img disperse star_p1s=[] for starImg in starImg_List: Loading Loading @@ -508,12 +508,12 @@ class MockObject(object): for starImg in starImg_List: subImg_p2 = starImg.array[:, subSlitPos + 1:starImg.array.shape[1]] subSlitPos:starImg.array.shape[1]] star_p2 = galsim.Image(subImg_p2) star_p2.setOrigin(0, 0) star_p2s.append(star_p2) origin_p2 = [origin_star[0], grating_split_pos_chip] xcenter_p2 = max(x_nominal, grating_split_pos_chip - 1) - 0 xcenter_p2 = max(x_nominal, grating_split_pos_chip) - 0 ycenter_p2 = y_nominal - 0 sdp_p2 = SpecDisperser(orig_img=star_p2s, xcenter=xcenter_p2, Loading
observation_sim/sim_steps/readout_output.py +1 −0 Original line number Diff line number Diff line Loading @@ -44,6 +44,7 @@ def apply_gain(self, chip, filt, tel, pointing, catalog, obs_param): seed=self.overall_config["random_seeds"]["seed_gainNonUniform"]+chip.chipID) elif obs_param["gain_16channel"] == False: chip.img /= chip.gain chip.gain_channel = np.ones(chip.nsecy*chip.nsecx)*chip.gain return chip, filt, tel, pointing Loading