update codestyle-PEP8

observation_sim/instruments/FilterParam.py

@@ -25,7 +25,7 @@ class FilterParam(object):
         # 6) sky background: e/pix/s
         # 7) saturation magnitude
         # 8) dim end magnitude
-        if filter_param == None:
+        if filter_param is None:
             filtP = {
                 "NUV":   [2867.7,   705.4,  2470.0,   3270.0,  0.1404, 0.004, 15.7, 25.4],
                 "u":     [3601.1,   852.1,  3120.0,   4090.0,  0.2176, 0.021, 16.1, 25.4],

observation_sim/instruments/FocalPlane.py

@@ -9,7 +9,7 @@ class FocalPlane(object):
         self.nchips = 42
         self.ignore_chips = []
 
-        if bad_chips == None:
+        if bad_chips is None:
             self.bad_chips = []
         else:
             self.bad_chips = bad_chips
@@ -80,7 +80,7 @@ class FocalPlane(object):
         if logger is not None:
             logger.info(
                 "    Construct the wcs of the entire image mosaic using Gnomonic/TAN projection")
-        if (xcen == None) or (ycen == None):
+        if (xcen is None) or (ycen is None):
             xcen = self.cen_pix_x
             ycen = self.cen_pix_y
 

observation_sim/instruments/chip/Chip.py

@@ -191,7 +191,7 @@ class Chip(FocalPlane):
         """Return the filter index and type for a given chip #(chipID)
         """
         filter_type_list = _util.ALL_FILTERS
-        if chipID == None:
+        if chipID is None:
             chipID = self.chipID
 
         # updated configurations

observation_sim/instruments/chip/chip_utils.py

@@ -206,7 +206,7 @@ def get_poisson(seed=0, sky_level=0.):
 
 
 def get_base_img(img, chip, read_noise, readout_time, dark_noise, exptime=150., InputDark=None):
-    if InputDark == None:
+    if InputDark is None:
         # base_level = read_noise**2 + dark_noise*(exptime+0.5*readout_time)
         # base_level = dark_noise*(exptime+0.5*readout_time)
         base_level = dark_noise*(exptime)
@@ -237,7 +237,7 @@ def add_poisson(img, chip, exptime=150., seed=0, sky_level=0., poisson_noise=Non
     img.addNoise(poisson_noise)
     # img -= read_noise**2
 
-    if InputDark != None:
+    if InputDark is not None:
         # "Instrument/data/dark/dark_1000s_example_0.fits"
         hdu = fits.open(InputDark)
         img += hdu[0].data/hdu[0].header['exptime']*exptime

observation_sim/sim_steps/add_pattern_noise.py

@@ -80,6 +80,6 @@ def add_bias(self, chip, filt, tel, pointing, catalog, obs_param):
                                                nsecy=chip.nsecy,
                                                nsecx=chip.nsecx,
                                                seed=self.overall_config["random_seeds"]["seed_biasNonUniform"]+chip.chipID)
-    elif obs_param["bias_16channel"] == False:
+    elif obs_param["bias_16channel"] is False:
         chip.img += chip.bias_level
     return chip, filt, tel, pointing