pep8 fixes

spacetelescope · Oct 18, 2021 · 226dcbb · 226dcbb
1 parent f9cc6ca
commit 226dcbb
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Showing 2 changed files with 10 additions and 15 deletions.
diff --git a/imexam/imexamine.py b/imexam/imexamine.py
@@ -507,8 +507,8 @@ def save(self, filename=None, fig=None):
 
         if fig is None:
             fig = self._plot_windows[-1]
-        
-        fig.savefig(self.plot_name)        
+
+        fig.savefig(self.plot_name)
         pstr = f"plot {fig.number} saved to {self.plot_name}"
         self.log.info(pstr)
 
@@ -879,7 +879,6 @@ def line_fit(self, x, y, data=None, form=None, genplot=True, fig=None, col=False
                 fig.canvas.draw_idle()
             self._plot_windows[-1] = plt.gcf()
 
-
         else:
             return fitted
 
@@ -1053,7 +1052,7 @@ def radial_profile(self, x, y, data=None, form=None,
                 form = getattr(models, pars["func"][0])
             if form.name not in self._fit_models:
                 raise ValueError(f"Functional {form.name} not in available: {self._fit_models}")
-           
+
             self.log.info(f"using model: {form}")
 
         subtract_background = bool(pars["background"][0])
@@ -1062,7 +1061,6 @@ def radial_profile(self, x, y, data=None, form=None,
                              "background subtraction")
             subtract_background = False
 
-
         getdata = bool(pars["getdata"][0])
         delta = int(pars["delta"][0])
 
@@ -1085,8 +1083,8 @@ def radial_profile(self, x, y, data=None, form=None,
             datasize = 3
 
         if pars["center"][0]:
-            xx=int(x)
-            yy=int(y)
+            xx = int(x)
+            yy = int(y)
             data_chunk = data[yy - datasize:yy + datasize,
                               xx - datasize:xx + datasize]
             amp, xx, yy, sigma, sigmay = self.gauss_center(xx,
@@ -1167,12 +1165,11 @@ def radial_profile(self, x, y, data=None, form=None,
             self.log.info(info)
             self.log.info(radius, flux)
 
-
         # Fit the functional form to the radial profile flux
         if fitplot:
             fline = np.linspace(0, datasize, 100)  # finer sample
             # fit model to data
-            if form.name == "Gaussian1D":# make center radii at max ********
+            if form.name == "Gaussian1D":  # make center radii at max ********
 
                 fitted = math_helper.fit_gauss_1d(radius, flux,
                                                   sigma_factor=sig_factor,
@@ -1211,7 +1208,7 @@ def radial_profile(self, x, y, data=None, form=None,
                 legendy = np.max(flux) / 2
 
             if fitted is None:
-                msg = f"Problem with the {fitform.name} fit"
+                msg = f"Problem with the {form.name} fit"
                 self.log.info(msg)
                 raise ValueError(msg)
 

diff --git a/imexam/math_helper.py b/imexam/math_helper.py
@@ -100,7 +100,6 @@ def fit_moffat_1d(data, gamma=2., alpha=1., sigma_factor=0.,
         x0 = center_at
         fluxmax = max(data)
 
-
     # assumes negligable background
     if weighted:
         z = np.nan_to_num(1. / np.sqrt(data))  # use as weight
@@ -168,15 +167,14 @@ def fit_gauss_1d(radius, flux, sigma_factor=0, center_at=None, weighted=False):
     if radius.shape != flux.shape:
         raise ValueError("Expected same sizes for radius and flux")
 
-
     if center_at is None:
         center_mean = sum(radius)/len(radius)
         fixed = {'amplitude': False}
-        bounds = {'amplitude': (flux.max()/2.,flux.max())}
+        bounds = {'amplitude': (flux.max() / 2., flux.max())}
     else:
         center_mean = center_at
         fixed = {'mean': True, 'amplitude': True}
-        bounds = {'amplitude': (flux.max()/2., flux.max())}
+        bounds = {'amplitude': (flux.max() / 2., flux.max())}
 
     # assumes negligable background
     if weighted:
@@ -194,7 +192,7 @@ def fit_gauss_1d(radius, flux, sigma_factor=0, center_at=None, weighted=False):
 
     # Gaussian1D + a constant
     model = (models.Gaussian1D(amplitude=flux.max(),
-                               mean=center_mean, stddev=1., 
+                               mean=center_mean, stddev=1.,
                                fixed=fixed,
                                bounds=bounds) +
              models.Polynomial1D(c0=flux.min(), degree=0))