Fix the E712 pep8

ptiming_ana/cphase/pulsarphase_cal.py

@@ -289,7 +289,7 @@ def DL3_calphase(
     parname = str(os.path.basename(file).replace(".fits", "")) + ".par"
 
     # Calculate phases
-    if use_interpolation == False:
+    if not use_interpolation:
         model = create_files(timelist, ephem, timname, parname, obs=obs)
         if timname is None:
             barycent_toas, phases = compute_phases_from_times_model(times, model)
@@ -494,7 +494,7 @@ def DL2_calphase(
     timname = str(os.path.basename(dl2file).replace(".h5", "")) + ".tim"
     parname = str(os.path.basename(dl2file).replace(".h5", "")) + ".par"
 
-    if use_interpolation == False:
+    if not use_interpolation:
         model = create_files(timelist, ephem, timname, parname, obs=obs)
         barycent_toas, phase = get_phase_list_from_tim(timname, model, pickle)
         phase = phase.frac

ptiming_ana/cphase/utils.py

@@ -57,14 +57,14 @@ def merge_dl2_pulsar(directory, run_number, output_dir, src_dep=False):
         df_list.append(df_i)
 
         # Include source dependent information if it is the case
-        if src_dep == True:
+        if src_dep:
             df_i_src = pd.read_hdf(
                 file, key=dl2_params_src_dep_lstcam_key, float_precision=20
             )
             df_src_list.append(df_i_src)
 
     df = pd.concat(df_list)
-    if src_dep == True:
+    if src_dep:
         df_src = pd.concat(df_src_list)
 
     # Write the new merged dataframe into a file
@@ -76,7 +76,7 @@ def merge_dl2_pulsar(directory, run_number, output_dir, src_dep=False):
     metadata = global_metadata()
     write_metadata(metadata, output_file)
 
-    if src_dep == False:
+    if not src_dep:
         write_dl2_dataframe(df, output_file, meta=metadata)
 
     else:

ptiming_ana/phaseogram/lightcurve.py

@@ -208,7 +208,7 @@ def draw_background(self, pulsar_phases, color, hline=True):
         )
 
         # Add hline for background level reference (default True)
-        if hline == True:
+        if hline:
             plt.hlines(
                 y=np.mean(
                     (
@@ -256,7 +256,7 @@ def draw_fitting(self, pulsar_phases, color, density=False, label=None):
         elif pulsar_phases.fitting.model == "gaussian":
             y = gaussian(x, *pulsar_phases.fitting.params)
 
-        if density == True:
+        if density:
             width = 1 / len(self.lc[0])
             weight = np.ones(len(y)) / (np.sum(self.lc[0]) * width)
             y = y * weight
@@ -397,14 +397,14 @@ def show_phaseogram(
             self.draw_stats(pulsar_phases, phase_limits, stats)
 
         # Plot regions (default True)
-        if background == True:
+        if background:
             self.draw_background(pulsar_phases, colorb, hline)
 
         for i in range(0, len(signal)):
             self.draw_peakregion(pulsar_phases, signal[i], color=colorP[i])
 
         # Plot fitted distribution (default True)
-        if fit == True:
+        if fit:
             try:
                 self.draw_fitting(pulsar_phases, color=colorfit)
             except AttributeError:

ptiming_ana/phaseogram/penergy_analysis.py

@@ -106,7 +106,7 @@ def run(self, pulsarana):
 
                 self.Parray[i].init_regions()
 
-                if self.Parray[i].do_fit == True:
+                if self.Parray[i].do_fit:
                     self.Parray[i].setFittingParams(
                         self.Parray[i].fit_model,
                         self.Parray[i].binned,
@@ -136,7 +136,7 @@ def run(self, pulsarana):
 
                 self.Parray_integral[i].init_regions()
 
-                if self.Parray_integral[i].do_fit == True:
+                if self.Parray_integral[i].do_fit:
                     self.Parray_integral[i].setFittingParams(
                         self.Parray_integral[i].fit_model,
                         self.Parray_integral[i].binned,
@@ -264,17 +264,17 @@ def show_joined_Energy_fits(self, integral=None):
             histogram_array = self.Parray
 
         for i in range(0, len(histogram_array)):
-            if histogram_array[i].fitting.check_fit_result() == True:
+            if histogram_array[i].fitting.check_fit_result():
                 fig = plt.figure(figsize=(17, 8))
                 break
             elif (
                 i == len(histogram_array) - 1
-                and histogram_array[i].fitting.check_fit_result() == False
+                and not histogram_array[i].fitting.check_fit_result()
             ):
                 print("No fit available for any energy bin")
                 return
         for i in range(0, len(histogram_array)):
-            if histogram_array[i].fitting.check_fit_result() == True:
+            if histogram_array[i].fitting.check_fit_result():
                 histogram_array[i].histogram.draw_fitting(
                     histogram_array[i],
                     color="C" + str(i),
@@ -390,7 +390,7 @@ def show_Energy_fitresults(self, integral=None):
                 + f"{self.energy_edges[i]*1000:.2f}-{self.energy_edges[i+1]*1000:.2f}"
                 + "\n"
             )
-            if histogram_array[i].fitting.check_fit_result() == True:
+            if histogram_array[i].fitting.check_fit_result():
                 fit_results[i] = histogram_array[i].show_fit_results()
             else:
                 print("No fit available for this energy range")

ptiming_ana/phaseogram/pfitting.py

@@ -32,7 +32,7 @@ def run(self, pulsar_phases):
 
         self.est_initial_values(pulsar_phases)
         # Do the fitting
-        if self.binned == True:
+        if self.binned:
             self.fit_Binned(pulsar_phases)
         else:
             self.fit_ULmodel(pulsar_phases)

ptiming_ana/phaseogram/pulsar_analysis.py

@@ -220,7 +220,7 @@ def set_config(self, configuration_file):
 
         # Read files
         self.filter_data = conf["cuts"]["filter_data"]
-        if conf["flags"]["DL2_format"] == True:
+        if conf["flags"]["DL2_format"]:
             if os.path.isdir(conf["pulsar_file_dir"]):
                 self.setLSTInputFile(
                     dirname=conf["pulsar_file_dir"],
@@ -275,7 +275,7 @@ def set_config(self, configuration_file):
             else:
                 self.setParamCuts(zd_cut=conf["cuts"]["zd_range"])
 
-        elif conf["flags"]["fits_format"] == True:
+        elif conf["flags"]["fits_format"]:
             self.setFermiInputFile(filename=conf["pulsar_file_dir"])
 
         else:
@@ -297,7 +297,7 @@ def set_config(self, configuration_file):
             P3_limits=conf["phase_regions"]["P3"],
         )
 
-        if conf["phase_binning"]["custom_binning"] == False:
+        if conf["phase_binning"]["custom_binning"]:
             self.setBinning(
                 conf["phase_binning"]["nbins"],
                 xmin=conf["phase_binning"]["xmin"],
@@ -445,7 +445,7 @@ def execute_stats(self, tobs):
         self.tobs = tobs
 
         # Fit the histogram using PeakFitting class. If binned is False, an Unbinned Likelihood method is used for the fitting
-        if self.do_fit == True:
+        if self.do_fit:
             logger.info("Fitting the data to the given model...")
             logger.info("Fit model: " + self.fit_model)
             logger.info("Binned fitting: " + str(self.binned))

ptiming_ana/phaseogram/read_events.py

@@ -216,7 +216,7 @@ def add_phases(self, pname):
 
     def read_LSTfile(self, fname, df_type="short", filter_data=True):
         if filter_data:
-            if self.src_dependent == False:
+            if not self.src_dependent:
                 df_or = pd.read_hdf(fname, key=dl2_params_lstcam_key)
                 if "pulsar_phase" not in df_or:
                     df_pulsar = pd.read_hdf(fname, key="phase_info")
@@ -252,7 +252,7 @@ def read_LSTfile(self, fname, df_type="short", filter_data=True):
                 else:
                     df = df_or
 
-            elif self.src_dependent == True:
+            elif self.src_dependent:
                 srcindep_df = pd.read_hdf(
                     fname, key=dl2_params_lstcam_key, float_precision=20
                 )