pep8

Author: ceb8

astroquery/esa/neocc/core.py

@@ -505,7 +505,7 @@ def query_object(name, tab, **kwargs):
 
         if not isinstance(neocc_obj, list):
             neocc_obj = [neocc_obj]
-        
+
         return neocc_obj
 
 

astroquery/esa/neocc/lists.py

@@ -192,7 +192,7 @@ def parse_risk(resp_str):
 
     if "Years" in neocc_lst.colnames:
         first_year, last_year = np.array([x.split("-") for x in neocc_lst["Years"]]).swapaxes(0, 1).astype(int)
-        yr_index = neocc_lst.index_column("Years") 
+        yr_index = neocc_lst.index_column("Years")
         neocc_lst.remove_column("Years")
         neocc_lst.add_column(Column(name="Last Year", data=last_year), index=yr_index)
         neocc_lst.add_column(Column(name="First Year", data=first_year), index=yr_index)
@@ -264,9 +264,8 @@ def parse_pri(resp_str):
                            names=['Priority', 'Object', 'R.A. in arcsec', 'Decl. in deg',
                                   'Elong. in deg', 'V in mag', 'Sky uncert.', 'End of Visibility'])
 
-    neocc_lst["Object"] = [x.replace(' ','') for x in neocc_lst["Object"]]
+    neocc_lst["Object"] = [x.replace(' ', '') for x in neocc_lst["Object"]]
     neocc_lst['End of Visibility'] = Time.strptime(neocc_lst['End of Visibility'], '%Y/%m/%d')
-    
 
     neocc_lst.meta = {'Priority': '0=UR: Urgent, 1=NE: Necessary, 2=US: Useful, 3=LP: Low Priority',
                       'Object': 'designator of the object',

astroquery/esa/neocc/tabs.py

@@ -319,12 +319,12 @@ def _parse_opt_obs(optical_str):
     """
 
     obs_table = Table.read(optical_str, format="ascii.fixed_width_no_header",
-                           col_starts=[ 0, 11, 13, 15, 17, 22, 25, 40, 50, 53, 56, 64, 75, 83, 87,
-                                        95,  103, 106, 110, 117, 128, 136, 140, 147, 156, 161, 164,
-                                        170, 177, 180, 187, 194, 196],
-                           col_ends=[ 10, 12, 14, 16, 21, 24, 39, 49, 52, 55, 63, 74, 82, 86, 94, 102,
-                                      105, 109, 116, 127, 135, 139, 146, 155, 160, 163, 169, 176, 179,
-                                      186, 193, 195, 197],
+                           col_starts=[0, 11, 13, 15, 17, 22, 25, 40, 50, 53, 56, 64, 75, 83, 87,
+                                       95, 103, 106, 110, 117, 128, 136, 140, 147, 156, 161, 164,
+                                       170, 177, 180, 187, 194, 196],
+                           col_ends=[10, 12, 14, 16, 21, 24, 39, 49, 52, 55, 63, 74, 82, 86, 94, 102,
+                                     105, 109, 116, 127, 135, 139, 146, 155, 160, 163, 169, 176, 179,
+                                     186, 193, 195, 197],
                            names=['Design.', 'K', 'T', 'N', 'Date', 'MM', 'DD.ddd',
                                   'Date Accuracy', 'RA HH', 'RA MM', 'RA SS.sss', 'RA Accuracy',
                                   'RA RMS', 'RA F', 'RA Bias', 'RA Resid', 'DEC sDD', 'DEC MM',
@@ -402,14 +402,14 @@ def _parse_rov_obs(rov_str):
     NOTE: THIS IS UNTESTED (can't find an object with these rows)
     """
 
-    rov_table = Table.read(rov_str, format="ascii.fixed_width_no_header", 
+    rov_table = Table.read(rov_str, format="ascii.fixed_width_no_header",
                            col_starts=[0, 11, 13, 15, 17, 22, 25, 34, 45, 56, 65],
                            col_ends=[10, 12, 14, 16, 21, 24, 33, 44, 55, 64, 68],
                            names=['Design.', 'K', 'T', 'N', 'Date', 'MM', 'DD.dddddd',
                                   'E longitude', 'Latitude', 'Altitude', 'Obs Code'])
 
     # Combining the date column
-    date_array = [f"{x}/{y}/{z}" for x,y,z in rov_table["Date", "MM", "DD.dddddd"]]
+    date_array = [f"{x}/{y}/{z}" for x, y, z in rov_table["Date", "MM", "DD.dddddd"]]
     rov_table["Date"] = convert_time(date_array, conversion_string='%Y/%m/%d')
     rov_table.remove_columns(["MM", "DD.dddddd"])
 
@@ -426,15 +426,15 @@ def _parse_radar_obs(radar_str):
     radar_str = radar_str[radar_str.find('\n')+1:]  # First row is header
     radar_table = Table.read(radar_str, format="ascii.fixed_width_no_header",
                              col_starts=[0, 11, 13, 15, 17, 22, 25, 28, 37, 54, 64,
-                                         73, 75, 87, 99,  106, 112, 124],
+                                         73, 75, 87, 99, 106, 112, 124],
                              col_ends=[10, 12, 14, 16, 21, 24, 27, 36, 53, 63, 72,
                                        74, 86, 98, 105, 111, 123, 125],
-                             names=["Design", "K", "T", "N", "Datetime", "MM", "DD", 
-                                    "hh:mm:ss", "Measure", "Accuracy", "rms", "F", 
+                             names=["Design", "K", "T", "N", "Datetime", "MM", "DD",
+                                    "hh:mm:ss", "Measure", "Accuracy", "rms", "F",
                                     "Bias", "Resid", "TRX", "RCX", "Chi", "S"])
 
     # Combining the datetime columns
-    date_array = [f"{x}/{y}/{z} {t}" for x,y,z,t in radar_table["Datetime", "MM", "DD", "hh:mm:ss"]]
+    date_array = [f"{x}/{y}/{z} {t}" for x, y, z, t in radar_table["Datetime", "MM", "DD", "hh:mm:ss"]]
     radar_table["Datetime"] = Time.strptime(date_array, '%Y/%m/%d %H:%M:%S')
     radar_table.remove_columns(["MM", "DD", "hh:mm:ss"])
 
@@ -472,10 +472,10 @@ def parse_observations(resp_str, verbose=False):
     Returns
     -------
     response : list(Table)
-        List of response tables. 
+        List of response tables.
     """
 
-    output_tables = list() # Setting up to collect the output tables
+    output_tables = list()  # Setting up to collect the output tables
 
     # Split the meta data from the data table(s)
     header, dat_tabs = resp_str.split("END_OF_HEADER")
@@ -528,7 +528,7 @@ def parse_physical_properties(resp_str):
 
     if resp_str == '':
         raise ValueError('Object not found: the name of the object is wrong or misspelt')
-    
+
     # Split apart the table and reference data
     tbl, refs = resp_str.split("REFERENCES")
 
@@ -539,7 +539,7 @@ def parse_physical_properties(resp_str):
     for elt in tbl_list:
         row = elt.split(",")
         if len(row) > 4:
-            for i in range(1,len(row)-2):
+            for i in range(1, len(row)-2):
                 repaired_string += f"{row[0]},{row[i]},{row[-2]},{row[-1]}\n"
         else:
             repaired_string += elt + "\n"
@@ -611,7 +611,7 @@ def parse_orbital_properties(resp_str):
     """
 
     table_lst = list()
-    
+
     header, body = resp_str.split("END_OF_HEADER")
 
     # Parse Header
@@ -676,14 +676,13 @@ def parse_orbital_properties(resp_str):
 
         ngr_tbl = _make_prop_table(ngr_names, ngr_vals, section)
         table_lst.append(ngr_tbl)
-        
+
         for row in ngr_tbl:
             if float(row["Value"]):
                 cols.append(row["Property"])
 
         kep_n = 5
 
-
     # Equinoctial or Keplarian specific code
     if "Equinoctial" in ek_section:
 
@@ -749,7 +748,7 @@ def parse_ephemerides(resp_str):
 
     if "No ephemerides file" in resp_str:
         raise ValueError('No ephemerides file found for this object.')
-    
+
     # Splitting the string into lines up to the nines which is where the table data starts
     resp_list = re.split("\n", resp_str, maxsplit=9)
 
@@ -759,7 +758,7 @@ def parse_ephemerides(resp_str):
 
     # Want to combine the column names and units
     colnames = [(' '.join(x)).strip() for x in zip([resp_list[6][x:y].strip() for x, y in col_inds],
-                                                    [resp_list[7][x:y].strip() for x, y in col_inds])]
+                                                   [resp_list[7][x:y].strip() for x, y in col_inds])]
 
     ephem_table = Table.read(resp_list[9], format="ascii.fixed_width_no_header",
                              col_starts=col_inds[:, 0], col_ends=col_inds[:, 1], names=colnames)
@@ -847,12 +846,12 @@ def parse_summary(resp_str):
             obs_ind = prop_list.index("Observatory")
         except ValueError:
             obs_ind = len(prop_list)
-    
+
     obs_props = prop_list[obs_ind:]
     prop_list = prop_list[:obs_ind]
 
     # Building the table
-    summary_tab = Table(names=["Physical Properties", "Value", "Units"], 
+    summary_tab = Table(names=["Physical Properties", "Value", "Units"],
                         data=np.array(prop_list).reshape((len(prop_list)//3, 3)))
 
     # Dealing with the special cases
@@ -864,7 +863,7 @@ def parse_summary(resp_str):
                                                                                     "(from Earth center)")
 
     # Adding the other properties as metadata
-    for i in range(0,len(obs_props), 2):
+    for i in range(0, len(obs_props), 2):
         summary_tab.meta[obs_props[i]] = obs_props[i+1]
 
     return summary_tab