Merge pull request #823 from dirac-institute/black_MJ_pR

black files linter checks are failing on

src/sorcha/ephemeris/simulation_driver.py

@@ -34,7 +34,8 @@ class EphemerisGeometryParameters:
 
 
 def get_vec(row, vecname):
-    return np.asarray([ row[f"{vecname}_x"], row[f"{vecname}_y"], row[f"{vecname}_z"] ])
+    return np.asarray([row[f"{vecname}_x"], row[f"{vecname}_y"], row[f"{vecname}_z"]])
+
 
 def create_ephemeris(orbits_df, pointings_df, args, configs):
     """Generate a set of observations given a collection of orbits
@@ -173,7 +174,7 @@ def create_ephemeris(orbits_df, pointings_df, args, configs):
         # the majority of the computation to build out `pixel_dict`.
         desigs = set()
         pixId = pointings_df.attrs["pixels"]
-        for pix in pixId[pointing["pixels_begin"]:pointing["pixels_end"]]:
+        for pix in pixId[pointing["pixels_begin"] : pointing["pixels_end"]]:
             desigs.update(pixel_dict[pix])
 
         for obj_id in sorted(desigs):
@@ -193,14 +194,10 @@ def create_ephemeris(orbits_df, pointings_df, args, configs):
                     _,
                     ephem_geom_params.r_ast,
                     ephem_geom_params.v_ast,
-                ) = integrate_light_time(
-                    sim, ex, pointing["JD_TDB"] - ephem.jd_ref, r_obs, lt0=0.01
-                )
+                ) = integrate_light_time(sim, ex, pointing["JD_TDB"] - ephem.jd_ref, r_obs, lt0=0.01)
                 ephem_geom_params.rho_hat = ephem_geom_params.rho / ephem_geom_params.rho_mag
 
-                ang_from_center = (
-                    180 / np.pi * np.arccos(np.dot(ephem_geom_params.rho_hat, visit_vector))
-                )
+                ang_from_center = 180 / np.pi * np.arccos(np.dot(ephem_geom_params.rho_hat, visit_vector))
                 if ang_from_center < ang_fov:
                     out_tuple = calculate_rates_and_geometry(pointing, ephem_geom_params)
                     in_memory_csv.writerow(out_tuple)

src/sorcha/ephemeris/simulation_setup.py

@@ -210,15 +210,17 @@ def precompute_pointing_information(pointings_df, args, configs):
     # use pandas `apply` again because healpy.query_disc is not easily vectorizable
     pixels, i = [], 0
     pixBeginEnd = np.empty((len(pointings_df), 2), dtype=np.int32)
-    for k, (fieldRa, fieldDec) in enumerate(zip(pointings_df["fieldRA"].values, pointings_df["fieldDec"].values)):
+    for k, (fieldRa, fieldDec) in enumerate(
+        zip(pointings_df["fieldRA"].values, pointings_df["fieldDec"].values)
+    ):
         fieldPix = partial_get_hp_neighbors(fieldRa, fieldDec)
         nPix = len(fieldPix)
         pixels.append(fieldPix)
         pixBeginEnd[k] = i, i + nPix
         i += nPix
     pointings_df["pixels_begin"], pointings_df["pixels_end"] = pixBeginEnd[:, 0], pixBeginEnd[:, 1]
     pixels = np.concatenate(pixels, dtype=np.int32)
-    pointings_df.attrs = { "pixels": pixels }
+    pointings_df.attrs = {"pixels": pixels}
 
     # create empty arrays for observatory position and velocity to be filled in
     r_obs = np.empty((len(pointings_df), 3))

src/sorcha/modules/PPMatchPointingToObservations.py

@@ -32,7 +32,7 @@ def PPMatchPointingToObservations(padain, pointfildb):
     # they don't need to be included in the result df, so exclude them from the merge.
     pointing_columns_to_skip = ["JD_TDB", "pixels_begin", "pixels_end"]
     for name in ["visit_vector", "pixels", "r_obs", "v_obs", "r_sun", "v_sun"]:
-        pointing_columns_to_skip += [ f"{name}_x", f"{name}_y", f"{name}_z" ]
+        pointing_columns_to_skip += [f"{name}_x", f"{name}_y", f"{name}_z"]
 
     resdf = pd.merge(
         padain,

src/sorcha/modules/PPReadPointingDatabase.py

@@ -43,7 +43,7 @@ def PPReadPointingDatabase(bsdbname, observing_filters, dbquery, surveyname):
     df["observationId_"] = df["observationId"]
     df = df.rename(columns={"observationId": "FieldID"})
     df = df.rename(columns={"filter": "optFilter"})  # not to confuse with the pandas filter command
-    df["optFilter"] = df["optFilter"].astype("category") # save memory
+    df["optFilter"] = df["optFilter"].astype("category")  # save memory
     dfo = df[df.optFilter.isin(observing_filters)].copy()
 
     # at the moment the RubinSim pointing databases don't record the observation

src/sorcha/sorcha.py

@@ -57,12 +57,14 @@ def cite():
     """
     cite_sorcha()
 
+
 def mem(df):
     usage = df.memory_usage(deep=True).sum()
     for k, v in df.attrs.items():
         usage += v.nbytes
     return usage
 
+
 def runLSSTSimulation(args, configs):
     """
     Runs the post processing survey simulator functions that apply a series of
@@ -117,17 +119,17 @@ def runLSSTSimulation(args, configs):
     filterpointing = PPReadPointingDatabase(
         args.pointing_database, configs["observing_filters"], configs["pointing_sql_query"], args.surveyname
     )
-##    print("POSTREAD:", len(filterpointing), type(filterpointing), mem(filterpointing))
-##    print(filterpointing.dtypes)
+    ##    print("POSTREAD:", len(filterpointing), type(filterpointing), mem(filterpointing))
+    ##    print(filterpointing.dtypes)
 
     # if we are going to compute the ephemerides, then we should pre-compute all
     # of the needed values derived from the pointing information.
     if configs["ephemerides_type"].casefold() != "external":
         verboselog("Pre-computing pointing information for ephemeris generation")
         filterpointing = precompute_pointing_information(filterpointing, args, configs)
-##        print("POSTPOINTING:", len(filterpointing), type(filterpointing), mem(filterpointing))
-##        print(filterpointing.dtypes)
-##        print("POSTPOINTING:", len(filterpointing), type(filterpointing), filterpointing.memory_usage(deep=True))
+    ##        print("POSTPOINTING:", len(filterpointing), type(filterpointing), mem(filterpointing))
+    ##        print(filterpointing.dtypes)
+    ##        print("POSTPOINTING:", len(filterpointing), type(filterpointing), filterpointing.memory_usage(deep=True))
 
     # Set up the data readers.
     ephem_type = configs["ephemerides_type"]
@@ -150,9 +152,9 @@ def runLSSTSimulation(args, configs):
     if configs["comet_activity"] is not None or configs["lc_model"] is not None:
         reader.add_aux_data_reader(CSVDataReader(args.complex_parameters, configs["aux_format"]))
 
-#    import time
-#    time.sleep(100)
-#    exit()
+    #    import time
+    #    time.sleep(100)
+    #    exit()
 
     # In case of a large input file, the data is read in chunks. The
     # "sizeSerialChunk" parameter in PPConfig.ini assigns the chunk.

tests/ephemeris/test_simulation_driver.py

@@ -31,10 +31,18 @@ def test_calculate_rates_and_geometry():
             "visit_vector_z": -0.399435561333849,
             "JD_TDB": 2460219.484998981,
             "pixels": None,
-            "r_obs_x":  0.9825025212987633,   "r_obs_y": 0.12894773431445178,   "r_obs_z": 0.056115072741286603,
-            "v_obs_x": -0.002514846222194574, "v_obs_y": 0.015645226468919866,  "v_obs_z": 0.006740310710189443,
-            "r_sun_x": -0.008375571318557293, "r_sun_y": -0.0021278397223137443, "r_sun_z": -0.0006896179222345509,
-            "v_sun_x":  4.014508061373484e-06,"v_sun_y": -7.199434717117629e-06, "v_sun_z": -3.1502131721138966e-06,
+            "r_obs_x": 0.9825025212987633,
+            "r_obs_y": 0.12894773431445178,
+            "r_obs_z": 0.056115072741286603,
+            "v_obs_x": -0.002514846222194574,
+            "v_obs_y": 0.015645226468919866,
+            "v_obs_z": 0.006740310710189443,
+            "r_sun_x": -0.008375571318557293,
+            "r_sun_y": -0.0021278397223137443,
+            "r_sun_z": -0.0006896179222345509,
+            "v_sun_x": 4.014508061373484e-06,
+            "v_sun_y": -7.199434717117629e-06,
+            "v_sun_z": -3.1502131721138966e-06,
         }
     )