fix new linting updates

doc/source/blog_posts/2022/TRACER.ipynb

@@ -599,7 +599,6 @@
     "\n",
     "\n",
     "def calculate_degrees(file_id):\n",
-    "\n",
     "    # Read in GOES ABI fixed grid projection variables and constants\n",
     "    x_coordinate_1d = file_id.variables[\"x\"][:]  # E/W scanning angle in radians\n",
     "    y_coordinate_1d = file_id.variables[\"y\"][:]  # N/S elevation angle in radians\n",

doc/source/blog_posts/2023/severe-storms-southern-wisconsin.ipynb

@@ -45,7 +45,7 @@
        "        "
       ],
       "text/plain": [
-       "<IPython.lib.display.IFrame at 0x110792770>"
+       "<IPython.lib.display.IFrame at 0x111992b00>"
       ]
      },
      "execution_count": 1,
@@ -347,15 +347,13 @@
     "    right_field=\"reflectivity\",\n",
     "    plot_config=plot_configuration,\n",
     "):\n",
-    "\n",
     "    # Read the radar data\n",
     "    radar = pyart.io.read_nexrad_archive(f\"s3://{file}\")\n",
     "\n",
     "    # Extract the lowest two sweeps - to help with speeding up the data cleaning\n",
     "    radar = radar.extract_sweeps([0, 1])\n",
     "\n",
     "    if \"velocity\" in [left_field, right_field]:\n",
-    "\n",
     "        # Dealias the radial velocities, using a reflectivity threshold to only look at precip regions\n",
     "        nyq = radar.instrument_parameters[\"nyquist_velocity\"][\"data\"][0]\n",
     "        gatefilter = pyart.filters.GateFilter(radar)\n",
@@ -372,7 +370,6 @@
     "    # Create a plot number to iterate over\n",
     "    plot_number = 0\n",
     "    for field in (left_field, right_field):\n",
-    "\n",
     "        # Use the configuration for the field\n",
     "        config = plot_config[field]\n",
     "\n",

examples/plotting/plot_rhi_cfradial.py

@@ -33,7 +33,6 @@
 nplots = radar.nsweeps
 
 for snum in radar.sweep_number["data"]:
-
     fixed_angle = radar.fixed_angle["data"][snum]
     title = "HSRHI Az=%.3f" % (fixed_angle)
     ax = fig.add_subplot(nplots, 1, snum + 1)

pyart/_debug_info.py

@@ -129,5 +129,4 @@ def _debug_info(stream=None):
 
 
 if __name__ == "__main__":
-
     _debug_info()

pyart/aux_io/gamic_hdf5.py

@@ -221,7 +221,6 @@ def read_gamic(
     moment_names = gfile.moment_names(moment_groups)
 
     for moment_name, group in zip(moment_names, moment_groups):
-
         field_name = filemetadata.get_field_name(moment_name)
         if field_name is None:
             continue

pyart/core/radar.py

@@ -189,7 +189,6 @@ def __init__(
         pitch=None,
         georefs_applied=None,
     ):
-
         if "calendar" not in time:
             time["calendar"] = "gregorian"
         self.time = time

pyart/correct/phase_proc.py

@@ -1003,7 +1003,6 @@ def LP_solver_cylp(A_Matrix, B_vectors, weights, really_verbose=False):
         s.logLevel = 0
 
     for raynum in range(n_rays):
-
         # set new B_vector values for actual ray
         s.setRowLowerArray(np.squeeze(np.asarray(B_vectors[raynum])))
         # set new weights (objectives) for actual ray
@@ -1518,7 +1517,6 @@ def get_phidp_unf_gf(
     cordata = np.zeros(my_phidp.shape, dtype=float)
     all_non_meteo = gatefilter.gate_excluded
     for radial in range(my_phidp.shape[0]):
-
         # deterimine non meteo from gatefilter CHANGED
         notmeteo = all_non_meteo[radial, :]
         x_ma = ma.masked_where(notmeteo, my_phidp[radial, :])

pyart/correct/region_dealias.py

@@ -161,7 +161,6 @@ def dealias_region_based(
 
     # loop over sweeps
     for nsweep, sweep_slice in enumerate(radar.iter_slice()):
-
         # extract sweep data
         sdata = vdata[sweep_slice].copy()  # is a copy needed here?
         scorr = data[sweep_slice]
@@ -365,7 +364,6 @@ def _find_regions(vel, gfilter, limits):
     label = np.zeros(vel.shape, dtype=np.int32)
     nfeatures = 0
     for lmin, lmax in zip(limits[:-1], limits[1:]):
-
         # find connected regions within the limits
         inp = (lmin <= vel) & (vel < lmax) & mask
         limit_label, limit_nfeatures = ndimage.label(inp)
@@ -627,7 +625,6 @@ def merge_nodes(self, base_node, merge_node, foo_edge):
             self._common_finder[:] = False
             edges_in_base = list(self.edges_in_node[base_node])
             for edge_num in edges_in_base:
-
                 # reverse edge if needed so node_alpha is base_node
                 if self.node_beta[edge_num] == base_node:
                     self._reverse_edge_direction(edge_num)
@@ -640,7 +637,6 @@ def merge_nodes(self, base_node, merge_node, foo_edge):
 
         # loop over edge nodes
         for edge_num in edges_in_merge:
-
             # reverse edge so that node alpha is the merge_node
             if self.node_beta[edge_num] == merge_node:
                 self._reverse_edge_direction(edge_num)

pyart/io/chl.py

@@ -104,7 +104,6 @@ def read_chl(
     # fields
     fields = {}
     for i, fdata in chl_file.fields.items():
-
         field_info = chl_file.field_info[i]
         field_name = filemetadata.get_field_name(field_info["name"])
         if field_name is None:
@@ -236,7 +235,6 @@ class ChlFile:
     """
 
     def __init__(self, filename, ns_time=True, debug=False):
-
         # initalize attributes
         self.ngates = None
         self.num_sweeps = None
@@ -402,7 +400,6 @@ def _extract_fields(self):
         all_data = np.frombuffer(self._dstring, dtype=self._dtype)
         all_data = all_data.reshape(-1, self.ngates)
         for i, field_num in enumerate(self._field_nums):
-
             fdata = np.ma.masked_values(all_data[all_data.dtype.names[i]], 0)
             # apply scale and offset factors to interger data types
             if issubclass(fdata.dtype.type, np.integer):

pyart/io/mdv_common.py

@@ -865,7 +865,6 @@ def _get_chunks(self, debug=False):
         # the file pointer must be set at the correct location prior to call
         radar_info, elevations, calib_info = None, [], None
         for cnum, curr_chunk_header in enumerate(self.chunk_headers):
-
             chunk_id = curr_chunk_header["chunk_id"]
             self.fileptr.seek(curr_chunk_header["chunk_data_offset"])
 

pyart/io/nexrad_cdm.py

@@ -139,7 +139,6 @@ def read_nexrad_cdm(
 
     ray_i = 0
     for scan_index, scan_dic in enumerate(scan_info):
-
         var_index = scan_dic["index"][0]
         nradials = scan_dic["nradials"][0]
 
@@ -155,7 +154,6 @@ def read_nexrad_cdm(
         fixed_agl_data[scan_index] = np.mean(dvars[elevation_var][var_index][:nradials])
 
         for i, moment in enumerate(scan_dic["moments"]):
-
             moment_index = scan_dic["index"][i]
             m_ngates = scan_dic["ngates"][i]
             m_nradials = scan_dic["nradials"][i]
@@ -321,7 +319,6 @@ def _scan_info(dvars):
 
     for time_var in time_variables:
         for time_var_i, time in enumerate(dvars[time_var][:, 0]):
-
             scan_index = scan_start_times.index(time)
             scan_dic = scan_info[scan_index]
             moment = time_var_to_moment[time_var]

pyart/io/uf_write.py

@@ -113,7 +113,6 @@ def write_uf(
     )
 
     for ray_num in range(radar.nrays):
-
         ray_bytes = raycreator.make_ray(ray_num)
         pad = struct.pack(b">i", raycreator.record_length * 2)
 
@@ -135,7 +134,6 @@ def _find_field_mapping(radar, uf_field_names, radar_field_names, exclude_fields
 
     field_mapping = {}
     for radar_field in radar.fields.keys():
-
         if radar_field in exclude_fields:
             continue
 
@@ -330,7 +328,6 @@ def make_ray(self, ray_num):
         ray += self.make_field_position()
 
         for field_info in field_positions:
-
             data_type = field_info["data_type"]
             offset = field_info["offset_field_header"] + 19
             radar_field = field_info["radar_field"]

pyart/io/uffile.py

@@ -112,7 +112,6 @@ def __init__(self, filename):
         # read in the records, store as a list of rays
         self.rays = []
         while len(buf) == 8:  # read until EOF reached
-
             # record size stored as a 2-byte int start at byte 2
             record_size = struct.unpack(">h", buf[padding + 2 : padding + 4])[0] * 2
 

pyart/map/gates_to_grid.py

@@ -132,7 +132,6 @@ def map_gates_to_grid(
 
     # project gates from each radar onto the grid
     for radar, gatefilter in zip(radars, gatefilters):
-
         # Copy the field data and masks.
         # TODO method that does not copy field data into new array
         if nfields == 0:

pyart/map/grid_mapper.py

@@ -522,7 +522,6 @@ def map_to_grid(
 
     # loop over the radars finding gate locations, field data, and offset
     for iradar, (radar, gatefilter) in enumerate(zip(radars, gatefilters)):
-
         # calculate radar offset from the origin
         x_disp, y_disp = geographic_to_cartesian(
             radar.longitude["data"], radar.latitude["data"], projparams
@@ -652,7 +651,6 @@ def map_to_grid(
 
     # interpolate field values for each point in the grid
     for iz, iy, ix in np.ndindex(nz, ny, nx):
-
         # calculate the grid point
         x = x_start + x_step * ix
         y = y_start + y_step * iy

pyart/retrieve/_echo_class.py

@@ -217,7 +217,6 @@ def steiner_class_buff(
     area_relation,
     use_intense,
 ):
-
     zslice = np.argmin(np.abs(z - work_level))
     refl = ze[zslice, :, :]
 

pyart/retrieve/advection.py

@@ -140,7 +140,6 @@ def grid_shift(grid, advection, trim_edges=0, field_list=None):
         field_list = grid.fields.keys()
 
     for field in field_list:
-
         # copy data and fill with nans
         data = grid.fields[field]["data"].copy()
         data = np.ma.filled(data, np.nan)

pyart/retrieve/comp_z.py

@@ -14,7 +14,6 @@
 
 
 def composite_reflectivity(radar, field="reflectivity", gatefilter=None):
-
     """
     Composite Reflectivity
 

pyart/retrieve/kdp_proc.py

@@ -1532,7 +1532,6 @@ def boundary_conditions_maesaka(
     idx_far = np.zeros(radar.nrays, dtype=np.int32)
 
     for ray, regions in enumerate(slices):
-
         # check if all range gates are missing
         if regions is None:
             continue
@@ -1543,10 +1542,8 @@ def boundary_conditions_maesaka(
 
         # near range gate boundary condition
         for slc in regions:
-
             # check if enough samples exist in slice
             if slc.stop - slc.start >= n:
-
                 # parse index and range of nearest range gate
                 idx = slice(slc.start, slc.start + n)
                 idx_near[ray] = idx.start
@@ -1571,9 +1568,7 @@ def boundary_conditions_maesaka(
 
         # far range gate boundary condition
         for slc in reversed(regions):
-
             if slc.stop - slc.start >= n:
-
                 # parse index and range of furthest range gate
                 idx = slice(slc.stop - n, slc.stop)
                 idx_far[ray] = idx.stop
@@ -1604,7 +1599,6 @@ def boundary_conditions_maesaka(
 
     # skip the check if there are no valid values
     if kwargs.get("check_outliers", True) and (phi_near_valid.size != 0):
-
         # bin and count near range boundary condition values, i.e., create
         # a distribution of values
         # the default bin width is 5 deg
@@ -1651,7 +1645,6 @@ def boundary_conditions_maesaka(
             print(f"Estimated system phase offset: {system_phase_offset:.0f} deg")
 
         for ray, bc in enumerate(phi_near):
-
             # if near range boundary condition does not draw from system phase
             # distribution then set it to the system phase offset
             if bc < left_edge or bc > right_edge:

pyart/retrieve/qvp.py

@@ -11,7 +11,6 @@
 def quasi_vertical_profile(
     radar, desired_angle=None, fields=None, gatefilter=None, verbose=False
 ):
-
     """
     Quasi Vertical Profile.
 
@@ -78,7 +77,6 @@ def quasi_vertical_profile(
         fields = radar.fields
 
         for field in fields:
-
             # Filtering data based on defined gatefilter
             # If none is defined goes to else statement
             if gatefilter is not None:

pyart/retrieve/vad.py

@@ -400,7 +400,6 @@ def __call__(self, x_new, window=None):
 
         y_new = np.zeros_like(x_new, dtype=self.y_sorted.dtype)
         for i, center in enumerate(x_new):
-
             bottom = center - window
             top = center + window
             start = np.searchsorted(self.x_sorted, bottom)

pyart/testing/data/check_nexrad_dummy.py

@@ -14,7 +14,6 @@ def test_dummy_similar():
 
 
 def radars_similar(r1, r2):
-
     ###########################
     # Attribute that are None #
     ###########################

pyart/testing/data/dummify_nexrad_file.py

@@ -29,7 +29,6 @@
 # replace all radial data with a single value so it compresses well
 pos = 0
 while pos < buf_length:
-
     # retrieve the record (msg31)
     new_pos, record = nexrad._get_record_from_buf(buf, pos)
     if record["header"]["type"] != 31:

pyart/util/columnsect.py

@@ -125,7 +125,6 @@ def for_azimuth(radar_latitude, target_latitude, radar_longitude, target_longitu
 
 
 def get_field_location(radar, latitude, longitude):
-
     """
     Given the location (in latitude, longitude) of a target, extract the
     radar column above that point for further analysis.
@@ -276,7 +275,6 @@ def get_field_location(radar, latitude, longitude):
 
 
 def get_column_rays(radar, azimuth):
-
     """
     Given the location (in latitude,longitude) of a target, return the rays
     that correspond to radar column above the target.
@@ -329,7 +327,6 @@ def get_column_rays(radar, azimuth):
 
 
 def check_latitude(latitude):
-
     """
     Function to check if input latitude is valid for type and value.
 
@@ -356,7 +353,6 @@ def check_latitude(latitude):
 
 
 def check_longitude(longitude):
-
     """
     Function to check if input latitude is valid for type and value.
 

pyart/util/radar_utils.py

@@ -459,7 +459,6 @@ def join_radar(radar1, radar2):
         == 1 & len(radar2.altitude["data"])
         == 1
     ):
-
         lat1 = float(radar1.latitude["data"])
         lon1 = float(radar1.longitude["data"])
         alt1 = float(radar1.altitude["data"])

scripts/anytocfradial

@@ -5,7 +5,6 @@ import argparse
 import pyart
 
 if __name__ == "__main__":
-
     # parse the arguments
     parser = argparse.ArgumentParser(
         description="Convert a radar file to CF/Radial format."