Merge branch 'master' of github.com:SuperDARN/pydarn

.github/workflows/flake8PR.yml

@@ -26,4 +26,4 @@ jobs:
         pip3 install flake8
         pip3 install --upgrade flake8
         # stop the build if there are Python syntax errors or undefined names
-        flake8 --exit-zero
+        flake8 --exit-zero --ignore=E501

README.md

@@ -15,7 +15,7 @@ Python data visualization library for the Super Dual Auroral Radar Network (Supe
 pyDARN release v2.0includes the following features:
 - Integration with pyDARNio to read files
 - Updates to Hardware utility
-- **Fan Plots**
+- **Fan Plots** with transparent fix
 - **Statistical Power Plots**
 - Slant range option for plotting 
 - getting beam/gate geographic/geomagnetic locations 

pydarn/exceptions/plot_exceptions.py

@@ -99,6 +99,11 @@ def __init__(self, parameter: str, beam_num: int,  opt_beam_num: int,
                         "".format(beam_num=self.beam_num,
                                   parameter=self.parameter,
                                   opt_beam=self.opt_beam_num,
+                                  start_time=self.start_time.strftime("%Y %m"
+                                                                      " %d %H"
+                                                                      ":%M"),
+                                  end_time=self.end_time.strftime("%Y %m"
+                                                                  " %d %H:%M"),
                                   parameter_value=opt_parameter_value)
 
         super().__init__(self.message)

pydarn/exceptions/rtp_exceptions.py

@@ -1,7 +1,6 @@
 # Copyright (C) SuperDARN Canada, Universtiy of Saskatchewan
 # Authors: Marina Schmidt
 import logging
-import datetime
 
 pydarn_log = logging.getLogger('pydarn')
 

pydarn/exceptions/warning_formatting.py

@@ -6,6 +6,7 @@
 # Disclaimer: pyDARN is licensed under the GPL v 3.0 found in LICENSE
 #
 
+
 def standard_warning_format(message: str, category: str, filename: str,
                             lineno: int, file: str = None,
                             line: int = None) -> str:
@@ -61,7 +62,6 @@ def only_message_warning_format(message: str, category: str, filename: str,
     -------
         formatted warning message to be printed to the console
     """
-    return "{category}: {message}\n".format(filename=filename,
-                                            linenum=lineno,
-                                            category=category.__name__,
-                                            message=message)
+    return "{filename} {linenum} {category}: {message}\n"\
+        "".format(filename=filename, linenum=lineno,
+                  category=category.__name__, message=message)

pydarn/io/superdarn_io.py

@@ -13,7 +13,7 @@ class SuperDARNRead(pydarnio.SDarnRead):
     Methods
     -------
     read_dmap : reads superDARN DMap formats
-    read_borealis: Reads Borealis hdf5 formats and converts 
+    read_borealis: Reads Borealis hdf5 formats and converts
         Borealis' data dictionary to SDARN data dictionary
     """
     def __init__(self, filename: str = None, stream: bool = False):
@@ -83,8 +83,8 @@ def read_borealis(self, filename: str, slice_id: int = None):
                 string name of the file, make sure "rawacf" or "bfiq" is in
                 the name
             slice_id: int
-                the Borealis slice id of the file, required if reading Borealis data
-                produced prior to when Borealis v0.5 was released
+                the Borealis slice id of the file, required if reading Borealis
+                data produced prior to when Borealis v0.5 was released
 
         Post
         ----

pydarn/plotting/acf.py

@@ -194,11 +194,11 @@ def plot_acfs(cls, dmap_data: List[dict], beam_num: int = 0,
                     break
                 scan_count += 1
         if record['cp'] == 503:
-            warnings.warn("Please note that this data is from Tauscan which has "
-                          "different lag properties compared to other control "
-                          "programs. The ACF plot may not be correct. "
-                          "Please contact the PI of the radar to "
-                          "confirm if the data looks correct.")
+            warnings.warn("Please note that this data is from Tauscan "
+                          "which has different lag properties compared "
+                          "to other control programs. The ACF plot may "
+                          "not be correct. Please contact the PI of the "
+                          "radar to confirm if the data looks correct.")
         if re == [] or im == []:
             if gate_num > 0 and gate_num < record['nrang']:
                 time = time2datetime(record)
@@ -262,6 +262,7 @@ def plot_acfs(cls, dmap_data: List[dict], beam_num: int = 0,
                       " https://zenodo.org/record/3978643. Citing information"
                       " for SuperDARN data is found at"
                       " https://pydarn.readthedocs.io/en/master/user/citing/")
+
     @classmethod
     def __found_scan(cls, scan_num: int, count_num: int,
                      start_time: datetime, time: datetime):
@@ -287,14 +288,13 @@ def __found_scan(cls, scan_num: int, count_num: int,
                 else False
         """
         if start_time is None:
-            if scan_num==count_num:
+            if scan_num == count_num:
                 return True
         elif start_time < time:
             return True
 
         return False
 
-
     @classmethod
     def __blanked_lags(cls, record: dict, lags: list, gate: int):
         """

pydarn/plotting/fan.py

@@ -9,8 +9,8 @@
 # document, but changing it is not allowed.
 #
 # This version of the GNU Lesser General Public License incorporates the terms
-# and conditions of version 3 of the GNU General Public License, supplemented by
-# the additional permissions listed below.
+# and conditions of version 3 of the GNU General Public License,
+# supplemented by the additional permissions listed below.
 
 
 """
@@ -20,7 +20,6 @@
 import datetime as dt
 import matplotlib.pyplot as plt
 import numpy as np
-import os
 
 from matplotlib import ticker, cm, colors
 from typing import List
@@ -30,6 +29,7 @@
 
 from pydarn import PyDARNColormaps, build_scan, radar_fov
 
+
 class Fan():
     """
         Fan plots for SuperDARN data
@@ -47,22 +47,25 @@ def __str__(self):
 
     @classmethod
     def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
-                       ranges: List = [0,75], boundary: bool = True,
-                       parameter: str = 'v', lowlat: int = 30, cmap: str = None,
-                       groundscatter: bool = False,
-                       zmin: int = None, zmax: int = None,
-                       colorbar: bool = True,
-                       colorbar_label: str = ''):
+                 ranges: List = [0, 75], boundary: bool = True,
+                 parameter: str = 'v', lowlat: int = 30,
+                 cmap: str = None, groundscatter: bool = False,
+                 zmin: int = None, zmax: int = None,
+                 colorbar: bool = True,
+                 colorbar_label: str = ''):
         """
-        Plots a radar's Field Of View (FOV) fan plot for the given data and scan number
+        Plots a radar's Field Of View (FOV)
+        fan plot for the given data and scan number
 
         Parameters
         -----------
             dmap_data: List[dict]
                 Named list of dictionaries obtained from SDarn_read
             ax: matplotlib.pyplot axis
-                Pre-defined axis object to pass in, must currently be polar projection
-                Default: Generates a polar projection for the user with MLT/latitude labels
+                Pre-defined axis object to pass in,
+                must currently be polar projection
+                Default: Generates a polar projection for
+                the user with MLT/latitude labels
             scan_index: int
                 Scan number from beginning of first record in file
                 Default: 1
@@ -95,7 +98,8 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
                 Draw a colourbar if True
                 Default: True
             colorbar_label: str
-                the label that appears next to the colour bar. Requires colorbar to be true
+                the label that appears next to the colour bar.
+                Requires colorbar to be true
                 Default: ''
         Returns
         -----------
@@ -104,32 +108,33 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
         beam_corners_aacgm_lons
             n_beams x n_gates numpy array of AACGMv2 longitudes
         scan
-            n_beams x n_gates numpy array of the scan data (for the selected parameter)
+            n_beams x n_gates numpy array of the scan data
+            (for the selected parameter)
         grndsct
-            n_beams x n_gates numpy array of the scan data (for the selected parameter)
+            n_beams x n_gates numpy array of the scan data
+            (for the selected parameter)
         dtime
             datetime object for the scan plotted
 
         """
 
-        my_path = os.path.abspath(os.path.dirname(__file__))
-        base_path = os.path.join(my_path, '..')
-
         # Get scan numbers for each record
-        beam_scan=build_scan(dmap_data)
+        beam_scan = build_scan(dmap_data)
 
         # Locate scan in loaded data
         plot_beams = np.where(beam_scan == scan_index)
 
         # Time for coordinate conversion
         dtime = dt.datetime(dmap_data[plot_beams[0][0]]['time.yr'],
-                            dmap_data[plot_beams[0][0]]['time.mo'], dmap_data[plot_beams[0][0]]['time.dy'],
-                            dmap_data[plot_beams[0][0]]['time.hr'], dmap_data[plot_beams[0][0]]['time.mt'],
+                            dmap_data[plot_beams[0][0]]['time.mo'],
+                            dmap_data[plot_beams[0][0]]['time.dy'],
+                            dmap_data[plot_beams[0][0]]['time.hr'],
+                            dmap_data[plot_beams[0][0]]['time.mt'],
                             dmap_data[plot_beams[0][0]]['time.sc'])
 
         # Get radar beam/gate locations
-        beam_corners_aacgm_lats, beam_corners_aacgm_lons=radar_fov(dmap_data[0]['stid'],
-            coords='aacgm', date=dtime)
+        beam_corners_aacgm_lats, beam_corners_aacgm_lons = \
+            radar_fov(dmap_data[0]['stid'], coords='aacgm', date=dtime)
         fan_shape = beam_corners_aacgm_lons.shape
 
         # Work out shift due in MLT
@@ -144,11 +149,13 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
 
         # Get range-gate data and groundscatter array for given scan
         scan = np.zeros((fan_shape[0] - 1, fan_shape[1]-1))
-        grndsct = np.zeros((fan_shape[0] - 1, fan_shape[1]-1)) #initialise arrays
+        grndsct = np.zeros((fan_shape[0] - 1, fan_shape[1]-1))
         for i in np.nditer(plot_beams):
             try:
-                slist = dmap_data[i.astype(int)]['slist'] #get a list of gates where there is data
-                beam = dmap_data[i.astype(int)]['bmnum'] #get the beam number for the record
+                # get a list of gates where there is data
+                slist = dmap_data[i.astype(int)]['slist']
+                # get the beam number for the record
+                beam = dmap_data[i.astype(int)]['bmnum']
                 scan[slist, beam] = dmap_data[i.astype(int)][parameter]
                 grndsct[slist, beam] = dmap_data[i.astype(int)]['gflg']
             # if there is no slist field this means partial record
@@ -157,8 +164,6 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
 
         # Colour table and max value selection depending on parameter plotted
         # Load defaults if none given
-        # TODO: use cmaps as over writting cmap is bad practice...
-        # did I do that in my code ... hmm
         if cmap is None:
             cmap = {'p_l': 'plasma', 'v': PyDARNColormaps.PYDARN_VELOCITY,
                     'w_l': PyDARNColormaps.PYDARN_VIRIDIS,
@@ -177,7 +182,7 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
         # This may screw up references
         if ax is None:
             ax = plt.axes(polar=True)
-            if beam_corners_aacgm_lats[0,0] > 0:
+            if beam_corners_aacgm_lats[0, 0] > 0:
                 ax.set_ylim(90, lowlat)
                 ax.set_yticks(np.arange(lowlat, 90, 10))
             else:
@@ -187,7 +192,7 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
             ax.set_theta_zero_location("S")
 
         # Begin plotting by iterating over ranges and beams
-        for gates in range(ranges[0],ranges[1]-1):
+        for gates in range(ranges[0], ranges[1] - 1):
             for beams in range(thetas.shape[1] - 2):
                 # Index colour table correctly
                 cmapindex = (scan[gates, beams] + abs(zmin)) /\
@@ -201,24 +206,24 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
 
                 # Check for zero values (white) and groundscatter (gray)
                 if scan[gates, beams] == 0:
-                    colour_rgba = 'w'
+                    colour_rgba = (1, 1, 1, 0)
 
                 if groundscatter and grndsct[gates, beams] == 1:
                     colour_rgba = 'gray'
 
-                #Angle for polar plotting
+                # Angle for polar plotting
                 theta = [thetas[gates, beams], thetas[gates + 1, beams],
                          thetas[gates + 1, beams + 1],
                          thetas[gates, beams + 1]]
-                #Radius for polar plotting
+                # Radius for polar plotting
                 r = [rs[gates, beams], rs[gates + 1, beams],
                      rs[gates + 1, beams + 1], rs[gates, beams + 1]]
-                im = ax.fill(theta, r, color=colour_rgba)
+                ax.fill(theta, r, color=colour_rgba)
 
         # Plot FOV outline
         if boundary is True:
-            plt.polar(thetas[0:ranges[1], 0], rs[0:ranges[1], 0], color='black',
-                      linewidth=0.5)
+            plt.polar(thetas[0:ranges[1], 0], rs[0:ranges[1], 0],
+                      color='black', linewidth=0.5)
             plt.polar(thetas[ranges[1] - 1, 0:thetas.shape[1] - 1],
                       rs[ranges[1] - 1, 0:thetas.shape[1] - 1], color='black',
                       linewidth=0.5)
@@ -238,9 +243,10 @@ def plot_fan(cls, dmap_data: List[dict], ax=None, scan_index: int = 1,
                                          integer=True, nbins='auto')
             ticks = locator.tick_values(vmin=zmin, vmax=zmax)
 
-            cb = ax.figure.colorbar(mappable, ax=ax, extend='both', ticks=ticks)
+            cb = ax.figure.colorbar(mappable, ax=ax,
+                                    extend='both', ticks=ticks)
 
             if colorbar_label != '':
                 cb.set_label(colorbar_label)
 
-        return beam_corners_aacgm_lats, beam_corners_aacgm_lons, scan, grndsct, dtime
+        return beam_corners_aacgm_lats, beam_corners_aacgm_lons,

pydarn/plotting/power.py

@@ -214,8 +214,6 @@ def plot_pwr0_statistic(cls, records: List[dict], beam_num: int = 0,
                     cls.__plot_pwr0(records_of_interest, beam_num,
                                     statistical_method)
 
-
-
     @staticmethod
     def __plot_pwr0(records: list, beam_num: int, statistical_method: object,
                     title: bool = True):