Remove last Basemap dependencies in mapping routines

DataProcess/DataProcess.py

@@ -170,19 +170,21 @@ def processData(self, restrictToWindfieldDomain=False):
 
         if config.has_option('DataProcess', 'InputFile'):
             inputFile = config.get('DataProcess', 'InputFile')
+            self.logger.info(f"Input file from DataProcess: {inputFile}")
 
         if config.has_option('DataProcess', 'Source'):
             source = config.get('DataProcess', 'Source')
-            self.logger.info('Loading %s dataset', source)
-            fn = config.get(source, 'filename')
-            path = config.get(source, 'path')
+            self.logger.info(f"Loading {source} dataset")
+            fn = config.get(source, 'Filename')
+            path = config.get(source, 'Path')
             inputFile = pjoin(path, fn)
+            self.logger.info(f"Input file set to {inputFile}")
 
         # If input file has no path information, default to tcrm input folder
         if len(os.path.dirname(inputFile)) == 0:
             inputFile = pjoin(self.tcrm_input_dir, inputFile)
 
-        self.logger.info("Processing {0}".format(inputFile))
+        self.logger.info(f"Processing {inputFile}")
 
         self.source = config.get('DataProcess', 'Source')
 
@@ -218,8 +220,8 @@ def processData(self, restrictToWindfieldDomain=False):
         except (ValueError, KeyError):
 
             try:
-                self.logger.info(("Filtering input data by season:"
-                                  "season > {0}". format(startSeason)))
+                self.logger.info(("Filtering input data by season: "
+                                  f"season >= {startSeason}"))
                 # Find indicies that satisfy minimum season filter
                 idx = np.where(inputData['season'] >= startSeason)[0]
                 # Filter records:
@@ -263,7 +265,7 @@ def processData(self, restrictToWindfieldDomain=False):
         flSaveFile(self.origin_year, np.transpose(origin_seasonOrYear),
                    header, ',', fmt='%d')
 
-        pressure = np.array(inputData['pressure'], 'd')
+        pressure = np.array(inputData['pressure'], 'float32')
         novalue_index = np.where(pressure == sys.maxsize)
         pressure = metutils.convert(pressure, inputPressureUnits, "hPa")
         pressure[novalue_index] = sys.maxsize
@@ -278,7 +280,7 @@ def processData(self, restrictToWindfieldDomain=False):
             self.progressbar.update(0.25)
 
         try:
-            vmax = np.array(inputData['vmax'], 'd')
+            vmax = np.array(inputData['vmax'], 'float32')
         except (ValueError, KeyError):
             self.logger.warning("No max wind speed data")
             vmax = np.empty(indicator.size, 'f')

PlotInterface/AutoPlotHazard.py

@@ -112,7 +112,7 @@ def plotMap(self):
 
         for i, year in enumerate(years):
             log.debug("Plotting %d-year return period hazard map", year)
-            title = '%d-Year Return Period Cyclonic Wind Hazard' % (year)
+            title = '%d-Year ARI Cyclonic Wind Hazard' % (year)
             imageFilename = '%d_yrRP_hazard_map.png' % (year)
             filename = pjoin(self.plotPath, imageFilename)
             cbarlab = "Wind speed (%s)"%self.plotUnits.units

PlotInterface/maps.py

@@ -3,7 +3,7 @@
 =============================================
 
 .. module:: maps
-    :synopsis: Generate map images using `mpl_toolkits.basemap`
+    :synopsis: Generate map images using `cartopy`
 
 .. moduleauthor: Craig Arthur <craig.arthur@ga.gov.au>
 
@@ -177,7 +177,7 @@ def addGraticule(self, axes, mapobj):
         :param mapobj: Current `GeoAxes` instance to annotate.
 
         """
-
+        from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
         xmin, xmax, ymin, ymax = mapobj.get_extent()
 
         dx = abs(xmin - xmax)
@@ -195,7 +195,10 @@ def addGraticule(self, axes, mapobj):
 
         gl = mapobj.gridlines(xlocs=meridians, ylocs=parallels,
                               draw_labels=True)
+        gl.xformatter = LONGITUDE_FORMATTER
+        gl.yformatter = LATITUDE_FORMATTER
         gl.xlabels_top = False
+        gl.ylabels_right = False
 
     def addCoastline(self, mapobj):
         """
@@ -205,7 +208,7 @@ def addCoastline(self, mapobj):
         :param mapobj: Current `GeoAxes` instance to add coastlines to.
 
         """
-        mapobj.coastlines(resolution='50m')
+        mapobj.coastlines(resolution='10m')
 
     def fillContinents(self, mapobj, fillcolor="#FFDAB5"):
         """
@@ -218,6 +221,16 @@ def fillContinents(self, mapobj, fillcolor="#FFDAB5"):
         """
         mapobj.add_feature(cartopy.feature.LAND, color=fillcolor)
 
+    def maskOceans(self, mapobj, fillcolor="#66ccff"):
+        """
+        Mask oceans with a blue background in the current `GeoAxes` instance.
+
+        :param mapobj: Current `GeoAxes` instance to colour fill the oceans
+        :param fillcolor: Optional colour to use (default #66CCFF)
+        """
+
+        mapobj.add_feature(cartopy.feature.OCEAN, color=fillcolor)
+
     def addMapScale(self, mapobj):
         """
         Add a map scale to the curent `Basemap` instance. This
@@ -228,7 +241,7 @@ def addMapScale(self, mapobj):
         :param mapobj: Current `Basemap` instance to add the scale bar to.
 
         """
-        return # TODO: migrate to cartopy
+        return # TODO: migrate to cartopy - see https://stackoverflow.com/questions/32333870/
 
         midlon = (mapobj.lonmax - mapobj.lonmin) / 2.
         midlat = (mapobj.latmax - mapobj.latmin) / 2.
@@ -344,7 +357,7 @@ def add(self, data, xgrid, ygrid, title, lvls, cbarlab, map_kwargs):
                        define the contour levels to use.
         :param str cbarlab: Label for the color bar.
         :param dict map_kwargs: A dict containing keyword arguments for
-                                setting up the :class:`basemap` instance.
+                                setting up the :class:`GeoAxes` instance.
 
         """
         super(FilledContourMapFigure, self).add(data, xgrid, ygrid,
@@ -392,24 +405,19 @@ def subplot(self, axes, subfigure):
                                 map keyword arguments.
 
         """
-        from mpl_toolkits.basemap import maskoceans
+
         data, xgrid, ygrid, title, lvls, cbarlab, map_kwargs = subfigure
         mapobj, mx, my = self.createMap(axes, xgrid, ygrid, map_kwargs)
-        dmask = data.mask
-        masked_data = maskoceans(xgrid, ygrid, data, inlands=False)
-        omask = ma.getmask(masked_data)
-        nmask = ma.mask_or(dmask, omask)
-        masked_data.mask = nmask
         cmap = selectColormap(lvls)
-        CS = mapobj.contourf(mx, my, masked_data, levels=lvls,
+        CS = mapobj.contourf(mx, my, data, levels=lvls,
                              extend='both', cmap=cmap)
         CB = self.colorbar(CS, ticks=lvls[::2], ax=axes, extend='both')
         CB.set_label(cbarlab)
         axes.set_title(title)
         self.labelAxes(axes)
         self.addGraticule(axes, mapobj)
         self.addCoastline(mapobj)
-        self.fillContinents(mapobj, fillcolor="#EEEEEE")
+        self.maskOceans(mapobj)
         self.addMapScale(mapobj)
 
 class ArrayMapFigure(MapFigure):
@@ -461,12 +469,10 @@ def subplot(self, axes, subfigure):
                                 map keyword arguments.
 
         """
-        from mpl_toolkits.basemap import maskoceans
         data, xgrid, ygrid, title, \
             datarange, cbarlab, map_kwargs = subfigure
 
-        masked_data = maskoceans(xgrid, ygrid, data, inlands=False)
-        subfigure = (masked_data, xgrid, ygrid, title,
+        subfigure = (data, xgrid, ygrid, title,
                      datarange, cbarlab, map_kwargs)
         super(MaskedArrayMapFigure, self).subplot(axes, subfigure)
 
@@ -553,7 +559,7 @@ def plot(self, data, xgrid, ygrid, title, lvls, cbarlab, map_kwargs):
         # Smooth the data to reduce 'lines-on-a-map' inferences:
         dx = np.mean(np.diff(xgrid))
         dmask = data.mask
-        data = smooth(data, int(1/dx))
+        #data = smooth(data, int(1/dx))
         data = ma.array(data, mask=dmask)
         self.add(data, xgrid, ygrid, title, lvls, cbarlab, map_kwargs)
         self.cmap = sns.light_palette("orange", as_cmap=True)

PlotInterface/tracks.py

@@ -128,7 +128,7 @@ def saveTrackMap(tracks, xgrid, ygrid, title, map_kwargs, filename):
                   domain.
     :param str title: Title string for the plot.
     :param dict map_kwargs: Keyword args that will define the
-                            :class:`Basemap` instance.
+                            :class:`GeoAxes` instance.
     :param str filename: Path to the file to save the image.
 
     """

hazard/__init__.py

@@ -290,8 +290,14 @@ def calculateHazard(self, tilelimits):
 
         log.info("Using {0} distribution for the hazard curves".format(self.evd))
         #Vr = loadFilesFromPath(self.inputPath, tilelimits)
-        #Rp, loc, scale, shp = evfunc(Vr, self.years, self.numSim, self.nodata, self.minRecords)
-
+        #Rp, loc, scale, shp = evfunc(Vr, self.years, self.numSim, self.nodata,
+        #self.minRecords)
+        if self.evd not in ["GPD", "GEV", "power", "emp"]:
+            msg = (f"Invalid extreme value distribution function: {self.evd} \n"
+                   "Set 'Hazard--ExtremeValueDistribution' to one of the following: \n"
+                   "GPD, GEV, power or emp")
+            raise ValueError (msg)
+
         if self.evd == 'GPD':
             log.info("Using the GPD distribution for the hazard curves")
             Vr = loadFilesFromPath(self.inputPath, tilelimits) 

tcrm.py

@@ -21,7 +21,6 @@
 import argparse
 import time
 import sys
-import imp
 import os
 
 from os.path import join as pjoin, realpath, isdir, dirname