schain Commit - r1715:e1fb60c9a537 · Jicamarca Repository

Update WeatherParamPlot maps and xlmits ylmits

jespinoza -

r1715:e1fb60c9a537

parent child

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r1715:e1fb60c9a537

schainpy/model/graphics/jroplot_base.py +21 -5

             from mpl_toolkits.axes_grid1 import make_axes_locatable
             from matplotlib.ticker import FuncFormatter, LinearLocator, MultipleLocator
+            import cartopy.crs as ccrs
             from .plotting_codes import register_cmap
             from schainpy.model.data.jrodata import PlotterData
                     self.zlimits = kwargs.get('zlimits', None)
                     self.xmin = kwargs.get('xmin', None)
                     self.xmax = kwargs.get('xmax', None)
-                    self.xrange = kwargs.get('xrange', 12)
+                    self.yrange = kwargs.get('yrange', None)
+                    self.xrange = kwargs.get('xrange', None)
                     self.xscale = kwargs.get('xscale', None)
                     self.ymin = kwargs.get('ymin', None)
                     self.ymax = kwargs.get('ymax', None)
                     self.mode = kwargs.get('mode', None)
                     self.mask = kwargs.get('mask', False)
                     self.shapes = kwargs.get('shapes', './')
+                    self.map = kwargs.get('map', False)
+                    self.latitude = kwargs.get('latitude', -12)
+                    self.longitude = kwargs.get('longitude', -74)
                     if self.server:
                         if not self.server.startswith('tcp://'):
                     if isinstance(self.attr_data, str):
                         self.attr_data = [self.attr_data]
                 def __setup_plot(self):
                     '''
                     Common setup for all figures, here figures and axes are created
                         self.figures['PPI'].append(fig_p)
                         self.figures['RHI'].append(fig_r)
                         for n in range(self.nplots):
-                            ax_p = fig_p.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar, projection=self.projection)
+                            if self.map:
+                                ax_p = fig_p.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar, projection=ccrs.PlateCarree())
+                            else:
+                                ax_p = fig_p.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar)
+                                print('sin projection')
                             ax_r = fig_r.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar)
                             ax_p.tick_params(labelsize=8)
                             ax_p.firsttime = True
                             fig = plt.figure(figsize=(self.width, self.height),
                                              edgecolor='k',
                                              facecolor='w')
-                            ax_p = fig.add_subplot(1, 1, 1, polar=self.polar, projection=self.projection)
+                            if self.map:
+                                ax_p = fig.add_subplot(1, 1, 1, polar=self.polar, projection=ccrs.PlateCarree())
+                            else:
+                                ax_p = fig.add_subplot(1, 1, 1, polar=self.polar)
+                                print('sin projection')
                             ax_r = fig.add_subplot(1, 1, 1, polar=self.polar)
                             ax_p.tick_params(labelsize=8)
                             ax_p.firsttime = True
                                     ax.cbar.set_label(self.cb_labels[n], size=8)
                             else:
                                 ax.cbar = None
-                            if self.mode == 'RHI':
+                            #if self.mode == 'RHI':
                             ax.set_xlim(xmin, xmax)
                             ax.set_ylim(ymin, ymax)
                             ax.firsttime = False
                             if self.grid:
                                 ax.grid(True)
                                     '%Y-%m-%d %H:%M:%S'),
                                 self.time_label),
                                 size=8)
-                            ax.set_ylim(0, self.ymax)
                             if self.mode == 'PPI':
                                 ax.set_yticks(ax.get_yticks(), labels=ax.get_yticks(), color='white')
                                 ax.yaxis.labelpad = 28

schainpy/model/graphics/jroplot_parameters.py +47 -26

             import numpy
             from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter
             from matplotlib.patches import Circle
-            import cartopy.crs as ccrs
             from cartopy.feature import ShapelyFeature
             import cartopy.io.shapereader as shpreader
-            from schainpy.model.graphics.jroplot_base import Plot, plt
+            from schainpy.model.graphics.jroplot_base import Plot, plt, ccrs
             from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
             from schainpy.utils import log
             from schainpy.model.graphics.plotting_codes import cb_tables
                         self.data.parameters[x], title) for x in self.channels]
             class WeatherParamsPlot(Plot):
-                #CODE = 'RHI'
-                #plot_name = 'RHI'
                 plot_type = 'scattermap'
                 buffering = False
-                projection = ccrs.PlateCarree()
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots= 1
-                    self.ylabel= 'Height [km]'
-                    self.xlabel= 'Distance from radar [km]'
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                     r = data['r']
                     self.titles = []
-                    self.ymax = self.ymax if self.ymax else numpy.nanmax(r)
-                    self.ymin = self.ymin if self.ymin else numpy.nanmin(r)
                     self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
                     self.zmin = self.zmin if self.zmin is not None else numpy.nanmin(z)
                         len_aux = int(data['azi'].shape[0]/4)
                         mean = numpy.mean(data['azi'][len_aux:-len_aux])
                         x, y = r*numpy.cos(theta), r*numpy.sin(theta)
+                        if self.yrange:
+                            self.ylabel= 'Height [km]'
+                            self.xlabel= 'Distance from radar [km]'
+                            self.ymax = self.yrange
+                            self.ymin = 0
+                            self.xmax = self.xrange if self.xrange else numpy.nanmax(r)
+                            self.xmin = -self.xrange if self.xrange else -numpy.nanmax(r)
+                            self.setrhilimits = False
+                        else:
+                            self.ymin = 0
+                            self.ymax = numpy.nanmax(r)
+                            self.xmin = -numpy.nanmax(r)
+                            self.xmax = numpy.nanmax(r)
                     elif data['mode_op'] == 'PPI':
                         r, theta = numpy.meshgrid(r, -numpy.radians(data['azi'])+numpy.pi/2)
                         len_aux = int(data['ele'].shape[0]/4)
                         mean = numpy.mean(data['ele'][len_aux:-len_aux])
                         x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(mean)), r*numpy.sin(
                                 theta)*numpy.cos(numpy.radians(mean))
-                        x = km2deg(x) + -75.295893
+                        x = km2deg(x) + self.longitude
-                        y = km2deg(y) + -12.040436
+                        y = km2deg(y) + self.latitude
+                        if self.xrange:
+                            self.ylabel= 'Latitude'
+                            self.xlabel= 'Longitude'
+                            self.xmin = km2deg(-self.xrange) + self.longitude
+                            self.xmax = km2deg(self.xrange) + self.longitude
+                            self.ymin = km2deg(-self.xrange) + self.latitude
+                            self.ymax = km2deg(self.xrange) + self.latitude
+                        else:
+                            self.xmin = km2deg(-numpy.nanmax(r)) + self.longitude
+                            self.xmax = km2deg(numpy.nanmax(r)) + self.longitude
+                            self.ymin = km2deg(-numpy.nanmax(r)) + self.latitude
+                            self.ymax = km2deg(numpy.nanmax(r)) + self.latitude
                     self.clear_figures()
                         norm = None
                     for i, ax in enumerate(axes):
-                        if data['mode_op'] == 'PPI':
-                            ax.set_extent([-75.745893, -74.845893, -12.490436, -11.590436])
                         if norm is None:
                             ax.plt = ax.pcolormesh(x, y, z[i], cmap=self.colormap, vmin=self.zmin, vmax=self.zmax)
                         self.mode_value = round(mean,1)
                         if data['mode_op'] == 'PPI':
+                            if self.map:
                                 gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
                                 linewidth=1, color='gray', alpha=0.5, linestyle='--')
                                 gl.xlabel_style = {'size': 8}
                                 gl.ylabel_style = {'size': 8}
                                 gl.xlabels_top = False
                                 gl.ylabels_right = False
-                            #self.shapes="/home/soporte/workspace/sirm/volumes/schain/shapes/"
-                            #print("self.shapes",self.shapes)
                                 shape_p = os.path.join(self.shapes,'PER_ADM2/PER_ADM2.shp')
                                 shape_d = os.path.join(self.shapes,'PER_ADM1/PER_ADM1.shp')
                                 capitales = os.path.join(self.shapes,'CAPITALES/cap_provincia.shp')
                                 reader_p = shpreader.BasicReader(shape_d, encoding='latin1')
                                 reader_c = shpreader.BasicReader(capitales, encoding='latin1')
                                 reader_v = shpreader.BasicReader(vias, encoding='latin1')
-                            caps = [x for x in reader_c.records()  if x.attributes["Departa"] in ("JUNIN", "LIMA", "AYACUCHO", "HUANCAVELICA")]
+                                caps = [x for x in reader_c.records()  ]#if x.attributes["Departa"] in ("JUNIN", "LIMA", "ICA", "PIURA")]
-                            districts = [x for x in reader_d.records() if x.attributes["Name"] in ("JUNÍN", "CHANCHAMAYO", "CHUPACA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "SATIPO", "TARMA", "YAUYOS", "HUAROCHIRÍ", "CANTA", "HUANTA", "TAYACAJA")]
+                                districts = [x for x in reader_d.records() ]# if x.attributes["Name"] in ("JUNÍN", "CHANCHAMAYO", "CHUPACA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "SATIPO", "TARMA", "YAUYOS", "HUAROCHIRÍ", "CANTA", "HUANTA", "TAYACAJA")]
-                            provs = [x for x in reader_p.records() if x.attributes["NAME"] in ("Junín", "Lima")]
+                                provs = [x for x in reader_p.records()]# if x.attributes["NAME"] in ("Junín", "Lima")]
-                            vias = [x for x in reader_v.records() if x.attributes["DEP"] in ("JUNIN", "LIMA")]
+                                vias = [x for x in reader_v.records()]# if x.attributes["DEP"] in ("JUNIN", "LIMA")]
                                 # Display limits and streets
                                 shape_feature = ShapelyFeature([x.geometry for x in districts], ccrs.PlateCarree(), facecolor="none", edgecolor='grey', lw=0.5)
                                 ax.add_feature(shape_feature)
                                 for cap in caps:
-                                if cap.attributes['Nombre'] in ("LA OROYA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "CHUPACA", "YAUYOS", "HUANTA", "PAMPAS"):
+                                    #if cap.attributes['Nombre'] in ("LA OROYA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "CHUPACA", "YAUYOS", "HUANTA", "PAMPAS"):
                                     ax.text(cap.attributes['X'], cap.attributes['Y'], cap.attributes['Nombre'].title(), size=7, color='white')
-                            ax.text(-75.052003, -11.915552, 'Huaytapallana', size=7, color='cyan')
+                                #ax.text(-75.052003, -11.915552, 'Huaytapallana', size=7, color='cyan')
-                            ax.plot(-75.052003, -11.915552, '*')
+                                #ax.plot(-75.052003, -11.915552, '*')
+                            else:
+                                ax.grid(color='grey', alpha=0.5, linestyle='--', linewidth=1)
                             for R in (10, 20, 30 , 40, 50):
-                                circle = Circle((-75.295893, -12.040436), km2deg(R), facecolor='none',
+                                if R <= self.xrange:
+                                    circle = Circle((self.longitude, self.latitude), km2deg(R), facecolor='none',
                                         edgecolor='skyblue', linewidth=1, alpha=0.5)
                                     ax.add_patch(circle)
-                                ax.text(km2deg(R)*numpy.cos(numpy.radians(45))-75.295893,
+                                    ax.text(km2deg(R)*numpy.cos(numpy.radians(45))+self.longitude,
-                                    km2deg(R)*numpy.sin(numpy.radians(45))-12.040436,
+                                        km2deg(R)*numpy.sin(numpy.radians(45))+self.latitude,
                                         '{}km'.format(R), color='skyblue', size=7)
                         elif data['mode_op'] == 'RHI':
                             ax.grid(color='grey', alpha=0.5, linestyle='--', linewidth=1)

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