gtfspy/mapviz.py: added functionality for plotting xy values with att…

…ribute, added colormaps.py for easier colormapping

gtfspy/colormaps.py

@@ -0,0 +1,22 @@
+import matplotlib.colors
+import matplotlib.cm
+import numpy
+
+# colormaps: "viridis", "plasma_r","seismic"
+
+
+def get_colormap(observable_name):
+    if "diff_minutes" in observable_name:
+        norm = matplotlib.colors.Normalize(vmin=-30, vmax=30)
+        cmap = matplotlib.cm.get_cmap(name="seismic", lut=None)
+    elif "diff_number" in observable_name:
+        norm = matplotlib.colors.Normalize(vmin=-4, vmax=4)
+        cmap = matplotlib.cm.get_cmap(name="seismic", lut=None)
+    elif "diff_percentage" in observable_name:
+        norm = matplotlib.colors.Normalize(vmin=-0.5, vmax=0.5)
+        cmap = matplotlib.cm.get_cmap(name="seismic", lut=None)
+    else:
+        norm = matplotlib.colors.Normalize(vmin=-30, vmax=30)
+        cmap = matplotlib.cm.get_cmap(name="seismic", lut=None)
+    return cmap, norm
+

gtfspy/mapviz.py

@@ -17,6 +17,7 @@
 
 smopy.TILE_SERVER = "https://cartodb-basemaps-1.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png"
 
+
 def _get_median_centered_plot_bounds(g):
     lon_min, lon_max, lat_min, lat_max = get_spatial_bounds(g)
     lat_median, lon_median = get_median_lat_lon_of_stops(g)
@@ -28,6 +29,7 @@ def _get_median_centered_plot_bounds(g):
     plot_lat_max = lat_median + lat_diff
     return plot_lon_min, plot_lon_max, plot_lat_min, plot_lat_max
 
+
 def plot_route_network(g, ax=None, spatial_bounds=None, map_alpha=0.8, scalebar=True, legend=True,
                        return_smopy_map=False):
     """
@@ -93,11 +95,13 @@ def plot_route_network(g, ax=None, spatial_bounds=None, map_alpha=0.8, scalebar=
     else:
         return ax
 
+
 def _add_scale_bar(ax, lat, lon_min, lon_max, width_pixels):
     distance_m = util.wgs84_distance(lat, lon_min, lat, lon_max)
     scalebar = ScaleBar(distance_m / width_pixels)  # 1 pixel = 0.2 meter
     ax.add_artist(scalebar)
 
+
 def plot_route_network_thumbnail(g):
     width = 512  # pixels
     height = 300  # pixels
@@ -121,6 +125,28 @@ def plot_route_network_thumbnail(g):
     return plot_route_network(g, ax, spatial_bounds, map_alpha=1.0, scalebar=False, legend=False)
 
 
+def plot_stops_with_attributes(lats, lons, attribute, colorbar=True, ax=None, cmap=None, norm=None):
+
+    lon_min = min(lons)
+    lon_max = max(lons)
+    lat_min = min(lats)
+    lat_max = max(lats)
+    smopy_map = get_smopy_map(lon_min, lon_max, lat_min, lat_max)
+    if ax is None:
+        fig = plt.figure()
+        ax = fig.add_subplot(111)
+    ax = smopy_map.show_mpl(figsize=None, ax=ax, alpha=0.8)
+
+    xs, ys = smopy_map.to_pixels(lats, lons)
+    cax = ax.scatter(xs, ys, c=attribute, s=0.5, cmap=cmap, norm=norm)
+
+    ax.set_xlim(min(xs), max(xs))
+    ax.set_ylim(max(ys), min(ys))
+    if colorbar:
+        return ax, cax
+    return ax
+
+
 def plot_all_stops(g, ax=None, scalebar=False):
     """
     Parameters
@@ -137,7 +163,6 @@ def plot_all_stops(g, ax=None, scalebar=False):
 
     """
     assert(isinstance(g, GTFS))
-    stats = g.get_stats()
     lon_min, lon_max, lat_min, lat_max = get_spatial_bounds(g)
     smopy_map = get_smopy_map(lon_min, lon_max, lat_min, lat_max)
     if ax is None:

gtfspy/routing/journey_data.py

@@ -315,7 +315,6 @@ def get_origins(self):
             self.origins = cur.fetchall()
         return self.origins
 
-    @timeit
     def add_coordinates(self, df, join_column='from_stop_I'):
         stops_df = self.gtfs.stops()
         return pd.merge(stops_df, df, left_on='stop_I', right_on=join_column)
@@ -439,6 +438,8 @@ def od_pair_data(self, analysis_start_time, analysis_end_time):
             data_dict["temporal_distance"].append(profile_block.measures_as_dict())
 
             for key, value in self.journey_parameters.items():
+                if value == (None, None):
+                    next()
                 value = [walking_duration if x == "t_walk" else x for x in value]
                 profile_block = fpa.get_prop_analyzer_flat(key, value[0], value[1])
                 data_dict[key].append(profile_block.measures_as_dict())