Add fastplot plot function

tests/test_fastplot.py

@@ -0,0 +1,21 @@
+import xarray as xr
+import trajan as _
+import matplotlib.pyplot as plt
+
+
+def test_fastplot(test_data, plot):
+    ds = xr.open_dataset(test_data / 'xr_spotter_bulk_test_data.nc')
+
+    # let us check that the conversion worked well, and that all main functionalities are working
+
+    # plotting without centering
+    plt.figure()
+    ds.traj.plot.fastplot()
+
+    # plotting with centering
+    plt.figure()
+    ds.traj.plot.fastplot(center_lon_circmean=True)
+
+    if plot:
+        plt.show()
+

trajan/plot/__init__.py

@@ -3,6 +3,7 @@
 import cartopy.crs as ccrs
 import numpy as np
 import xarray as xr
+import scipy as sp
 
 from .land import add_land
 
@@ -135,6 +136,46 @@ def set_up_map(
     def __call__(self, *args, **kwargs):
         return self.lines(*args, **kwargs)
 
+    def fastplot(self, center_lon_circmean=False):
+        """
+        Do a fast plot of the data. This uses PlateCarree, no transform on the plotting,
+        and circmean to determine the optimal central longitude to use.
+
+        This only plots markers, not lines, to avoid wrapping lines on global datasets.
+
+        Args:
+
+            center_lon_circmean: bool, whether to use the circmean of the longitude
+                of the data to set the central_longitude in PlateCarree (if True), or
+                the default (0) if False.
+        """
+
+        if self.__cartesian__:
+            x = self.ds.traj.tx.values.T
+            y = self.ds.traj.ty.values.T
+        else:
+            x = self.ds.traj.tlon.values.T
+            y = self.ds.traj.tlat.values.T
+
+        if center_lon_circmean:
+            all_y = x.flatten()
+            mid_y = 180.0 / np.pi * sp.stats.circmean(all_y * np.pi / 180.0, nan_policy="omit")
+        else:
+            mid_y = 0.0
+
+        ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=mid_y))
+        ax.coastlines()
+
+        if len(x.shape) == 2:
+            for crrt_buoy_idx in range(x.shape[1]):
+                plt.plot(x[:, crrt_buoy_idx], y[:, crrt_buoy_idx], linestyle="none", marker=".", markersize=1)
+        elif len(x.shape) == 1:
+            plt.plot(x, y, linestyle="none", marker=".", markersize=1)
+        else:
+            raise ValueError(f"the position data to plot has shape {x.shape = }; unclear how to plot this!")
+
+        gl = ax.gridlines(transform=ccrs.PlateCarree(central_longitude=mid_y), draw_labels=True)
+
     def lines(self, *args, **kwargs):
         """
         Plot the trajectory lines.