Fix ETD calculation error

ecoscope/analysis/UD/etd_range.py

@@ -4,15 +4,16 @@
 from dataclasses import dataclass
 
 import numpy as np
+
 from ecoscope.base import Trajectory
 from ecoscope.io import raster
 
 try:
     import numba as nb
     import scipy
-    from sklearn import neighbors
     from scipy.optimize import minimize
     from scipy.stats import weibull_min
+    from sklearn import neighbors
 except ModuleNotFoundError:
     raise ModuleNotFoundError(
         'Missing optional dependencies required by this module. \
@@ -169,8 +170,12 @@ def calculate_etd_range(
     grid_centroids[1, 0] = y_max - raster_profile.pixel_size * 0.5
 
     centroids_coords = np.dot(grid_centroids, np.mgrid[1:2, :num_columns, :num_rows].T.reshape(-1, 3, 1))
+    centroids_coords = centroids_coords.squeeze().T
+
+    if centroids_coords.ndim != 2:
+        centroids_coords = centroids_coords.reshape(1, -1)
 
-    tr = neighbors.KDTree(centroids_coords.squeeze().T)
+    tr = neighbors.KDTree(centroids_coords)
 
     del centroids_coords
 
@@ -207,7 +212,7 @@ def calculate_etd_range(
     raster_ndarray = raster_ndarray / raster_ndarray.sum()
 
     # Set the null data values
-    raster_ndarray[raster_ndarray == 0] = raster_profile.nodata_value
+    raster_ndarray[np.isnan(raster_ndarray) | (raster_ndarray == 0)] = raster_profile.nodata_value
 
     # write raster_ndarray to GeoTIFF file.
     raster.RasterPy.write(

ecoscope/analysis/percentile.py

@@ -51,6 +51,10 @@ def calculate_percentile_area(cls, profile: PercentileAreaProfile):
                 # calculate percentile value
                 # percentile_val = np.percentile(data_array[~np.isnan(data_array)], 100.0 - percentile)
                 values = np.sort(data_array[~np.isnan(data_array)]).flatten()
+
+                if len(values) == 0:
+                    continue
+
                 csum = np.cumsum(values)
                 percentile_val = values[np.argmin(np.abs(csum[-1] * (1 - percentile / 100) - csum))]
 

ecoscope/io/earthranger.py

@@ -1186,7 +1186,7 @@ def upload(obs):
                     "records"
                 )
                 del obs["geometry"]
-                obs = pack_columns(obs, columns=["source", "recorded_at", "location"])
+                obs = pack_columns(obs, columns=["source", "recorded_at", "location", "exclusion_flags", "additional"])
                 post_data = obs.to_dict("records")
                 results = super(EarthRangerIO, self).post_observation(post_data)
             except ERClientException as exc:

ecoscope/plotting/plot.py

@@ -422,7 +422,7 @@ def draw_historic_timeseries(
         The title shown in the plot legend for historic band
     historic_mean_column: str
         The name of the dataframe column to pull historic mean values from
-    current_value_title: str
+    historic_mean_title: str
         The title shown in the plot legend for historic mean values
     layout_kwargs: dict
         Additional kwargs passed to plotly.go.Figure(layout)