Add informations on nice display of observations

Author: AntSimi

src/py_eddy_tracker/appli/eddies.py

@@ -104,6 +104,13 @@ def display_infos():
         "latitude",
     ]
     for filename in args.observations:
-        print(f"-- {filename} --")
-        e = EddiesObservations.load_file(filename, include_vars=vars)
+        with Dataset(filename) as h:
+            track = 'track' in h.variables
+        print(f"-- {filename} -- ")
+        if track:
+            vars_ = vars.copy()
+            vars_.extend(('track', 'observation_number', 'observation_flag'))
+            e = TrackEddiesObservations.load_file(filename, include_vars=vars_)
+        else:
+            e = EddiesObservations.load_file(filename, include_vars=vars)
         print(e)

src/py_eddy_tracker/generic.py

@@ -39,6 +39,7 @@
     bool_,
     concatenate,
     radians,
+    histogram,
 )
 from numba import njit, prange, types as numba_types
 from .poly import winding_number_grid_in_poly
@@ -82,6 +83,11 @@ def build_index(groups):
     return first_index, last_index, i0
 
 
+@njit(cache=True)
+def hist_numba(x, bins):
+    return histogram(x, bins)
+
+
 @njit(cache=True, fastmath=True, parallel=False)
 def distance_grid(lon0, lat0, lon1, lat1):
     """

src/py_eddy_tracker/observations/observation.py

@@ -70,6 +70,7 @@
     reverse_index,
     get_pixel_in_regular,
     bbox_indice_regular,
+    hist_numba,
 )
 from ..poly import bbox_intersection, vertice_overlap, create_vertice
 
@@ -112,11 +113,6 @@ def shifted_ellipsoid_degrees_mask2(lon0, lat0, lon1, lat1, minor=1.5, major=1.5
     return m
 
 
-@njit(cache=True)
-def hist_numba(x, bins):
-    return histogram(x, bins)
-
-
 class EddiesObservations(object):
     """
     Class to hold eddy properties *amplitude* and counts of
@@ -220,6 +216,32 @@ def _repr_html_(self):
         infos = self.get_infos()
         return f"""<b>{infos['nb_obs']} observations from {infos['t0']} to {infos['t1']} </b>"""
 
+    def hist(self, varname, x, bins, percent=False, mean=False, nb=False):
+        """
+            :param str varname: variable to use to compute stat
+            :param str x: variable to use to know in which bins
+            :param array bins:
+            :param bool percent: normalize by sum of all bins
+            :param bool mean: compute mean by bins
+            :param nb mean: only count by bins
+            :return: value by bins
+            :rtype: array
+            """
+        if nb:
+            v = hist_numba(self[x], bins=bins)[0]
+        else:
+            v = histogram(self[x], bins=bins, weights=self[varname])[0]
+        if percent:
+            v = v.astype("f4") / v.sum() * 100
+        elif mean:
+            v /= hist_numba(self[x], bins=bins)[0]
+        return v
+
+    @staticmethod
+    def box_display(value):
+        """Return value evenly spaced with few numbers"""
+        return "".join([f"{v_:10.2f}" for v_ in value])
+
     def __repr__(self):
         """
         return general informations on dataset as a string
@@ -234,48 +256,25 @@ def __repr__(self):
         bins_radius = array((0, 15, 30, 45, 60, 75, 100, 200, 2000))
         nb_obs = self.observations.shape[0]
 
-        def hist(varname, x="lat", bins=bins_lat, percent=False, mean=False, nb=False):
-            """
-            :param str varname: variable to use to compute stat
-            :param str x: variable to use to know in which bins
-            :param array bins:
-            :param bool percent: normalize by sum of all bins
-            :param bool mean: compute mean by bins
-            :param nb mean: only count by bins
-            :return: value by bins
-            :rtype: array
-            """
-            if nb:
-                v = hist_numba(self[x], bins=bins)[0]
-            else:
-                v = histogram(self[x], bins=bins, weights=self[varname])[0]
-            if percent:
-                v = v.astype("f4") / v.sum() * 100
-            elif mean:
-                v /= hist_numba(self[x], bins=bins)[0]
-            return v
-
-        def box_display(value):
-            """Return value evenly spaced with few numbers"""
-            return "".join([f"{v_:10.2f}" for v_ in value])
-
-        return f"""{nb_obs} observations from {t0} to {t1} ({period} days, ~{nb_obs / period:.0f} obs/day)
-    Speed area      : {self["speed_area"].sum() / period / 1e12:.2f} Mkm²/day
-    Effective area  : {self["effective_area"].sum() / period / 1e12:.2f} Mkm²/day
-----Distribution in Amplitude:
-    Amplitude bounds (cm)  {box_display(bins_amplitude)}
-    Percent of eddies         : {box_display(hist('time', 'amplitude', bins_amplitude / 100., percent=True, nb=True))}
-----Distribution in Radius:
-    Speed radius (km)      {box_display(bins_radius)}
-    Percent of eddies         : {box_display(hist('time', 'radius_s', bins_radius * 1000., percent=True, nb=True))}
-----Distribution in Latitude
-    Latitude bounds        {box_display(bins_lat)}
-    Percent of eddies         : {box_display(hist('time', percent=True, nb=True))}
-    Percent of speed area     : {box_display(hist('speed_area', percent=True))}
-    Percent of effective area : {box_display(hist('effective_area', percent=True))}
-    Mean speed radius (km)    : {box_display(hist('radius_s', mean=True) / 1000.)}
-    Mean effective radius (km): {box_display(hist('radius_e', mean=True) / 1000.)}
-    Mean amplitude (cm)       : {box_display(hist('amplitude', mean=True) * 100.)}"""
+        return f"""    | {nb_obs} observations from {t0} to {t1} ({period} days, ~{nb_obs / period:.0f} obs/day)
+    |   Speed area      : {self["speed_area"].sum() / period / 1e12:.2f} Mkm²/day
+    |   Effective area  : {self["effective_area"].sum() / period / 1e12:.2f} Mkm²/day
+    ----Distribution in Amplitude:
+    |   Amplitude bounds (cm)  {self.box_display(bins_amplitude)}
+    |   Percent of eddies         : {
+        self.box_display(self.hist('time', 'amplitude', bins_amplitude / 100., percent=True, nb=True))}
+    ----Distribution in Radius:
+    |   Speed radius (km)      {self.box_display(bins_radius)}
+    |   Percent of eddies         : {
+        self.box_display(self.hist('time', 'radius_s', bins_radius * 1000., percent=True, nb=True))}
+    ----Distribution in Latitude
+        Latitude bounds        {self.box_display(bins_lat)}
+        Percent of eddies         : {self.box_display(self.hist('time', 'lat', bins_lat, percent=True, nb=True))}
+        Percent of speed area     : {self.box_display(self.hist('speed_area', 'lat', bins_lat, percent=True))}
+        Percent of effective area : {self.box_display(self.hist('effective_area', 'lat', bins_lat, percent=True))}
+        Mean speed radius (km)    : {self.box_display(self.hist('radius_s', 'lat', bins_lat, mean=True) / 1000.)}
+        Mean effective radius (km): {self.box_display(self.hist('radius_e', 'lat', bins_lat, mean=True) / 1000.)}
+        Mean amplitude (cm)       : {self.box_display(self.hist('amplitude', 'lat', bins_lat, mean=True) * 100.)}"""
 
     def __getitem__(self, attr):
         if attr in self.elements:

src/py_eddy_tracker/observations/tracking.py

@@ -38,6 +38,7 @@
     zeros,
     array,
     median,
+    histogram
 )
 from datetime import datetime, timedelta
 from numba import njit
@@ -62,6 +63,8 @@ class TrackEddiesObservations(EddiesObservations):
         "lat",
         "radius_s",
         "radius_e",
+        "speed_area",
+        "effective_area",
         "amplitude",
         "speed_average",
         "time",
@@ -83,6 +86,31 @@ def __init__(self, *args, **kwargs):
         self.__first_index_of_track = None
         self.__obs_by_track = None
 
+    def __repr__(self):
+        content = super().__repr__()
+        t0, t1 = self.period
+        period = t1 - t0 + 1
+        nb = self.nb_obs_by_track
+        nb_obs = self.observations.shape[0]
+        m = self["virtual"].astype("bool")
+        nb_m = m.sum()
+        bins_t = (0, 20, 50, 100, 200, 1000, 10000)
+        nb_tracks_by_t = histogram(nb, bins=bins_t)[0]
+        nb_obs_by_t = histogram(nb, bins=bins_t, weights=nb)[0]
+        pct_tracks_by_t = nb_tracks_by_t / nb_tracks_by_t.sum() * 100.
+        pct_obs_by_t = nb_obs_by_t / nb_obs_by_t.sum() * 100.
+        content += f"""
+    | {nb.shape[0]} tracks ({nb.mean():.2f} obs/tracks, shorter {nb.min()} obs, longer {nb.max()} obs)
+    |   {nb_m} filled observations ({nb_m / nb.shape[0]:.2f} obs/tracks, {nb_m / nb_obs * 100:.2f} % of total)
+    |   Intepolated speed area : {self["speed_area"][m].sum() / period / 1e12:.2f} Mkm²/day
+    |   Intepolated effective area : {self["effective_area"][m].sum() / period / 1e12:.2f} Mkm²/day
+    ----Distribution in lifetime:
+    |   Lifetime (days  )      {self.box_display(bins_t)}
+    |   Percent of tracks         : {self.box_display(pct_tracks_by_t)}
+    |   Percent of eddies         : {self.box_display(pct_obs_by_t)}
+"""
+        return content
+
     def filled_by_interpolation(self, mask):
         """Filled selected values by interpolation
         """