Merge branch 'main' into ashwin/android_derived

Author: kanhereashwin

gnss_lib_py/algorithms/residuals.py

@@ -27,7 +27,7 @@ def solve_residuals(measurements, state_estimate):
 
     unique_timesteps = np.unique(measurements["gps_millis",:])
     for t_idx, timestep in enumerate(unique_timesteps):
-        idxs = np.where(measurements["gps_millis",:] == timestep)[1]
+        idxs = np.where(measurements["millisSinceGpsEpoch",:] == timestep)[0]
 
         pos_sv_m = np.hstack((measurements["x_sv_m",idxs].reshape(-1,1),
                               measurements["y_sv_m",idxs].reshape(-1,1),

gnss_lib_py/algorithms/snapshot.py

@@ -65,7 +65,7 @@ def solve_wls(measurements, weight_type = None,
     states = np.nan*np.ones((4,len(unique_timesteps)))
 
     for t_idx, timestep in enumerate(unique_timesteps):
-        idxs = np.where(measurements["gps_millis",:] == timestep)[1]
+        idxs = np.where(measurements["millisSinceGpsEpoch",:] == timestep)[0]
         pos_sv_m = np.hstack((measurements["x_sv_m",idxs].reshape(-1,1),
                               measurements["y_sv_m",idxs].reshape(-1,1),
                               measurements["z_sv_m",idxs].reshape(-1,1)))

gnss_lib_py/parsers/navdata.py

@@ -107,7 +107,7 @@ def from_pandas_df(self, pandas_df):
 
         for _, col_name in enumerate(pandas_df.columns):
             newvalue = pandas_df[col_name].to_numpy()
-            self.__setitem__(col_name, newvalue)
+            self[col_name] = newvalue
 
     def from_numpy_array(self, numpy_array):
         """Build attributes of NavData using np.ndarray.
@@ -125,7 +125,7 @@ def from_numpy_array(self, numpy_array):
         self.build_navdata()
 
         for row_num in range(numpy_array.shape[0]):
-            self.__setitem__(str(row_num), numpy_array[row_num,:])
+            self[str(row_num)] = numpy_array[row_num,:]
 
     @staticmethod
     def _row_map():
@@ -277,7 +277,8 @@ def __getitem__(self, key_idx):
         -------
         arr_slice : np.ndarray
             Array of data containing row names and time indexed
-            columns
+            columns. The return is squeezed meaning that all dimensions
+            of the output that are length of one are removed
         """
         rows, cols = self._parse_key_idx(key_idx)
         row_list, row_str = self._get_str_rows(rows)
@@ -293,6 +294,10 @@ def __getitem__(self, key_idx):
                 # arr_slice.append(str_arr[ cols])
         else:
             arr_slice = self.array[rows, cols]
+
+        # remove all dimensions of length one
+        arr_slice = np.squeeze(arr_slice)
+
         return arr_slice
 
     def __setitem__(self, key_idx, newvalue):
@@ -330,7 +335,7 @@ def __setitem__(self, key_idx, newvalue):
             else:
                 # print("\n",key_idx,"\n")#,newvalue)
                 if not isinstance(newvalue, int) and not isinstance(newvalue, float):
-                    assert not isinstance(np.asarray(newvalue)[0], str), \
+                    assert not isinstance(np.asarray(newvalue).item(0), str), \
                             "Cannot set a row with list of strings, please use np.ndarray with dtype=object"
                 # Adding numeric values
                 self.str_map[key_idx] = {}
@@ -408,7 +413,10 @@ def _str_2_val(self, new_str_vals, newvalue, key):
                                                    dtype=self.arr_dtype)
             # Set unassigned value to int not accessed by string map
             for str_key, str_val in str_dict.items():
-                new_str_vals[newvalue==str_val] = str_key
+                if new_str_vals.size == 1:
+                    new_str_vals = np.array(str_key,dtype=self.arr_dtype)
+                else:
+                    new_str_vals[newvalue==str_val] = str_key
             # Copy set to false to prevent memory overflows
             new_str_vals = np.round(new_str_vals.astype(self.arr_dtype,
                                                         copy=False))
@@ -693,7 +701,10 @@ def fillna(self, array):
 
         """
         nan_str = np.array([np.nan]).astype(str)[0]
-        array[np.where(array.astype(str)==nan_str)] = ""
+        if array.size > 1:
+            array[np.where(array.astype(str)==nan_str)] = ""
+        elif array.size == 1 and array == nan_str:
+            array = np.array("")
 
     def rename(self, mapper):
         """Rename rows of NavData class.

gnss_lib_py/utils/visualizations.py

@@ -132,7 +132,7 @@ def plot_metric(navdata, *args, save=True, prefix=""):
         plt_title = y_metric
         plt.title(plt_title)
         data = navdata[y_metric]
-        axes.scatter(range(data.shape[1]),data,s=5.)
+        axes.scatter(range(data.shape[0]),data,s=5.)
         plt.xlabel("index")
         plt.ylabel(y_metric)
     else:
@@ -319,7 +319,7 @@ def plot_skyplot(navdata, state_estimate, save=True, prefix=""):
                           navdata["z_sv_m",:].reshape(-1,1)))
 
     for t_idx, timestep in enumerate(np.unique(navdata["gps_millis",:])):
-        idxs = np.where(navdata["gps_millis",:] == timestep)[1]
+        idxs = np.where(navdata["gps_millis",:] == timestep)[0]
         for m_idx in idxs:
 
             if signal_types[m_idx] not in skyplot_data:

tests/parsers/test_android.py

@@ -219,7 +219,7 @@ def test_get_and_set_num(derived):
     key = 'testing123'
     value = np.zeros(len(derived))
     derived[key] = value
-    np.testing.assert_equal(derived[key, :], np.reshape(value, [1, -1]))
+    np.testing.assert_equal(derived[key, :], value)
 
 
 def test_get_and_set_str(derived):
@@ -240,7 +240,7 @@ def test_get_and_set_str(derived):
     value = np.concatenate((np.asarray(value1, dtype=object), np.asarray(value2, dtype=object)))
     derived[key] = value
 
-    np.testing.assert_equal(derived[key, :], [value])
+    np.testing.assert_equal(derived[key, :], value)
 
 
 def test_imu_raw(android_raw_path):

tests/parsers/test_navdata.py

@@ -546,7 +546,7 @@ def test_get_item(data, index, exp_value):
     exp_value : np.ndarray
         Expected value at queried indices
     """
-    np.testing.assert_array_equal(data[index], exp_value)
+    np.testing.assert_array_equal(data[index], np.squeeze(exp_value))
 
 
 def test_get_all_numpy(numpy_array):
@@ -648,7 +648,7 @@ def test_set_get_item(data, index, new_value, exp_value):
         Expected value at queried indices
     """
     data[index] = new_value
-    np.testing.assert_array_equal(data[index], exp_value)
+    np.testing.assert_array_equal(data[index], np.squeeze(exp_value))
 
 @pytest.mark.parametrize("row_idx",
                         [slice(7, 8),
@@ -709,8 +709,8 @@ def test_add_numpy_1d():
     """
     data = NavData(numpy_array=np.zeros([1,6]))
     data.add(numpy_array=np.ones(8))
-    np.testing.assert_array_equal(data[0, :], np.hstack((np.zeros([1,6]),
-                                  np.ones([1, 8]))))
+    np.testing.assert_array_equal(data[0, :], np.hstack((np.zeros(6),
+                                  np.ones(8))))
 
     # test adding to empty NavData
     data_empty = NavData()