inverted original mask_nans in interpolation function

MDAnalysis · Jul 25, 2021 · 45c2b06 · 45c2b06
1 parent ed2ede3
commit 45c2b06
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Showing 2 changed files with 19 additions and 21 deletions.
diff --git a/membrane_curvature/surface.py b/membrane_curvature/surface.py
@@ -21,7 +21,7 @@ def derive_surface(atoms, n_cells_x, n_cells_y, max_width_x, max_width_y):
 
     Returns
     -------
-    z_coordinates: numpy.ndarray
+    z_coordinates: np.ndarray
         Average z-coordinate values. Return Numpy array of floats of
         shape `(n_cells_x, n_cells_y)`.
 
@@ -37,8 +37,8 @@ def get_z_surface(coordinates, n_x_bins=10, n_y_bins=10, x_range=(0, 100), y_ran
 
     Parameters
     ----------
-    coordinates : numpy.ndarray 
-        Coordinates of AtomGroup. Numpy array of shape=(n_atoms, 3).
+    coordinates : np.ndarray 
+        Coordinates of AtomGroup. NumPy array of shape=(n_atoms, 3).
     n_x_bins : int.
         Number of bins in grid in the `x` dimension. 
     n_y_bins : int.
@@ -50,9 +50,9 @@ def get_z_surface(coordinates, n_x_bins=10, n_y_bins=10, x_range=(0, 100), y_ran
 
     Returns
     -------
-    z_surface: numpy.ndarray 
+    z_surface: np.ndarray 
         Surface derived from set of coordinates in grid of `x_range, y_range` dimensions.
-        Returns Numpy array of floats of shape (`n_x_bins`, `n_y_bins`)
+        Returns NumPy array of floats of shape (`n_x_bins`, `n_y_bins`)
 
     """
 
@@ -109,53 +109,53 @@ def normalized_grid(grid_z_coordinates, grid_norm_unit):
 
 def interpolation_by_array(array_surface):
     """
-        Interpolates values contained in array_surface over axi
+        Interpolates values contained in `array_surface` over axis
 
     Parameters
     ----------
 
-    array_surface: numpy.ndarray
-        Numpy array of floats of shape (`n_x_bins`, `n_y_bins`)
+    array_surface: np.ndarray
+        Array of floats of shape (`n_x_bins`, `n_y_bins`)
 
     Returns
     -------
     interpolated_array: np.ndarray
         Returns interpolated array.
-        Numpy array of shape (`n_x_bins` x `n_y_bins`,)
+        Array of shape (`n_x_bins` x `n_y_bins`,)
 
     """
 
     # create mask for nans
-    mask_nans = np.isnan(array_surface)
+    mask_nans = ~np.isnan(array_surface)
 
     # index of array_surface
     index_array = np.arange(array_surface.shape[0])
 
     # interpolate values in array
     interpolated_array = np.interp(index_array,
-                                   np.flatnonzero(~mask_nans),
-                                   array_surface[~mask_nans])
+                                   np.flatnonzero(mask_nans),
+                                   array_surface[mask_nans])
 
     return interpolated_array
 
 
 def surface_interpolation(array_surface):
     """
-        Calculates interpolation
+        Calculates interpolation of arrays.
 
     Parameters
     ----------
 
     array_surface: np.ndarray
-        Numpy array of floats of shape (`n_x_bins`, `n_y_bins`)
+        Array of floats of shape (`n_x_bins`, `n_y_bins`)
 
     Returns
     -------
 
-    Returns interpolated surface
+    interpolated_surface: np.ndarray
         Interpolated surface derived from set of coordinates
         in grid of `x_range, y_range` dimensions.
-        Numpy array of floats of shape (`n_x_bins`, `n_y_bins`)
+        Array of floats of shape (`n_x_bins`, `n_y_bins`)
 
     """
 

diff --git a/membrane_curvature/tests/test_membrane_curvature.py b/membrane_curvature/tests/test_membrane_curvature.py
@@ -7,7 +7,7 @@
                                         derive_surface, get_z_surface, surface_interpolation)
 from membrane_curvature.curvature import mean_curvature, gaussian_curvature
 import numpy as np
-from numpy.testing import assert_almost_equal
+from numpy.testing import assert_almost_equal, assert_allclose
 import MDAnalysis as mda
 from membrane_curvature.tests.datafiles import (GRO_PO4_SMALL, XTC_PO4_SMALL)
 from membrane_curvature.base import MembraneCurvature
@@ -215,13 +215,11 @@ def test_get_z_surface(x_bin, y_bin, x_range, y_range, expected_surface):
                [150., np.nan, 150.],
                [150., 150., 150.])),
      np.full((3, 3), 150.)),
-    # array 4x3 with all 150 and two nans
+    # array 3x4 with all 150 and two nans
     (np.array([[150.,  150, 150.,  150.],
                [150., np.nan, np.nan,  150.],
                [150., 150., 150.,  150.]]),
-     np.array([[150., 150,  150.,  150.],
-               [150., 150., 150.,  150.],
-               [150., 150., 150.,  150.]])),
+     np.full((3,4), 150.)),
     # array 4x4 with all 150 and two nans
     (np.array([[150., 150,  150.,  150.],
                [150., np.nan, np.nan,  150.],