Added capablity to accept bounds for interpolation

setup.cfg

@@ -7,7 +7,7 @@
 
 [metadata]
 name = empyre
-version = 0.3.0
+version = 0.3.1
 author = Jan Caron
 author-email = j.caron@fz-juelich.de
 description = Electron Microscopy Python Reconstruction

src/empyre/io/field_plugins/vtk.py

@@ -11,7 +11,7 @@ from numbers import Number
 import numpy as np
 
 from ...fields.field import Field
-from ...utils.misc import interp_to_regular_grid
+from ...utils.misc import interp_to_regular_grid, restrict_points
 from ...vis import colors
 
 
@@ -20,7 +20,7 @@ _log = logging.getLogger(__name__)
 file_extensions = ('.vtk',)  # Recognised file extensions
 
 
-def reader(filename, scale=None, vector=None, **kwargs):
+def reader(filename, scale=None, vector=None, bounds=None, **kwargs):
     """More infos at:
 
     overview: https://docs.enthought.com/mayavi/mayavi/data.html
@@ -88,6 +88,10 @@ def reader(filename, scale=None, vector=None, **kwargs):
             scale = (scale,) * 3
         elif isinstance(scale, tuple):
             assert len(scale) == 3, f'Each dimension (z, y, x) needs a scale, but {scale} was given!'
+        # Crop data to required range, if necessary
+        if bounds is not None:
+            _log.info('Restrict data')
+            point_array, data_array = restrict_points(point_array, data_array, bounds)
         data = interp_to_regular_grid(point_array, data_array, scale, **kwargs)
     else:
         raise TypeError('Data type of {} not understood!'.format(output))

src/empyre/utils/misc.py

@@ -15,7 +15,7 @@ from scipy.spatial import cKDTree, qhull
 from scipy.interpolate import LinearNDInterpolator
 
 
-__all__ = ['levi_civita', 'interp_to_regular_grid']
+__all__ = ['levi_civita', 'interp_to_regular_grid', 'restrict_points']
 _log = logging.getLogger(__name__)
 
 
@@ -121,3 +121,39 @@ def interp_to_regular_grid(points, values, scale, scale_factor=1, step=1, convex
         # Set these points to zero (NOTE: This can take a looooong time):
         interpolation[mask, :] = 0
     return np.squeeze(interpolation)
+
+
+def restrict_points(point_array, data_array, bounds):
+    """Restrict range of point_array and data_array
+
+    Parameters
+    ----------
+    points_array : np.ndarray, (N, 3)
+        Array of points, describing the location of the values that should be interpolated. Three columns x, y, z!
+    data_array : np.ndarray, (N, c)
+        Array of values that should be interpolated to the new grid. `c` is the number of components (`1` for scalar
+        fields, `3` for normal 3D vector fields).
+    bounds : tuple of 6 values
+        Restrict data range to given bounds, x0, x1, y0, y1, z0, z1.
+
+    Returns
+    -------
+    point_restricted: np.ndarray
+        Cut out of the array of points inside the bounds, describing the location of the values that should be
+        interpolated. Three columns x, y, z!
+    value_restricted: np.ndarray
+        Cut out of the array of values inside the bounds, describing the location of the values that should be
+        interpolated. Three columns x, y, z!
+
+    """
+    point_restricted = []
+    data_restricted = []
+    for i, pos in enumerate(point_array):
+        if bounds[0] <= pos[0] <= bounds[1]:
+            if bounds[2] <= pos[1] <= bounds[3]:
+                if bounds[4] <= pos[2] <= bounds[5]:
+                    point_restricted.append(pos)
+                    data_restricted.append(data_array[i])  
+    point_restricted = np.array(point_restricted)
+    data_restricted = np.array(data_restricted)
+    return point_restricted, data_restricted