cleaning up docs in funcs
@@ -19,9 +19,6 @@ def map_to_regions(regions, values):
r"""
Maps pore values from a network onto the image from which it was extracted
- This function assumes that the pore numbering in the network has remained
- unchanged from the region labels in the partitioned image.
-
Parameters
----------
regions : ND-array
@@ -30,7 +27,7 @@ def map_to_regions(regions, values):
values : array_like
An array containing the numerical values to insert into each region.
The value at location *n* will be inserted into the image where
- ``regions`` is *n+1*. This mis-match is caused by the fact that 0's
+ ``regions`` is *n+1*. This mismatch is caused by the fact that 0's
in the ``regions`` image is assumed to be the backgroung phase, while
pore index 0 is valid.
@@ -154,7 +151,7 @@ def add_boundary_regions2(regions, pad_width=3):
pad_width : array_like
Number of layers to add to the edges of each axis. An integer pads
each axis equally in both direction. An ND-by-1 list pads each axis
- by given amount in both directions. An ND-by-1 list of pairs pad
+ by the given amount in both directions. An ND-by-1 list of pairs pad
each axis by a unique amount. This argument is handled the same as
``pad_width`` in the ``np.pad`` function. The default is to add
3 voxels on each axis.
@@ -347,8 +344,8 @@ def add_phase_interconnections(net, snow_partitioning_n, voxel_size=1,
marching_cubes_area=False,
alias=None):
r"""
- This function connects networks of two or more phases together by
- interconnecting neighbouring nodes inside different phases.
+ Connects networks of two or more phases together by interconnecting
+ neighbouring nodes of different phases.
The resulting network can be used for the study of transport and kinetics
at interphase of two phases.
@@ -359,24 +356,20 @@ def add_phase_interconnections(net, snow_partitioning_n, voxel_size=1,
A dictoionary containing structural information of two or more
phases networks. The dictonary format must be same as porespy
region_to_network function.
-
snow_partitioning_n : tuple
The output generated by snow_partitioning_n function. The tuple should
have phases_max_labels and original image of material.
-
voxel_size : scalar
The resolution of the image, expressed as the length of one side of a
voxel, so the volume of a voxel would be **voxel_size**-cubed. The
default is 1, which is useful when overlaying the PNM on the original
image since the scale of the image is alway 1 unit lenth per voxel.
-
marching_cubes_area : bool
If ``True`` then the surface area and interfacial area between regions
will be causing the marching cube algorithm. This is a more accurate
representation of area in extracted network, but is quite slow, so
it is ``False`` by default. The default method simply counts voxels
so does not correctly account for the voxelated nature of the images.
-
alias : dict (Optional)
A dictionary that assigns unique image label to specific phase.
For example {1: 'Solid'} will show all structural properties associated
