upxo.pxtal.images module

class upxo.pxtal.images.IMAGE_3D(image3d)[source]

Bases: object

Description of slot variables

img: 3D Numpy array. np.int32 fid: 0D Numpy array of list of feature IDs. np.int32 n: Number of individual features. int neigh_fid: immediate neighbour feature ID database. dict

vox: Information on voxels in the image. dataclass

vol: Total volume bvox:

ctrl

base

vox

rve

coords

mops

img

tops

sops

rops

build_coords()[source]: Build and return coords.

part()[source]: Partition the 3D image into below individual features. * closed domains (ex. grains) * total domain boundary (ex. all grain boundary segments) * domain boundary segments (ex. individual grain boundary segments) * domain boundary segment edges * domain bondarty segment edge junction points

class mops_CLS(ctrl, fx)[source]

Bases: object

Morphological operations

ctrl

fx

part(img)[source]: Partition the 3D image into below individual features. * closed domains (ex. grains) * total domain boundary (ex. all grain boundary segments) * domain boundary segments (ex. individual grain boundary segments) * domain boundary segment edges * domain bondarty segment edge junction points

find_CLS_mprops()[source]: Find CLS mprops.

class tops_CLS(def_cls_inst)[source]

Bases: object

Topological operations 1. handle all ops with neighbour database

DCI

find_on_neighs(on, prob)[source]: Find on neighs.

find_onth_neighs(on, prob)[source]: Find onth neighs.

cluster(clustering_stats)[source]: Cluster.

make_graph()[source]: Build and return graph.

partition()[source]: Partition.

crop_neigh_gid(neigh_gid='O(1)', gids_to_crop=None)[source]

Removes gids in gids_to_crop from neighbour order dictionary. Both keys and appearences in values get removed. :param neigh_gid: Neighbour gid dictionary. If a string liuke ‘O(1)’ is entered,

then the corresponding will be extracted. Idf the neighbour does not exist, the method should rauise an error and stop. If the value is dictionary, then entered value will be used without any validations. Defaults to ‘O(1)’.

Parameters:: gids_to_crop (dth.dt.ITERABLES | integer) – Grain ids to be cropped from neigh_gid. Value could be any in dth.dt.ITERABLES or of any integrer type in dth.dt.INTEGERS. Defaults to None.

Examples

gstlice.crop_neigh_gid(neigh_gid='O(1)', gids_to_crop=[1])

maps

no

ntype

pairs

G

class sops_CLS(fx)[source]

Bases: object

Spatial operations

fx

find_loc()[source]: Find loc.

class mprops_CLS[source]

Bases: object

Class to find morphological propertues

class tprops_CLS[source]

Bases: object

Class to find topological properties

G_max_ind_set(G)[source]: G max ind set.

G_conn_comp(G)[source]: G conn comp.

class sprops_CLS[source]

Bases: object

Class to find spatial properties

class rprops_CLS[source]

Bases: object

Class to find representativeness properties

class mviz_CLS(outer)[source]: Bases: object

class tviz_CLS(outer)[source]: Bases: object

class mpviz_CLS[source]: Bases: object

class meta_ops_CLS[source]

Bases: object

subdomain()[source]: Subdomain.

coarse(k)[source]: Coarse.

fine(k)[source]: Fine.

class cell_CLS[source]

Bases: object

type

class xtal_CLS[source]

Bases: cell_CLS

a

class xb_CLS[source]

Bases: cell_CLS

xtal_boundary

a

class xbseg_CLS[source]

Bases: cell_CLS

xtal_boundary segment

a

class xjv_CLS[source]

Bases: cell_CLS

xtal_junction_voxels

a

H

fid

n

neigh_fid

bvox

neigh_pairs

mprop

tprop

srep