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Create input for CraFT

Create input for CraFT#

Warning

This notebook should be removed as it is specific for our use case. I don’t know how to deal with it. Therefore the same question is asked for the function within the notebook

This notebook shows how to create input for CraFT.

import xarrayaita.loadData_aita as lda #here are some function to build xarrayaita structure
import xarrayaita.aita as xa
import xarrayuvecs.uvecs as xu
import xarrayuvecs.lut2d as lut2d

import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np

import datetime
from skimage import morphology
from tqdm.notebook import tqdm
import scipy

%matplotlib widget

Load your data#

# path to data and microstructure
path_data='orientation_test.dat'
path_micro='micro_test.bmp'

data=lda.aita5col(path_data,path_micro)

data

<xarray.Dataset> Size: 100MB
Dimensions:      (y: 2500, x: 1000, uvecs: 2)
Coordinates:
  * x            (x) float64 8kB 0.0 0.02 0.04 0.06 ... 19.92 19.94 19.96 19.98
  * y            (y) float64 20kB 49.98 49.96 49.94 49.92 ... 0.06 0.04 0.02 0.0
Dimensions without coordinates: uvecs
Data variables:
    orientation  (y, x, uvecs) float64 40MB 2.395 0.6451 5.377 ... 0.6098 0.6473
    quality      (y, x) int64 20MB 0 90 92 93 92 92 94 ... 96 96 96 96 97 97 96
    micro        (y, x) float64 20MB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0
    grainId      (y, x) int64 20MB 1 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1 1
Attributes:
    date:       b'Thursday, 19 Nov 2015, 11:24 am\r'
    unit:       millimeters
    step_size:  0.02
    path_dat:   orientation_test.dat

CraFTWith G50 fabric analyser we usually filter the value with a quality below \(75\).

data.aita.filter(50)

Export input file for CraFT#

Two files are created using this function :

  1. The .vtk of the microstructure where the each pixel of the same grain has the same integer value.

  2. A .phase that is a text file where the orientation values are stored \([grainId, material, \phi_1, \phi, \phi_2]\). \(\phi_2\) is choosen randomly as it is unknown. If \(\phi_1, \phi\) are not resolved by the analyser, they are also choosen randomly.

data.aita.craft('granular',res=0.5)
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