update workflows for generating initial guess radii for morphological

imbibition
This commit is contained in:
zherexli 2016-11-04 15:43:15 -04:00
parent c98ba48a40
commit 9d3e9284ba
2 changed files with 88 additions and 0 deletions

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#!/usr/bin/env python
import sys
import numpy as np
from dist_func_utils import *
from glob import glob
# Check if there is a proper command line argument
if len(sys.argv) !=2:
sys.stderr.write('Usage: ' + sys.argv[0] + ' <Domain.in>\n')
sys.exit()
# end if
# Read 'Domain.in' to obtain the size of 'SignDist.xxxxx'
f = open(sys.argv[1],'r')
lines = f.readlines()
nx,ny,nz = np.fromstring(lines[1].splitlines()[0],dtype = np.int32,sep=' ')
f.close()
#nx = ny = nz = 128
nx+=2 # consider the halo layer
ny+=2
nz+=2
base_name = 'SignDist.'
file_input_group = glob(base_name+'*')
# Prepare output file: 'pores_xxxxx.csv'
output_data_name = 'pores_'
output_data_format = '.csv'
# Process all imported experimental images
if not file_input_group:
print 'Error: Input files cannot be found ! '
else:
for ii in range(len(file_input_group)):
file_input_single = file_input_group[ii]
file_input_single_idx = file_input_single[file_input_single.find(base_name)+len(base_name):]
print '--- Get pore size information for '+file_input_single+' now ---'
dist = np.fromfile(file_input_single,dtype = np.float64)
dist_on_skel,connect_stats = detect_intersection_point_with_cluster_filter(dist,nx,ny,nz)
[z_skel,y_skel,x_skel] = np.where(dist_on_skel>0.0)
output_data = np.column_stack((x_skel,y_skel,z_skel,dist_on_skel[dist_on_skel>0.0]))
print '--- Save pore size csv file ---'
np.savetxt(output_data_name+file_input_single_idx+output_data_format,output_data,delimiter=' ')
#end for
#end if

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#!/usr/bin/env python
import numpy as np
import sys
# Check if there is a proper command line argument
if len(sys.argv) !=3:
sys.stderr.write('Usage: ' + sys.argv[0] + ' pores.csv Sw_list\n')
sys.exit()
# end if
# Read 'pores.csv' and a list of Sw
pores = np.genfromtxt(sys.argv[1])
Sw = np.genfromtxt(sys.argv[2])
#NOTE: 'pores.csv' has a layout of : [x,y,z,pore_radius]
pores = pores[:,-1]
# Calculate the percentile according to the Sw list
if Sw.max()<=1.0 and Sw.min()>=0.0:
radii_init_imbib = np.percentile(pores,100.0*Sw.ravel())
else:
print 'Error: the list of Sw should have values 0.0 - 1.0 !'
sys.exit()
#end if
radii_init_imbib.shape = (radii_init_imbib.size,1)
# Write out initial guess for imbibition
output_name = 'radius.csv'
print '------ Initial radii for morphological imbibition is written to the file: '+output_name+' ------'
np.savetxt(output_name,radii_init_imbib)