ASCIItable -> Table
This commit is contained in:
Martin Diehl
parent
1c75198af5
commit
b5a1295cb9
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@ -2,6 +2,7 @@
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import os
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import sys
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from io import StringIO
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from optparse import OptionParser
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import numpy as np
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@ -71,60 +72,30 @@ parser.set_defaults(bins = (10,10),
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)
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(options,filenames) = parser.parse_args()
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if filenames == []: filenames = [None]
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minmax = np.array([np.array(options.xrange),
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np.array(options.yrange),
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np.array(options.zrange)])
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grid = np.zeros(options.bins,'f')
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result = np.zeros((options.bins[0],options.bins[1],3),'f')
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minmax = np.array([options.xrange,options.yrange,options.zrange])
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result = np.empty((options.bins[0],options.bins[1],3),'f')
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if options.data is None: parser.error('no data columns specified.')
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labels = list(options.data)
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if options.weight is not None: labels += [options.weight] # prevent character splitting of single string value
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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outname = os.path.join(os.path.dirname(name),
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'binned-{}-{}_'.format(*options.data) +
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('weighted-{}_'.format(options.weight) if options.weight else '') +
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os.path.basename(name)) if name else name)
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except IOError:
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continue
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damask.util.report(scriptName,name)
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# ------------------------------------------ read header ------------------------------------------
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table.head_read()
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# ------------------------------------------ sanity checks ----------------------------------------
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missing_labels = table.data_readArray(labels)
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if len(missing_labels) > 0:
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damask.util.croak('column{} {} not found.'.format('s' if len(missing_labels) > 1 else '',', '.join(missing_labels)))
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table.close(dismiss = True)
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continue
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table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
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data = np.hstack((table.get(options.data[0]),table.get(options.data[1])))
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for c in (0,1): # check data minmax for x and y (i = 0 and 1)
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if (minmax[c] == 0.0).all(): minmax[c] = [table.data[:,c].min(),table.data[:,c].max()]
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if (minmax[c] == 0.0).all(): minmax[c] = [data[:,c].min(),data[:,c].max()]
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if options.type[c].lower() == 'log': # if log scale
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table.data[:,c] = np.log(table.data[:,c]) # change x,y coordinates to log
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data[:,c] = np.log(data[:,c]) # change x,y coordinates to log
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minmax[c] = np.log(minmax[c]) # change minmax to log, too
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delta = minmax[:,1]-minmax[:,0]
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(grid,xedges,yedges) = np.histogram2d(table.data[:,0],table.data[:,1],
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(grid,xedges,yedges) = np.histogram2d(data[:,0],data[:,1],
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bins=options.bins,
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range=minmax[:2],
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weights=None if options.weight is None else table.data[:,2])
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weights=table.get(options.weight) if options.weight else None)
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if options.normCol:
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for x in range(options.bins[0]):
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sum = np.sum(grid[x,:])
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@ -153,24 +124,20 @@ for name in filenames:
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for y in range(options.bins[1]):
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result[x,y,:] = [minmax[0,0]+delta[0]/options.bins[0]*(x+0.5),
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minmax[1,0]+delta[1]/options.bins[1]*(y+0.5),
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min(1.0,max(0.0,(grid[x,y]-minmax[2,0])/delta[2]))]
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np.clip((grid[x,y]-minmax[2,0])/delta[2],0.0,1.0)]
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for c in (0,1):
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if options.type[c].lower() == 'log': result[:,:,c] = np.exp(result[:,:,c])
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if options.invert: result[:,:,2] = 1.0 - result[:,:,2]
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# --- assemble header -------------------------------------------------------------------------------
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table.info_clear()
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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table.labels_clear()
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table.labels_append(['bin_%s'%options.data[0],'bin_%s'%options.data[1],'z'])
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table.head_write()
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# --- output result ---------------------------------------------------------------------------------
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table.data = result.reshape(options.bins[0]*options.bins[1],3)
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table.data_writeArray()
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table.close()
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comments = scriptID + '\t' + ' '.join(sys.argv[1:])
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shapes = {'bin_%s'%options.data[0]:(1,),'bin_%s'%options.data[1]:(1,),'z':(1,)}
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table = damask.Table(result.reshape(options.bins[0]*options.bins[1],3),shapes,[comments])
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if name:
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outname = os.path.join(os.path.dirname(name),'binned-{}-{}_'.format(*options.data) +
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('weighted-{}_'.format(options.weight) if options.weight else '') +
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os.path.basename(name))
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table.to_ASCII(outname)
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else:
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table.to_ASCII(sys.stdout)
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@ -255,8 +255,8 @@ for name in filenames:
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table.data_readArray(labels)
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coords = table.data[:,table.label_indexrange(options.pos)] * info['size'] if options.normalized \
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else table.data[:,table.label_indexrange(options.pos)] - info['origin']
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eulers = table.data[:,table.label_indexrange(options.eulers)] if hasEulers \
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else np.zeros(3*len(coords))
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if hasEulers:
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eulers = table.data[:,table.label_indexrange(options.eulers)]
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grains = table.data[:,table.label_indexrange(options.microstructure)].astype(int) if hasGrains \
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else np.arange(len(coords))+1
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@ -1,11 +1,16 @@
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#!/usr/bin/env python3
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# -*- coding: UTF-8 no BOM -*-
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import os
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import sys
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import math
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import random
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from optparse import OptionParser
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import damask
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import os,sys,math,random
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import numpy as np
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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@ -223,54 +228,29 @@ parser.set_defaults(randomSeed = None,
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)
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(options,filenames) = parser.parse_args()
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nSamples = options.number
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methods = [options.algorithm]
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name, readonly=True)
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except IOError:
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continue
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damask.util.report(scriptName,name)
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randomSeed = int(os.urandom(4).hex(), 16) if options.randomSeed is None else options.randomSeed # random seed per file for second phase
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table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
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randomSeed = int(os.urandom(4).hex(),16) if options.randomSeed is None else options.randomSeed # random seed per file
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random.seed(randomSeed)
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# ------------------------------------------ read header and data ---------------------------------
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table.head_read()
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errors = []
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labels = ['1_euler','2_euler','3_euler','intensity']
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for i,index in enumerate(table.label_index(labels)):
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if index < 0: errors.append('label {} not present.'.format(labels[i]))
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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table.data_readArray(labels)
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# --------------- figure out limits (left/right), delta, and interval -----------------------------
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ODF = {}
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limits = np.array([np.min(table.data[:,0:3],axis=0),
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np.max(table.data[:,0:3],axis=0)]) # min/max euler angles in degrees
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eulers = table.get('euler')
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limits = np.array([np.min(eulers,axis=0),np.max(eulers,axis=0)]) # min/max euler angles in degrees
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ODF['limit'] = np.radians(limits[1,:]) # right hand limits in radians
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ODF['center'] = 0.0 if all(limits[0,:]<1e-8) else 0.5 # vertex or cell centered
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ODF['interval'] = np.array(list(map(len,[np.unique(table.data[:,i]) for i in range(3)])),'i') # steps are number of distict values
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ODF['interval'] = np.array(list(map(len,[np.unique(eulers[:,i]) for i in range(3)])),'i') # steps are number of distict values
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ODF['nBins'] = ODF['interval'].prod()
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ODF['delta'] = np.radians(np.array(limits[1,0:3]-limits[0,0:3])/(ODF['interval']-1)) # step size
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if table.data.shape[0] != ODF['nBins']:
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damask.util.croak('expecting %i values but got %i'%(ODF['nBins'],table.data.shape[0]))
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if eulers.shape[0] != ODF['nBins']:
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damask.util.croak('expecting %i values but got %i'%(ODF['nBins'],eulers.shape[0]))
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continue
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# ----- build binnedODF array and normalize ------------------------------------------------------
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@ -278,9 +258,10 @@ for name in filenames:
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ODF['dV_V'] = [None]*ODF['nBins']
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ODF['nNonZero'] = 0
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dg = ODF['delta'][0]*2.0*math.sin(ODF['delta'][1]/2.0)*ODF['delta'][2]
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intensity = table.get('intensity')
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for b in range(ODF['nBins']):
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ODF['dV_V'][b] = \
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max(0.0,table.data[b,table.label_index('intensity')]) * dg * \
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max(0.0,intensity[b,0]) * dg * \
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math.sin(((b//ODF['interval'][2])%ODF['interval'][1]+ODF['center'])*ODF['delta'][1])
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if ODF['dV_V'][b] > 0.0:
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sumdV_V += ODF['dV_V'][b]
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@ -296,11 +277,10 @@ for name in filenames:
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'Reference Integral: %12.11f\n'%(ODF['limit'][0]*ODF['limit'][2]*(1-math.cos(ODF['limit'][1]))),
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])
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# call methods
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Functions = {'IA': 'directInversion', 'STAT': 'TothVanHoutteSTAT', 'MC': 'MonteCarloBins'}
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method = Functions[options.algorithm]
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Orientations, ReconstructedODF = (globals()[method])(ODF,nSamples)
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Orientations, ReconstructedODF = (globals()[method])(ODF,options.number)
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# calculate accuracy of sample
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squaredDiff = {'orig':0.0,method:0.0}
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@ -319,7 +299,7 @@ for name in filenames:
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indivSum['orig'] += ODF['dV_V'][bin]
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indivSquaredSum['orig'] += ODF['dV_V'][bin]**2
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damask.util.croak(['sqrt(N*)RMSD of ODFs:\t %12.11f'% math.sqrt(nSamples*squaredDiff[method]),
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damask.util.croak(['sqrt(N*)RMSD of ODFs:\t %12.11f'% math.sqrt(options.number*squaredDiff[method]),
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'RMSrD of ODFs:\t %12.11f'%math.sqrt(squaredRelDiff[method]),
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'rMSD of ODFs:\t %12.11f'%(squaredDiff[method]/indivSquaredSum['orig']),
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'nNonZero correlation slope:\t %12.11f'\
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@ -331,10 +311,10 @@ for name in filenames:
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(indivSquaredSum[method]/ODF['nNonZero']-(indivSum[method]/ODF['nNonZero'])**2)))),
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])
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if method == 'IA' and nSamples < ODF['nNonZero']:
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if method == 'IA' and options.number < ODF['nNonZero']:
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strOpt = '(%i)'%ODF['nNonZero']
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formatwidth = 1+int(math.log10(nSamples))
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formatwidth = 1+int(math.log10(options.number))
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materialConfig = [
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'#' + scriptID + ' ' + ' '.join(sys.argv[1:]),
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@ -344,7 +324,7 @@ for name in filenames:
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'#-------------------#',
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]
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for i,ID in enumerate(range(nSamples)):
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for i,ID in enumerate(range(options.number)):
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materialConfig += ['[Grain%s]'%(str(ID+1).zfill(formatwidth)),
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'(constituent) phase %i texture %s fraction 1.0'%(options.phase,str(ID+1).rjust(formatwidth)),
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]
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@ -355,7 +335,7 @@ for name in filenames:
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'#-------------------#',
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]
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for ID in range(nSamples):
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for ID in range(options.number):
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eulers = Orientations[ID]
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materialConfig += ['[Grain%s]'%(str(ID+1).zfill(formatwidth)),
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@ -364,7 +344,5 @@ for name in filenames:
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#--- output finalization --------------------------------------------------------------------------
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with (open(os.path.splitext(name)[0]+'_'+method+'_'+str(nSamples)+'_material.config','w')) as outfile:
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with (open(os.path.splitext(name)[0]+'_'+method+'_'+str(options.number)+'_material.config','w')) as outfile:
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outfile.write('\n'.join(materialConfig)+'\n')
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table.close()
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@ -1,9 +1,15 @@
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#!/usr/bin/env python3
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import threading,time,os,sys,random
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import numpy as np
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import threading
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import time
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import os
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import sys
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import random
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from optparse import OptionParser
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from io import StringIO
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import numpy as np
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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@ -49,7 +55,7 @@ class myThread (threading.Thread):
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s.acquire() # ensure only one thread acces global data
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if bestSeedsUpdate > knownSeedsUpdate: # write best fit to virtual file
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knownSeedsUpdate = bestSeedsUpdate
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bestSeedsVFile.reset()
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bestSeedsVFile.seek(0)
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myBestSeedsVFile.close()
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myBestSeedsVFile = StringIO()
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i=0
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@ -67,46 +73,38 @@ class myThread (threading.Thread):
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for i in range(NmoveGrains):
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selectedMs.append(random.randrange(1,nMicrostructures))
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direction.append(np.array(((random.random()-0.5)*delta[0],
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(random.random()-0.5)*delta[1],
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(random.random()-0.5)*delta[2])))
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direction.append((np.random.random()-0.5)*delta)
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perturbedSeedsVFile.close() # reset virtual file
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perturbedSeedsVFile = StringIO()
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myBestSeedsVFile.reset()
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myBestSeedsVFile.seek(0)
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perturbedSeedsTable = damask.ASCIItable(myBestSeedsVFile,perturbedSeedsVFile,labeled=True) # write best fit to perturbed seed file
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perturbedSeedsTable.head_read()
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perturbedSeedsTable.head_write()
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outputAlive=True
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ms = 1
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perturbedSeedsTable = damask.Table.from_ASCII(myBestSeedsVFile)
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coords = perturbedSeedsTable.get('pos')
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i = 0
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while outputAlive and perturbedSeedsTable.data_read(): # perturbe selected microstructure
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for ms,coord in enumerate(coords):
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if ms in selectedMs:
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newCoords=np.array(tuple(map(float,perturbedSeedsTable.data[0:3]))+direction[i])
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newCoords=coord+direction[i]
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newCoords=np.where(newCoords>=1.0,newCoords-1.0,newCoords) # ensure that the seeds remain in the box
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newCoords=np.where(newCoords <0.0,newCoords+1.0,newCoords)
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perturbedSeedsTable.data[0:3]=[format(f, '8.6f') for f in newCoords]
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coords[i]=newCoords
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direction[i]*=2.
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i+= 1
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ms+=1
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perturbedSeedsTable.data_write()
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#--- do tesselation with perturbed seed file ----------------------------------------------------------
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perturbedSeedsTable.set('pos',coords)
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perturbedSeedsTable.to_ASCII(perturbedSeedsVFile)
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#--- do tesselation with perturbed seed file ------------------------------------------------------
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perturbedGeomVFile.close()
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perturbedGeomVFile = StringIO()
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perturbedSeedsVFile.reset()
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perturbedSeedsVFile.seek(0)
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perturbedGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
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' -g '+' '.join(list(map(str, options.grid))),streamIn=perturbedSeedsVFile)[0])
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perturbedGeomVFile.reset()
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perturbedGeomVFile.seek(0)
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#--- evaluate current seeds file ----------------------------------------------------------------------
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perturbedGeomTable = damask.ASCIItable(perturbedGeomVFile,None,labeled=False,readonly=True)
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perturbedGeomTable.head_read()
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for i in perturbedGeomTable.info:
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if i.startswith('microstructures'): myNmicrostructures = int(i.split('\t')[1])
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perturbedGeomTable.data_readArray()
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perturbedGeomTable.output_flush()
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currentData=np.bincount(perturbedGeomTable.data.astype(int).ravel())[1:]/points
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#--- evaluate current seeds file ------------------------------------------------------------------
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perturbedGeom = damask.Geom.from_file(perturbedGeomVFile)
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myNmicrostructures = len(np.unique(perturbedGeom.microstructure))
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currentData=np.bincount(perturbedGeom.microstructure.ravel())[1:]/points
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currentError=[]
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currentHist=[]
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for i in range(nMicrostructures): # calculate the deviation in all bins per histogram
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@ -137,7 +135,7 @@ class myThread (threading.Thread):
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damask.util.croak(' target: '+np.array_str(target[i]['histogram']))
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damask.util.croak(' best: '+np.array_str(currentHist[i]))
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currentSeedsName = baseFile+'_'+str(bestSeedsUpdate).replace('.','-') # name of new seed file (use time as unique identifier)
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perturbedSeedsVFile.reset()
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perturbedSeedsVFile.seek(0)
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bestSeedsVFile.close()
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bestSeedsVFile = StringIO()
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sys.stdout.flush()
|
||||
|
|
@ -154,7 +152,7 @@ class myThread (threading.Thread):
|
|||
break
|
||||
if i == min(nMicrostructures,myMatch+options.bins)-1: # same quality as before: take it to keep on moving
|
||||
bestSeedsUpdate = time.time()
|
||||
perturbedSeedsVFile.reset()
|
||||
perturbedSeedsVFile.seek(0)
|
||||
bestSeedsVFile.close()
|
||||
bestSeedsVFile = StringIO()
|
||||
for line in perturbedSeedsVFile:
|
||||
|
|
@ -216,7 +214,7 @@ damask.util.report(scriptName,options.seedFile)
|
|||
if options.randomSeed is None:
|
||||
options.randomSeed = int(os.urandom(4).hex(),16)
|
||||
damask.util.croak(options.randomSeed)
|
||||
delta = (options.scale/options.grid[0],options.scale/options.grid[1],options.scale/options.grid[2])
|
||||
delta = options.scale/np.array(options.grid)
|
||||
baseFile=os.path.splitext(os.path.basename(options.seedFile))[0]
|
||||
points = np.array(options.grid).prod().astype('float')
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue