ThermoCorr 1.0

Getting Started

I recommend the SublimeText editor to work with python code. You can download sample experimental data from here
Bellow you can find the minimal example of the ThermoCorr script to run the DIC 2D analysis.

from thermocorr.dic2d import Dic2d from thermocorr.log import Log from thermocorr.frames import Frames from thermocorr.settings import Settings from thermocorr.hdfodb import HdfOdb from thermocorr.point_region_2d import PointRegion2d # Error handling (optional) log = Log(mode='info', file='job_u.txt') log.exit_when_error(True) # rectangular region of intrest region = PointRegion2d() region.point_step = 10.0 region.distribution = 'grid' region.integer_position = True region.rectangle(a=1000.0, b=125.0, x0=200.0, y0=50.0) # images are loaded from directory frames = Frames(log=log) path = './tc_01/dsp' frames.load_from_directory(path=path, start=1, step=2, end=40, last=False, frequency=1439.88) # create output file path = './temp.hdf5' odb = HdfOdb(path=path, mode='w', log=log) # load default settings from json file sts = Settings(log=log) sts.load_default('dic2d.json') # edit default settings (optional) sts.edit( subset_radius=15, searching_area_radius=15, interpolation_orient='frame', ref_update=['every_n_step', 10], tolerance=0.001, subset_spacing=1, subset_type='circle', threshold = 0.6, searching_area_type='circle', newton_max_iter=20, interpolation_type='cubic', cpu=12, chunk=20, ) # digitial image correlation analysis # set the settings, region of interest, # frames and output file dic2d = Dic2d(log=log) dic2d.set_settings(sts) dic2d.set_region(region) dic2d.set_frames(frames) dic2d.set_odb(odb) # display the first frame and region using matplotlib dic2d.show() # start computation dic2d.compute()

The displacement gradient can be calculated using the following script.

from thermocorr.grd2d import Grd2d from thermocorr.hdfodb import HdfOdb from thermocorr.log import Log from thermocorr.frames import Frames from thermocorr.settings import Settings # error handling (optional) log = Log(mode='info', file='./job_dudx.txt') log.exit_when_error(False) # open the output file with computed displacement field odb_inp = HdfOdb(log=log, path='./temp.hdf5') # create output file (in this case is the same as input file) odb_out = odb_inp # load default settings from json file sts = Settings(log=log) sts.load_default(name='grd2d.json') # size - radius of circural region for calulation of the slop sts.edit( size=40.0, cpu=1, nmin = 10, max_neighbors=10000, weight = 'none', configuration='reference' ) # gradinet algorithm # compute the displacement gradinet # H = grad(u) and save it in ./temp.hdf5 file grd2d = Grd2d(log=log) grd2d.set_field_from_odb(odb=odb_inp, name='u') grd2d.set_odb(odb_out, name='H') grd2d.set_settings(sts) # start computation grd2d.compute()

Finally the coupled thermal field is computed as described bellow.

from thermocorr.cpf2d import Cpf2d from thermocorr.hdfodb import HdfOdb from thermocorr.log import Log from thermocorr.settings import Settings from thermocorr.frames import Frames # error handling (optional) log = Log(mode='info', file='./job_T.txt') log.exit_when_error(True) # open the output file with computed displacement field odb_inp = HdfOdb(path='./temp.hdf5', log=log) # create output file (in this case is the same as input file) odb_out = odb_inp # create frames object for loading the temperature data # from directory, the temperatrue field is saved in txt file as 2d array frames = Frames(log=log) path = './tc_01/tmp' frames.load_from_directory(path=path, start=1, step=1, end=41, last=False, frequency=1438.85) # load default settings from json file sts = Settings(log=log) sts.load_default(name= 'cpf2d.json') # set 3 pair of points with the same location on dic and cpf frame # set dic and cpf time which define the same moment during the process sts.edit( dic_points= [[255.0, 31.0], [1121.0, 34.0], [1121.0, 202.0]], cpf_points =[[ 68.00, 52.00],[291.00, 53.00],[291.00, 11.00]], dic_time = 0.0017, cpf_time = 0.0, cpu = 2, chunk = 10 ) # coupled field analysis # transform the temperature field in the dic2d frame # ad save it as field "T" in the file "./temp.hdf5" cpf2d = Cpf2d(log=log) cpf2d.set_settings(sts) cpf2d.set_dic_field_from_odb(odb=odb_inp) cpf2d.set_frames(frames, name='T') cpf2d.set_odb(odb_out) # show the analysis cpf2d.show() # start computation cpf2d.compute()

The output database can be viewed using the matplotlib library. The following script displays the displacement gradient and temperature for the same instant of time.

import matplotlib.pyplot as plt from thermocorr.hdfodb import HdfOdb from thermocorr.log import Log from thermocorr.frames import Frames # error handling log=Log(mode='debug') log.exit_when_error(True) # open output file path = './temp.hdf5' odb = HdfOdb(path=path, log=log) odb.open('r') # get nodes nodes = odb.get_array(name='nodes') frames = Frames() n=8 fig = plt.figure(figsize=(7, 6)) vmin1 = 0.0 vmax1 = 0.044 vmin2 = 27.52 vmax2 = 32.73 axs = [] w = 0.4 h=0.08 hp =0.02 for i in range(n): ax1 = fig.add_axes([0.05, 1.0-(h+hp)*i, w, h]) ax2 = fig.add_axes([0.55, 1.0-(h+hp)*i, w, h]) axs.append([ax1,ax2]) for i in range(n): step = 2+i*2 # get displacement gradient field for every nodes, first component dudx = odb.get_time_array(name='H', step=step)[:,0] # get temperature field T = odb.get_time_array(name='T', step=step)[:,0] # get displacment field u = odb.get_time_array(name='u', step=step) # get image path = odb.get_time_value(base='u', name='path', step=step) f0 = frames.open_image(path=path) # show image axs[i][0].imshow(f0.T, cmap='gray') axs[i][1].imshow(f0.T, cmap='gray') # get indices of valid points ind1 = odb.get_valid_points(data=[u,dudx]) ind2 = odb.get_valid_points(data=[u,T]) # compute actual positons of the valid points x = nodes[ind1,0] + u[ind1,0] y = nodes[ind1,1] + u[ind1,1] # get only the valid data dudx_v = dudx[ind2] T_v = T[ind2] s1 = axs[i][0].scatter(x, y, c=dudx_v, cmap='jet',s=2, vmin=vmin1, vmax=vmax1) s2 = axs[i][1].scatter(x, y, c=T_v, cmap='RdBu_r',s=2, vmin=vmin2, vmax=vmax2) axs[i][0].set_axis_off() axs[i][1].set_axis_off() ax1 = fig.add_axes([0.05, 0.20, 0.9, 0.04]) ax2 = fig.add_axes([0.05, 0.07, 0.9, 0.04]) p1 = plt.colorbar(s1, orientation='horizontal', cax=ax1) fig.text(0.5,0.26, r'$Displacement \,gradient \, du/dx \, [-]$',ha='center', va='center') p2 = plt.colorbar(s2, orientation='horizontal', cax=ax2) fig.text(0.5,0.13, r'$Temperature \, [^\circ C]$',ha='center', va='center') # close odb file odb.close() plt.show()