A PoleFigure object is then created using this microstructure and the pole figures
(both direct and inverse) are drawn by calling the plot_pole_figures() method.
'''
micro = Microstructure(name='Au_6grains', overwrite_hdf5=True)
micro.autodelete = True
gid_list = [1158, 1349, 1585, 1805, 1833, 2268]
euler_list = [(344.776, 52.2589, 53.9933),
(344.899, 125.961, 217.330),
(228.039, 57.4791, 143.171),
(186.741, 60.333, 43.311),
(151.709, 55.0406, 44.1051),
(237.262, 125.149, 225.615),
]
micro.add_grains(euler_list, grain_ids=gid_list)
# create pole figure (both direct and inverse)
pf = PoleFigure(hkl='111', axis='Z', proj='stereo', microstructure=micro)
pf.mksize = 100
pf.set_map_field('grain_id')
pf.pflegend = True # this works well for a few grains
pf.plot_pole_figures(plot_sst=True, display=False, save_as='png')
del pf
del micro
image_name = os.path.splitext(__file__)[0] + '.png'
print('writing %s' % image_name)
from matplotlib import image
image.thumbnail(image_name, 'thumb_' + image_name, 0.2)
def index(hkl_normals, hkl_planes, tol_angle=0.5, tol_disorientation=1.0, symmetry=Symmetry.cubic, display=False):
# angles between normal from the gnomonic projection
angles_exp = np.zeros((len(hkl_normals), len(hkl_normals)), dtype=float)
print('\nlist of angles between points on the detector')
for i in range(len(hkl_normals)):
for j in range(i + 1, len(hkl_normals)):
angle = 180 / pi * np.arccos(np.dot(hkl_normals[i], hkl_normals[j]))
angles_exp[i, j] = angle
print('%.2f, OP%d, OP%d' % (angles_exp[i, j], i, j))
# keep a list of the hkl values as string
hkl_str = []
for p in hkl_planes:
(h, k, l) = p.miller_indices()
hkl_str.append('(%d%d%d)' % (h, k, l))
# compute theoretical angle between each plane normal, store the results using a structured array
angles_th = np.empty(len(hkl_planes) * (len(hkl_planes) - 1) / 2,
dtype=[('angle', 'f4'), ('hkl1', 'i4'), ('hkl2', 'i4')])
index = 0
for i in range(len(hkl_planes)):
for j in range(i + 1, len(hkl_planes)):
angle = 180 / pi * np.arccos(np.dot(hkl_planes[i].normal(), hkl_planes[j].normal()))
angles_th[index] = (angle, i, j)
index += 1
# sort the array by increasing angle
angles_th.sort(order='angle')
print('\nsorted list of angles between hkl plane normals')
for i in range(len(angles_th)):
print('%.3f, (%d, %d) -> %s, %s' % (
angles_th['angle'][i], angles_th['hkl1'][i], angles_th['hkl2'][i], hkl_str[angles_th['hkl1'][i]],
hkl_str[angles_th['hkl2'][i]]))
# index by triplets
normal_indexed = triplet_indexing(hkl_normals, angles_exp, angles_th, tol=tol_angle)
print('indexed list length is %d' % len(normal_indexed))
print(normal_indexed)
# Compute the orientation matrix g for all different triplets
g_indexation = []
for i in range(len(normal_indexed)):
# a given indexed triplet allow to construct 3 orientation matrices (which should be identical)
pos = [[0, 1, 3, 4], [1, 2, 4, 5], [2, 0, 5, 3]]
for j in range(3):
orientation_matrix = transformation_matrix(
hkl_planes[normal_indexed[i][pos[j][2]]], hkl_planes[normal_indexed[i][pos[j][3]]],
hkl_normals[normal_indexed[i][pos[j][0]]], hkl_normals[normal_indexed[i][pos[j][1]]])
# move to the fundamental zone
om_fz = symmetry.move_rotation_to_FZ(orientation_matrix) # we only add the third one
g_indexation.append(om_fz)
final_orientation_matrix, vote, ci, vote_field = poll_system(g_indexation, dis_tol=tol_disorientation)
if final_orientation_matrix == 0:
print('Troubles in the data set !')
else:
print('\n\n\n### FINAL SOLUTION(S) ###\n')
for n in range(len(final_orientation_matrix)):
print('- SOLUTION %d -' % (n + 1))
final_orientation = Orientation(final_orientation_matrix[n])
print(final_orientation.inFZ())
print ('- Cristal orientation in Fundamental Zone \n {0:s} \n'.format(final_orientation.euler))
print('- Rodrigues vector in the fundamental Zone \n {0:s} \n'.format(final_orientation.rod))
if display:
from pymicro.crystal.texture import PoleFigure
PoleFigure.plot(final_orientation, axis='Z')
return final_orientation_matrix, ci
from pymicro.crystal.microstructure import Microstructure, Grain, Orientation
from pymicro.crystal.texture import PoleFigure
from matplotlib import pyplot as plt, colors, cm
if __name__ == '__main__':
'''
111 Pole figure of a copper sample containing 10000 grains with a fibre
texture.
'''
eulers = Orientation.read_euler_txt('../data/Cu_111.dat')
micro = Microstructure(name='Cu_111')
for index in eulers:
micro.grains.append(Grain(index, eulers[index]))
# create pole figure (both direct and inverse)
pf = PoleFigure(hkl='111',
proj='stereo',
microstructure=micro,
verbose=False)
pf.color_by_grain_id = False
pf.mksize = 5
pf.pflegend = False
pf.plot_pole_figures(plot_sst=True, display=False, save_as='png')
image_name = os.path.splitext(__file__)[0] + '.png'
print('writting %s' % image_name)
from matplotlib import image
image.thumbnail(image_name, 'thumb_' + image_name, 0.2)
poles are colored according using IPF coloring and resized proportionally
to each grain volume.
"""
# create a microstructure with a random texture and 200 grains
micro = Microstructure.random_texture(n=200)
micro.autodelete = True
# set random values for the grain volumes
np.random.seed(22)
for g in micro.grains:
g['volume'] = 100 * np.random.random()**3
g.update()
micro.grains.flush()
# first pole figure
pf = PoleFigure(microstructure=micro)
pf.resize_markers = True
pf.set_hkl_poles('001')
pf.axis = 'Z'
pf.set_map_field('ipf')
pf.plot_pole_figures(plot_sst=True, display=False, save_as='png')
del pf
del micro
image_name = os.path.splitext(__file__)[0] + '.png'
print('writing %s' % image_name)
from matplotlib import image
image.thumbnail(image_name, 'thumb_' + image_name, 0.2)
from pymicro.crystal.microstructure import Microstructure, Grain, Orientation
from matplotlib import pyplot as plt
if __name__ == '__main__':
"""
A pole figure plotted using contours.
.. note::
Use this example carefully since this is just using a matplotlib contourf
function, and has not been tested properly.
"""
euler_list = np.genfromtxt('../data/pp100', usecols=(0, 1, 2))
micro = Microstructure(name='test', autodelete=True)
micro.add_grains(euler_list)
pf = PoleFigure(hkl='111', proj='stereo', microstructure=micro)
pf.mksize = 40
fig = plt.figure(1, figsize=(12, 5))
ax1 = fig.add_subplot(121, aspect='equal')
ax2 = fig.add_subplot(122, aspect='equal')
pf.create_pf_contour(ax=ax1, ang_step=20)
pf.plot_pf(ax=ax2)
image_name = os.path.splitext(__file__)[0] + '.png'
print('writting %s' % image_name)
plt.savefig(image_name, format='png')
from matplotlib import image
image.thumbnail(image_name, 'thumb_' + image_name, 0.2)
del pf, micro
from pymicro.crystal.microstructure import Microstructure, Grain, Orientation
from matplotlib import pyplot as plt, colors, colorbar, cm
'''
An inverse pole figure with symboled colored by the grain size.
'''
eulers = Orientation.read_orientations('../data/EBSD_20grains.txt',
data_type='euler',
usecols=[1, 2, 3])
grain_sizes = np.genfromtxt('../data/EBSD_20grains.txt', usecols=[9])
micro = Microstructure(name='test')
for i in range(20):
micro.grains.append(Grain(i + 1, eulers[i + 1]))
micro.get_grain(i + 1).volume = grain_sizes[i]
# build a custom pole figure
pf = PoleFigure(microstructure=micro, hkl='001') #, lattice=Ti7Al)
#pf.resize_markers = True
pf.mksize = 100
pf.set_map_field('strain',
grain_sizes,
field_min_level=0.0,
field_max_level=1000.,
lut='jet')
fig = plt.figure(figsize=(8, 5))
ax1 = fig.add_axes([0.05, 0.05, 0.8, 0.9], aspect='equal')
pf.plot_sst(ax=ax1, mk='o')
ax1.set_title('%s-axis SST inverse %s projection' % (pf.axis, pf.proj))
# to add the color bar
ax2 = fig.add_axes([0.85, 0.05, 0.05, 0.9])
norm = colors.Normalize(vmin=0., vmax=1000.)
from pymicro.crystal.microstructure import Orientation, Grain from pymicro.crystal.texture import PoleFigure from pymicro.view.scene3d import Scene3D from pymicro.view.vtk_utils import pole_figure_3d, axes_actor, setup_camera ''' Create a 3d scene with a cubic crystal lattice at the center. Hkl planes are added to the lattice and their normal displayed. A sphere is added to show how a pole figure can be constructed. ''' base_name = os.path.splitext(__file__)[0] s3d = Scene3D(display=False, ren_size=(800, 800), name=base_name) orientation = Orientation.from_euler(numpy.array([142.8, 32.0, 214.4])) pf = PoleFigure(hkl='111') pf.microstructure.grains.append(Grain(1, orientation)) pole_figure = pole_figure_3d(pf, radius=1.0, show_lattice=True) # add all actors to the 3d scene s3d.add(pole_figure) axes = axes_actor(1.0, fontSize=60) s3d.add(axes) # set up camera cam = setup_camera(size=(1, 1, 1)) cam.SetViewUp(0, 0, 1) cam.SetPosition(0, -4, 0) cam.SetFocalPoint(0, 0, 0) s3d.set_camera(cam) s3d.render()
import os, numpy as np
from pymicro.crystal.texture import PoleFigure
from pymicro.crystal.microstructure import Microstructure, Grain, Orientation
from matplotlib import pyplot as plt
if __name__ == '__main__':
'''
A pole figure plotted using contours.
'''
eulers = Orientation.read_orientations('../data/pp100', data_type='euler')
micro = Microstructure(name='test')
for i in range(100):
micro.grains.append(Grain(i + 1, eulers[i + 1]))
pf = PoleFigure(microstructure=micro)
pf.mksize = 40
pf.proj = 'stereo'
pf.set_hkl_poles('111')
fig = plt.figure(1, figsize=(12, 5))
ax1 = fig.add_subplot(121, aspect='equal')
ax2 = fig.add_subplot(122, aspect='equal')
pf.create_pf_contour(ax=ax1, ang_step=20)
pf.plot_pf(ax=ax2)
image_name = os.path.splitext(__file__)[0] + '.png'
print('writting %s' % image_name)
plt.savefig(image_name, format='png')
from matplotlib import image
image.thumbnail(image_name, 'thumb_' + image_name, 0.2)
from pymicro.crystal.microstructure import Microstructure, Orientation, Grain
from pymicro.crystal.texture import PoleFigure
from matplotlib import pyplot as plt
# read data from Z-set calculation (50% tension load)
data = np.genfromtxt('../data/R_1g.dat')
t, R11, R22, R33, R12, R23, R31, R21, R32, R13, _, _, _, _ = data.T
step = 1 # plot every step point
max_step = data.shape[0]
# create a microstructure with the initial grain orientation
micro = Microstructure(name='1g', autodelete=True)
g = Grain(50, Orientation.from_euler((12.293, 149.266, -167.068)))
micro.add_grains([(12.293, 149.266, -167.068)], grain_ids=[50])
ipf = PoleFigure(proj='stereo', microstructure=micro)
ipf.mksize = 100
ipf.set_map_field('grain_id')
fig = plt.figure(1, figsize=(6, 5)) # for IPF
ax1 = fig.add_subplot(111, aspect='equal')
print('** plotting the initial orientation (with label for legend) **')
ipf.plot_sst(ax=ax1, mk='.', col='k', ann=False)
ax1.set_title('grain rotation in tension')
axis = np.array([0, 0, 1])
grain = micro.get_grain(50)
cgid = Microstructure.rand_cmap().colors[grain.id] # color by grain id
g = grain.orientation_matrix()
axis_rot_sst_prev = np.array(ipf.sst_symmetry_cubic(g.dot(axis)))
print('** plotting ipf loading axis trajectory **')