print("Dimensions must be one of ", dim_names)
exit()
if dim.getMaximum() != -dim.getMinimum():
print('Workspace dimensions must be centered on zero')
exit()
#dim_list.append((dim.getNBins(), (dim.getMaximum()-dim.getMinimum())/dim.getNBins()))
fft_dim = np.fft.fftshift(
np.fft.fftfreq(dim.getNBins(),
(dim.getMaximum() - dim.getMinimum()) / dim.getNBins()))
dim_list.append((fft_dim[0], fft_dim[-1]))
dimX = ws.getXDimension()
dimY = ws.getYDimension()
dimZ = ws.getZDimension()
signal = ws.getSignalArray().copy()
sg = SpaceGroupFactory.createSpaceGroup(space_group)
X = np.linspace(dimX.getMinimum(), dimX.getMaximum(), dimX.getNBins() + 1)
Y = np.linspace(dimY.getMinimum(), dimY.getMaximum(), dimY.getNBins() + 1)
Z = np.linspace(dimZ.getMinimum(), dimZ.getMaximum(), dimZ.getNBins() + 1)
box_width = 0.1 # in hkl dimensions
for h in range(int(np.ceil(dimX.getMinimum())),
int(np.floor(dimX.getMaximum())) + 1):
for k in range(int(np.ceil(dimY.getMinimum())),
int(np.floor(dimY.getMaximum())) + 1):
for l in range(int(np.ceil(dimZ.getMinimum())),
int(np.floor(dimZ.getMaximum())) + 1):
from mantid.simpleapi import LoadMD
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.transforms as mtransforms
import numpy as np
benzil = LoadMD('/SNS/users/rwp/benzil/benzil_300K_bkg_subtract_sym_All_noCC_flat2_fft.nxs')
signal = benzil.getSignalArray()
x, y = np.meshgrid(np.linspace(-10,10,501),np.linspace(-10,10,501))
plt.pcolormesh(x, y, signal[:,:,252], norm=colors.SymLogNorm(linthresh=0.2, linscale=0, vmin=-1.0, vmax=1.0), cmap='coolwarm')
plt.colorbar()
plt.show()
plt.pcolormesh(x, y, signal[:,260,:], norm=colors.SymLogNorm(linthresh=0.05, linscale=1, vmin=-1.0, vmax=1.0), cmap='coolwarm')
plt.colorbar()
plt.show()
fig = plt.pcolormesh(x, y, signal[:,:,252].transpose(), vmax=1,vmin=0,cmap='viridis')
trans_data = mtransforms.Affine2D().skew(np.arctan(np.sin(np.deg2rad(-30))), 0) + fig.get_transform()
fig.set_transform(trans_data)
plt.show()
fig = plt.pcolormesh(x, y, signal[:,:,252], norm=colors.SymLogNorm(linthresh=0.1, linscale=1, vmin=-1.0, vmax=1.0), cmap='coolwarm')
trans_data = mtransforms.Affine2D().skew(np.arctan(np.sin(np.deg2rad(-30))), 0) + fig.get_transform()
fig.set_transform(trans_data)
plt.colorbar()
plt.show()