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# -*- coding: utf-8 -*-
"""
The module provides visualization routines for displaying spatial and
energy distributions of synchrotron sources in 2D and 3D."""
__author__ = "Konstantin Klementiev"
__date__ = "12 Mar 2014"
#import cmath
import time
import copy
import numpy as np
#import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
import os, sys; sys.path.append(os.path.join('..', '..')) # analysis:ignore
#import xrt.backends.raycing as raycing
import xrt.backends.raycing.sources as rs
vmin = 2.5e-3
dpi = 82
xOrigin2d = 84 # all sizes are in pixels
yOrigin2d = 48
space2dto1d = 8
height1d = 100
xSpaceExtra = 20
ySpaceExtra = 28
def visualize(source, data, title, saveName=None, sign=1):
def one_fig(what, ts, tChar, otherChar):
sh = what.shape
xFigSize = float(xOrigin2d + sh[0] + space2dto1d +
height1d + xSpaceExtra)
yFigSize = float(yOrigin2d + sh[1] + space2dto1d +
height1d + ySpaceExtra)
fig = plt.figure(figsize=(xFigSize/dpi, yFigSize/dpi), dpi=dpi)
rect_2D = [xOrigin2d / xFigSize, yOrigin2d / yFigSize,
(sh[0]-1) / xFigSize, (sh[1]-1) / yFigSize]
rect_1DE = copy.deepcopy(rect_2D)
rect_1DE[1] = rect_2D[1] + rect_2D[3] + space2dto1d/yFigSize
rect_1DE[3] = height1d / yFigSize
rect_1Dx = copy.deepcopy(rect_2D)
rect_1Dx[0] = rect_2D[0] + rect_2D[2] + space2dto1d/xFigSize
rect_1Dx[2] = height1d / xFigSize
extent = [source.eMin, source.eMax, ts[0], ts[-1]]
ax2D = plt.axes(rect_2D)
dataMax = what.max()
ax2D.imshow(
what.T, aspect='auto', cmap='hot', extent=extent,
# interpolation='nearest', origin='lower', figure=fig,
interpolation=None, origin='lower', figure=fig,
norm=LogNorm(vmin=dataMax*vmin, vmax=dataMax))
ax2D.set_xlabel('energy (eV)')
ax2D.set_ylabel(r"${0}'$ (mrad)".format(tChar))
ax1DE = plt.axes(rect_1DE, sharex=ax2D)
ax1Dt = plt.axes(rect_1Dx, sharey=ax2D)
plt.setp(ax1DE.get_xticklabels() + ax1Dt.get_yticklabels(),
visible=False)
dE = energies[1] - energies[0]
dt = ts[1] - ts[0]
ax1DE.plot(energies, np.sum(what, axis=1)*dt, 'r')
# ax1DE.set_yscale('log')
ax1Dt.plot(np.sum(what/energies[:, None]*dE, axis=0), ts, 'r')
# ax1Dt.set_xscale('log')
ax1DE.set_ylim(bottom=0)
ax1DE.set_yticks(np.array([0, 2, 4, 6, 8])*1e16)
ax2D.set_xlim(extent[0], extent[1])
ax2D.set_ylim(extent[2], extent[3])
ax1DE.text(
0.65, 1.0, r"Angular flux density {0} at ".format(title) +
r"${0}'=0$".format(otherChar) +
r" (ph/s/mrad$^2$/0.1%bw)", transform=ax1DE.transAxes,
size=12, color='r', ha='center', va='bottom')
ax1DE.text(
0.7, 0.95, "integrated\nover " + r"$d{0}'$".format(tChar),
transform=ax1DE.transAxes, size=12, color='k', ha='center',
va='top')
ax1Dt.text(
0.25, 0.5, "integrated\nover " + r"$d$ln(energy)", rotation=-90,
transform=ax1Dt.transAxes, size=12, color='k', ha='center',
va='center')
return fig, ax2D, ax1DE, ax1Dt
if hasattr(source, 'xs'):
xs = source.xs * 1e3 # from rad to mrad
zs = source.zs * 1e3 # from rad to mrad
energies = source.energies
else:
xs = np.mgrid[source.Theta_min:source.Theta_max + 0.5*source.dTheta:
source.dTheta] * 1e3
zs = np.mgrid[source.Psi_min:source.Psi_max + 0.5*source.dPsi:
source.dPsi] * 1e3
energies = np.mgrid[source.E_min:source.E_max + 0.5*source.dE:
source.dE]
xSlice = 0
zSlice = 0
if 'xrt' in source.prefix_save_name() or\
'srw' in source.prefix_save_name():
pass
else:
data = np.concatenate((data[:, :0:-1, :], data), axis=1)
data = np.concatenate((data[:, :, :0:-1], sign*data), axis=2)
xs = np.concatenate((-xs[:0:-1], xs), axis=1)
zs = np.concatenate((-zs[:0:-1], zs), axis=1)
xSlice = (data.shape[1]-1) // 2
zSlice = (data.shape[2]-1) // 2
figX, ax2EX, ax1EX, ax1XX = one_fig(data[:, :, zSlice], xs, 'x', 'z')
figZ, ax2EZ, ax1EZ, ax1ZZ = one_fig(data[:, xSlice, :], zs, 'z', 'x')
dE = energies[1] - energies[0]
integralEvsX = np.sum(data[:, :, zSlice]/energies[:, None], axis=0)*dE
integralEvsZ = np.sum(data[:, xSlice, :]/energies[:, None], axis=0)*dE
maxIntegral = max(np.max(integralEvsX), np.max(integralEvsZ))
ax1XX.set_xlim(maxIntegral*(sign-1)*0.5, maxIntegral)
ax1ZZ.set_xlim(maxIntegral*(sign-1)*0.5, maxIntegral)
if saveName is not None:
fName = "{0}_{1}'E-" + source.prefix_save_name() + ".png"
figX.savefig(fName.format(saveName, 'x'))
figZ.savefig(fName.format(saveName, 'z'))
def visualize3D(source, data, isZplane=True, saveName=None):
# Enthought library imports
from mayavi.scripts import mayavi2
from mayavi.sources.array_source import ArraySource
# from mayavi.modules.outline import Outline
# from mayavi.modules.volume import Volume
from mayavi.modules.text3d import Text3D
from mayavi.modules.image_plane_widget import ImagePlaneWidget
from mayavi.tools.camera import view
from mayavi.tools.animator import animate
@mayavi2.standalone
def view_data(data):
"""Example showing how to view a 3D numpy array in mayavi2.
"""
def set_labelE(ind):
if hasattr(source, 'energies'):
energies = source.energies
else:
energies = np.mgrid[source.E_min:source.E_max + 0.5*source.dE:
source.dE]
return '{0:.0f} eV'.format(energies[ind])
def move_view(obj, evt):
labelE.text = set_labelE(ipwX.ipw.slice_index)
pos = labelE.position
labelE.position = ipwX.ipw.slice_index * src.spacing[0] + 1,\
pos[1], pos[2]
labelE.vector_text.update()
def set_lut(ipw):
lutM = ipw.module_manager.scalar_lut_manager
# lutM.show_scalar_bar = True
# lutM.number_of_labels = 9
lutM.lut.scale = 'log10'
lutM.lut.range = [dataMax*vmin, dataMax]
lutM.lut_mode = 'hot'
@animate()
def anim(data, ipwX):
scene.scene.off_screen_rendering = True
scene.scene.anti_aliasing_frames = 0
for i in range(0, data.shape[0], 1):
ipwX.ipw.slice_index = i
move_view(None, None)
if saveName is not None:
scene.scene.save('{0}{1:04d}.png'.format(saveName, i))
yield
# 'mayavi' is always defined on the interpreter.
scene = mayavi.new_scene() # analysis:ignore
scene.scene.background = (0, 0, 0)
print(source.prefix_save_name())
src = ArraySource(transpose_input_array=True)
sh = data.shape
# print(sh)
if 'xrt' in source.prefix_save_name() or\
'srw' in source.prefix_save_name():
src.scalar_data = data[:, :sh[1]//2+1, :sh[2]//2+1].copy()
else:
src.scalar_data = data[:, ::-1, ::-1].copy()
# src.spacing = np.array([-0.05, 1, 1])
# src.spacing = np.array([-0.25, 1, 1])
src.spacing = np.array([-0.25, 0.25, 0.25])
mayavi.add_source(src) # analysis:ignore
# Visualize the data.
# o = Outline()
# mayavi.add_module(o)
ipwY = ImagePlaneWidget()
mayavi.add_module(ipwY) # analysis:ignore
ipwY.ipw.plane_orientation = 'y_axes' # our x-axis
ipwY.ipw.slice_index = int(data.shape[1] - 1)
# if 'xrt' in source.prefix_save_name():
# ipwY.ipw.slice_index /= int(2)
ipwY.ipw.left_button_action = 0
set_lut(ipwY)
if isZplane:
ipwZ = ImagePlaneWidget()
mayavi.add_module(ipwZ) # analysis:ignore
ipwZ.ipw.plane_orientation = 'z_axes' # our z-axis
ipwZ.ipw.slice_index = int(data.shape[2] - 1)
# if 'xrt' in source.prefix_save_name():
# ipwZ.ipw.slice_index /= int(2)
ipwZ.ipw.left_button_action = 0
if 'xrt' in source.prefix_save_name() or\
'srw' in source.prefix_save_name():
pass
else:
data = np.concatenate((data[:, :0:-1, :], data), axis=1)
data = np.concatenate((data[:, :, :0:-1], data), axis=2)
sh = data.shape
print(sh)
src = ArraySource(transpose_input_array=True)
src.scalar_data = data.copy()
# src.spacing = np.array([-0.05, 1, 1])
# src.spacing = np.array([-0.25, 1, 1])
src.spacing = np.array([-0.25, 0.25, 0.25])
mayavi.add_source(src) # analysis:ignore
ipwX = ImagePlaneWidget()
mayavi.add_module(ipwX) # analysis:ignore
ipwX.ipw.plane_orientation = 'x_axes' # energy
set_lut(ipwX)
ipwX.ipw.add_observer('WindowLevelEvent', move_view)
ipwX.ipw.add_observer('StartInteractionEvent', move_view)
ipwX.ipw.add_observer('EndInteractionEvent', move_view)
labelE = Text3D()
mayavi.add_module(labelE) # analysis:ignore
labelE.position = (1, data.shape[1]*0.73*src.spacing[1],
data.shape[2]*0.85*src.spacing[2])
labelE.orientation = 90, 0, 90
labelE.text = 'Energy'
labelE.scale = 3, 3, 1
labelE.actor.property.color = 0, 1, 1
labelE.orient_to_camera = False
labelE.text = set_labelE(0)
view(45, 70, 200)
wantToAnimate = True
if wantToAnimate:
anim(data, ipwX)
else:
ipwX.ipw.slice_index = data.shape[0]-1
move_view(None, None)
data[data < 1e-7] = 1e-7
dataMax = np.max(data)
view_data(data)
def test_synchrotron_source(SourceClass, **kwargs):
tstart = time.time()
source = SourceClass(**kwargs)
# if source.prefix_save_name().startswith('srw'):
# import pickle
# pickleName = 'srw-und-non0em.pickle'
# with open(pickleName, 'rb') as f:
# I0, l1, l2, l3 = pickle.load(f)[0:4]
print('started')
I0, l1, l2, l3 = source.intensities_on_mesh()
I0 *= 1e-6 # from /sr to /mrad²
print('finished')
tstop = time.time()
print('calculations took {0:.1f} s'.format(tstop - tstart))
##for long calculations like srw:
# if source.prefix_save_name().startswith('srw'):
# import pickle
# pickleName = source.prefix_save_name()+'.pickle'
# with open(pickleName, 'wb') as f:
# pickle.dump((I0, l1, l2, l3, tstop-tstart), f, protocol=2)
##visualize in 2D:
visualize(source, I0, r'$I_0$', 'I0')
# visualize(source, I0*(1+l1)/2., r'$I_{\sigma\sigma}$', 'Is')
# visualize(source, I0*(1-l1)/2., r'$I_{\pi\pi}$', 'Ip')
# visualize(source, I0*l2/2., r'$\Re{I_{\sigma\pi}}$', 'IspRe')
# sign = -1
# if hasattr(source, 'Kx'):
# if source.Kx > 0:
# sign = 1
# visualize(source, I0*l3/2., r'$\Im{I_{\sigma\pi}}$', 'IspIm', sign=sign)
##select only one visualize3D at a time:
# visualize3D(source, I0, isZplane=False, saveName='Itot')
# visualize3D(source, I0*(1+l1)/2., isZplane=False, saveName='IsPol')
# visualize3D(source, I0*(1-l1)/2., isZplane=False, saveName='IpPol')
# visualize3D(source, I0*l2/2., saveName='IspRe')
# visualize3D(source, I0*l3/2., saveName='IspIm')
#
if __name__ == '__main__':
"""Uncomment the block you want to test."""
##*********** Bending Magnet ***************
# kwargs = dict(B0=1.7, eE=3., xPrimeMax=2.5, zPrimeMax=0.3,
# eMin=1500, eMax=31500, eN=3000, nx=1, nz=10)
###by WS:
## Source = rs.BendingMagnetWS
##by xrt:
# kwargs['distE'] = 'BW'
# Source = rs.BendingMagnet
##*********** Wiggler ***************
# kwargs = dict(period=80., K=13., n=12, eE=3., xPrimeMax=2.5,
# zPrimeMax=0.3, eMin=1500, eMax=31500, eN=3000, nx=20, nz=20)
##by WS:
# Source = rs.WigglerWS
##by xrt:
# kwargs['distE'] = 'BW'
# Source = rs.Wiggler
#*********** undulator ***************
# kwargs = dict(
# period=31.4, K=2.7, n=63, eE=6.08,
# xPrimeMax=0.3, zPrimeMax=0.3,
# eMin=500, eMax=31500, eN=1000, nx=20, nz=20)
# Kmax = 1.92
# thetaMax, psiMax = 100e-6, 50e-6
# kwargs = dict(name='IVU18.5', eE=3.0, eI=0.5,
# eEpsilonX=0.263, eEpsilonZ=0.008, betaX=9., betaZ=2.,
# period=18.5, n=108, K=Kmax,
# eMin=1500, eMax=31500, eN=1000, nx=40, nz=4,
# xPrimeMax=thetaMax*1e3, zPrimeMax=psiMax*1e3, distE='BW')
kwargs = dict(
period=31.4, K=2.7, n=63, eE=6.08, eI=0.5, xPrimeMax=0.3, zPrimeMax=0.15,
eSigmaX=134.2, eSigmaZ=6.325, eEpsilonX=1., eEpsilonZ=0.01,
eMin=1500, eMax=5000, eN=350, nx=40*4, nz=20*4)
##by Urgent:
# kwargs['icalc'] = 3 # 0 emittance
# Source = rs.UndulatorUrgent
###by SRW:
# import srw.xrtSRW as xrtSRW
# kwargs['R0'] = 50000
## 974 s - single electron
## 65501 s - zero spread
## 66180 s -nonzero spread
# kwargs['eSigmaX'] = 0
# kwargs['eSigmaZ'] = 0
# kwargs['eEpsilonX'] = 0
# kwargs['eEpsilonZ'] = 0
## kwargs['eEspread'] = 1e-3
# kwargs['harmonicStart'] = 1
# kwargs['harmonicFin'] = 4
# Source = xrtSRW.UndulatorSRW
#by xrt:
kwargs['R0'] = 50000
# kwargs['eSigmaX'] = 0
# kwargs['eSigmaZ'] = 0
# kwargs['eEpsilonX'] = 0
# kwargs['eEpsilonZ'] = 0
kwargs['eEspread'] = 1e-3*0
kwargs['distE'] = 'BW'
kwargs['xPrimeMaxAutoReduce'] = False
kwargs['zPrimeMaxAutoReduce'] = False
# kwargs['targetOpenCL'] = "CPU"
kwargs['filamentBeam'] = True
Source = rs.Undulator
##*** helical undulator **************
# kwargs = dict(
# period=31.4, Ky=2.7, Kx=2.7, n=63, eE=6.08,
# xPrimeMax=0.3, zPrimeMax=0.3,
# eMin=500, eMax=10500, eN=1000, nx=20, nz=20)
###by Urgent:
## Source = rs.UndulatorUrgent
##by xrt:
# kwargs['phaseDeg'] = 90
# kwargs['distE'] = 'BW'
# kwargs['xPrimeMaxAutoReduce'] = False
# kwargs['zPrimeMaxAutoReduce'] = False
# Source = rs.Undulator
test_synchrotron_source(Source, **kwargs)
plt.show()
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