def test_parseXML(): # Improve this test!
from MJOLNIR.Geometry import Wedge, Analyser, Detector, Instrument
import os
tempFileName = '__temp__'
Instr = Instrument.Instrument()
Instr.settings['Author'] = 'Jakob Lass'
wedge = Wedge.Wedge(position=(0.5, 0, 0))
Det = Detector.TubeDetector1D(position=(1.0, 1, 0), direction=(1, 0, 0))
Ana = Analyser.FlatAnalyser(position=(0.5, 0, 0), direction=(1, 0, 1))
wedge.append([Det, Ana])
Instr.append([wedge, wedge])
Instr.append(wedge)
f = open(tempFileName, 'w')
f.write(createXMLString(Instr))
f.close()
InstrLoaded = parseXML(tempFileName)
os.remove(tempFileName)
assert (Instr == InstrLoaded)
def test_CalcualteA4Ef():
Instr = Instrument.Instrument()
Det = Detector.TubeDetector1D(position=(1, 0, 1),
direction=(1, 0, 0),
pixels=10,
split=[2, 5, 8],
length=1.0)
Det2 = Detector.TubeDetector1D(position=(1, 0.1, 1),
direction=(1, 0, 0),
pixels=10,
split=[2, 5, 8],
length=1.0)
Ana = Analyser.FlatAnalyser(position=(0.5, 0, 0), direction=(1, 0, 1))
Ana2 = Analyser.FlatAnalyser(position=(1, 0, 0), direction=(1, 0, 1))
wedge = Wedge.Wedge(position=(0, 0, 0),
detectors=[Det, Det2],
analysers=[Ana, Ana2])
Instr.append(wedge)
Instr.initialize()
print(Instr.A4)
print(Instr.Ef)
def test_Build_a_simple_instrument(saveFig=False):
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
Instr = Instrument.Instrument()
Det = Detector.TubeDetector1D(position=(1, 0, 1), direction=(1, 0, 0))
Ana = Analyser.FlatAnalyser(position=(1, 0, 0), direction=(1, 0, 1))
wedge = Wedge.Wedge(position=(0, 0, 0), detectors=Det, analysers=Ana)
Instr.append(wedge)
fig = plt.figure()
ax = fig.gca(projection='3d')
Instr.plot(ax)
ax.set_xlim(-0.1, 1.1)
ax.set_ylim(-0.1, 1.1)
ax.set_zlim(-0.1, 1.1)
if saveFig:
plt.savefig('../docs/_templates/Build_a_simple_instrument.png',
format='png',
dpi=300)
plt.show()
def Tester():
from MJOLNIR.Geometry import Instrument,Detector,Analyser,Wedge
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
Instr = Instrument.Instrument()
Det = Detector.TubeDetector1D(position=(1,0,1),direction=(1,0,0))
Ana = Analyser.FlatAnalyser(position=(1,0,0),direction=(1,0,1))
wedge = Wedge.Wedge(position=(0,0,0),detectors=Det,analysers=Ana)
Instr.append(wedge)
fig = plt.figure()
ax = fig.gca(projection='3d')
Instr.plot(ax)
ax.set_xlim(-0.1,1.1)
ax.set_ylim(-0.1,1.1)
ax.set_zlim(-0.1,1.1)
fig.savefig('/home/lass/Dropbox/PhD/Software/MJOLNIR/docs/Tutorials/Instrument/SimpleInstrument.png',format='png')
def Tester():
from MJOLNIR.Geometry import Instrument, Detector, Analyser, Wedge
# Create instrument
Instr = Instrument.Instrument()
# Create two detectors and their corresponding analysers
Det = Detector.TubeDetector1D(position=(1, 0, 1),
direction=(1, 0, 0),
pixels=10,
split=[2, 5, 8],
length=1.0)
Det2 = Detector.TubeDetector1D(position=(1, 0.1, 1),
direction=(1, 0, 0),
pixels=10,
split=[2, 5, 8],
length=1.0)
Ana = Analyser.FlatAnalyser(position=(0.5, 0, 0), direction=(1, 0, 1))
Ana2 = Analyser.FlatAnalyser(position=(1, 0, 0), direction=(1, 0, 1))
# Collect everything in the wedge object
wedge = Wedge.Wedge(position=(0, 0, 0),
detectors=[Det, Det2],
analysers=[Ana, Ana2])
Instr.append(wedge)
Instr.initialize()
print(Instr.A4)
print(Instr.Ef)
def test_Load_XML(save=False):
import matplotlib.pyplot as plt
import numpy as np
Instr = Instrument.Instrument(
fileName='Tutorials/SimpleInstrument.xml') # Load XML file
fig = plt.figure() # Create 3D figure
ax = fig.gca(projection='3d')
Instr.plot(ax) # Plot instrument
ax.set_ylim(0.0, 1.5)
ax.set_xlim(-0.2, 0.2)
ax.set_zlim(0.0, 1.1)
ax.set_xlabel('x [m]')
ax.set_ylabel('y [m]')
ax.set_zlabel('z [m]')
plt.tight_layout()
if save:
plt.savefig('SimpleInstrument.png', format='png', dpi=300)
Instr.initialize() # Initialize instrument
plt.figure()
for det in range(len(Instr.wedges[0].detectors)):
start, stop = Instr.wedges[0].detectors[det]._split[[0, -1]]
plt.scatter(
np.arange(start,
stop), #range(Instr.wedges[0].detectors[det].pixels),
Instr.A4[0][det] * 180.0 / np.pi,
zorder=10,
s=3)
plt.grid(True)
plt.xlabel('Pixel')
plt.ylabel('A4 [deg]')
if save:
plt.savefig('SimpleInstrument_A4.png', format='png', dpi=300)
plt.figure()
for det in range(len(Instr.wedges[0].detectors)):
start, stop = Instr.wedges[0].detectors[det]._split[[0, -1]]
plt.scatter(
np.arange(start, stop), #Instr.wedges[0].detectors[det].pixels),
Instr.Ef[0][det],
zorder=10,
s=3)
plt.grid(True)
plt.xlabel('Pixel')
plt.ylabel('Ef [meV]')
plt.tight_layout()
if save:
plt.savefig('SimpleInstrument_Ef.png', format='png', dpi=300)
plt.show()
def Generate_normalization(plot=False):
Instr = Instrument.Instrument(
fileName='/home/lass/Dropbox/PhD/Software/MJOLNIR/Data/CAMEA_Updated.xml'
) #'TestData/1024/CAMEA_Full.xml')
Instr.initialize()
VanNormFile = '/home/lass/Dropbox/PhD/CAMEAData/camea2018n000119.hdf' #'/home/lass/Dropbox/PhD/CAMEAData/camea2018n000084.hdf'#'/TestData/1024/camea2018n000038.hdf'#'TestData/1024/EScanRunDoubleFocusHS.h5'
Instr.generateCalibration(
Vanadiumdatafile=VanNormFile,
savelocation='/home/lass/Dropbox/PhD/CAMEAData/NormalizationUpdated/',
plot=plot,
tables=[1, 3, 8])
def Tester():
from MJOLNIR.Geometry import Instrument
import matplotlib.pyplot as plt
import numpy as np
Instr = Instrument.Instrument(fileName='/home/lass/Dropbox/PhD/Software/MJOLNIR/Tutorials/SimpleInstrument.xml') # Load XML file
fig = plt.figure() # Create 3D figure
ax = fig.gca(projection='3d')
Instr.plot(ax) # Plot instrument
ax.set_ylim(0.0,1.5)
ax.set_xlim(-0.2,0.2)
ax.set_zlim(0.0,1.1)
ax.set_xlabel('x [m]')
ax.set_ylabel('y [m]')
ax.set_zlabel('z [m]')
plt.tight_layout()
plt.savefig('/home/lass/Dropbox/PhD/Software/MJOLNIR/docs/Tutorials/Instrument/SimpleInstrument2.png',format='png',dpi=300)
Instr.initialize() # Initialize instrument
plt.figure()
for det in range(len(Instr.wedges[0].detectors)):
start,stop = Instr.wedges[0].detectors[det]._split[[0,-1]]
plt.scatter(np.arange(start,stop),#range(Instr.wedges[0].detectors[det].pixels),
Instr.A4[0][det]*180.0/np.pi,zorder=10,s=3)
plt.grid(True)
plt.xlabel('Pixel')
plt.ylabel('A4 [deg]')
plt.savefig('/home/lass/Dropbox/PhD/Software/MJOLNIR/docs/Tutorials/Instrument/SimpleInstrument2_A4.png',format='png',dpi=300)
plt.figure()
for det in range(len(Instr.wedges[0].detectors)):
start,stop = Instr.wedges[0].detectors[det]._split[[0,-1]]
plt.scatter(np.arange(start,stop),
Instr.Ef[0][det],zorder=10,s=3)
plt.grid(True)
plt.xlabel('Pixel')
plt.ylabel('Ef [meV]')
plt.tight_layout()
plt.savefig('/home/lass/Dropbox/PhD/Software/MJOLNIR/docs/Tutorials/Instrument/SimpleInstrument2_Ef.png',format='png',dpi=300)
def parseXML(filename):
from MJOLNIR.Geometry import Detector, Analyser, Wedge, Instrument
import xml.etree.ElementTree as ET
import numpy as np
tree = ET.parse(filename)
instr_root = tree.getroot()
instrSettings = {}
for attrib in instr_root.keys():
instrSettings[attrib] = instr_root.attrib[attrib]
Instr = Instrument.Instrument(**instrSettings)
for wedge in list(instr_root): #.getchildren():
if wedge.tag in dir(Wedge):
Wedgeclass_ = getattr(Wedge, wedge.tag)
else:
raise ValueError(
"Element is supposed to be a Wedge, but got '{}'.".format(
wedge.tag))
wedgeSettings = {}
for attrib in wedge.keys():
if attrib == 'concept':
wedgeSettings[attrib] = np.array(
wedge.attrib[attrib].strip().split(','), dtype=str)
else:
wedgeSettings[attrib] = np.array(
wedge.attrib[attrib].strip().split(','), dtype=float)
temp_wedge = Wedgeclass_(**wedgeSettings)
#print(temp_wedge)
for item in list(wedge): #.getchildren():
if item.tag in dir(Detector):
class_ = getattr(Detector, item.tag)
elif item.tag in dir(Analyser):
class_ = getattr(Analyser, item.tag)
else:
raise ValueError(
"Item '{}' not recognized as MJOLNIR detector or analyser."
.format(item.tag))
itemSettings = {}
for attrib in item.keys():
attribVal = item.get(attrib).strip().split(',')
if len(attribVal) == 1:
itemSettings[attrib] = float(attribVal[0])
else:
if (attrib == 'split'):
#print(type(attribVal))
itemSettings[attrib] = attribVal
else:
itemSettings[attrib] = np.array(attribVal, dtype=float)
try:
temp_item = class_(**itemSettings)
except TypeError as e:
print(e.args[0])
raise ValueError('Item {} misses argument(s):{}'.format(
class_, e.args[0].split(':')[1]))
except ValueError:
raise ValueError(
'Item {} not initialized due to error.'.format(class_))
#print(temp_item)
temp_wedge.append(temp_item)
#print()
#print(str(temp_wedge))
Instr.append(temp_wedge)
return Instr
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 26 16:49:34 2018
@author: lass
"""
from MJOLNIR.Geometry import Detector, Analyser, Wedge, Instrument
from MJOLNIR.Data import DataSet
import numpy as np
import h5py as hdf
import matplotlib.pylab as plt
Instr = Instrument.Instrument(
filename='/home/lass/Dropbox/PhD/Software/CAMEA_Full.xml')
Instr.initialize()
NF = '/home/lass/Dropbox/PhD/Software/CAMEA_Test_Files/cameasim2018n000004.h5' #'/home/lass/Documents/PhD/McStas/HDFFullEi/RITA_FULL_AUTO_20171023_103342.hdf'
dataset = DataSet.DataSet(instrument=Instr, normalizationfiles=NF)
dataset.EnergyCalibration(
NF,
'Normalization/',
plot=True,
tables=['Single', 'PrismaticLowDefinition', 'PrismaticHighDefinition'])