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ShadowLibExtensions.py
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ShadowLibExtensions.py
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#
# This file contains the new classes programmed in python added to the
# main objects (Beam, OE and Source) defined in C (in ShadowLib)
#
# It also define GeometricSource and Beamline
#
import sys
import Shadow.ShadowLib as ShadowLib
import numpy
import inspect
import copy
class Beam(ShadowLib.Beam):
def __init__(self, N=None):
ShadowLib.Beam.__init__(self)
if N is not None:
self.SetRayZeros(N)
def duplicate(self):
beam_copy = Beam()
beam_copy.rays = copy.deepcopy(self.rays)
return beam_copy
def retrace(self,dist):
try:
tof = (-self.rays[:,1].flatten() + dist)/self.rays[:,4].flatten()
self.rays[:,0] += tof*self.rays[:,3].flatten()
self.rays[:,1] += tof*self.rays[:,4].flatten()
self.rays[:,2] += tof*self.rays[:,5].flatten()
except AttributeError:
print ('retrace: No rays')
def traceCompoundOE(self,compoundOE,from_oe=1,write_start_files=0,write_end_files=0,\
write_star_files=0, write_mirr_files=0):
"""
traces a compound optical element
IMPORTANT: Note that shadow3 changes the values of the OE when tracing (i.e., oe1 changes after
beam.traceOE(oe1) ). This does not happen with compoundOE: Each oe inside compoundOE is
copied before tracing.
Note also that when using write_*_files keyword, the files are written by python, not
by SHADOW (so FWRITE is not changed), with the exception of write_mirr_files. In this case
the code changes in the oe copy FWRITE=1 (mirror files only). This affects the returned
list of oe's after tracing.
:param compoundOE: input object
:param from_oe: index of the first oe (for tracing compoundOE after an existing system) (default=1)
:param write_start_files: 0=No (default), 1=Yes (all), 2: only first and last ones
:param write_end_files: 0=No (default), 1=Yes (all), 2: only first and last ones
:param write_star_files: 0=No (default), 1=Yes (all), 2: only first and last ones
:param write_mirr_files: 0=No (default), 1=Yes (all), 2: only first and last ones
:return: a new compoundOE with the list of the OE objects after tracing (the info of end.xx files)
"""
# oe_index = from_oe
# oe_n = compoundOE.number_oe()
# list = CompoundOE()
#
# for i,oe in enumerate(compoundOE.list):
# print("\nTracing compound oe %d from %d. Absolute oe number is: %d"%(i+1,oe_n,oe_index))
#
# print(">>>>>>>>> FILE_SOURCE before 0",len(oe.FILE_SOURCE))
# oe1 = oe.duplicate()
# print(">>>>>>>>> FILE_SOURCE before 1",len(oe1.FILE_SOURCE))
# iwrite = 0
# if write_mirr_files == 1: iwrite = 1
# if write_mirr_files == 2 and i == 0: iwrite = 1
# if write_mirr_files == 2 and i == oe_n-1: iwrite = 1
# if iwrite:
# oe1.FWRITE = 1
# iwrite = 0
# if write_start_files == 1: iwrite = 1
# if write_start_files == 2 and i == 0: iwrite = 1
# if write_start_files == 2 and i == oe_n-1: iwrite = 1
#
# if iwrite:
# #TODO: check possible bug: the length of FILE_SOURCE is changed when writing start file
# print(">>>>>>>> TRACE BEFORE WRITE <<<<<< type(oe1.FILE_SOURCE)",i,(oe1.FILE_SOURCE),len(oe1.FILE_SOURCE))
# #tmp = oe1.duplicate()
# oe1.write("start.%02d"%(oe_index))
# print(">>>>>>>> TRACE AFTER WRITE <<<<<< type(oe1.FILE_SOURCE)",i,(oe1.FILE_SOURCE),len(oe1.FILE_SOURCE))
#
# print("File written to disk: start.%02d"%(oe_index))
#
# print(">>>>>>>>> FILE_SOURCE before",len(oe1.FILE_SOURCE),len(oe1.FILE_REFL))
# #tmp = oe1.duplicate()
# self.traceOE(oe1,oe_index)
# print(">>>>>>>>> FILE_SOURCE after",len(oe1.FILE_SOURCE),len(oe1.FILE_REFL))
#
# list.append(oe1)
#
# iwrite = 0
# if write_star_files == 1: iwrite = 1
# if write_star_files == 2 and i == 0: iwrite = 1
# if write_star_files == 2 and i == oe_n-1: iwrite = 1
# if iwrite == 1:
# self.write("star.%02d"%(oe_index))
# print("File written to disk: star.%02d"%(oe_index))
#
# iwrite = 0
# if write_end_files == 1: iwrite = 1
# if write_end_files == 2 and i == 0: iwrite = 1
# if write_end_files == 2 and i == oe_n-1: iwrite = 1
# if write_end_files == 1:
# oe1.write("end.%02d"%(oe_index))
# print("File written to disk: end.%02d"%(oe_index))
#
# oe_index += 1
#
# return list
oe_n = len(compoundOE.list)
for i in range(oe_n):
print("\nTracing compound oe %d from %d. Absolute oe number is: %d"%(i+1,oe_n,from_oe+i))
#if wanted to write mirr.xx, tell SHADOW to do it
if write_mirr_files == 1:
compoundOE.list[i].FWRITE = 1
if write_mirr_files == 2:
if i == 0 or i == oe_n-1:
compoundOE.list[i].FWRITE = 1
#dump start.xx files, if selected
if write_start_files == 1:
compoundOE.list[i].write("start.%02d"%(from_oe+i))
if write_start_files == 2:
if i == 0 or i == oe_n-1:
compoundOE.list[i].write("start.%02d"%(from_oe+i))
self.traceOE( compoundOE.list[i], from_oe+1)
#dump star.xx files, if selected
if write_star_files == 1:
self.write("star.%02d"%(from_oe+i))
if write_star_files == 2:
if i == 0 or i == oe_n-1:
self.write("star.%02d"%(from_oe+i))
#dump end.xx files, of selected
if write_end_files == 1:
compoundOE.list[i].write("end.%02d"%(from_oe+i))
if write_end_files == 2:
if i == 0 or i == oe_n-1:
compoundOE.list[i].write("end.%02d"%(from_oe+i))
return
def get_standard_deviation(self,col, nolost=1, ref=0):
'''
returns the standard deviation of one viariable in the beam
:param col: variable (shadow column number)
:param nolost: 0 = use all rays, 1=good only, 2= lost only
:param ref: 0 = no weight, 1=weight with intensity (col23)
:return:
'''
x = self.getshonecol(col=col,nolost=nolost)
if ref == 0:
return x.std()
else:
w = self.getshonecol(23,nolost=nolost)
average = numpy.average(x, weights=w)
variance = numpy.average( (x-average)**2, weights=w)
return(numpy.sqrt(variance))
#added srio 2015
def getshonecol(self,col, nolost=0):
'''
Extract a column from a shadow file (eg. begin.dat) or a Shadow.Beam instance.
The column are numbered in the fortran convention, i.e. starting from 1.
It returns a numpy.array filled with the values of the chosen column.
Inumpy.ts:
beam : str instance with the name of the shadow file to be loaded. OR
Shadow.Beam initialized instance.
col : int for the chosen columns.
Outputs:
numpy.array 1-D with length numpy.INT.
Error:
if an error occurs an ArgsError is raised.
Possible choice for col are:
1 X spatial coordinate [user's unit]
2 Y spatial coordinate [user's unit]
3 Z spatial coordinate [user's unit]
4 Xp direction or divergence [rads]
5 Yp direction or divergence [rads]
6 Zp direction or divergence [rads]
7 X component of the electromagnetic vector (s-polariz)
8 Y component of the electromagnetic vector (s-polariz)
9 Z component of the electromagnetic vector (s-polariz)
10 Lost ray flag
11 Energy [eV]
12 Ray index
13 Optical path length
14 Phase (s-polarization)
15 Phase (p-polarization)
16 X component of the electromagnetic vector (p-polariz)
17 Y component of the electromagnetic vector (p-polariz)
18 Z component of the electromagnetic vector (p-polariz)
19 Wavelength [A]
20 R= SQRT(X^2+Y^2+Z^2)
21 angle from Y axis
22 the magnituse of the Electromagnetic vector
23 |E|^2 (total intensity)
24 total intensity for s-polarization
25 total intensity for p-polarization
26 K = 2 pi / lambda [A^-1]
27 K = 2 pi / lambda * col4 [A^-1]
28 K = 2 pi / lambda * col5 [A^-1]
29 K = 2 pi / lambda * col6 [A^-1]
30 S0-stokes = |Es|^2 + |Ep|^2
31 S1-stokes = |Es|^2 - |Ep|^2
32 S2-stokes = 2 |Es| |Ep| cos(phase_s-phase_p)
33 S3-stokes = 2 |Es| |Ep| sin(phase_s-phase_p)
'''
#A2EV = 50676.89919462
codata_h = numpy.array(6.62606957e-34)
codata_ec = numpy.array(1.602176565e-19)
codata_c = numpy.array(299792458.0)
A2EV = 2.0*numpy.pi/(codata_h*codata_c/codata_ec*1e2)
col=col-1
ray = self.rays
column = None
if col>=0 and col<18 and col!=10: column = ray[:,col]
if col==10: column = ray[:,col]/A2EV
if col==18: column = 2*numpy.pi*1.0e8/ray[:,10]
if col==19: column = numpy.sqrt(ray[:,0]*ray[:,0]+ray[:,1]*ray[:,1]+ray[:,2]*ray[:,2])
if col==20: column = numpy.arccos(ray[:,4])
if col==21: column = numpy.sqrt(numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8,15,16,17] ]),axis=0))
if col==22: column = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8,15,16,17] ]),axis=0)
if col==23: column = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8] ]),axis=0)
if col==24: column = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [15,16,17] ]),axis=0)
if col==25: column = ray[:,10]*1.0e8
if col==26: column = ray[:,3]*ray[:,10]*1.0e8
if col==27: column = ray[:,4]*ray[:,10]*1.0e8
if col==28: column = ray[:,5]*ray[:,10]*1.0e8
if col==29:
E2s = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8] ]),axis=0)
E2p = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [15,16,17] ]),axis=0)
column = E2p+E2s
if col==30:
E2s = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8] ]),axis=0)
E2p = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [15,16,17] ]),axis=0)
column = E2p-E2s
if col==31:
E2s = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8] ]),axis=0)
E2p = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [15,16,17] ]),axis=0)
Cos = numpy.cos(ray[:,13]-ray[:,14])
column = 2*E2s*E2p*Cos
if col==32:
E2s = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [6,7,8] ]),axis=0)
E2p = numpy.sum(numpy.array([ ray[:,i]*ray[:,i] for i in [15,16,17] ]),axis=0)
Sin = numpy.sin(ray[:,13]-ray[:,14])
column = 2*E2s*E2p*Sin
if nolost == 0:
return column.copy()
if nolost == 1:
f = numpy.where(ray[:,9] > 0.0)
if len(f[0])==0:
print ('getshonecol: no GOOD rays, returning empty array')
return numpy.empty(0)
return column[f].copy()
if nolost == 2:
f = numpy.where(ray[:,9] < 0.0)
if len(f[0])==0:
print ('getshonecol: no BAD rays, returning empty array')
return numpy.empty(0)
return column[f].copy()
return None
def getshcol(self,col,nolost=0):
'''
Extract multiple columns from a shadow file (eg.'begin.dat') or a Shadow.Beam instance.
The column are numbered in the fortran convention, i.e. starting from 1.
It returns a numpy.array filled with the values of the chosen column.
Inputs:
beam : str instance with the name of the shadow file to be loaded. OR
Shadow.Beam initialized instance.
col : tuple or list instance of int with the number of columns chosen.
Outputs:
numpy.array 2-D with dimension R x numpy.INT. Where R is the total number of column chosen
Error:
if an error occurs an ArgsError is raised.
Possible choice for col are:
1 X spatial coordinate [user's unit]
2 Y spatial coordinate [user's unit]
3 Z spatial coordinate [user's unit]
4 X' direction or divergence [rads]
5 Y' direction or divergence [rads]
6 Z' direction or divergence [rads]
7 X component of the electromagnetic vector (s-polariz)
8 Y component of the electromagnetic vector (s-polariz)
9 Z component of the electromagnetic vector (s-polariz)
10 Lost ray flag
11 Energy [eV]
12 Ray index
13 Optical path length
14 Phase (s-polarization)
15 Phase (p-polarization)
16 X component of the electromagnetic vector (p-polariz)
17 Y component of the electromagnetic vector (p-polariz)
18 Z component of the electromagnetic vector (p-polariz)
19 Wavelength [A]
20 R= SQRT(X^2+Y^2+Z^2)
21 angle from Y axis
22 the magnituse of the Electromagnetic vector
23 |E|^2 (total intensity)
24 total intensity for s-polarization
25 total intensity for p-polarization
26 K = 2 pi / lambda [A^-1]
27 K = 2 pi / lambda * col4 [A^-1]
28 K = 2 pi / lambda * col5 [A^-1]
29 K = 2 pi / lambda * col6 [A^-1]
30 S0-stokes = |Es|^2 + |Ep|^2
31 S1-stokes = |Es|^2 - |Ep|^2
32 S2-stokes = 2 |Es| |Ep| cos(phase_s-phase_p)
33 S3-stokes = 2 |Es| |Ep| sin(phase_s-phase_p)
'''
ret = []
if isinstance(col, int): return self.getshonecol(col,nolost=nolost)
for c in col:
ret.append(self.getshonecol(c,nolost=nolost))
return tuple(ret)
def intensity(self,nolost=0):
w = self.getshonecol(23,nolost=nolost)
return w.sum()
def nrays(self,nolost=0):
try:
w = self.getshonecol(10)
except Exception:
print("Error: Empty beam...")
return 0
if nolost == 0:
return w.size
if nolost == 1:
return numpy.array(numpy.where(w >= 0)).size
if nolost == 2:
return numpy.array(numpy.where(w < 0)).size
def histo1(self,col,xrange=None,nbins=50,nolost=0,ref=0,write=None,factor=1.0):
'''
Calculate the histogram of a column, simply counting the rays, or weighting with the intensity.
It returns a dictionary which contains the histogram data.
Inumpy.ts:
beam : str instance with the name of the shadow file to be loaded, or a Shadow.Beam initialized instance.
col : int for the chosen column.
Optional keywords:
xrange : tuple or list of length 2 describing the interval of interest for x, the data read from the chosen column.
(default: None, thus using min and max of the array)
nbins : number of bins of the histogram.
nolost :
0 All rays
1 Only good rays
2 Only lost rays
ref :
0 (or None) only count the rays
1 weight with intensity (look at col=23 |E|^2 total intensity)
other value: use that column as weight
write :
None (default) don't write any file
file_name write the histogram into the file 'file_name'.
factor : a scalar factor to multiply the selected column before histogramming
(e.g., for changing scale from cm to um then factor=1e4).
Outputs:
a python dictionary with the calculated histogram. The following keys are set:
histogram, histogram_sigma, bin_center, bin_left, xramge, intensity
xrange, nbins, ref, nolost
Error:
if an error occurs an ArgsError is raised.
Possible choice for col are:
1 X spatial coordinate [user's unit]
1 X spatial coordinate [user's unit]
2 Y spatial coordinate [user's unit]
3 Z spatial coordinate [user's unit]
4 X' direction or divergence [rads]
5 Y' direction or divergence [rads]
6 Z' direction or divergence [rads]
7 X component of the electromagnetic vector (s-polariz)
8 Y component of the electromagnetic vector (s-polariz)
9 Z component of the electromagnetic vector (s-polariz)
10 Lost ray flag
11 Energy [eV]
12 Ray index
13 Optical path length
14 Phase (s-polarization)
15 Phase (p-polarization)
16 X component of the electromagnetic vector (p-polariz)
17 Y component of the electromagnetic vector (p-polariz)
18 Z component of the electromagnetic vector (p-polariz)
19 Wavelength [A]
20 R= SQRT(X^2+Y^2+Z^2)
21 angle from Y axis
22 the magnituse of the Electromagnetic vector
23 |E|^2 (total intensity)
24 total intensity for s-polarization
25 total intensity for p-polarization
26 K = 2 pi / lambda [A^-1]
27 K = 2 pi / lambda * col4 [A^-1]
28 K = 2 pi / lambda * col5 [A^-1]
29 K = 2 pi / lambda * col6 [A^-1]
30 S0-stokes = |Es|^2 + |Ep|^2
31 S1-stokes = |Es|^2 - |Ep|^2
32 S2-stokes = 2 |Es| |Ep| cos(phase_s-phase_p)
33 S3-stokes = 2 |Es| |Ep| sin(phase_s-phase_p)
'''
#initialize return value
ticket = {'error':1}
coli = col - 1
if ref == 1: ref = 23
if ref == None: ref = 0
# copy the inputs
ticket['col'] = col
ticket['write'] = write
ticket['nolost'] = nolost
ticket['nbins'] = nbins
ticket['xrange'] = xrange
ticket['write'] = write
ticket['factor'] = factor
ticket['ref'] = ref
if ref==0:
x = self.getshonecol(nolost=nolost)
w = numpy.ones(len(x))
else:
x, w = self.getshcol((col,ref),nolost=nolost)
if factor != 1.0: x *= factor
# if nolost==0:
# t = numpy.where(a!=-3299)
#
# if nolost==1:
# t = numpy.where(a > 0.0)
#
# if nolost==2:
# t = numpy.where(a < 0.0)
#
# if nolost > 2:
# print ('invalid value for nolost flag: %d'%(nolost))
# #raise KeyError ('invalid value for nolost flag: %d'%(nolost))
# return ticket
#
#
# t = numpy.array(t)
# t.shape = -1
#
# if t.size == 0:
# print ('no rays match the selection, the histogram will not be calculated')
# return ticket
if xrange == None:
xrange = [x.min(), x.max() ]
h,bins = numpy.histogram(x,bins=nbins,range=xrange,weights=w)
#evaluate the histogram with squares of the weight for error calculations
h2,bins2 = numpy.histogram(x,bins=nbins,range=xrange,weights=(w*w))
#Evaluation of histogram error.
# See Pag 17 in Salvat, Fernandez-Varea and Sempau
# Penelope, A Code System for Monte Carlo Simulation of
# Electron and Photon Transport, AEN NEA (2003)
#
# See James, Rep. Prog. Phys., Vol 43 (1980) pp 1145-1189 (special attention to pag. 1184)
h_sigma = numpy.sqrt( h2 - h*h/float(len(w)) )
if write != None and write != "":
f = open(write,'w')
f.write('#F %s \n'%(write))
f.write('#C This file has been created using Shadow.Beam.histo1() \n')
f.write('#C COLUMN 1 CORRESPONDS TO ABSCISSAS IN THE CENTER OF EACH BIN\n')
f.write('#C COLUMN 2 CORRESPONDS TO ABSCISSAS IN THE THE LEFT CORNER OF THE BIN\n')
f.write('#C COLUMN 3 CORRESPONDS TO INTENSITY\n')
f.write('#C COLUMN 4 CORRESPONDS TO ERROR: SIGMA_INTENSITY\n')
f.write('#C col = %d\n'%(col))
f.write('#C nolost = %d\n'%(nolost))
f.write('#C nbins = %d\n'%(nbins))
f.write('#C ref = %d\n'%(ref),)
f.write(' \n')
f.write('#S 1 histogram\n')
f.write('#N 4\n')
f.write('#L X1 X2 Y YERR\n')
for i in range(len(h)):
f.write('%f\t%f\t%f\t%f\n' % ( (bins[i]+bins[i+1])*0.5, bins[i], h[i], h_sigma[i] ))
f.close()
print('histo1: file written to disk: %s'%(write))
#
# output
ticket['error'] = 0
ticket['histogram'] = h
ticket['histogram_sigma'] = h_sigma
bin_center = bins[:-1]+(bins[1]-bins[0])*0.5
ticket['bin_center'] = bin_center
ticket['bin_left'] = bins[:-1]
ticket['bin_right'] = bins[:-1]+(bins[1]-bins[0])
ticket['xrange'] = xrange
ticket['intensity'] = w.sum()
ticket['fwhm'] = None
#for practical purposes, writes the points the will define the histogram area
tmp_b = []
tmp_h = []
for s,t,v in zip(ticket["bin_left"],ticket["bin_right"],ticket["histogram"]):
tmp_b.append(s)
tmp_h.append(v)
tmp_b.append(t)
tmp_h.append(v)
ticket['histogram_path'] = numpy.array(tmp_h)
ticket['bin_path'] = numpy.array(tmp_b)
#CALCULATE fwhm
tt = numpy.where(h>=max(h)*0.5)
if h[tt].size > 1:
binSize = bins[1]-bins[0]
ticket['fwhm'] = binSize*(tt[0][-1]-tt[0][0])
ticket['fwhm_coordinates_h'] = (bin_center[tt[0][0]],bin_center[tt[0][-1]])
return ticket
def get_good_range(self,icol, nolost=0):
"""
:param icol: the column number (SHADOW convention, starting from 1)
:param nolost: lost rays flag (0=all, 1=good, 2=losses)
:return: [rmin,rmax] the selected range
"""
col = self.getshonecol(icol,nolost=nolost)
if col.size == 0:
return [-1,1]
rmin = min(col)
rmax = max(col)
if rmin>0.0:
rmin = rmin*0.95
else:
rmin = rmin*1.05
if rmax<0.0:
rmax = rmax*0.95
else:
rmax = rmax*1.05
if rmin==rmax:
rmin = rmin*0.95
rmax = rmax*1.05
if rmin==0.0:
rmin = -1.0
rmax = 1.0
return [rmin,rmax]
def plotxy(self,col_h,col_v,nbins=25,ref=23, nbins_h=None, nbins_v=None, nolost=0,xrange=None,yrange=None):
"""
performs a plotxy plot using matplotlib backend.
It uses Shadow.Beam.plotxy() for calculations
:param col_h: the horizontal column
:param col_v: the vertical column
:param nbins: number of bins
:param ref: ref=0:weight with rays, ref=1 or 23 weight with intensities, ref=col weight with col ,
:param nbins_h: number of bins in H
:param nbins_v: number of bins in V
:param nolost: 0 or None: all rays, 1=good rays, 2=only losses
:param xrange: range for H
:param yrange: range for V
:return: a dictionary as produced by Shadow.Beam.plotxy() and with some keys added
"""
ticket = {'error':1}
if ref == 1: ref = 23
if ref == None: ref = 0
if nbins_h == None: nbins_h = nbins
if nbins_v == None: nbins_v = nbins
# copy the inputs
ticket['col_h'] = col_h
ticket['col_v'] = col_v
ticket['nolost'] = nolost
ticket['nbins_h'] = nbins_h
ticket['nbins_v'] = nbins_v
ticket['ref'] = ref
(col1,col2) = self.getshcol((col_h,col_v),nolost=nolost)
if xrange==None: xrange = self.get_good_range(col_h,nolost=nolost)
if yrange==None: yrange = self.get_good_range(col_v,nolost=nolost)
if ref == 0:
weights = col1*0+1
else:
weights = self.getshonecol(ref,nolost=nolost)
(hh,xx,yy) = numpy.histogram2d(col1, col2, bins=[nbins_h,nbins_v], range=[xrange,yrange], normed=False, weights=weights)
ticket['xrange'] = xrange
ticket['yrange'] = yrange
ticket['bin_h_edges'] = xx
ticket['bin_v_edges'] = yy
ticket['bin_h_left'] = numpy.delete(xx,-1)
ticket['bin_v_left'] = numpy.delete(yy,-1)
ticket['bin_h_right'] = numpy.delete(xx,0)
ticket['bin_v_right'] = numpy.delete(yy,0)
ticket['bin_h_center'] = 0.5*(ticket['bin_h_left']+ticket['bin_h_right'])
ticket['bin_v_center'] = 0.5*(ticket['bin_v_left']+ticket['bin_v_right'])
ticket['histogram'] = hh
ticket['histogram_h'] = hh.sum(axis=1)
ticket['histogram_v'] = hh.sum(axis=0)
ticket['intensity'] = self.intensity(nolost=nolost)
ticket['nrays'] = self.nrays(nolost=0)
ticket['good_rays'] = self.nrays(nolost=1)
#CALCULATE fwhm
h = ticket['histogram_h']
tt = numpy.where(h>=max(h)*0.5)
if h[tt].size > 1:
binSize = ticket['bin_h_center'][1]-ticket['bin_h_center'][0]
ticket['fwhm_h'] = binSize*(tt[0][-1]-tt[0][0])
ticket['fwhm_coordinates_h'] = (ticket['bin_h_center'][tt[0][0]],ticket['bin_h_center'][tt[0][-1]])
else:
ticket["fwhm_h"] = None
h = ticket['histogram_v']
tt = numpy.where(h>=max(h)*0.5)
if h[tt].size > 1:
binSize = ticket['bin_v_center'][1]-ticket['bin_v_center'][0]
ticket['fwhm_v'] = binSize*(tt[0][-1]-tt[0][0])
ticket['fwhm_coordinates_v'] = (ticket['bin_v_center'][tt[0][0]],ticket['bin_v_center'][tt[0][-1]])
else:
ticket["fwhm_v"] = None
# print(">>>>Sum of H: ",ticket["histogram_h"].sum())
# print(">>>>Sum of V: ",ticket["histogram_v"].sum())
# print(">>>>Sum of I: ",ticket["histogram"].sum())
# print(">>>>Sum of W: ",weights.sum())
return ticket
# commented [email protected] 2015-03-26 Never used...
# class GeometricSource(ShadowLib.Source):
# def __init__(self):
# ShadowLib.Source.__init__(self)
#
# def setNumberRaysInit(self,nRays=5000,seed=6775431):
# self.N = nRays
# if(seed%2==0): seed += 1
# self.ISTAR1 = seed
# self.NCOL = 18 # shadow3 it will be rewritten anyway
#
# def setSpaceDistribution(self,transverse='gauss',longitude='no',param=numpy.zeros(3)):
# distTran = {'point':0 ,'rectangle':1,'ellipse':2,'gauss':3}
# distLong = {'no':1 ,'flat':2,'gauss':3}#,'synchrotron':4} synchrotron implemented in a different class
# try:
# self.FSOUR = distType[transverse]
# self.FSOURCE_DEPTH = distType[longitude]
#
# if self.FSOUR in [1,2]:
# self.WXSOU = param[0]
# self.WZSOU = param[1]
# if self.FSOUR==3:
# self.SIGMAX = param[0]
# self.SIGMAZ = param[1]
#
# if self.FSOURCE_DEPTH==2:
# self.WYSOU = param[2]
# if self.FSOURCE_DEPTH==3:
# self.SIGMAY = param[2]
#
# except KeyError:
# print ('setSpaceDistribution: wrong distribution name')
# #TODO
# # def setAngleDistribution(self,angle='gauss',)
#
# #
# # TODO: Put all classes starting with capital letter
# # in the meantime, bind as this one:
# #
# class geometricSource(GeometricSource):
# def __init__(self):
# print(' DEPRECATION WARNING: Use GeometricSource ')
# GeometricSource.__init__(self)
class OE(ShadowLib.OE):
def __init__(self):
ShadowLib.OE.__init__(self)
# here methods to initialize the OE
# renamed setScreens -> set_screens [email protected]
def set_screens(self,
n_screen=1,
i_screen=numpy.zeros(10),
i_abs=numpy.zeros(10),
sl_dis=numpy.zeros(10),
i_slit=numpy.zeros(10),
i_stop=numpy.zeros(10),
k_slit=numpy.zeros(10),
thick=numpy.zeros(10),
file_abs=numpy.array(['', '', '', '', '', '', '', '', '', '']),
rx_slit=numpy.zeros(10),
rz_slit=numpy.zeros(10),
cx_slit=numpy.zeros(10),
cz_slit=numpy.zeros(10),
file_src_ext=numpy.array(['', '', '', '', '', '', '', '', '', ''])
):
self.F_SCREEN = 1
if n_screen<=10 and n_screen>0:
self.N_SCREEN = n_screen
else:
print ('Shadow cannot handle more then 10 screens')
return
self.I_SCREEN = i_screen
self.I_ABS = i_abs
self.SL_DIS = sl_dis
self.I_SLIT = i_slit
self.I_STOP = i_stop
self.K_SLIT = k_slit
self.THICK = thick
self.FILE_ABS = file_abs
self.RX_SLIT = rx_slit
self.RZ_SLIT = rz_slit
self.CX_SLIT = cx_slit
self.CZ_SLIT = cz_slit
self.FILE_SRC_EXT = file_src_ext
return self
#SCR_NUMBER automastically set
def set_empty(self,T_INCIDENCE=0,T_REFLECTION=180.0,T_SOURCE=0.0,T_IMAGE=0.0,ALPHA=0.0):
"""
Defines an empty optical element (useful as an arm, eg. to rotate reference frames)
By default, there is no change
:param T_INCIDENCE: incidence angle (default=0)
:param T_REFLECTION: reflection angle (default=180)
:param T_SOURCE: distance from previous o.e. (default=0)
:param T_IMAGE: ddistance to next or (default=0)
:param ALPHA: mirror oriantation angle (default=0)
:return:
"""
self.F_REFRAC = 2
self.T_INCIDENCE = T_INCIDENCE
self.T_REFLECTION = T_REFLECTION
self.T_SOURCE = T_SOURCE
self.T_IMAGE = T_IMAGE
self.ALPHA = ALPHA
return self
# def setOutput(self,fwrite=0):
# self.FWRITE = fwrite
# return self
#
#
#
# def setFrameOfReference(self,source_distance=10.0,image_distance=20.0,source_angle=10.0,image_angle=10.0,alpha=0.0):
# self.T_SOURCE = source_distance
# self.T_IMAGE = image_distance
# self.T_INCIDENCE = source_angle
# self.T_REFLECTION = image_angle
# self.ALPHA = alpha
# return self
#
#
# def setSeed(self,istar=12345701):
# self.ISTAR1 = istar
# return self
#
#
# def setConvex(self):
# self.F_CONVEX = 1
# return self
#
#
# def setConcave(self):
# self.F_CONVEX = 0
# return self
#
#
# def setCylindric(self,cyl_ang=0.0):
# self.FCYL = 1
# self.CIL_ANG = cyl_ang
# return self
#
#
# def unsetCylinder(self):
# self.FCYL = 0
# return self
#
#
# def setAutoFocus(self,f_default=0,ssour=0.0,simag=0.0,theta=0.0):
# self.F_EXT = 0
# self.F_DEFAULT = f_default
# if f_default==0:
# self.SSOUR = ssour
# self.SIMAG = simag
# self.THETA = theta
# return self
#
# def unsetReflectivity(self):
# self.F_REFLEC = 0
# return self
#
# def setReflectivityFull(self,f_refl=0,file_refl='GAAS.SHA',rparams=numpy.zeros(2,dtype=numpy.float64),f_thick=0):
# self.F_REFLEC = 1
# self.F_REFL = f_refl
# self.FILE_REFL = file_refl
# self.ALFA = rparams[0]
# self.GAMMA = rparams[1]
# self.F_THICK = f_thick
# return self
#
# def setReflectivityScalar(self,f_refl=0,file_refl='GAAS.SHA',rparams=numpy.zeros(2,dtype=numpy.float64),f_thick=0):
# self.F_REFLEC = 2
# self.F_REFL = f_refl
# self.FILE_REFL = file_refl
# self.F_THICK = f_thick
# return self
#
# def setMultilayer(self,f_reflec=1,file_refl='GAAS.SHA',f_thick=0):
# self.F_REFLEC = f_reflec
# self.F_REFL = 2
# self.FILE_REFL = file_refl
# self.F_THICK = f_thick
# return self
#
#
# def setSpheric(self,rmirr=20.0):
# self.FMIRR = 1
# self.F_EXT = 1
# self.RMIRR = rmirr
# return self
#
# def setSphericAuto(self,fparams=None):#):f_default=0,ssour=0.0,simag=0.0,theta=0.0):
# self.FMIRR = 1
# if fparams == None:
# self.setAutoFocus(1)
# else:
# self.setAutoFocus(0,ssour=fparams[0],simag=fparams[1],theta=fparams[2])
# return self
#
#
# def setEllipsoid(self,ell_the=0.0,axmaj=0.0,axmin=0.0):
# self.FMIRR = 2
# self.F_EXT = 1
# self.ELL_THE = ell_the
# self.AXMAJ = axmaj
# self.AXMIN = axmin
# return self
#
# def setEllipsoidAuto(self,fparams=None):#ell_the=0.0,axmaj=0.0,axmin=0.0,f_default=0,ssour=0.0,simag=0.0,theta=0.0):
# self.FMIRR = 2
# if fparams==None:
# self.setAutoFocus(1)
# else:
# self.setAutoFocus(0,ssour=fparams[0],simag=fparams[1],theta=fparams[2])
# return self
#
#
# def setToroid(self,f_torus=0,r_maj=0.0,r_min=0.0):
# self.FMIRR = 3
# self.F_EXT = 1
# self.F_TORUS = f_torus
# self.R_MAJ = r_maj
# self.R_MIN = r_min
# return self
#
# def setToroidAuto(self,f_torus=0,r_maj=0.0,r_min=0.0,f_default=0,ssour=0.0,simag=0.0,theta=0.0):
# self.FMIRR = 3
# self.F_TORUS = f_torus
# self.R_MAJ = r_maj
# self.R_MIN = r_min
# self.setAutoFocus(f_default,ssour,simag,theta)
# return self
#
#
# def setParaboloid(self,f_side=1,param=0.0):
# self.FMIRR = 4
# self.F_EXT = 1
# self.F_SIDE = f_side
# self.PARAM = param
# return self
#
# def setParaboloidAuto(self,f_side=1,fparams=None):#f_side=1,param=0.0,f_default=0,ssour=0.0,simag=0.0,theta=0.0,f_side=0):
# self.FMIRR = 4
# self.F_SIDE = f_side
# if fparams==None:
# self.setAutoFocus(1)
# else:
# self.setAutoFocus(0,ssour=fparam[0],simag=fparam[1],theta=fparams[2])
# return self
#
#
# def setPlane(self):
# self.FMIRR = 5
# self.F_EXT = 1
# return self
#
#
# def setCodlingSlit(self,cod_len=0.0,cod_wid=0.0): # HERE ASK MANOLO, always 1 or 0
# self.FMIRR = 6
# self.F_EXT = 1
# self.COD_LEN = 0.0
# self.COD_WID = 0.0
# return self
#
#
# def setHyperboloid(self,ell_the=0.0,axmaj=0.0,axmin=0.0):
# self.FMIRR = 7
# self.F_EXT = 1
# self.ELL_THE = ell_the
# self.AXMAJ = axmaj
# self.AXMIN = axmin
# return self
#
# def setHyperboloidAuto(self,fparams=None):#ell_the=0.0,axmaj=0.0,axmin=0.0,f_default=0,ssour=0.0,simag=0.0,theta=0.0):
# self.FMIRR = 2
# if fparams==None:
# self.setAutoFocus(1)
# else:
# self.setAutoFocus(0,ssour=fparams[0],simag=fparams[1],theta=fparams[2])
# return self
#
#
# def setCone(self,cone_a=0.0):
# self.FMIRR = 8
# self.F_EXT = 1
# self.CONE_A = cone_a
# return self
#
#
# def setPoly(self,file_mir=''):
# self.FMIRR = 9
# self.F_EXT = 1
# self.FILE_MIR = file_mir
# return self
#
#
# def setCCC(self,ccc=numpy.array([1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],dtype=numpy.float64)):
# self.FMIRR = 10
# self.F_EXT = 1
# self.CCC[:] = ccc[:]
# return self
#
#
# def setRipple(self,f_g_s=0,xyAmpWavPha=numpy.array([0.0,0.0,0.0,0.0,0.0,0.0],dtype=numpy.float64),file_rip=''):
# self.F_RIPPLE = 1
# self.F_G_S = f_g_s
# self.X_RIP_AMP = xyAmpWavPha[0]
# self.X_RIP_WAV = xyAmpWavPha[1]
# self.X_PHASE = xyAmpWavPha[2]
# self.Y_RIP_AMP = xyAmpWavPha[3]
# self.Y_RIP_WAV = xyAmpWavPha[4]
# self.Y_PHASE = xyAmpWavPha[5]
# self.FILE_RIP = file_rip
# return self
#
#