Commit 0fedb516 authored by Daniel Toyra's avatar Daniel Toyra
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Merge branch 'master' of gitlab.aei.uni-hannover.de:finesse/pykat

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Pipeline #1181 passed with stage
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import pykat.exceptions as pkex
import numpy as np
import math
......@@ -7,59 +12,6 @@ import cmath
from scipy.special import hermite
from pykat.SIfloat import SIfloat
def fit_beam_size(z_data, w_data, w0guess, z0guess, lam=1064e-9, show_plot=True,
plotpts=100, title='Beam scan fit', w2zero=True, filename=None):
"""
Function to fit a beam size (w0 and z) to a 2D intensity array. Plotting can
be switched on or off.
Returns best fit of (w0, z)
Contributed by Paul Fulda on 15/01/16
"""
import scipy.optimize
def zw0z02w(z, w0, z0, lam):
z_R = pl.pi*w0**2/lam
w = w0*pl.sqrt(1+((z-z0)/z_R)**2)
return w
popt,pcov = scipy.optimize.curve_fit(lambda z_data, w0, z0: zw0z02w(z_data, w0, z0, lam), z_data, w_data, p0=[w0guess,z0guess])
w0out=popt[0]
z0out=popt[1]
z_fit = pl.linspace(min(z_data),max(z_data),plotpts)
w_fit = zw0z02w(z_fit, w0out, z0out, lam)
if show_plot or filename is not None:
import pylab as pl
um=1e6
pl.figure()
pl.plot(z_data,w_data*um,'bo', label = 'Data')
pl.plot(z_fit,w_fit*um,'b', label = 'Fit')
pl.tight_layout
pl.grid()
pl.xlabel('Position [m]')
pl.ylabel('Beam size [$\mu$m]')
pl.xlim((min(z_data),max(z_data)))
if w2zero:
pl.ylim((0,max(w_data)*um))
pl.legend(loc=0)
pl.title(title)
if filename is not None:
pl.savefig(filename)
return w0out, z0out
class gauss_param(object):
"""
Use beam_param instead, will be the future name of this object.
......@@ -317,8 +269,14 @@ class gauss_param(object):
class beam_param(gauss_param):
pass
# Should be renamed to HG_mode?
class HG_beam(object):
""" Hermite-Gauss beam profile. Example usage:
import pykat.optics.gaussian_beams as gb
qx=gb.beam_param(w0=1e-3,z=0)
beam=gb.HG_beam(qx,n=2,m=0)
beam.plot()
"""
def __init__(self, qx, qy=None, n=0, m=0):
self._qx = copy.deepcopy(qx)
self._2pi_qrt = math.pow(2.0/math.pi, 0.25)
......@@ -427,7 +385,9 @@ class HG_beam(object):
return np.outer(_un, _um)
def plot(self, ndx=100, ndy=100, xscale=4, yscale=4):
import pylab
""" Make a simple plot the HG_beam """
import pykat.plotting
import matplotlib.pyplot as plt
xrange = xscale * np.linspace(-self._qx.w, self._qx.w, ndx)
yrange = yscale * np.linspace(-self._qy.w, self._qy.w, ndy)
......@@ -437,11 +397,11 @@ class HG_beam(object):
data = self.Unm(xrange,yrange)
fig = pylab.figure()
axes = pylab.imshow(np.abs(data), aspect=dx/dy, extent=[min(xrange),max(xrange),min(yrange),max(yrange)])
pylab.xlabel('x [m]')
pylab.ylabel('y [m]')
fig = pykat.plotting.figure()
axes = plt.imshow(np.abs(data.T), aspect=dx/dy, extent=[min(xrange),max(xrange),min(yrange),max(yrange)])
plt.xlabel('x [m]')
plt.ylabel('y [m]')
cbar = fig.colorbar(axes)
pylab.show()
plt.show()
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import pykat.exceptions as pkex
import numpy as np
import math
import copy
import warnings
import cmath
from math import factorial
from scipy.integrate import quad
from scipy.special import hermite
from pykat.SIfloat import SIfloat
def finesse_split_photodiode(maxtem, xy='x'):
"""Prints beat coefficients for HG modes on a split photo detector
in the format for insertion into the kat.ini file of Finesse.
Example use:
finesse_split_photodiode(5, xy='x')
The default kat.ini numbers have been generated with:
finesse_split_photodiode(40, xy='x')
finesse_split_photodiode(40, xy='y')
"""
assert (xy=="x" or xy=="y"), "xy function parameter must be 'x' or 'y'"
assert (isinstance(maxtem, int) and maxtem >=0), "maxtem must be integer >=0"
if (xy=="x"):
print('PDTYPE x-split')
else:
print('PDTYPE y-split')
# running through even modes
for n1 in np.arange(0,maxtem+1,2):
# running through odd modes
for n2 in np.arange(1,maxtem+1,2) :
c_n1n2= HG_split_diode_coefficient_numerical(n1,n2)
if (xy=="x"):
print("{:2d} x {:2d} x {:.15g}".format(n1,n2,c_n1n2))
else:
print("x {:2d} x {:2d} {:.15g}".format(n1,n2,c_n1n2))
print('END')
def HG_split_diode_coefficient_analytical(n1,n2):
""" Using an analytical equation to compute beat coefficients
betwween mode n1 and n2 on a split photo detector. Uses arbitrary
precision (from gmpy) because otherwise errors get very large
for n1,n2>30. This is for comparison with the numerical method
HG_split_diode_coefficient_numerical only. """
import gmpy
temp=gmpy.mpq(0.0)
for l in np.arange(0,n1/2+1):
for k in np.arange(0,(n2-1)/2+1):
temp += gmpy.mpq(pow((-1.0/4.0),l+k)*gmpy.mpz(factorial((n2+n1-1)/2-l-k))/gmpy.mpz((factorial(l)*factorial(k)*factorial(n1-2*l)*factorial(n2-2*k))))
c_n1n2=gmpy.mpq(temp*gmpy.mpq(math.sqrt(2.0**(n1+n2)*gmpy.mpz(factorial(n1)*factorial(n2))/np.pi)))
return float(gmpy.mpf(c_n1n2))
def HG_split_diode_coefficient_numerical(n1,n2):
""" Compute beam coefficient between mode n1 and n2 on a split
photo detector using numerical integration, tested up to n1,n2 = 40.
This is primarily used by finesse_split_photodiode()"""
A = 2.0 * np.sqrt(2.0/np.pi) * np.sqrt(1.0 / (2.0**(n1+n2) * factorial(n1) * factorial(n2)))
f = lambda x: hermite(n1)(np.sqrt(2.0)*x) * math.exp(-2.0*x*x) * hermite(n2)(np.sqrt(2.0)*x)
c_n1n2= quad(f, 0.0, np.Inf, epsabs=1e-10, epsrel=1e-10, limit=200)
return A*c_n1n2[0]
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