def test_opd_from_zernikes():
coeffs = [0,0.1, 0.4, 2, -0.3]
opd = zernike.opd_from_zernikes(coeffs, npix=256)
outcoeffs = zernike.opd_expand(opd, nterms=len(coeffs))
# only compare on indices 1-3 to avoid divide by zero on piston
diffs = np.abs(np.asarray(coeffs[1:5]) - np.asarray(outcoeffs[1:5]))/np.asarray(coeffs[1:5])
max_diff = np.max(diffs )
assert max_diff < 2e-3, "recovered coefficients from opd_expand differ more than expected"
def test_opd_from_zernikes():
coeffs = [0,0.1, 0.4, 2, -0.3]
opd = zernike.opd_from_zernikes(coeffs, npix=256)
outcoeffs = zernike.opd_expand(opd, nterms=len(coeffs))
# only compare on indices 1-3 to avoid divide by zero on piston
diffs = np.abs(np.asarray(coeffs[1:5]) - np.asarray(outcoeffs[1:5]))/np.asarray(coeffs[1:5])
max_diff = np.max(diffs )
assert max_diff < 2e-3, "recovered coefficients from opd_expand differ more than expected"
def test_opd_from_zernikes():
coeffs = [0, 0.1, 0.4, 2, -0.3]
opd = zernike.opd_from_zernikes(coeffs, npix=256)
outcoeffs = zernike.opd_expand(opd, nterms=len(coeffs))
diffs = np.abs(np.asarray(coeffs) -
np.asarray(outcoeffs)) / np.asarray(coeffs)
diffs[0] = 0 # ignore divide by zero on piston
max_diff = np.max(diffs)
assert max_diff < 2e-3, "recovered coefficients from opd_expand differ more than expected"
def test_opd_from_zernikes():
coeffs = [0,0.1, 0.4, 2, -0.3]
opd = zernike.opd_from_zernikes(coeffs, npix=256)
outcoeffs = zernike.opd_expand(opd, nterms=len(coeffs))
diffs = np.abs(np.asarray(coeffs) - np.asarray(outcoeffs))/np.asarray(coeffs)
diffs[0] = 0 # ignore divide by zero on piston
max_diff = np.max(diffs )
assert max_diff < 2e-3, "recovered coefficients from opd_expand differ more than expected"
def fitZernicke(wfr, mode='integrated', nterms=1250):
nx, ny, nz = wfr.params.Mesh.nx, wfr.params.Mesh.ny, wfr.params.Mesh.nSlices
aperture = create_circular_mask(nx, ny, r=nx // 2 - 2)
if mode == 'integrated':
ph = wfr.data.arrEhor[:, :, :, 1].sum(axis=2)
#ii = wfr.get_intensity()[:,:,0]
zc = zernike.opd_expand(ph, aperture=aperture, nterms=nterms)
#rc = zernike.opd_from_zernikes(zc)
return zc
def test_opd_expand(npix=512, input_coefficients=(0.1, 0.2, 0.3, 0.4, 0.5)):
basis = zernike.zernike_basis(nterms=len(input_coefficients), npix=npix)
for idx, coeff in enumerate(input_coefficients):
basis[idx] *= coeff
opd = basis.sum(axis=0)
recovered_coeffs = zernike.opd_expand(opd, nterms=len(input_coefficients))
max_diff = np.max(np.abs(np.asarray(input_coefficients) - np.asarray(recovered_coeffs)))
assert max_diff < 1e-3, "recovered coefficients from wf_expand more than 0.1% off"
# Test the nonorthonormal version too
# At a minimum, fitting with this variant version shouldn't be
# worse than the regular one on a clear circular aperture.
# We do the test in this same function for efficiency
recovered_coeffs_v2 = zernike.opd_expand_nonorthonormal(opd, nterms=len(input_coefficients))
max_diff_v2 = np.max(np.abs(np.asarray(input_coefficients) - np.asarray(recovered_coeffs_v2)))
assert max_diff_v2 < 1e-3, "recovered coefficients from wf_expand more than 0.1% off"
def test_opd_expand(npix=512, input_coefficients=(0.1, 0.2, 0.3, 0.4, 0.5)):
basis = zernike.zernike_basis(nterms=len(input_coefficients), npix=npix)
for idx, coeff in enumerate(input_coefficients):
basis[idx] *= coeff
opd = basis.sum(axis=0)
recovered_coeffs = zernike.opd_expand(opd, nterms=len(input_coefficients))
max_diff = np.max(np.abs(np.asarray(input_coefficients) - np.asarray(recovered_coeffs)))
assert max_diff < 1e-3, "recovered coefficients from wf_expand more than 0.1% off"
# Test the nonorthonormal version too
# At a minimum, fitting with this variant version shouldn't be
# worse than the regular one on a clear circular aperture.
# We do the test in this same function for efficiency
recovered_coeffs_v2 = zernike.opd_expand_nonorthonormal(opd, nterms=len(input_coefficients))
max_diff_v2 = np.max(np.abs(np.asarray(input_coefficients) - np.asarray(recovered_coeffs_v2)))
assert max_diff_v2 < 1e-3, "recovered coefficients from wf_expand more than 0.1% off"
from matplotlib import pyplot as plt
from poppy import zernike
from model.src.coherent import construct_SA1_wavefront
import numpy as np
from wpg.wpg_uti_wf import calculate_fwhm
wfr = construct_SA1_wavefront(1000, 1000, 12, 0.1)
ii = wfr.get_intensity()[:,:,0]
ph = wfr.get_phase()[:,:,0]
aperture = np.ones(ii.shape)
aperture[np.where(ii < ii.max()/10)] = 0
zc = zernike.opd_expand(ph, aperture = aperture)
opd = zernike.opd_from_zernikes(zc)
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.bar(np.linspace(0,len(zc), len(zc)),zc)
ax1.set_xticks(np.linspace(0+1,len(zc)+1, len(zc)+1))
ax1.set_xticklabels(labels = ["$Z_{}$".format(int(z)) for z in np.linspace(0+1,len(zc)+1, len(zc)+1)])
plt.show()
for i in range(15):
if i == 0:
pass
else:
