def test_saveloadScrn(self):
# test the saving and loading phase screens
config = confParse.Configurator(os.path.join(CONFIG_PATH,"sh_8x8.py"))
config.loadSimParams()
config.atmos.wholeScrnSize = 512
atmos = atmosphere.atmos(config)
# Make a directory to save the screens in
if os.path.exists('testscrns'):
shutil.rmtree('testscrns')
os.makedirs('testscrns')
atmos.saveScrns('testscrns')
try:
# change config to load scrns
config.atmos.scrnNames = []
for i in range(config.atmos.scrnNo):
config.atmos.scrnNames.append('testscrns/scrn{}.fits'.format(i))
atmos2 = atmosphere.atmos(config)
# Check that all scrns are identical
for i in range(config.atmos.scrnNo):
assert numpy.allclose(atmos.wholeScrns[i], atmos2.wholeScrns[i])
# delete that dir
shutil.rmtree('testscrns')
except:
# always delete that dir - even in case of failure
shutil.rmtree('testscrns')
raise
def test_saveloadScrn(self):
# test the saving and loading phase screens
config = confParse.loadSoapyConfig(os.path.join(CONFIG_PATH,"sh_8x8.yaml"))
config.atmos.wholeScrnSize = 512
config.atmos.infinite = False
atmos = atmosphere.atmos(config)
# Make a directory to save the screens in
if os.path.exists('testscrns'):
shutil.rmtree('testscrns')
os.makedirs('testscrns')
atmos.saveScrns('testscrns')
try:
# change config to load scrns
config.atmos.scrnNames = []
for i in range(config.atmos.scrnNo):
config.atmos.scrnNames.append('testscrns/scrn{}.fits'.format(i))
atmos2 = atmosphere.atmos(config)
# Check that all scrns are identical
for i in range(config.atmos.scrnNo):
assert numpy.allclose(atmos.wholeScrns[i], atmos2.wholeScrns[i])
# delete that dir
shutil.rmtree('testscrns')
except:
# always delete that dir - even in case of failure
shutil.rmtree('testscrns')
raise
def run_scrns(self):
slopes = numpy.zeros((N_SCRNS * self.nIters, 2, self.wfs.activeSubaps))
for iscrn in range(N_SCRNS):
atmos = atmosphere.atmos(self.config)
print('Made screen - starting run')
for i in range(self.nIters):
fullSlopes = self.wfs.frame(atmos.moveScrns())
slopes[iscrn*self.nIters + i, 0] = fullSlopes[:self.wfs.activeSubaps]
slopes[iscrn*self.nIters + i, 1] = fullSlopes[self.wfs.activeSubaps:]
return slopes
def run_scrns(self):
slopes = numpy.zeros((N_SCRNS * self.nIters, 2, self.wfs.activeSubaps))
for iscrn in range(N_SCRNS):
atmos = atmosphere.atmos(self.config)
print('Made screen - starting run')
for i in range(self.nIters):
fullSlopes = self.wfs.frame(atmos.moveScrns())
slopes[iscrn * self.nIters + i,
0] = fullSlopes[:self.wfs.activeSubaps]
slopes[iscrn * self.nIters + i,
1] = fullSlopes[self.wfs.activeSubaps:]
return slopes
def test_randomAtmos(self):
config = confParse.Configurator(os.path.join(CONFIG_PATH,"sh_8x8.py"))
config.loadSimParams()
atmos = atmosphere.atmos(config)
atmos.randomScrns()
import numpy as np
import matplotlib.pyplot as pl
from soapy import confParse, SCI, atmosphere
# load a sim config that defines lots of science cameras across the field
config = confParse.loadSoapyConfig('sh_8x8.py')
# Init a science camera
sci_camera = SCI.PSF(config, mask=np.ones((154,154)))
# init some atmosphere
atmos = atmosphere.atmos(config)
# Now loop over lots of difference turbulence
for i in range(100):
print(i)
# Get phase for this time step
phase_scrns = atmos.moveScrns()
# Calculate all the PSF for this turbulence
psf = sci_camera.frame(phase_scrns)
# You can also get the phase if you’d like from each science detector with
# phase = sci_camera.los.phase
pl.imshow(psf)
pl.show()
def test_randomAtmos(self):
config = confParse.Configurator(os.path.join(CONFIG_PATH, "sh_8x8.py"))
config.loadSimParams()
atmos = atmosphere.atmos(config)
atmos.randomScrns()
def initAtmos(self, whole_scrn_size=None):
if whole_scrn_size is not None:
self.config.atmos.wholeScrnSize = whole_scrn_size
self.atmos = atmosphere.atmos(self.config)
def test_randomAtmos(self):
config = confParse.loadSoapyConfig(os.path.join(CONFIG_PATH,"sh_8x8.yaml"))
atmos = atmosphere.atmos(config)
atmos.randomScrns()
import numpy from soapy import confParse, SCI, atmosphere, DM from SPGD import SPGD # setup soapy conf conf_path = "conf/sim.yaml" conf = confParse.loadSoapyConfig(conf_path) # setup atmospheric distortion atmos = atmosphere.atmos(conf) dist = atmos.randomScrns() # setup simulations DM dm = DM.Piezo(conf) n_acts = dm.getActiveActs() # initiate control object control = numpy.zeros((conf.sim.nDM, conf.sim.scrnSize, conf.sim.scrnSize)) # setup camera cam = SCI.PSF(conf) # light with no correction beam = cam.frame(dist[0]).copy() # target target = cam.frame(None).copy() # import SPGDutils # target = SPGDutils.generate_gaussian_target(beam, 10)
def test_initAtmos(self):
config = confParse.Configurator(os.path.join(CONFIG_PATH,"sh_8x8.py"))
config.loadSimParams()
atmos = atmosphere.atmos(config.sim, config.atmos)
def generate_training(n_patches, n_patches_validation, n_stars, n_frames):
# Size of final images
nx = 256
ny = 256
n_zernike = 40
# GREGOR
telescope_radius = 1.44 * 1.440 * u.meter
secondary_radius = 0.404 * 0.404 * u.meter
pixSize = (6.0/512.0) * u.arcsec / u.pixel
lambda0 = 850.0 * u.nm
fov = 3.0 * u.arcsec
border = 100
f_images = h5py.File('database.h5', 'w')
f_images_validation = h5py.File('database_validation.h5', 'w')
database_images = f_images.create_dataset('intensity', (n_patches, n_frames+1, nx, ny, 1), 'f')
database_images_validation = f_images_validation.create_dataset('intensity', (n_patches_validation, n_frames+1, nx, ny, 1), 'f')
loop = 0
loop_val = 0
# load a sim config that defines lots of science cameras across the field
config = confParse.loadSoapyConfig('sh_8x8.py')
# Init a science camera
sci_camera = SCI.PSF(config, mask=np.ones((154,154)))
# init some atmosphere
atmos = atmosphere.atmos(config)
##############
# Training set
##############
for i in range(n_patches):
progressbar(i, n_patches, text='Progress (traininig set)')
star_field = np.zeros((nx, ny))
indx = np.random.randint(border, nx-border)
indy = np.random.randint(border, ny-border)
star_field[indx, indy] = 1.0
# Save original image in file
database_images[i,0,:,:,0] = star_field
star_field_fft = pyfftw.interfaces.numpy_fft.fft2(star_field)
for j in range(n_frames):
# Get phase for this time step
phase_scrns = atmos.moveScrns()
# Calculate all the PSF for this turbulence
psf = sci_camera.frame(phase_scrns)
nx_psf, ny_psf = psf.shape
psf_roll = np.roll(psf.data, int(nx_psf/2), axis=0)
psf_roll = np.roll(psf_roll, int(ny_psf/2), axis=1)
psf_fft = pyfftw.interfaces.numpy_fft.fft2(psf_roll)
image_final = np.real(pyfftw.interfaces.numpy_fft.ifft2(psf_fft * star_field_fft))
database_images[i,j+1,:,:,0] = image_final
for j in range(50):
phase_scrns = atmos.moveScrns()
##############
# Validation set
##############
for i in range(n_patches_validation):
progressbar(i, n_patches_validation, text='Progress (validation set)')
star_field = np.zeros((nx, ny))
indx = np.random.randint(border, nx-border)
indy = np.random.randint(border, ny-border)
star_field[indx, indy] = 1.0
# Save original image in file
database_images_validation[i,0,:,:,0] = star_field
star_field_fft = pyfftw.interfaces.numpy_fft.fft2(star_field)
for j in range(n_frames):
# Get phase for this time step
phase_scrns = atmos.moveScrns()
# Calculate all the PSF for this turbulence
psf = sci_camera.frame(phase_scrns)
nx_psf, ny_psf = psf.shape
psf_roll = np.roll(psf.data, int(nx_psf/2), axis=0)
psf_roll = np.roll(psf_roll, int(ny_psf/2), axis=1)
psf_fft = pyfftw.interfaces.numpy_fft.fft2(psf_roll)
image_final = np.real(pyfftw.interfaces.numpy_fft.ifft2(psf_fft * star_field_fft))
database_images_validation[i,j+1,:,:,0] = image_final
for j in range(50):
phase_scrns = atmos.moveScrns()
f_images.close()
f_images_validation.close()
