def loadData(downsample=1.0):
'''
'''
dat = np.genfromtxt('dat/Intensity.csv', delimiter = ',',
dtype="f8,f8,f8,f8,f8,f8,f8,S20,f8,f8",
names=True, skip_header=0)
intensity = {}
meta = {}
meta['model'] = dat['model'][0]
meta['iterations'] = int(dat['iterations'][0])
meta['samples'] = int(dat.shape[0] / meta['iterations'])
# Preallocate memory:
intensity['rawintensity'] = np.zeros((meta['iterations'],
meta['samples']))
intensity['intensity'] = np.zeros((meta['iterations'],
meta['samples']))
meta['lens_accom'] = np.zeros(meta['iterations'])
meta['pupil_size_%'] = np.zeros(meta['iterations'])
meta['off_axis_*'] = np.zeros(meta['iterations'])
meta['object_distance'] = np.zeros(meta['iterations'])
meta['age_&'] = np.zeros(meta['iterations'])
meta['eye_length_%'] = np.zeros(meta['iterations'])
for i in range(0, meta['iterations']):
ind1 = i * meta['samples']
ind2 = (i + 1) * meta['samples']
intensity['rawintensity'][i,:] = dat['encircled_intensity'][ind1:ind2]
intensity['intensity'][i,:] = (dat['encircled_intensity'][ind1:ind2]
/ np.max(intensity['rawintensity'][i,:]))
meta['lens_accom'][i] = dat['lens_focus_D'][ind1]
meta['pupil_size_%'][i] = dat['pupil_size_mm'][ind1]
meta['off_axis_*'][i] = dat['offaxis_deg'][ind1]
meta['object_distance'][i] = dat['obj_distance_mm'][ind1]
meta['age_&'][i] = dat['age_y'][ind1]
meta['eye_length_%'][i] = dat['axial_len_mm'][ind1]
# set up parameters of the eye:
xvals = dat['radius_mm'][0: meta['samples']]
# retinal image, here is radius of image area
meta['retImg'] = np.max(xvals) # 1/2 size of image in mm
radians = 2 * np.arctan(meta['retImg'] / (meta['eye_length_%'][0]))
meta['deg'] = dm.rad2deg(radians)
meta['mm/deg'] = meta['retImg'] * 2 / meta['deg']
meta['xvals'] = xvals
variable = findDependentVar(meta)
printParams(meta)
return intensity, meta
def genMeta():
'''Just temporary.
'''
# get from ray tracer eventually
_meta = {}
_meta['samples'] = 399
_meta['retImg'] = 0.1995 #this is only radius, D = 2x 0.1995
_meta['eye_length'] = 23.92
_meta['pupil_size'] = 3
radians = 2 * np.arctan(_meta['retImg'] / _meta['eye_length'])
_meta['deg'] = rad2deg(radians)
_meta['mm/deg'] = 2 * _meta['retImg'] / _meta['deg']
cycles = np.arange(0, _meta['samples']) / 2.0
cpd = (cycles / _meta['retImg']) * _meta['mm/deg']
return _meta, cpd
