import tomograpy
# object
obj = tomograpy.centered_cubic_map(3, 128, fill=1.)
# number of images
n = 20
# reshape object for 4d model
obj4 = obj.reshape(obj.shape + (1, )).repeat(n, axis=-1)
obj4.header['NAXIS'] = 4
obj4.header['NAXIS4'] = obj4.shape[3]
obj4.header['CRVAL4'] = 0.
# data
radius = 200
a = tomograpy.fov(obj.header, radius)
data = tomograpy.centered_stack(a,
128,
n_images=n,
radius=radius,
max_lon=np.pi)
data[:] = np.zeros(data.shape)
# projection
t = time.time()
data = tomograpy.projector4d(data, obj4)
print("projection time : " + str(time.time() - t))
# backprojection
x0 = obj4.copy()
x0[:] = 0.
t = time.time()
x0 = tomograpy.backprojector4d(data, x0)
print("backprojection time : " + str(time.time() - t))
#!/usr/bin/env python
import time
import numpy as np
import tomograpy
# object
obj = tomograpy.centered_cubic_map(3, 128, fill=1.)
# number of images
n = 20
# reshape object for 4d model
obj4 = obj.reshape(obj.shape + (1,)).repeat(n, axis=-1)
obj4.header['NAXIS'] = 4
obj4.header['NAXIS4'] = obj4.shape[3]
obj4.header['CRVAL4'] = 0.
# data
radius = 200
a = tomograpy.fov(obj.header, radius)
data = tomograpy.centered_stack(a, 128, n_images=n, radius=radius,
max_lon=np.pi)
data[:] = np.zeros(data.shape)
# projection
t = time.time()
data = tomograpy.projector4d(data, obj4)
print("projection time : " + str(time.time() - t))
# backprojection
x0 = obj4.copy()
x0[:] = 0.
t = time.time()
x0 = tomograpy.backprojector4d(data, x0)
print("backprojection time : " + str(time.time() - t))
# times
DT = 1000.
dt_min = 100.
dates = np.arange(n / 2) * DT / 2.
dates = np.concatenate(2 * (dates, ))
dates = [
time.strftime('%Y-%m-%dT%H:%M:%S', time.localtime((t))) for t in dates
]
for i in xrange(len(data.header)):
data.header[i]['DATE_OBS'] = dates[i]
data = tomograpy.solar.sort_data_array(data)
# projection
t = time.time()
data = tomograpy.projector4d(data, obj4, obstacle="sun")
print("projection time : " + str(time.time() - t))
# backprojection
x0 = obj4.copy()
x0[:] = 0.
t = time.time()
x0 = tomograpy.backprojector4d(data, x0, obstacle="sun")
print("backprojection time : " + str(time.time() - t))
# model
kwargs = {
'obj_rmin': 1., #'obj_rmax':1.3,
'mask_negative': False,
'dt_min': 100
}
P, D, obj_mask, data_mask = tomograpy.models.stsrt(data, obj, **kwargs)
data = tomograpy.solar.concatenate((data1, data2))
# times
DT = 1000.
dt_min = 100.
dates = np.arange(n / 2) * DT / 2.
dates = np.concatenate(2 * (dates, ))
dates = [time.strftime('%Y-%m-%dT%H:%M:%S', time.localtime((t))) for t in dates]
for i in xrange(len(data.header)):
data.header[i]['DATE_OBS'] = dates[i]
data = tomograpy.solar.sort_data_array(data)
# projection
t = time.time()
data = tomograpy.projector4d(data, obj4, obstacle="sun")
print("projection time : " + str(time.time() - t))
# backprojection
x0 = obj4.copy()
x0[:] = 0.
t = time.time()
x0 = tomograpy.backprojector4d(data, x0, obstacle="sun")
print("backprojection time : " + str(time.time() - t))
# model
kwargs = {'obj_rmin':1., #'obj_rmax':1.3,
'mask_negative':False, 'dt_min':100}
P, D, obj_mask, data_mask = tomograpy.models.stsrt(data, obj, **kwargs)
# hyperparameters
hypers = (1e-1, 1e-1, 1e-1, 1e3)
# test time for one projection