$ conda install -c dgursoy tomopy

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$ conda install -c astra-toolbox astra-toolbox

---

import tomopy

# Read data from APS 32ID beamline
prj, flat, dark = tomopy.read_aps_32id('data.h5')

# Normalize data
prj = tomopy.normalize(prj, flat, dark)

# Define acquired angles
ang = tomopy.angles(1024)

# Reconstruct data using TomoPy gridrec
rec = tomopy.recon(prj, ang, algorithm='gridrec')

---

# Reconstruct data using ASTRA FBP
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options={'method': 'FBP', 'proj_type': 'linear'})

---

# Reconstruct data using ASTRA FBP on the GPU
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options={'method': 'FBP_CUDA', 'proj_type': 'cuda'})

---

# Reconstruct data using ASTRA CGLS on the GPU
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options={'method': 'CGLS_CUDA', 'proj_type': 'cuda',
   'num_iter': 10})
    
---  
    
# Reconstruct data using ASTRA SIRT on the GPU,
# with nonnegativity constraint
extra_options = {'MinConstraint':0}
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options={'method': 'SIRT_CUDA', 'proj_type': 'cuda',
   'num_iter': 100, 'extra_options': extra_options})

---

# Reconstruct data using ASTRA CGLS on 4 GPUs
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options={'method': 'CGLS_CUDA', 'proj_type': 'cuda'
   ,'num_iter': 10, 'gpu_list': [0, 1, 2, 3]})

---

# Reconstruct data using an ASTRA plugin,
# performing FISTA total variation minimization
import astra
import tvtomo
astra.plugin.register(tvtomo.plugin)
extra_options = {'tv_reg':1}
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options={'method': 'TV-FISTA', 'proj_type': 'cuda',
   'num_iter': 100, 'extra_options':extra_options})

---

import tomopy
import numpy as np

# Set up dataset variables
file_name = './data.h5'
center = 1286 # center of rotation
start = 740 # first slice
end = 1500 # last slice
miss_ang = [142, 228] # blocked angle range

# Read data from APS 32ID beamline
prj, flat, dark = tomopy.read_aps_32id(file_name,
   sino=(start, end))

# Remove the blocked projections
ang = tomopy.angles(359)
prj = np.concatenate((prj[:miss_ang[0]], prj[miss_ang[1]:]),
      axis=0)
ang = np.concatenate((ang[:miss_ang[0]], ang[miss_ang[1]:]))

# Normalize data
prj = tomopy.normalize(prj, flat, dark)

# Remove ring artifacts
prj = tomopy.remove_stripe_fw(prj)

# Setup ASTRA options
opts = {}
opts['method'] = 'SIRT_CUDA'
opts['num_iter'] = 100
opts['proj_type'] = 'cuda'
opts['extra_options'] = {'MinConstraint':0}

# Perform reconstruction
rec = tomopy.recon(prj, ang, algorithm=tomopy.astra,
   options=opts)

# Export reconstructed slices as TIFFs
tomopy.io.writer.write_tiff_stack(rec, fname='./recs',
   start=start)