lemon-sandbox/mat-preview/260816.ipynb

In [1]:

from scipy.io import loadmat as scipy_loadmat
from mat73 import loadmat as mat73_loadmat
import numpy as np

In [3]:

# fold_slice output
f = "/home/swim/data/mose2-chen-natcomm/rawdata_1x_crop.mat"
contents = scipy_loadmat(f)
print([key for key in contents.keys() if not key.startswith('__')])

['ADU', 'alpha0', 'cbed', 'df', 'rbf', 'rot_ang', 'scanstep', 'voltage']

In [9]:

for key in contents.keys():
    print(key)
    print(contents[key])
    print()

__header__
b'MATLAB 5.0 MAT-file, Platform: PCWIN64, Created on: Sat Feb 22 01:27:35 2020'

__version__
1.0

__globals__
[]

ADU
[[151]]

alpha0
[[21.4]]

cbed
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     0.00000000e+00  0.00000000e+00]
   ...
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     0.00000000e+00  0.00000000e+00]
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     0.00000000e+00  0.00000000e+00]]

  ...

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  ...

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 ...


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  ...

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    -2.30636263e+00  1.77461624e-01]
   [-1.63512802e+00 -3.13571835e+00  2.15324497e+00 ...  6.33438396e+00
     6.69365525e-01  5.23701000e+00]]

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]]


 [[[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]

  [[ 6.40643311e+00 -3.71599388e+00  1.16903591e+00 ... -4.23146725e+00
     2.28081512e+00 -2.96396875e+00]
   [-7.15778828e-01  2.12799549e+00 -6.02464676e-01 ...  1.60336590e+00
    -6.71727324e+00  2.11588669e+00]
   [ 1.43009853e+00 -1.22071266e-01  3.99591875e+00 ... -7.08824873e-01
    -6.84431076e-01 -7.11320877e-01]
   ...
   [-7.52473164e+00 -3.10640621e+00 -1.02152920e+00 ... -3.25083256e-01
    -1.07500362e+00  2.95745301e+00]
   [-1.14887190e+00 -2.53660011e+00 -1.71011734e+00 ...  1.35035515e-01
     1.74112272e+00 -2.77505302e+00]
   [-5.87642670e-01 -2.08823299e+00  3.20073032e+00 ... -2.61813068e+00
    -7.28314924e+00 -2.71550465e+00]]

  [[-3.43695068e+00 -3.55937767e+00 -3.67434788e+00 ... -7.48510361e-02
    -3.56256866e+00 -3.80735254e+00]
   [-5.59162617e-01 -6.71538830e+00 -5.44584846e+00 ... -7.24001789e+00
     4.39342976e-01 -1.72749710e+00]
   [-2.41328526e+00 -4.96545506e+00 -3.84746504e+00 ... -1.55220866e+00
    -5.52781487e+00 -1.55470467e+00]
   ...
   [ 6.31884575e-01  1.05021000e+00 -8.64912987e-01 ... -2.16846704e+00
    -6.91838741e+00  1.11406922e+00]
   [ 7.74431229e-03 -3.37998390e+00  4.46498871e-01 ... -3.70834827e+00
    -7.10226107e+00 -3.61843681e+00]
   [-1.43102646e+00 -9.31616783e-01  2.35734653e+00 ... -8.46151447e+00
    -2.12653303e+00  4.41111565e-01]]

  ...

  [[-4.35150146e+00 -4.47392845e+00 -1.58889866e+00 ... -3.98940182e+00
    -1.47711945e+00 -7.21903324e-01]
   [ 5.26286602e-01  1.37006104e+00  1.32639603e+02 ...  6.84543133e+00
    -4.75207806e-01 -8.64204788e+00]
   [-4.32783604e+00 -2.88000584e+00 -2.76201582e+00 ... -3.46675944e+00
     4.55763435e+00 -3.46925545e+00]
   ...
   [ 6.77173309e+01  1.35659218e-01  1.22053623e+00 ... -7.08301783e+00
     6.16706181e+00 -1.80048156e+00]
   [-4.90680647e+00 -6.29453468e+00  1.53194809e+00 ...  2.43771019e+01
     9.83188152e-01  5.46701241e+00]
   [-2.34557724e+00 -1.18461676e+01 -3.55720425e+00 ... -4.37606525e+00
    -4.04108381e+00 -1.47343922e+00]]

  [[-9.73449707e-01 -9.58766937e-02 -2.10846901e-01 ... -1.61135006e+00
     1.90093231e+00 -3.43851566e-01]
   [ 2.90433836e+00  2.74811268e+00  1.70176525e+01 ...  5.22348309e+00
    -9.71560478e-02 -2.63996124e-01]
   [ 3.05021572e+00  6.49804592e+00 -3.38396406e+00 ...  9.11292315e-01
     2.93568611e+00  2.90879631e+00]
   ...
   [ 1.09538555e+00  1.41513718e+02  5.98587990e-01 ...  1.29503393e+00
     2.54511356e+00  4.57757044e+00]
   [-5.28754711e-01 -9.16482925e-01  3.90999985e+00 ... -1.24484730e+00
    -5.63876009e+00  6.84506416e+00]
   [ 2.03247452e+00 -1.46811581e+00  1.82084751e+00 ...  2.00198650e+00
     3.33696795e+00  1.90461254e+00]]

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]]


 [[[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]

  ...

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]

  [[ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   ...
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]
   [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 ...  0.00000000e+00
     0.00000000e+00  0.00000000e+00]]]]

df
[[-500]]

rbf
[[26]]

rot_ang
[[-30]]

scanstep
[[0.85]]

voltage
[[80]]

In [10]:

contents['cbed'].shape

Out [10]:

(124, 124, 60, 60)

In [11]:

from matplotlib import pyplot as plt

In [37]:

contents['cbed'].min()

Out [37]:

np.float32(-36.020027)

In [40]:

plt.imshow(
    np.log1p((contents['cbed'] - contents['cbed'].min()) / contents['ADU'] + 1e-10).sum(axis=(0, 1))
)

Out [40]:

<matplotlib.image.AxesImage at 0x7f18a10bd2b0>