Unverified Commit 3035ac9d authored by AustinSanders's avatar AustinSanders Committed by GitHub
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Initial cropping utilities (#4094) 

* Initial cropping utilities

* Moved notebooks from scripts to notebooks directory
parent d2e3399e

isis/notebooks/crop_chandrayaan.ipynb

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%% Cell type:code id: tags:



``` python

import pvl

import struct

import matplotlib.pyplot as plt

import numpy as np

import datetime

import os.path

import binascii

```



%% Cell type:code id: tags:



``` python

class RealIsisCubeLabelEncoder(pvl.encoder.IsisCubeLabelEncoder):

    def encode_time(self, value):

        if value.microsecond:

            second = u'%02d.%06d' % (value.second, value.microsecond)

        else:

            second = u'%02d' % value.second



        time = u'%02d:%02d:%s' % (value.hour, value.minute, second)

        return time.encode('utf-8')

```



%% Cell type:code id: tags:



``` python

chan_file = '/home/arsanders/testData/chandrayaan/forwardDescending/input/M3G20081129T171431_V03_L1B.LBL'

image_file = chan_file

```



%% Cell type:code id: tags:



``` python

header = pvl.load(chan_file)

```



%% Cell type:code id: tags:



``` python

rdn_file = os.path.dirname(chan_file) + "/"+ header['RDN_FILE']['^RDN_IMAGE']

obs_file = os.path.dirname(chan_file) + "/"+ header['OBS_FILE']['^OBS_IMAGE']

loc_file = os.path.dirname(chan_file) + "/"+ header['LOC_FILE']['^LOC_IMAGE']

tab_file = os.path.dirname(chan_file) + "/"+ header['UTC_FILE']['^UTC_TIME_TABLE']

```



%% Cell type:code id: tags:



``` python

with open(rdn_file, 'rb') as f:

    # From the end, seek n_records * record_size backwards

    f.seek(-header['RDN_FILE']['RECORD_BYTES'] * header['RDN_FILE']['FILE_RECORDS'], 2)

    b_image_data = f.read()

```



%% Cell type:code id: tags:



``` python

n_lines = 5

line_length = header['RDN_FILE']['RDN_IMAGE']['LINE_SAMPLES'] * (header['RDN_FILE']['RDN_IMAGE']['SAMPLE_BITS']//8)

```



%% Cell type:code id: tags:



``` python

def read_chandrayaan(b_image_data, line_length, n_lines, n_bands):

    image_data = []

    for j in range(n_lines*n_bands):

        image_sample = np.frombuffer(b_image_data[j*line_length:(j+1)*line_length],

                                     dtype=np.float32, count=int(line_length/4))

        image_data.append(image_sample)

    return np.array(image_data)

```



%% Cell type:code id: tags:



``` python

n_bands = header['RDN_FILE']['RDN_IMAGE']['BANDS']

n_output_bands = 3

image_data = read_chandrayaan(b_image_data, line_length, n_lines, n_bands)

cropped_image_data = image_data[np.where(np.arange(image_data.shape[0]) % n_bands < n_output_bands)]

#cropped_image_data = image_data

```



%% Cell type:code id: tags:



``` python

cropped_image_data.shape

```



%% Output



    (15, 304)



%% Cell type:code id: tags:



``` python

plt.imshow(cropped_image_data[0::n_output_bands])

```



%% Output



    <matplotlib.image.AxesImage at 0x2b86cb7c04d0>





%% Cell type:code id: tags:



``` python

with open(obs_file, 'rb') as f:

    # From the end, seek n_records * record_size backwards

    f.seek(-header['OBS_FILE']['RECORD_BYTES'] * header['OBS_FILE']['FILE_RECORDS'], 2)

    b_image_data = f.read()

```



%% Cell type:code id: tags:



``` python

n_bands = header['OBS_FILE']['OBS_IMAGE']['BANDS']

obs_image_data = read_chandrayaan(b_image_data, line_length, n_lines, n_bands)

```



%% Cell type:code id: tags:



``` python

obs_image_data.shape

```



%% Output



    (50, 304)



%% Cell type:code id: tags:



``` python

plt.imshow(obs_image_data[1::10])

```



%% Output



    <matplotlib.image.AxesImage at 0x2b8639c12a50>





%% Cell type:code id: tags:



``` python

with open(loc_file, 'rb') as f:

    # From the end, seek n_records * record_size backwards

    f.seek(-header['LOC_FILE']['RECORD_BYTES'] * header['LOC_FILE']['FILE_RECORDS'], 2)

    b_image_data = f.read()

```



%% Cell type:code id: tags:



``` python

line_length = header['LOC_FILE']['LOC_IMAGE']['LINE_SAMPLES'] * (header['LOC_FILE']['LOC_IMAGE']['SAMPLE_BITS']//8)

n_bands = header['LOC_FILE']['LOC_IMAGE']['BANDS']

image_data = []

for j in range(n_lines*n_bands):

    image_sample = np.frombuffer(b_image_data[j*line_length:(j+1)*line_length],

                                 dtype=np.float64, count=int(line_length/8))

    image_data.append(image_sample)

loc_image_data = np.array(image_data)

```



%% Cell type:code id: tags:



``` python

plt.imshow(loc_image_data[0::n_bands])

```



%% Output



    <matplotlib.image.AxesImage at 0x2b86cba33b90>





%% Cell type:code id: tags:



``` python

rdn_fn, rdn_ext = os.path.splitext(rdn_file)

obs_fn, obs_ext = os.path.splitext(obs_file)

loc_fn, loc_ext = os.path.splitext(loc_file)

tab_fn, tab_ext = os.path.splitext(tab_file)



mini_rdn_fn = rdn_fn + '_cropped' + rdn_ext

mini_rdn_bn = os.path.basename(mini_rdn_fn)



mini_obs_fn = obs_fn + '_cropped' + obs_ext

mini_obs_bn = os.path.basename(mini_obs_fn)



mini_loc_fn = loc_fn + '_cropped' + loc_ext

mini_loc_bn = os.path.basename(mini_loc_fn)



mini_tab_fn = tab_fn + '_cropped' + tab_ext

mini_tab_bn = os.path.basename(mini_tab_fn)

```



%% Cell type:code id: tags:



``` python

header['RDN_FILE']['^RDN_IMAGE'] = mini_rdn_bn

header['OBS_FILE']['^OBS_IMAGE'] = mini_obs_bn

header['LOC_FILE']['^LOC_IMAGE'] = mini_loc_bn

header['UTC_FILE']['^UTC_TIME_TABLE'] = mini_tab_bn



header['RDN_FILE']['FILE_RECORDS'] = n_lines

header['RDN_FILE']['RDN_IMAGE']['LINES'] = n_lines

header['RDN_FILE']['RDN_IMAGE']['BANDS'] = n_output_bands

header['RDN_FILE']['RECORD_BYTES'] = int(n_output_bands * (header['RDN_FILE']['RDN_IMAGE']['SAMPLE_BITS']/8) *header['RDN_FILE']['RDN_IMAGE']['LINE_SAMPLES'])



header['LOC_FILE']['FILE_RECORDS'] = n_lines

header['LOC_FILE']['LOC_IMAGE']['LINES'] = n_lines



header['OBS_FILE']['FILE_RECORDS'] = n_lines

header['OBS_FILE']['OBS_IMAGE']['LINES'] = n_lines



header['UTC_FILE']['FILE_RECORDS'] = n_lines

header['UTC_FILE']['UTC_TIME_TABLE']['ROWS'] = n_lines

```



%% Cell type:code id: tags:



``` python

label_fn, label_ext = os.path.splitext(chan_file)

out_label = label_fn + '_cropped' + label_ext

pvl.dump(header, out_label, cls=RealIsisCubeLabelEncoder)

```



%% Cell type:code id: tags:



``` python

with open(mini_rdn_fn, 'wb+') as f:

    b_reduced_image_data = cropped_image_data.tobytes()

    f.seek(0, 2)

    f.write(b_reduced_image_data)

```



%% Cell type:code id: tags:



``` python

with open(mini_loc_fn, 'wb+') as f:

    b_reduced_image_data = loc_image_data.tobytes()

    f.seek(0, 2)

    f.write(b_reduced_image_data)

```



%% Cell type:code id: tags:



``` python

with open(mini_obs_fn, 'wb+') as f:

    b_reduced_image_data = obs_image_data.tobytes()

    f.seek(0, 2)

    f.write(b_reduced_image_data)

```



%% Cell type:code id: tags:



``` python

with open(tab_file) as f:

    head = [next(f) for x in range(n_lines)]

    head = "".join(head)

with open(mini_tab_fn, 'w+') as f:

    f.write(head)

```



%% Cell type:code id: tags:



``` python

```

isis/notebooks/crop_kaguya.ipynb

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isis/notebooks/crop_leisa.ipynb

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isis/notebooks/crop_marci.ipynb

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