fixed typo

# Conflicts:
#	landsat/image.py
#	landsat/landsat.py
This commit is contained in:
Scisco
2015-10-02 15:34:28 +02:00
5 changed files with 542 additions and 3 deletions

262
landsat/colormapNDVI Normal file
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@@ -0,0 +1,262 @@
# Tue Jul 14 2015 14:40:26 GMT+0200
# ---------------------------------------------
# Intuitive Colormap for NDVI mapping. Not suited for grayscale print or colorblind people though...
# The value "mode" is the maximum value of the color intensity, e.g. 1 or 255
mode = 1
0 0 0
0.006299213 0.006299213 0.006299213
0.012598425 0.012598425 0.012598425
0.018897638 0.018897638 0.018897638
0.02519685 0.02519685 0.02519685
0.031496063 0.031496063 0.031496063
0.037795275 0.037795275 0.037795275
0.044094488 0.044094488 0.044094488
0.050393701 0.050393701 0.050393701
0.056692913 0.056692913 0.056692913
0.062992126 0.062992126 0.062992126
0.069291338 0.069291338 0.069291338
0.075590551 0.075590551 0.075590551
0.081889763 0.081889763 0.081889763
0.088188976 0.088188976 0.088188976
0.094488189 0.094488189 0.094488189
0.100787401 0.100787401 0.100787401
0.107086614 0.107086614 0.107086614
0.113385826 0.113385826 0.113385826
0.119685039 0.119685039 0.119685039
0.125984251 0.125984251 0.125984251
0.132283464 0.132283464 0.132283464
0.138582677 0.138582677 0.138582677
0.144881889 0.144881889 0.144881889
0.151181102 0.151181102 0.151181102
0.157480314 0.157480314 0.157480314
0.163779527 0.163779527 0.163779527
0.17007874 0.17007874 0.17007874
0.176377952 0.176377952 0.176377952
0.182677165 0.182677165 0.182677165
0.188976377 0.188976377 0.188976377
0.19527559 0.19527559 0.19527559
0.201574802 0.201574802 0.201574802
0.207874015 0.207874015 0.207874015
0.214173228 0.214173228 0.214173228
0.22047244 0.22047244 0.22047244
0.226771653 0.226771653 0.226771653
0.233070865 0.233070865 0.233070865
0.239370078 0.239370078 0.239370078
0.24566929 0.24566929 0.24566929
0.251968503 0.251968503 0.251968503
0.25826773 0.25826773 0.25826773
0.264566928 0.264566928 0.264566928
0.270866156 0.270866156 0.270866156
0.277165353 0.277165353 0.277165353
0.283464581 0.283464581 0.283464581
0.289763778 0.289763778 0.289763778
0.296063006 0.296063006 0.296063006
0.302362204 0.302362204 0.302362204
0.308661431 0.308661431 0.308661431
0.314960629 0.314960629 0.314960629
0.321259856 0.321259856 0.321259856
0.327559054 0.327559054 0.327559054
0.333858281 0.333858281 0.333858281
0.340157479 0.340157479 0.340157479
0.346456707 0.346456707 0.346456707
0.352755904 0.352755904 0.352755904
0.359055132 0.359055132 0.359055132
0.365354329 0.365354329 0.365354329
0.371653557 0.371653557 0.371653557
0.377952754 0.377952754 0.377952754
0.384251982 0.384251982 0.384251982
0.39055118 0.39055118 0.39055118
0.396850407 0.396850407 0.396850407
0.403149605 0.403149605 0.403149605
0.409448832 0.409448832 0.409448832
0.41574803 0.41574803 0.41574803
0.422047257 0.422047257 0.422047257
0.428346455 0.428346455 0.428346455
0.434645683 0.434645683 0.434645683
0.44094488 0.44094488 0.44094488
0.447244108 0.447244108 0.447244108
0.453543305 0.453543305 0.453543305
0.459842533 0.459842533 0.459842533
0.466141731 0.466141731 0.466141731
0.472440958 0.472440958 0.472440958
0.478740156 0.478740156 0.478740156
0.485039383 0.485039383 0.485039383
0.491338581 0.491338581 0.491338581
0.497637808 0.497637808 0.497637808
0.503937006 0.503937006 0.503937006
0.510236204 0.510236204 0.510236204
0.516535461 0.516535461 0.516535461
0.522834659 0.522834659 0.522834659
0.529133856 0.529133856 0.529133856
0.535433054 0.535433054 0.535433054
0.541732311 0.541732311 0.541732311
0.548031509 0.548031509 0.548031509
0.554330707 0.554330707 0.554330707
0.560629904 0.560629904 0.560629904
0.566929162 0.566929162 0.566929162
0.573228359 0.573228359 0.573228359
0.579527557 0.579527557 0.579527557
0.585826755 0.585826755 0.585826755
0.592126012 0.592126012 0.592126012
0.59842521 0.59842521 0.59842521
0.604724407 0.604724407 0.604724407
0.611023605 0.611023605 0.611023605
0.617322862 0.617322862 0.617322862
0.62362206 0.62362206 0.62362206
0.629921257 0.629921257 0.629921257
0.636220455 0.636220455 0.636220455
0.642519712 0.642519712 0.642519712
0.64881891 0.64881891 0.64881891
0.655118108 0.655118108 0.655118108
0.661417305 0.661417305 0.661417305
0.667716563 0.667716563 0.667716563
0.67401576 0.67401576 0.67401576
0.680314958 0.680314958 0.680314958
0.686614156 0.686614156 0.686614156
0.692913413 0.692913413 0.692913413
0.699212611 0.699212611 0.699212611
0.705511808 0.705511808 0.705511808
0.711811006 0.711811006 0.711811006
0.718110263 0.718110263 0.718110263
0.724409461 0.724409461 0.724409461
0.730708659 0.730708659 0.730708659
0.737007856 0.737007856 0.737007856
0.743307114 0.743307114 0.743307114
0.749606311 0.749606311 0.749606311
0.755905509 0.755905509 0.755905509
0.762204707 0.762204707 0.762204707
0.768503964 0.768503964 0.768503964
0.774803162 0.774803162 0.774803162
0.781102359 0.781102359 0.781102359
0.787401557 0.787401557 0.787401557
0.787401557 0.787401557 0.787401557
0.768627465 0.368627459 0.168627456
0.768627465 0.368627459 0.168627456
0.768929541 0.369346976 0.16918768
0.769231617 0.370066464 0.169747904
0.769533694 0.370785981 0.170308128
0.76983577 0.371505469 0.170868352
0.770137846 0.372224987 0.171428576
0.770439982 0.372944474 0.1719888
0.770742059 0.373663992 0.172549024
0.771044135 0.374383479 0.173109248
0.771346211 0.375102997 0.173669472
0.771648288 0.375822484 0.174229696
0.771950364 0.376542002 0.17478992
0.77225244 0.37726149 0.175350145
0.772554517 0.377981007 0.175910369
0.772856593 0.378700495 0.176470593
0.773158669 0.379420012 0.177030817
0.773460805 0.3801395 0.177591041
0.773762882 0.380859017 0.178151265
0.774064958 0.381578505 0.178711489
0.774367034 0.382298023 0.179271713
0.774669111 0.38301751 0.179831937
0.774971187 0.383737028 0.180392161
0.780972838 0.400119334 0.194455713
0.786974549 0.416501611 0.20851928
0.792976201 0.432883918 0.222582832
0.798977852 0.449266195 0.236646384
0.804979563 0.465648502 0.250709951
0.810981214 0.482030779 0.264773518
0.816982865 0.498413086 0.278837055
0.822984517 0.514795363 0.292900622
0.828986228 0.53117764 0.306964189
0.834987879 0.547559977 0.321027726
0.84098953 0.563942254 0.335091293
0.846991241 0.580324531 0.34915486
0.852992892 0.596706867 0.363218397
0.858994544 0.613089144 0.377281964
0.864996254 0.629471421 0.391345531
0.870997906 0.645853698 0.405409068
0.876999557 0.662236035 0.419472635
0.883001268 0.678618312 0.433536202
0.889002919 0.695000589 0.447599739
0.89500457 0.711382926 0.461663306
0.901006281 0.727765203 0.475726873
0.907007933 0.74414748 0.48979041
0.913009584 0.760529757 0.503853977
0.919011235 0.776912093 0.517917514
0.925012946 0.79329437 0.531981111
0.931014597 0.809676647 0.546044648
0.937016249 0.826058924 0.560108185
0.94301796 0.842441261 0.574171782
0.949019611 0.858823538 0.588235319
0.913870752 0.858823538 0.566448808
0.878721833 0.858823538 0.544662356
0.843572974 0.858823538 0.522875845
0.808424115 0.858823538 0.501089334
0.773275256 0.858823538 0.479302853
0.738126338 0.858823538 0.457516372
0.702977479 0.858823538 0.435729861
0.667828619 0.858823538 0.41394338
0.63267976 0.858823538 0.392156869
0.597530842 0.858823538 0.370370388
0.562381983 0.858823538 0.348583907
0.527233124 0.858823538 0.326797396
0.492084235 0.858823538 0.305010915
0.456935376 0.858823538 0.283224404
0.421786487 0.858823538 0.261437923
0.386637628 0.858823538 0.239651427
0.351488739 0.858823538 0.217864931
0.31633988 0.858823538 0.196078435
0.281190991 0.858823538 0.174291953
0.246042117 0.858823538 0.152505457
0.210893244 0.858823538 0.130718961
0.17574437 0.858823538 0.108932465
0.140595496 0.858823538 0.087145977
0.105446622 0.858823538 0.065359481
0.070297748 0.858823538 0.043572988
0.035148874 0.858823538 0.021786494
0 0.858823538 0
0 0.846087515 0
0 0.833351493 0
0 0.82061547 0
0 0.807879448 0
0 0.795143425 0
0 0.782407403 0
0 0.769671381 0
0 0.756935358 0
0 0.744199336 0
0 0.731463313 0
0 0.718727291 0
0 0.705991268 0
0 0.693255246 0
0 0.680519283 0
0 0.66778326 0
0 0.655047238 0
0 0.642311215 0
0 0.629575193 0
0 0.61683917 0
0 0.604103148 0
0 0.591367126 0
0 0.578631103 0
0 0.565895081 0
0 0.553159058 0
0 0.540423036 0
0 0.527687013 0
0 0.514950991 0
0 0.514215708 0
0 0.513480425 0
0 0.512745082 0
0 0.512009799 0
0 0.511274517 0
0 0.510539234 0
0 0.509803951 0
0 0.509068608 0
0 0.508333325 0
0 0.507598042 0
0 0.50686276 0
0 0.506127477 0
0 0.505392134 0
0 0.504656851 0
0 0.503921568 0
0 0.503186285 0
0 0.502451003 0
0 0.50171566 0
0 0.500980377 0
0 0.500245094 0
0 0.499509811 0
0 0.498774499 0
0 0.498039216 0

275
landsat/colormap_cubehelix Normal file
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@@ -0,0 +1,275 @@
# Thu Jul 23 2015 10:14:15 GMT+0200
# ---------------------------------------------
# R/G/B cubehelix colour scheme
#
# see http://www.mrao.cam.ac.uk/~dag/CUBEHELIX/
#----------------------------------------------
# see Green (2011), BASI, 39, 289.
#
# start............: 1.0
# rotations........: -0.8
# hue..............: 1.6
# gamma............: 1.0
# number of levels.: 256
#----------------------------------------------
# Dave Green: dag@mrao.cam.ac.uk
#----------------------------------------------
# The value "mode" is the maximum value of the color intensity, e.g. 1 or 255
mode = 1
0 0 0
0.009 0.002 0.001
0.018 0.004 0.002
0.027 0.005 0.004
0.036 0.007 0.005
0.046 0.009 0.007
0.055 0.01 0.009
0.064 0.012 0.012
0.073 0.013 0.014
0.082 0.015 0.017
0.092 0.016 0.02
0.101 0.018 0.023
0.11 0.019 0.027
0.119 0.02 0.031
0.128 0.021 0.035
0.137 0.023 0.039
0.146 0.024 0.044
0.155 0.025 0.048
0.164 0.026 0.053
0.173 0.027 0.058
0.182 0.029 0.064
0.19 0.03 0.069
0.199 0.031 0.075
0.208 0.032 0.081
0.216 0.033 0.087
0.224 0.035 0.094
0.233 0.036 0.1
0.241 0.037 0.107
0.249 0.038 0.114
0.257 0.04 0.121
0.265 0.041 0.129
0.272 0.042 0.136
0.28 0.044 0.144
0.287 0.045 0.152
0.294 0.046 0.16
0.301 0.048 0.168
0.308 0.05 0.177
0.315 0.051 0.185
0.322 0.053 0.194
0.328 0.054 0.203
0.335 0.056 0.212
0.341 0.058 0.221
0.347 0.06 0.23
0.353 0.062 0.239
0.359 0.064 0.248
0.364 0.066 0.258
0.369 0.068 0.268
0.375 0.07 0.277
0.38 0.073 0.287
0.384 0.075 0.297
0.389 0.077 0.307
0.393 0.08 0.317
0.398 0.082 0.327
0.402 0.085 0.337
0.406 0.088 0.347
0.409 0.091 0.358
0.413 0.094 0.368
0.416 0.097 0.378
0.419 0.1 0.389
0.422 0.103 0.399
0.425 0.106 0.409
0.428 0.11 0.42
0.43 0.113 0.43
0.432 0.117 0.44
0.434 0.121 0.451
0.436 0.124 0.461
0.438 0.128 0.471
0.439 0.132 0.481
0.441 0.136 0.492
0.442 0.14 0.502
0.443 0.145 0.512
0.444 0.149 0.522
0.444 0.154 0.532
0.445 0.158 0.542
0.445 0.163 0.552
0.445 0.168 0.562
0.445 0.172 0.571
0.445 0.177 0.581
0.444 0.182 0.59
0.444 0.188 0.6
0.443 0.193 0.609
0.443 0.198 0.618
0.442 0.203 0.627
0.441 0.209 0.636
0.439 0.215 0.645
0.438 0.22 0.654
0.437 0.226 0.662
0.435 0.232 0.671
0.433 0.238 0.679
0.432 0.244 0.687
0.43 0.25 0.695
0.428 0.256 0.703
0.426 0.263 0.711
0.423 0.269 0.718
0.421 0.275 0.725
0.419 0.282 0.732
0.416 0.289 0.739
0.414 0.295 0.746
0.411 0.302 0.753
0.409 0.309 0.759
0.406 0.316 0.766
0.403 0.323 0.772
0.4 0.33 0.777
0.397 0.337 0.783
0.394 0.344 0.789
0.391 0.351 0.794
0.389 0.358 0.799
0.386 0.365 0.804
0.383 0.373 0.809
0.379 0.38 0.813
0.376 0.387 0.817
0.373 0.395 0.822
0.37 0.402 0.825
0.367 0.41 0.829
0.364 0.417 0.833
0.361 0.425 0.836
0.358 0.432 0.839
0.355 0.44 0.842
0.353 0.448 0.845
0.35 0.455 0.847
0.347 0.463 0.849
0.344 0.47 0.852
0.341 0.478 0.853
0.339 0.486 0.855
0.336 0.494 0.857
0.334 0.501 0.858
0.331 0.509 0.859
0.329 0.517 0.86
0.327 0.524 0.861
0.325 0.532 0.861
0.322 0.539 0.862
0.32 0.547 0.862
0.319 0.555 0.862
0.317 0.562 0.862
0.315 0.57 0.862
0.314 0.577 0.861
0.312 0.585 0.861
0.311 0.592 0.86
0.31 0.6 0.859
0.309 0.607 0.858
0.308 0.614 0.856
0.307 0.622 0.855
0.307 0.629 0.854
0.306 0.636 0.852
0.306 0.643 0.85
0.306 0.65 0.848
0.306 0.657 0.846
0.306 0.664 0.844
0.306 0.671 0.842
0.307 0.678 0.839
0.307 0.685 0.837
0.308 0.691 0.834
0.309 0.698 0.832
0.31 0.705 0.829
0.311 0.711 0.826
0.313 0.718 0.823
0.315 0.724 0.82
0.316 0.73 0.817
0.318 0.736 0.814
0.321 0.743 0.811
0.323 0.749 0.808
0.326 0.754 0.805
0.328 0.76 0.802
0.331 0.766 0.798
0.335 0.772 0.795
0.338 0.777 0.792
0.341 0.783 0.788
0.345 0.788 0.785
0.349 0.794 0.782
0.353 0.799 0.778
0.357 0.804 0.775
0.361 0.809 0.772
0.366 0.814 0.769
0.371 0.819 0.765
0.376 0.823 0.762
0.381 0.828 0.759
0.386 0.833 0.756
0.392 0.837 0.753
0.397 0.841 0.75
0.403 0.846 0.747
0.409 0.85 0.744
0.415 0.854 0.741
0.421 0.858 0.739
0.428 0.862 0.736
0.434 0.865 0.734
0.441 0.869 0.731
0.448 0.873 0.729
0.455 0.876 0.727
0.462 0.879 0.725
0.469 0.883 0.723
0.477 0.886 0.721
0.484 0.889 0.719
0.492 0.892 0.718
0.5 0.895 0.717
0.508 0.898 0.715
0.516 0.901 0.714
0.524 0.903 0.713
0.532 0.906 0.713
0.541 0.908 0.712
0.549 0.911 0.712
0.558 0.913 0.711
0.566 0.915 0.711
0.575 0.918 0.711
0.584 0.92 0.712
0.593 0.922 0.712
0.602 0.924 0.713
0.611 0.926 0.713
0.62 0.928 0.714
0.629 0.929 0.716
0.638 0.931 0.717
0.647 0.933 0.719
0.656 0.934 0.721
0.665 0.936 0.723
0.675 0.938 0.725
0.684 0.939 0.727
0.693 0.94 0.73
0.702 0.942 0.733
0.712 0.943 0.736
0.721 0.945 0.739
0.73 0.946 0.743
0.739 0.947 0.746
0.748 0.948 0.75
0.758 0.95 0.755
0.767 0.951 0.759
0.776 0.952 0.764
0.785 0.953 0.768
0.794 0.954 0.773
0.802 0.956 0.779
0.811 0.957 0.784
0.82 0.958 0.79
0.829 0.959 0.795
0.837 0.96 0.801
0.845 0.962 0.808
0.854 0.963 0.814
0.862 0.964 0.821
0.87 0.965 0.828
0.878 0.967 0.835
0.886 0.968 0.842
0.894 0.969 0.849
0.901 0.971 0.857
0.909 0.972 0.865
0.916 0.973 0.873
0.923 0.975 0.881
0.93 0.976 0.889
0.937 0.978 0.898
0.944 0.98 0.906
0.95 0.981 0.915
0.956 0.983 0.924
0.963 0.985 0.933
0.969 0.987 0.942
0.974 0.989 0.951
0.98 0.991 0.961
0.985 0.993 0.971
0.99 0.995 0.98
0.995 0.998 0.99
1.000 1.000 1.000

View File

@@ -284,5 +284,4 @@ if __name__ == '__main__':
d = Downloader()
# d.download(['LC81990242015046LGN00', 'LC80030172015001LGN00'])
d.download(['LC80030172015001LGN00'], bands=[5, 4])
# d.download(['LC81990242015046LGN00', 'LC80030172015001LGN00'])

View File

@@ -27,3 +27,6 @@ BASE_DIR = abspath(dirname(__file__))
LANDSAT_DIR = join(HOME_DIR, 'landsat')
DOWNLOAD_DIR = join(LANDSAT_DIR, 'downloads')
PROCESSED_IMAGE = join(LANDSAT_DIR, 'processed')
# Colormap File
COLORMAP = join(abspath(dirname(__file__)), 'colormap_cubehelix')

View File

@@ -34,7 +34,7 @@ class TestLandsat(unittest.TestCase):
args = ['search', '--start', 'berlin', '--end', 'january 10 2014']
self.assertEquals(landsat.main(self.parser.parse_args(args)),
['You date format is incorrect. Please try again!', 1])
['Your date format is incorrect. Please try again!', 1])
def test_too_many_results(self):
""" Test when search return too many results """