In [1]:

    

%pylab notebook
import matplotlib.pyplot as plt
import numpy as np

from charistools.readers import read_tile
pylab.rcParams['figure.figsize'] = (10.0, 8.0)


    

    




/Users/brodzik/miniconda3/envs/charis/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')






    




Populating the interactive namespace from numpy and matplotlib

In [4]:

    

%cd /Users/brodzik/projects/CHARIS/elevation_data/SRTMGL3_version2_SIN
%ls


    

    




/Users/brodzik/projects/CHARIS/elevation_data/SRTMGL3_version2_SIN
00notes.txt                 CHARIS_DEM.v2.0.h24v04.tif
AM_buff_MODIS_SIN.tfw       CHARIS_DEM.v2.0.h24v05.tif
AM_buff_MODIS_SIN.tif       CHARIS_DEM.v2.0.h24v06.tif
CHARIS_DEM.2.0.sin.tif      CHARIS_DEM.v2.0.h25v04.tif
CHARIS_DEM.v2.0.h22v04.tif  CHARIS_DEM.v2.0.h25v05.tif
CHARIS_DEM.v2.0.h22v05.tif  CHARIS_DEM.v2.0.h25v06.tif
CHARIS_DEM.v2.0.h23v04.tif  CHARIS_DEM.v2.0.h26v05.tif
CHARIS_DEM.v2.0.h23v05.tif  CHARIS_DEM.v2.0.h26v06.tif
CHARIS_DEM.v2.0.h23v06.tif  CHARIS_DEM.v2.0.h27v06.tif

In [6]:

    

dem22=read_tile('CHARIS_DEM.v2.0.h22v05.tif')
dem23=read_tile('CHARIS_DEM.v2.0.h23v05.tif')


    

In [7]:

    

np.amin(dem22), np.amax(dem22), np.amin(dem23), np.amax(dem23)


    

    
Out[7]:





(94, 32767, 180, 32767)

In [21]:

    

%cd /Users/brodzik/projects/CHARIS/basins/subbasins_of_major_basins/AM_snow_subs_basins_modis_masks
%ls


    

    




/Users/brodzik/projects/CHARIS/basins/subbasins_of_major_basins/AM_snow_subs_basins_modis_masks
AM_1tile_basins.txt          AM_OBJECTID84_h23v05.tif
AM_2tile_basins.txt          AM_OBJECTID85_h23v05.tif
AM_4tile_basins.txt          AM_OBJECTID86_h23v05.tif
AM_OBJECTID100_h23v05.tif    AM_OBJECTID88_h23v05.tif
AM_OBJECTID62_h22v04.tif     AM_OBJECTID89_h23v05.tif
AM_OBJECTID62_h22v05.tif     AM_OBJECTID90_h23v05.tif
AM_OBJECTID62_h23v04.tif     AM_OBJECTID91_h23v05.tif
AM_OBJECTID62_h23v05.tif     AM_OBJECTID93_h23v05.tif
AM_OBJECTID64_h22v05.tif     AM_OBJECTID94_h23v05.tif
AM_OBJECTID65_h23v04.tif     AM_OBJECTID97_h23v05.tif
AM_OBJECTID65_h23v05.tif     AM_OBJECTID98_h23v05.tif
AM_OBJECTID66_h23v04.tif     AM_OBJECTID99_h23v05.tif
AM_OBJECTID66_h23v05.tif     AM_run_forcings_1strikes.sh
AM_OBJECTID68_h22v04.tif     AmuDarya_snow_subs.cpg
AM_OBJECTID68_h22v05.tif     AmuDarya_snow_subs.dbf
AM_OBJECTID68_h23v04.tif     AmuDarya_snow_subs.prj
AM_OBJECTID68_h23v05.tif     AmuDarya_snow_subs.sbn
AM_OBJECTID69_h22v05.tif     AmuDarya_snow_subs.sbx
AM_OBJECTID69_h23v05.tif     AmuDarya_snow_subs.shp
AM_OBJECTID72_h22v05.tif     AmuDarya_snow_subs.shp.xml
AM_OBJECTID72_h23v05.tif     AmuDarya_snow_subs.shx
AM_OBJECTID77_h23v05.tif     AmuDarya_snow_subs_sinu.dbf
AM_OBJECTID78_h23v05.tif     AmuDarya_snow_subs_sinu.prj
AM_OBJECTID79_h23v05.tif     AmuDarya_snow_subs_sinu.shp
AM_OBJECTID80_h23v05.tif     AmuDarya_snow_subs_sinu.shx
AM_OBJECTID81_h23v05.tif     CHARIS_subbasins_AM.jpg
AM_OBJECTID82_h23v05.tif     mk_masks.sh*
AM_OBJECTID83_h23v05.tif     mk_sinu_versions.sh*

In [22]:

    

basin22 = read_tile('AM_OBJECTID72_h22v05.tif')
basin23 = read_tile('AM_OBJECTID72_h23v05.tif')


    

In [23]:

    

np.amin(basin22), np.amax(basin22), np.amin(basin23), np.amax(basin23)


    

    
Out[23]:





(0, 1, 0, 1)

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fig, ax = plt.subplots(1,2)
ax[0].imshow(data, cmap=plt.cm.gray, vmin=170, vmax=8000, interpolation='None')
ax[0].set_title('SRTMGL3 (v1)')
ax[1].imshow(datav2, cmap=plt.cm.gray, vmin=170, vmax=8000, interpolation='None')
ax[1].set_title('CHARIS_DEM (v2)')
plt.axis('off')
fig.savefig('/Users/brodzik/tmp/SRTMGL3_vs_CHARIS_DEMv2.png')


    

In [ ]:

    

diff = datav2.astype('float') - data.astype('float')
diff[data == -32768] = 0
diff[datav2 == 32767] = 0


    

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print np.amin(diff)
print np.amax(diff)


    

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print(data[1:2,:])


    

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test = np.array([3.2, 5.6, 2.0, 4.4])
test


    

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test / 1.25


    

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new = test / 1.25
new


    

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new = np.array([2.5, 4.5, 1.5, 3.5])
print new * 0.75
print new
print new * 1.25


    

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