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47 lines
1.0 KiB
Python
47 lines
1.0 KiB
Python
7 years ago
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# -*- coding: utf-8 -*-
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# Preamble
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import ee
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import matplotlib.pyplot as plt
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import matplotlib.cm as cm
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import numpy as np
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import pandas as pd
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from datetime import datetime
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import pickle
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import pdb
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import pytz
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from pylab import ginput
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import scipy.io as sio
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import scipy.interpolate
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import os
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# image processing modules
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import skimage.filters as filters
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import skimage.exposure as exposure
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import skimage.transform as transform
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import sklearn.decomposition as decomposition
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import skimage.morphology as morphology
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import skimage.measure as measure
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# my functions
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import functions.utils as utils
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import functions.sds as sds
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np.seterr(all='ignore') # raise/ignore divisions by 0 and nans
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ee.Initialize()
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with open('data\wl_final.pkl', 'rb') as f:
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wl = pickle.load(f)
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i = 0
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x = wl[i]['quad_data']['x']
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y = wl[i]['quad_data']['y']
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z = wl[i]['quad_data']['z']
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x = x.reshape(x.shape[0] * x.shape[1])
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y = y.reshape(y.shape[0] * y.shape[1])
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z = z.reshape(z.shape[0] * z.shape[1])
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idx_nan = np.isnan(z)
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x = x[~idx_nan]
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y = y[~idx_nan]
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z = z[~idx_nan]
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