58 lines
1.6 KiB
Python
58 lines
1.6 KiB
Python
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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# \file dfc_lfsdaps.py
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# \brief TODO
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# \author Florent Guiotte <florent.guiotte@gmail.com>
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# \version 0.1
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# \date 28 août 2018
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#
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# TODO details
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import numpy as np
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import sys
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sys.path.append('..')
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import ld2dap
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# TODO: Add param percentile?
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dispatcher = {
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'mean': np.mean, # Arithmetic mean
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'median': np.median, # Median
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'average': np.average, # Weighted average (=mean ?)
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'std': np.std, # Standard deviation
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'var': np.var, # Variance
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'amax': np.amax, # Maximum
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'amin': np.amin, # Minimum
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'ptp': np.ptp, # Range of values (max - min)
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}
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def run(rasters, treshold=1e4, areas=None, sd=None, moi=None, features=['mean'], patch_size=3):
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# Parse parameters type
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treshold = float(treshold)
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areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
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sd = None if sd is None else np.array(sd).astype(np.float)
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moi = None if moi is None else np.array(moi).astype(np.float)
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patch_size = int(patch_size)
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features = [dispatcher[x] for x in features]
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# Pipelines
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loader = ld2dap.LoadTIFF(rasters)
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dfc_filter = ld2dap.Treshold(treshold)
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dfc_filter.input = loader
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sdaps = ld2dap.SelfDualAttributeProfiles(area=areas, sd=sd, moi=moi)
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sdaps.input = dfc_filter
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local_features = ld2dap.LocalFeatures(features, patch_size)
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local_features.input = sdaps
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out_vectors = ld2dap.RawOutput()
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out_vectors.input = local_features
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# Compute vectors
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out_vectors.run()
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return out_vectors.data
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def version():
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return 'v0.0'
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