#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_lfaps.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 27 août 2018
#
# TODO details

import numpy as np

import sys
sys.path.append('..')
import ld2dap

# TODO: Add param percentile?

dispatcher = {
        'mean': np.mean, # Arithmetic mean
        'median': np.median, # Median
        'average': np.average, # Weighted average (=mean ?)
        'std': np.std, # Standard deviation
        'var': np.var, # Variance
        'amax': np.amax, # Maximum
        'amin': np.amin, # Minimum
        'ptp': np.ptp, # Range of values (max - min)
        }

def run(rasters, treshold=1e4, areas=None, sd=None, moi=None, features=['mean'], patch_size=3):
    # Parse parameters type
    treshold = float(treshold)
    areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
    sd = None if sd is None else np.array(sd).astype(np.float)
    moi = None if moi is None else np.array(moi).astype(np.float)
    patch_size = int(patch_size)
    features = [dispatcher[x] for x in features]

    # Pipelines
    loader = ld2dap.LoadTIFF(rasters)
    dfc_filter = ld2dap.Treshold(treshold)
    dfc_filter.input = loader
    aps = ld2dap.AttributeProfiles(area=areas, sd=sd, moi=moi)
    aps.input = dfc_filter
    local_features = ld2dap.LocalFeatures(features, patch_size)
    local_features.input = aps
    out_vectors = ld2dap.RawOutput()
    out_vectors.input = local_features

    # Compute vectors
    out_vectors.run()

    return out_vectors.data

def version():
    return 'v0.0'