v0lat1le

import lldb
import lldb.formatters.Logger


def templateParams(s):  
    depth = 0
    start = s.find('<') + 1
    result = []
    for i, c in enumerate(s[start:], start):
        if c == '<':

v0lat1le

import rasterio
import ctypes

_gdal = ctypes.cdll.LoadLibrary('libgdal.so.1')
OSRNewSpatialReference = _gdal.OSRNewSpatialReference
OSRIsGeographic = _gdal.OSRIsGeographic
OSRIsGeographic.restype = ctypes.c_bool
OSRGetSemiMajor = _gdal.OSRGetSemiMajor
OSRGetSemiMajor.restype = ctypes.c_double

v0lat1le

class GeoTiffBandArrayWrapper(xray.core.utils.NdimSizeLenMixin):
    def __init__(self, raster, band):
        self._band = raster.GetRasterBand(band)     
        self.dtype = {gdalconst.GDT_Int16: numpy.int16}[self._band.DataType]
        self.shape = (raster.RasterYSize, raster.RasterXSize)
        
    def __array__(self, dtype=None):
        return self._band.ReadAsArray()

    def __getitem__(self, key):

v0lat1le

    def get_descriptor(query=None):
            # descriptor = {
            #     'LS5TM': { # storage_type identifier
            #          'dimensions': ['x', 'y', 't'],
            #          'variables': { # These will be the variables which can be accessed as arrays
            #                'B10': {
            #                     'datatype': 'int16',
            #                     'nodata_value': -999
            #                     },

v0lat1le

import re
from collections import namedtuple

MGRS = namedtuple('MGRS', ['zone', 'band', 'col', 'row', 'east', 'north'])
UTM = namedtuple('UTM', ['zone', 'band', 'east', 'north'])

def idx(ch):
    idx = ord(ch)-ord('A')
    if ch > 'O': idx -= 1 # skip 'O'
    if ch > 'I': idx -= 1 # skip 'I'

v0lat1le

import numpy


def argpercentile(a, q, axis=0):
    """
    Compute the index of qth percentile of the data along the specified axis.

    Returns the index of qth percentile of the array elements.

    Parameters