Commit 71e36fed authored by Daniel Scheffler's avatar Daniel Scheffler

added first compilation of GeoArray source codes

NOTE: This package was part of the 'py_tools_ds' package until 2017/03/31.
Last commit within py_tools_ds: eef1b4303ba2faed8950f3cd302453129df090e9 (tag 'v20170331_01')
parent 6c784526
......@@ -60,3 +60,6 @@ target/
# pyenv python configuration file
.python-version
# PyCharm settings
.idea/
<component name="InspectionProjectProfileManager">
<profile version="1.0">
<option name="myName" value="Project Default" />
<inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
<option name="ignoredPackages">
<value>
<list size="1">
<item index="0" class="java.lang.String" itemvalue="py_tools_ds" />
</list>
</value>
</option>
</inspection_tool>
<inspection_tool class="PyPep8Inspection" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
<inspection_tool class="PyPep8NamingInspection" enabled="false" level="WEAK WARNING" enabled_by_default="false" />
<inspection_tool class="SpellCheckingInspection" enabled="false" level="TYPO" enabled_by_default="false">
......
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......@@ -6,6 +6,8 @@ Development Lead
----------------
* Daniel Scheffler <danschef@gfz-potsdam.de>
** <http://www.gfz-potsdam.de/en/section/remote-sensing/staff/profil/daniel-scheffler/>
Contributors
------------
......
......@@ -3,3 +3,15 @@
__author__ = """Daniel Scheffler"""
__email__ = 'danschef@gfz-potsdam.de'
__version__ = '0.1.0'
from .baseclasses import GeoArray
from .masks import BadDataMask
from .masks import NoDataMask
from .masks import CloudMask
#__all__=['GeoArray',
# 'BadDataMask',
# 'NoDataMask',
# 'CloudMask'
# ]
This diff is collapsed.
# -*- coding: utf-8 -*-
# -*- coding: utf-8 -*-
__author__='Daniel Scheffler'
import numpy as np
# internal imports
from . import GeoArray
class BadDataMask(GeoArray):
def __init__(self, path_or_array, geotransform=None, projection=None, bandnames=None, nodata=False, progress=True,
q=False):
super(BadDataMask, self).__init__(path_or_array, geotransform=geotransform, projection=projection,
bandnames=bandnames, nodata=nodata, progress=progress, q=q)
if self.is_inmem:
# validate input data - before converting to bool
self._validate_array_values(self.arr)
self.arr = self.arr.astype(np.bool)
# del self._mask_baddata, self.mask_baddata # TODO delete property (requires deleter)
@property
def arr(self):
return self._arr
@arr.setter
def arr(self, ndarray):
assert isinstance(ndarray, np.ndarray), "'arr' can only be set to a numpy array!"
self._validate_array_values(ndarray)
self._arr = ndarray.astype(np.bool)
def _validate_array_values(self, maskarray):
pixelVals_in_mask = sorted(list(np.unique(maskarray)))
assert len(pixelVals_in_mask) <= 2, 'Bad data mask must have only two pixel values (boolean) - 0 and 1 or ' \
'False and True! The given mask for %s contains the values %s.' \
% (self.basename, pixelVals_in_mask)
assert pixelVals_in_mask in [[0, 1], [0],[1], [False, True], [False], [True]],\
'Found unsupported pixel values in the given bad data mask for %s: %s. Only the values True, False, 0 ' \
'and 1 are supported. ' % (self.basename, pixelVals_in_mask)
class NoDataMask(GeoArray):
def __init__(self, path_or_array, geotransform=None, projection=None, bandnames=None, nodata=False, progress=True,
q=False):
super(NoDataMask, self).__init__(path_or_array, geotransform=geotransform, projection=projection,
bandnames=bandnames, nodata=nodata, progress=progress, q=q)
if self.is_inmem:
# validate input data - before converting to bool
self._validate_array_values(self.arr)
self.arr = self.arr.astype(np.bool)
# del self._mask_nodata, self.mask_nodata # TODO delete property (requires deleter)
# TODO disk-mode: init must check the numbers of bands, and ideally also the pixel values in mask
@property
def arr(self):
return self._arr
@arr.setter
def arr(self, ndarray):
assert isinstance(ndarray, np.ndarray), "'arr' can only be set to a numpy array!"
self._validate_array_values(ndarray)
self._arr = ndarray.astype(np.bool)
def _validate_array_values(self, maskarray):
pixelVals_in_mask = sorted(list(np.unique(maskarray)))
assert len(pixelVals_in_mask) <= 2, 'Nodata mask must have only two pixel values (boolean) - 0 and 1 or ' \
'False and True! The given mask for %s contains the values %s.' % (
self.basename, pixelVals_in_mask)
assert pixelVals_in_mask in [[0, 1], [0], [1], [False, True], [False], [True]], \
'Found unsupported pixel values in the given Nodata mask for %s: %s. Only the values True, False, 0 ' \
'and 1 are supported. ' % (self.basename, pixelVals_in_mask)
class CloudMask(GeoArray):
def __init__(self, path_or_array, geotransform=None, projection=None, bandnames=None, nodata=None, progress=True,
q=False):
# TODO implement class definitions and specific metadata
super(CloudMask, self).__init__(path_or_array, geotransform=geotransform, projection=projection,
bandnames=bandnames, nodata=nodata, progress=progress, q=q)
# del self._mask_nodata, self.mask_nodata # TODO delete property (requires deleter)
# TODO check that: "Automatically detected nodata value for CloudMask 'IN_MEM': 1.0"
# -*- coding: utf-8 -*-
__author__='Daniel Scheffler'
import warnings
import numpy as np
from shapely.geometry import box, Polygon
from py_tools_ds.ptds.geo.coord_calc import get_corner_coordinates, calc_FullDataset_corner_positions
from py_tools_ds.ptds.geo.coord_grid import snap_bounds_to_pixGrid
from py_tools_ds.ptds.geo.coord_trafo import mapXY2imXY, transform_any_prj, imXY2mapXY
from py_tools_ds.ptds.geo.projection import prj_equal
from py_tools_ds.ptds.geo.vector.topology import get_overlap_polygon
from py_tools_ds.ptds.numeric.array import get_outFillZeroSaturated
def _clip_array_at_mapPos(arr, mapBounds, arr_gt, band2clip=None, fillVal=0):
# type: (np.ndarray, tuple, tuple, int, int) -> (np.ndarray, tuple)
"""
NOTE: asserts that mapBounds have the same projection like the coordinates in arr_gt
:param arr:
:param mapBounds: xmin, ymin, xmax, ymax
:param arr_gt:
:param band2clip: band index of the band to be returned (full array if not given)
:param fillVal:
:return:
"""
# assertions
assert isinstance(arr_gt, (tuple,list))
assert isinstance(band2clip, int) or band2clip is None
# get array metadata
rows, cols = arr.shape[:2]
bands = arr.shape[2] if len(arr.shape) == 3 else 1
arr_dtype = arr.dtype
ULxy, LLxy, LRxy, URxy = get_corner_coordinates(gt=arr_gt, rows=rows, cols=cols)
arrBounds = ULxy[0], LRxy[1], LRxy[0], ULxy[1]
# snap mapBounds to the grid of the array
mapBounds = snap_bounds_to_pixGrid(mapBounds, arr_gt)
xmin, ymin, xmax, ymax = mapBounds
# get out_gt and out_prj
out_gt = list(arr_gt)
out_gt[0], out_gt[3] = xmin, ymax
# get image area to read
cS, rS = [int(i) for i in mapXY2imXY((xmin, ymax), arr_gt)] # UL
cE, rE = [int(i)-1 for i in mapXY2imXY((xmax, ymin), arr_gt)] # LR
if 0 <= rS <= rows - 1 and 0 <= rE <= rows - 1 and 0 <= cS <= cols - 1 and 0 <= cE <= cols - 1:
"""requested area is within the input array"""
if bands==1:
out_arr = arr[rS:rE + 1, cS:cE + 1]
else:
out_arr = arr[rS:rE + 1, cS:cE + 1, band2clip] if band2clip is not None else arr[rS:rE + 1, cS:cE + 1, :]
else:
"""requested area is not completely within the input array"""
# create array according to size of mapBounds + fill with nodata
tgt_rows = int(abs((ymax - ymin) / arr_gt[5]))
tgt_cols = int(abs((xmax - xmin) / arr_gt[1]))
tgt_bands = bands if band2clip is None else 1
tgt_shape = (tgt_rows, tgt_cols, tgt_bands) if tgt_bands > 1 else (tgt_rows, tgt_cols)
try:
fillVal = fillVal if fillVal is not None else get_outFillZeroSaturated(arr)[0]
out_arr = np.full(tgt_shape, fillVal, arr_dtype)
except MemoryError:
raise MemoryError('Calculated target dimensions are %s. Check your inputs!' %str(tgt_shape))
# calculate image area to be read from input array
overlap_poly = get_overlap_polygon(box(*arrBounds), box(*mapBounds))['overlap poly']
assert overlap_poly, 'The input array and the requested geo area have no spatial overlap.'
xmin_in, ymin_in, xmax_in, ymax_in = overlap_poly.bounds
cS_in, rS_in = [int(i) for i in mapXY2imXY((xmin_in, ymax_in), arr_gt)]
cE_in, rE_in = [int(i)-1 for i in mapXY2imXY((xmax_in, ymin_in), arr_gt)] # -1 because max values do not represent pixel origins
# read a subset of the input array
if bands == 1:
data = arr[rS_in:rE_in + 1, cS_in:cE_in + 1]
else:
data = arr[rS_in:rE_in + 1, cS_in:cE_in + 1, band2clip] if band2clip is not None else \
arr[rS_in:rE_in + 1, cS_in:cE_in + 1, :]
# calculate correct area of out_arr to be filled and fill it with read data from input array
cS_out, rS_out = [int(i) for i in mapXY2imXY((xmin_in, ymax_in), out_gt)]
cE_out, rE_out = [int(i)-1 for i in mapXY2imXY((xmax_in, ymin_in), out_gt)] # -1 because max values do not represent pixel origins
# fill newly created array with read data from input array
if tgt_bands==1:
out_arr[rS_out:rE_out + 1, cS_out:cE_out + 1] = data
else:
out_arr[rS_out:rE_out + 1, cS_out:cE_out + 1,:] = data
return out_arr, out_gt
def get_array_at_mapPosOLD(arr, arr_gt, arr_prj, mapBounds, mapBounds_prj, band2get=None, fillVal=0):
# FIXME mapBounds_prj should not be handled as target projection
"""
:param arr:
:param arr_gt:
:param arr_prj:
:param mapBounds: xmin, ymin, xmax, ymax
:param mapBounds_prj:
:param band2get: band index of the band to be returned (full array if not given)
:param fillVal:
:return:
"""
#[print(i,'\n') for i in [arr, arr_gt, arr_prj, mapBounds, mapBounds_prj]]
# check if requested bounds have the same projection like the array
samePrj = prj_equal(arr_prj, mapBounds_prj)
if samePrj:
out_prj = arr_prj
out_arr, out_gt = _clip_array_at_mapPos(arr, mapBounds, arr_gt, band2clip=band2get, fillVal=fillVal)
else:
# calculate requested corner coordinates in the same projection like the input array (bounds are not sufficient due to projection rotation)
xmin, ymin, xmax, ymax = mapBounds
ULxy, URxy, LRxy, LLxy = (xmin, ymax), (xmax, ymax), (xmax, ymin), (xmin, ymin)
ULxy, URxy, LRxy, LLxy = [transform_any_prj(mapBounds_prj, arr_prj, *xy) for xy in [ULxy, URxy, LRxy, LLxy]]
mapBounds_arrPrj = Polygon([ULxy, URxy, LRxy, LLxy]).buffer(arr_gt[1]).bounds
# read subset of input array as temporary data (that has to be reprojected later)
temp_arr, temp_gt = _clip_array_at_mapPos(arr, mapBounds_arrPrj, arr_gt, band2clip=band2get, fillVal=fillVal)
# eliminate no data area for faster warping
try:
oneBandArr = np.all(np.where(temp_arr == fillVal, 0, 1), axis=2) \
if len(temp_arr.shape) > 2 else np.where(temp_arr == fillVal, 0, 1)
corners = [(i[1], i[0]) for i in
calc_FullDataset_corner_positions(oneBandArr, assert_four_corners=False)]
bounds = [int(i) for i in Polygon(corners).bounds]
cS, rS, cE, rE = bounds
temp_arr = temp_arr[rS:rE + 1, cS:cE + 1]
temp_gt[0], temp_gt[3] = [int(i) for i in imXY2mapXY((cS, rS), temp_gt)]
except:
warnings.warn('Could not eliminate no data area for faster warping. '
'Result will not be affected but processing takes a bit longer..')
#from matplotlib import pyplot as plt
#plt.figure()
#plt.imshow(temp_arr[:,:])
# calculate requested geo bounds in the target projection, snapped to the output array grid
mapBounds = snap_bounds_to_pixGrid(mapBounds, arr_gt)
xmin, ymin, xmax, ymax = mapBounds
out_gt = list(arr_gt)
out_gt[0], out_gt[3] = xmin, ymax
out_rows = int(abs((ymax - ymin) / arr_gt[5]))
out_cols = int(abs((xmax - xmin) / arr_gt[1])) # FIXME using out_gt and outRowsCols is a workaround for not beeing able to pass output extent in the OUTPUT projection
# reproject temporary data to target projection (the projection of mapBounds)
from py_tools_ds.ptds.geo.raster.reproject import warp_ndarray
out_arr, out_gt, out_prj = warp_ndarray(temp_arr, temp_gt, arr_prj, mapBounds_prj,
in_nodata=fillVal, out_nodata=fillVal, out_gt=out_gt,
outRowsCols=(out_rows, out_cols), outExtent_within=True,rsp_alg=0) # FIXME resampling alg
return out_arr, out_gt, out_prj
def get_array_at_mapPos(arr, arr_gt, arr_prj, out_prj, mapBounds, mapBounds_prj=None, out_gsd=None, band2get=None,
fillVal=0, rspAlg='near', progress=True):
# type: (np.ndarray, tuple, str, str, tuple, str, tuple, int, int, str, bool) -> (np.ndarray, tuple, str)
"""
:param arr:
:param arr_gt:
:param arr_prj:
:param out_prj: output projection as WKT string
:param mapBounds: xmin, ymin, xmax, ymax
:param mapBounds_prj: the projection of the given map bounds (default: output projection)
:param out_gsd: (X,Y)
:param band2get: band index of the band to be returned (full array if not given)
:param fillVal:
:param rspAlg: <str> Resampling method to use. Available methods are:
near, bilinear, cubic, cubicspline, lanczos, average, mode, max, min, med, q1, q2
:param progress:
:return:
"""
# check if reprojection is needed
mapBounds_prj = mapBounds_prj if mapBounds_prj else out_prj
samePrj = prj_equal(arr_prj, out_prj)
if samePrj:
# output array is requested in the same projection like input array => no reprojection needed
# mapBounds are expected to have the same projection like the input array
if not prj_equal(arr_prj, mapBounds_prj):
xmin, ymin, xmax, ymax = mapBounds
(xmin, ymin), (xmax, ymax) = \
[transform_any_prj(mapBounds_prj, arr_prj, X, Y) for X,Y in [(xmin, ymin), (xmax, ymax)]]
mapBounds = xmin, ymin, xmax, ymax
out_prj = arr_prj
out_arr, out_gt = _clip_array_at_mapPos(arr, mapBounds, arr_gt, band2clip=band2get, fillVal=fillVal)
else:
# output array is requested in another projection => reprojection needed
# calculate requested geo bounds in the target projection, snapped to the output array grid
mapBounds = snap_bounds_to_pixGrid(mapBounds, arr_gt)
arr = arr[:,:,band2get] if band2get else arr[:] # also converts GeoArray to numpy.ndarray
from py_tools_ds.ptds.geo.raster.reproject import warp_ndarray
out_arr, out_gt, out_prj = \
warp_ndarray(arr, arr_gt, arr_prj, out_prj=out_prj, out_bounds=mapBounds, out_bounds_prj=mapBounds_prj,
in_nodata=fillVal, out_nodata=fillVal, rspAlg=rspAlg, out_gsd=out_gsd, progress=progress)
return out_arr, out_gt, out_prj
......@@ -10,7 +10,8 @@ with open('HISTORY.rst') as history_file:
history = history_file.read()
requirements = [
# TODO: put package requirements here
'numpy', 'matplotlib', 'six', 'gdal', 'shapely', 'geopandas', 'py_tools_ds', 'dill', 'mpld3', 'geojson', 'folium',
'holoviews'
]
test_requirements = [
......
......@@ -12,7 +12,7 @@ Tests for `geoarray` module.
import sys
import unittest
from geoarray import geoarray
from geoarray import GeoArray
......
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