def frequencies(r, excludeNoData=True):
"""
Return frequencies table
"""
import numpy as np
from osgeo import gdal
from gasp.g.prop.img import get_nd
if type(r).__name__ == 'str':
img = gdal.Open(r)
arr = img.ReadAsArray()
elif type(r).__name__ == 'Dataset':
img = r
arr = img.ReadAsArray()
else:
img = None
arr = r
unique = list(np.unique(arr))
one_arr = arr.reshape(arr.shape[0] * arr.shape[1])
freq = np.bincount(one_arr)
freq = freq[freq != 0]
if excludeNoData:
if type(r).__name__ == 'str' or type(r).__name__ == 'Dataset':
ndval = get_nd(img)
return {unique[i] : freq[i] for i in range(len(unique)) if unique[i] != ndval}
else:
return {unique[i] : freq[i] for i in range(len(unique))}
else:
return {unique[i] : freq[i] for i in range(len(unique))}
def resample_by_majority(refrst, valrst, out_rst):
"""
Resample valrst based on refrst:
Get Majority value of valrst for each cell in refrst
Useful when ref raster has cellsize greater
than value raster.
TODO: Valrst must be of int type
"""
import numpy as np
from osgeo import gdal
from gasp.g.prop.img import get_cell_size, get_nd
from gasp.gt.torst import obj_to_rst
# Data to Array
if type(refrst) == gdal.Dataset:
refsrc = refrst
else:
refsrc = gdal.Open(refrst)
if type(valrst) == gdal.Dataset:
valsrc = valrst
else:
valsrc = gdal.Open(valrst)
refnum = refsrc.ReadAsArray()
valnum = valsrc.ReadAsArray()
# Get Ref shape
ref_shape = refnum.shape
# in a row, how many cells valnum are for each refnum cell
refcs = int(get_cell_size(refsrc)[0])
valcs = int(get_cell_size(valsrc)[0])
dcell = int(refcs / valcs)
# Valnum must be of int type
# Create generalized/resampled raster
resnum = np.zeros(ref_shape, dtype=valnum.dtype)
for row in range(ref_shape[0]):
for col in range(ref_shape[1]):
resnum[row, col] = np.bincount(
valnum[row*dcell:row*dcell+dcell, col*dcell : col*dcell+dcell].reshape(dcell*dcell)
).argmax()
# Export out raster
return obj_to_rst(resnum, out_rst, refsrc, noData=get_nd(valsrc))
def gdal_mapcalc(expression,
exp_val_paths,
outRaster,
template_rst,
outNodata=-99999):
"""
GDAL Raster Calculator
TODO: Check if rasters dimensions are equal
"""
import numpy as np
import os
from osgeo import gdal, osr
from gasp.gt.prop.ff import drv_name
from py_expression_eval import Parser
from gasp.g.prop.img import get_nd
from gasp.gt.torst import obj_to_rst
parser = Parser()
EXPRESSION = parser.parse(expression)
evalValue = {}
noDatas = {}
for x in EXPRESSION.variables():
img = gdal.Open(exp_val_paths[x])
arr = img.ReadAsArray().astype(float)
evalValue[x] = arr
noDatas[x] = get_nd(img)
result = EXPRESSION.evaluate(evalValue)
for v in noDatas:
np.place(result, evalValue[v] == noDatas[v], outNodata)
# Write output and return
return obj_to_rst(result, outRaster, template_rst, noData=outNodata)
def get_nodata(r):
"""
Returns the value defining NoData in a Raster file
API'S Available:
* gdal;
"""
gisApi = 'gdal'
if gisApi == 'gdal':
from gasp.g.prop.img import get_nd
from osgeo import gdal
img = gdal.Open(r)
ndVal = get_nd(img)
else:
raise ValueError('The api {} is not available'.format(gisApi))
return ndVal
def rcls_rst(inrst, rclsRules, outrst, api='gdal', maintain_ext=True):
"""
Reclassify a raster (categorical and floating points)
if api == 'gdal
rclsRules = {
1 : 99,
2 : 100
...
}
or
rclsRules = {
(0, 8) : 1
(8, 16) : 2
'*' : 'NoData'
}
elif api == grass:
rclsRules should be a path to a text file
"""
if api == 'gdal':
import numpy as np
import os
from osgeo import gdal
from gasp.gt.torst import obj_to_rst
from gasp.g.fm import imgsrc_to_num
from gasp.g.prop.img import get_nd
if not os.path.exists(inrst):
raise ValueError('File {} does not exist!'.format(inrst))
# Open Raster
img = gdal.Open(inrst)
# Raster to Array
rst_num = imgsrc_to_num(img)
nodataVal = get_nd(img)
rcls_num = np.full(rst_num.shape, 255, dtype=np.uint8)
# Change values
for k in rclsRules:
if rclsRules[k] == 'NoData':
continue
if type(k) == str:
continue
elif type(k) == tuple:
q = (rst_num > k[0]) & (rst_num <= k[1])
else:
q = rst_num == k
np.place(rcls_num, q, rclsRules[k])
if '*' in rclsRules and rclsRules['*'] != 'NoData':
np.place(rcls_num, rcls_num == 255, rclsRules['*'])
if 'NoData' in rclsRules and rclsRules['NoData'] != 'NoData':
np.place(rcls_num, rst_num == nodataVal, rclsRules['NoData'])
if not maintain_ext:
from gasp.g.nop.rshp import rshp_to_data
left, cellx, z, top, c, celly = img.GetGeoTransform()
clip_rcls, n_left, n_top = rshp_to_data(rcls_num, 255, left, cellx,
top, celly)
return obj_to_rst(clip_rcls,
outrst,
img,
noData=255,
geotrans=(n_left, cellx, z, n_top, c, celly))
else:
return obj_to_rst(rcls_num, outrst, img, noData=255)
elif api == "pygrass":
from grass.pygrass.modules import Module
r = Module('r.reclass',
input=inrst,
output=outrst,
rules=rclsRules,
overwrite=True,
run_=False,
quiet=True)
r()
else:
raise ValueError(("API {} is not available").format(api))
def floatrst_to_intrst(in_rst, out_rst):
"""
Raster with float data to Raster with Integer Values
"""
import numpy as np
from osgeo import gdal
from gasp.g.prop.img import get_nd
from gasp.gt.torst import obj_to_rst
nds = {
'int8': -128,
'int16': -32768,
'int32': -2147483648,
'uint8': 255,
'uint16': 65535,
'uint32': 4294967295
}
# Open Raster
img = gdal.Open(in_rst)
# Raster to Array
rstnum = img.ReadAsArray()
# Round data
rstint = np.around(rstnum, decimals=0)
# Get min and max
tstmin = rstint.min()
tstmax = rstint.max()
try:
nd = int(round(get_nd(img), 0))
except:
nd = None
if tstmin == nd:
np.place(rstint, rstint == nd, np.nan)
rstmin = rstint.min()
rstmax = tstmax
else:
rstmin = tstmin
if tstmax == nd:
np.place(rstint, rstint == nd, np.nan)
rstmax = rstint.max()
else:
rstmax = tstmax
# Get dtype for output raster
if rstmin < 0:
if rstmin <= -128:
if rstmin <= -32768:
tmin = 'int32'
else:
tmin = 'int16'
else:
tmin = 'int8'
else:
tmin = 'u'
if tmin == 'u':
if rstmax >= 255:
if rstmax >= 65535:
tmax = 'uint32'
else:
tmax = 'uint16'
else:
tmax = 'uint8'
else:
if tmin == 'int8':
if rstmax >= 127:
if rstmax >= 32767:
tmax = 'int32'
else:
tmax = 'int16'
else:
tmax = 'int8'
elif tmin == 'int16':
if rstmax >= 32767:
tmax = 'int32'
else:
tmax = 'int16'
else:
tmax = 'int32'
if tmax == 'int8':
nt = np.int8
elif tmax == 'int16':
nt = np.int16
elif tmax == 'int32':
nt = np.int32
elif tmax == 'uint8':
nt = np.uint8
elif tmax == 'uint16':
nt = np.uint16
else:
nt = np.uint32
# Get nodata for new raster
new_nd = nds[tmax]
# Place NoData value
np.nan_to_num(rstint, copy=False, nan=new_nd)
# Convert array type to integer
rstint = rstint.astype(nt)
# Export result to file and return
return obj_to_rst(rstint, out_rst, img, noData=new_nd)