def create_gcp_list(latitude, longitude, rescaling_coef=1.0):
n_gcp = 150 # Maximum allow GCPs
percentage_gcp_per_line = 0.2
latitude_ds = gdal.OpenShared(str(latitude))
longitude_ds = gdal.OpenShared(str(longitude))
lat = (latitude_ds.GetRasterBand(1)).ReadAsArray().astype(np.float32)
lon = (longitude_ds.GetRasterBand(1)).ReadAsArray().astype(np.float32)
gcp_list_o = []
pas_pixel = np.int(latitude_ds.RasterXSize * percentage_gcp_per_line) + 1
pas_line = np.int((latitude_ds.RasterYSize * latitude_ds.RasterXSize) /
(n_gcp * pas_pixel)) + 1
print latitude_ds.RasterXSize / pas_pixel, ' ', latitude_ds.RasterYSize / pas_line
k = 0
for line in range(0, latitude_ds.RasterYSize - 1, pas_line):
for px in range(0, latitude_ds.RasterXSize - 1, pas_pixel):
gcp = gdal.GCP(
np.multiply(np.double(lon[line][px]), rescaling_coef),
np.multiply(np.double(lat[line][px]), rescaling_coef), 0, (px),
(line))
gcp_list_o.append(gcp)
k = k + 1
latitude_ds = None
longitude_ds = None
return gcp_list_o #Gdal osgeo gcp object
def add_band(src_file, src_add, option="COMPRESS=DEFLATE"):
"""
adding a band/bands to an existing file
just working if the files have the same extent, resolution and nr of pixel
add_band(src_file, file_to_add) (bands will be added to src_file)
"""
#pointer/open to files
src_ds = gdal.OpenShared(src_file)
add_ds = gdal.OpenShared(src_add)
#check extent and resolution and ...
src_ext = get_extent(src_file)
add_ext = get_extent(src_add)
if src_ext.ret_extent() != add_ext.ret_extent():
print("Error in extent, the files are not equal in extent/resolution/pixel\nnot able to perform the function")
print("src_file:", src_ext.ret_extent())
print("src_add:", add_ext.ret_extent())
else:
#get band counts for the rasters
src_bands_count = src_ds.RasterCount
add_bands_count = add_ds.RasterCount
#create copy of orig in RAM
tmp_ds = gdal.GetDriverByName('MEM').CreateCopy('', src_ds, 0)
#add all bands
del src_ds
for bands2add in range(1,add_bands_count+1):
add_b = add_ds.GetRasterBand(bands2add).ReadAsArray()
tmp_ds.AddBand()
tmp_ds.GetRasterBand(src_bands_count+bands2add).WriteArray(add_b)
#write / overwrite file to disk
gdal.GetDriverByName('GTiff').CreateCopy(src_file, tmp_ds, 0, options=[option]) #CreateCopy(output_path, data2write)
del tmp_ds, add_b, add_ds
def __getitem__(self, idx):
# Get the number n of workers and the current worker's id
info = torch.utils.data.get_worker_info()
# Open the data with gdal n times in multithread shared mode
# The operation is done once
if not self.done:
raster_path = self.raster.get('reader', self.raster['path'])
self.logger.info(f"Single time load of raster: [{raster_path}]")
for _ in range(info.num_workers):
raster_ds = gdal.OpenShared(raster_path, gdal.GA_ReadOnly)
self.raster_dss.append(raster_ds)
self.done = True
# Do your processing with the gdal dataset associated with the worker's id
image = []
patch = self.samples[idx]
for raster_band in self.raster["bands"]:
image.append(self.raster_dss[info.id].GetRasterBand(raster_band).ReadAsArray(*patch))
image = np.dstack(image)
offsets = patch[:2]
half_size = self.patch_size // 2
sample = {
self.image_key: np.array(image.data, copy=True, dtype='float32'),
self.center_key: (offsets[0] + half_size, offsets[1] + half_size),
}
if self.transforms:
sample = self.transforms(sample)
return sample
def __init__(self, raster_path, raster_bands, patch_size, transforms=None, image_key="image"):
super().__init__(transforms=transforms)
self.logger.debug("Creating %s with [%s]", type(self).__name__, raster_path)
self.image_key = image_key
self.center_key = "center"
self.raster_dss = []
# update raster metadata that can be used by other objects
self.raster = {"path": raster_path, "bands": raster_bands}
raster_ds = gdal.OpenShared(raster_path, gdal.GA_ReadOnly)
parse_raster_metadata(self.raster, raster_ds)
xsize = raster_ds.RasterXSize
ysize = raster_ds.RasterYSize
self.patch_size = patch_size
self.raster["xsize"] = xsize
self.raster["ysize"] = ysize
self.raster["georef"] = raster_ds.GetProjectionRef()
self.raster["affine"] = raster_ds.GetGeoTransform()
raster_ds = None # noqa # flush dataset
# generate patch sample locations
lines = ysize - self.patch_size
cols = xsize - self.patch_size
self.samples = []
for y in range(lines):
for x in range(cols):
self.samples.append((x, y, self.patch_size, self.patch_size))
self.n_samples = len(self.samples)
self.logger.info(f"Number of samples: {self.n_samples}")
self.done = False
def pixfun_inv_c():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_inv_c.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cint_sar.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata = refds.GetRasterBand(1).ReadAsArray()
refdata = refdata.astype('complex')
delta = data - 1. / refdata
if not numpy.alltrue(abs(delta.real) < 1e-13):
return 'fail'
if not numpy.alltrue(abs(delta.imag) < 1e-13):
return 'fail'
return 'success'
def raster_to_csv(InRaster, OutCSV):
# open the raster and get some properties
ds = gdal.OpenShared(InRaster, gdalconst.GA_ReadOnly)
GeoTrans = ds.GetGeoTransform()
ColRange = range(ds.RasterXSize)
RowRange = range(ds.RasterYSize)
rBand = ds.GetRasterBand(1) # first band
nData = rBand.GetNoDataValue()
if nData == None:
nData = np.nan # set it to something if not set
else:
print("NoData value is {0}".format(nData))
# specify the centre offset
HalfX = GeoTrans[1] / 2
HalfY = GeoTrans[5] / 2
with open(OutCSV, 'w') as CSVwrite:
for ThisRow in RowRange:
RowData = rBand.ReadAsArray(0, ThisRow, ds.RasterXSize, 1)[0]
for ThisCol in ColRange:
if RowData[ThisCol] != nData:
if RowData[ThisCol] > -1000:
X = GeoTrans[0] + (ThisCol * GeoTrans[1])
Y = GeoTrans[3] + (ThisRow * GeoTrans[5]
) # Y is negative so it's a minus
# this gives the upper left of the cell, offset by half a cell to get centre
X += HalfX
Y += HalfY
CSVwrite.write('{0},{1},{2}\n'.format(
X, Y, RowData[ThisCol]
)) # I think newline might be different on linux
def raster2gpd(InRaster, feature_name, band=1, nodataval=-9999):
'''
Description:
Takes the path of a raster (.tiff) file and produces a Geopandas Data Frame.
Params:
- InRaster: the path of the input raster file
- feature_name: the name of the feature represented by the pixel values
'''
# open the raster and get some properties
ds = gdal.OpenShared(InRaster, gdalconst.GA_ReadOnly)
GeoTrans = ds.GetGeoTransform()
ColRange = range(ds.RasterXSize)
RowRange = range(ds.RasterYSize)
rBand = ds.GetRasterBand(band) # first band
nData = rBand.GetNoDataValue()
if nData == None:
logging.info(f"No nodataval found, setting to {nodataval}")
nData = np.float32(nodataval) # set it to something if not set
else:
logging.info(f"Nodataval is: {nData}")
# specify the center offset (takes the point in middle of pixel)
HalfX = GeoTrans[1] / 2
HalfY = GeoTrans[5] / 2
# Check that NoDataValue is of the same type as the raster data
RowData = rBand.ReadAsArray(0, 0, ds.RasterXSize, 1)[0]
if type(nData) != type(RowData[0]):
logging.warning(
f"NoData type mismatch: NoDataValue is type {type(nData)} and raster data is type {type(RowData[0])}"
)
points = []
for ThisRow in RowRange:
RowData = rBand.ReadAsArray(0, ThisRow, ds.RasterXSize, 1)[0]
for ThisCol in ColRange:
# need to exclude NaN values since there is no nodataval
if (RowData[ThisCol] != nData) and not (np.isnan(
RowData[ThisCol])):
# TODO: implement filters on valid pixels
# for example, the below would ensure pixel values are between -100 and 100
#if (RowData[ThisCol] <= 100) and (RowData[ThisCol] >= -100):
X = GeoTrans[0] + (ThisCol * GeoTrans[1])
Y = GeoTrans[3] + (ThisRow * GeoTrans[5]
) # Y is negative so it's a minus
# this gives the upper left of the cell, offset by half a cell to get centre
X += HalfX
Y += HalfY
points.append(
[Point(X, Y), X, Y, RowData[ThisCol], feature_name])
return gpd.GeoDataFrame(points,
columns=[
'geometry', 'longitude', 'latitude',
'feature_value', 'feature_name'
])
def radarGeometryTransformer(latfile, lonfile, epsg=4326):
'''
Create a coordinate transformer to convert map coordinates to radar image line/pixels.
'''
driver = gdal.GetDriverByName('VRT')
inds = gdal.OpenShared(latfile, gdal.GA_ReadOnly)
tempds = driver.Create('', inds.RasterXSize, inds.RasterYSize, 0)
inds = None
tempds.SetMetadata(
{
'SRS': 'EPSG:{0}'.format(epsg),
'X_DATASET': lonfile,
'X_BAND': '1',
'Y_DATASET': latfile,
'Y_BAND': '1',
'PIXEL_OFFSET': '0',
'LINE_OFFSET': '0',
'PIXEL_STEP': '1',
'LINE_STEP': '1'
}, 'GEOLOCATION')
trans = gdal.Transformer(tempds, None, ['METHOD=GEOLOC_ARRAY'])
return trans
def pixfun_imag_c():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_imag_c.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cint_sar.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata = refds.GetRasterBand(1).ReadAsArray()
if not numpy.alltrue(data == refdata.imag):
gdaltest.post_reason('fail')
return 'fail'
# Test bugfix of #6599
copied_ds = gdal.Translate('', filename, format='MEM')
data_ds = copied_ds.GetRasterBand(1).ReadAsArray()
copied_ds = None
if not numpy.alltrue(data == data_ds):
gdaltest.post_reason('fail')
return 'fail'
return 'success'
def pixfun_mul_r():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_mul_r.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
if numpy_available:
refdata = numpy.ones(data.shape, 'float')
for reffilename in ('data/uint16.tif', 'data/int32.tif',
'data/float32.tif'):
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' %
reffilename)
return 'fail'
refdata *= refds.GetRasterBand(1).ReadAsArray()
if not numpy.alltrue(data == refdata):
return 'fail'
return 'success'
def pixfun_dB2pow():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_dB2pow.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/float32.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata = refds.GetRasterBand(1).ReadAsArray()
refdata = refdata.astype('float64')
#if not numpy.allclose(data, 10.**(refdata/10.)):
if not numpy.alltrue(data == 10.**(refdata / 10.)):
return 'fail'
return 'success'
def pixfun_cmul_r():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_cmul_r.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/uint16.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata1 = refds.GetRasterBand(1).ReadAsArray()
refdata1 = refdata1.astype('float64')
reffilename = 'data/int32.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata2 = refds.GetRasterBand(1).ReadAsArray()
refdata2 = refdata2.astype('float64')
if not numpy.alltrue(data == refdata1 * refdata2.conj()):
return 'fail'
return 'success'
def pixfun_diff_c():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_diff_c.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cint_sar.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata1 = refds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cfloat64.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata2 = refds.GetRasterBand(1).ReadAsArray(0, 0, 5, 6)
if not numpy.alltrue(data == refdata1 - refdata2):
return 'fail'
return 'success'
def pixfun_sum_c():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_sum_c.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
if numpy_available:
refdata = numpy.zeros(data.shape, 'complex')
for reffilename in ('data/uint16.tif', 'data/cint_sar.tif',
'data/cfloat64.tif'):
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' %
reffilename)
return 'fail'
refdata += refds.GetRasterBand(1).ReadAsArray(0, 0, 5, 6)
if not numpy.alltrue(data == refdata):
return 'fail'
return 'success'
def pixfun_phase_c():
if not numpy_available:
return 'skip'
filename = 'data/pixfun_phase_c.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
if ds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % filename)
return 'fail'
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cint_sar.tif'
refds = gdal.Open(reffilename)
if refds is None:
gdaltest.post_reason('Unable to open "%s" dataset.' % reffilename)
return 'fail'
refdata = refds.GetRasterBand(1).ReadAsArray()
refdata = refdata.astype('complex128')
if not numpy.allclose(data, numpy.arctan2(refdata.imag, refdata.real)):
print(data - numpy.arctan2(refdata.imag, refdata.real))
return 'fail'
return 'success'
def vrtfilt_3():
ds = gdal.OpenShared('data/rgbsmall.tif')
vrt_ds = gdal.GetDriverByName('VRT').CreateCopy('', ds)
ds = None
filterSourceXML = """ <KernelFilteredSource>
<SourceFilename>data/rgbsmall.tif</SourceFilename>
<SourceBand>1</SourceBand>
<SrcRect xOff="0" yOff="0" xSize="50" ySize="50"/>
<DstRect xOff="0" yOff="0" xSize="50" ySize="50"/>
<Kernel>
<Size>3</Size>
<Coefs>0.111111 0.111111 0.111111 0.111111 0.111111 0.111111 0.111111 0.111111 0.111111</Coefs>
</Kernel>
</KernelFilteredSource>"""
try:
vrt_ds.GetRasterBand(1).SetMetadataItem
except:
return 'skip'
vrt_ds.GetRasterBand(1).SetMetadataItem('source_0', filterSourceXML, 'vrt_sources')
if vrt_ds.GetRasterBand(1).Checksum() != 21890:
return 'fail'
return 'success'
def raster2gpd(InRaster,feature_name,band=1,nodataval=-9999):
'''
Description:
Takes the path of a raster (.tiff) file and produces a Geopandas Data Frame.
Params:
- InRaster: the path of the input raster file
- feature_name: the name of the feature represented by the pixel values
'''
with rasterio.open(InRaster) as r:
T0 = r.transform # upper-left pixel corner affine transform
p1 = Proj(r.crs)
p2 = Proj(proj='latlong',datum='WGS84')
# open the raster and get some properties
ds = gdal.OpenShared(InRaster,gdalconst.GA_ReadOnly)
GeoTrans = ds.GetGeoTransform()
ColRange = range(ds.RasterXSize)
RowRange = range(ds.RasterYSize)
rBand = ds.GetRasterBand(band) # first band
nData = np.float32(rBand.GetNoDataValue())
if nData == None:
print("No nodataval for raster")
nData = nodataval # set it to something if not set
else:
print("NoData value is {0}".format(nData))
# specify the center offset (takes the point in middle of pixel)
HalfX = GeoTrans[1] / 2
HalfY = GeoTrans[5] / 2
points = []
for ThisRow in RowRange:
RowData = rBand.ReadAsArray(0,ThisRow,ds.RasterXSize,1)[0]
for ThisCol in ColRange:
# need to exclude NaN values since there is no nodataval
if (np.float32(RowData[ThisCol]) != nData) and not (np.isnan(RowData[ThisCol])):
# TODO: implement filters on valid pixels
# for example, the below would ensure pixel values are between -100 and 100
#if (RowData[ThisCol] <= 100) and (RowData[ThisCol] >= -100):
X = GeoTrans[0] + ( ThisCol * GeoTrans[1] )
Y = GeoTrans[3] + ( ThisRow * GeoTrans[5] ) # Y is negative so it's a minus
# this gives the upper left of the cell, offset by half a cell to get centre
X += HalfX
Y += HalfY
points.append([X,Y,RowData[ThisCol],feature_name])
gdf = gpd.GeoDataFrame(points, columns=['longitude','latitude','feature_value','feature_name'])
X, Y = list(gdf.longitude), list(gdf.latitude)
T = transform(p1, p2, X, Y)
gdf['latitude'] = T[1]
gdf['longitude'] = T[0]
gdf['geometry'] = gdf.apply(lambda x: Point(x.longitude, x.latitude),axis=1)
return gdf
def test_misc_3():
with gdaltest.error_handler():
ds = gdal.OpenShared('../gdrivers/data/small16.aux')
ds.GetRasterBand(1).Checksum()
cache_size = gdal.GetCacheUsed()
with gdaltest.error_handler():
ds2 = gdal.OpenShared('../gdrivers/data/small16.aux')
ds2.GetRasterBand(1).Checksum()
cache_size2 = gdal.GetCacheUsed()
if cache_size != cache_size2:
print("--> OpenShared didn't work as expected")
ds = None
ds2 = None
def misc_3():
ds = gdal.OpenShared('../gdrivers/data/small16.aux')
ds.GetRasterBand(1).Checksum()
cache_size = gdal.GetCacheUsed()
ds2 = gdal.OpenShared('../gdrivers/data/small16.aux')
ds2.GetRasterBand(1).Checksum()
cache_size2 = gdal.GetCacheUsed()
if cache_size != cache_size2:
print("--> OpenShared didn't work as expected")
ds = None
ds2 = None
return 'success'
def test_pixfun_phase_unsigned():
filename = 'data/vrt/pixfun_phase_unsigned.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
assert ds is not None, ('Unable to open "%s" dataset.' % filename)
data = ds.GetRasterBand(1).ReadAsArray()
assert numpy.alltrue(data == numpy.zeros(data.shape))
def test_pixfun_imag_r():
filename = 'data/vrt/pixfun_imag_r.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
assert ds is not None, ('Unable to open "%s" dataset.' % filename)
data = ds.GetRasterBand(1).ReadAsArray()
assert numpy.alltrue(data == 0)
def changeResolution():
inputTiff = gdal.OpenShared(outputTest, gdal.GA_Update)
inputTiff2 = gdal.OpenShared(rasterWarpOut, gdal.GA_Update)
#getting geotransform info
infoGeoTrans = inputTiff.GetGeoTransform()
infoProj = inputTiff.GetProjection()
infoGeoTrans2 = inputTiff2.GetGeoTransform()
infoProj2 = inputTiff2.GetProjection()
#in order to make cell size small enough to register, divide x and y resoultion by 6
xres_var = infoGeoTrans2[1]
yres_var = infoGeoTrans2[5]
warpOptions = gdal.WarpOptions(xRes= xres_var/6.0, yRes=yres_var/6.0)
warp_out = gdal.Warp(rasterWarpOut, outputTest, options=warpOptions)
infoGeoTrans3 = inputTiff2.GetGeoTransform()
warp_out = None
del warp_out
inputTiff=None
inputTiff2=None
def misc_2():
tab_ds = [None for i in range(5000)]
for i, _ in enumerate(tab_ds):
tab_ds[i] = gdal.OpenShared('data/byte.tif')
if tab_ds[i] is None:
return 'fail'
return 'success'
def raster2gpd(InRaster, feature_name, band=1, nodataval=-9999):
'''
Description:
Takes the path of a raster (.tiff) file and produces a Geopandas Data Frame.
Params:
- InRaster: the path of the input raster file
- feature_name: the name of the feature represented by the pixel values
'''
# open the raster and get some properties
ds = gdal.OpenShared(InRaster, gdalconst.GA_ReadOnly)
ds = gdal.Warp('out_raster.tif', ds,
dstSRS='EPSG:4326') # fixes projection issue
GeoTrans = ds.GetGeoTransform()
ColRange = range(ds.RasterXSize)
RowRange = range(ds.RasterYSize)
rBand = ds.GetRasterBand(band) # first band
nData = rBand.GetNoDataValue()
if nData == None:
print("No nodataval for raster")
nData = nodataval # set it to something if not set
else:
print("NoData value is {0}".format(nData))
# specify the center offset (takes the point in middle of pixel)
HalfX = GeoTrans[1] / 2
HalfY = GeoTrans[5] / 2
points = []
for ThisRow in RowRange:
RowData = rBand.ReadAsArray(0, ThisRow, ds.RasterXSize, 1)[0]
for ThisCol in ColRange:
# need to exclude NaN values since there is no nodataval
if (RowData[ThisCol] != nData) and not (np.isnan(
RowData[ThisCol])):
# TODO: implement filters on valid pixels
# for example, the below would ensure pixel values are between -100 and 100
#if (RowData[ThisCol] <= 100) and (RowData[ThisCol] >= -100):
X = GeoTrans[0] + (ThisCol * GeoTrans[1])
Y = GeoTrans[3] + (ThisRow * GeoTrans[5]
) # Y is negative so it's a minus
# this gives the upper left of the cell, offset by half a cell to get centre
X += HalfX
Y += HalfY
points.append(
[Point(X, Y), X, Y, RowData[ThisCol], feature_name])
return gpd.GeoDataFrame(points,
columns=[
'geometry', 'longitude', 'latitude',
'feature_value', 'feature_name'
])
def misc_2():
tab_ds = [None for i in range(5000)]
for i in range(len(tab_ds)):
tab_ds[i] = gdal.OpenShared('data/byte.tif')
if tab_ds[i] is None:
return 'fail'
for i in range(len(tab_ds)):
tab_ds[i] = None
return 'success'
def tryopends(filepath):
dsogr, dsgdal = False, False
try:
#print "trying" + filepath
dsgdal = gdal.OpenShared(filepath)
except gdal.GDALError:
return False
try:
dsogr = ogr.OpenShared(filepath)
except ogr.OGRError:
return False
return dsgdal, dsogr
def test_pixfun_dB_c_intensity():
filename = 'data/vrt/pixfun_dB_c_intensity.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
assert ds is not None, ('Unable to open "%s" dataset.' % filename)
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cint_sar.tif'
refds = gdal.Open(reffilename)
assert refds is not None, ('Unable to open "%s" dataset.' % reffilename)
refdata = refds.GetRasterBand(1).ReadAsArray()
assert numpy.allclose(data, 10. * numpy.log10(numpy.abs(refdata)))
def test_pixfun_dB2amp():
filename = 'data/vrt/pixfun_dB2amp.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
assert ds is not None, ('Unable to open "%s" dataset.' % filename)
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/float32.tif'
refds = gdal.Open(reffilename)
assert refds is not None, ('Unable to open "%s" dataset.' % reffilename)
refdata = refds.GetRasterBand(1).ReadAsArray()
assert numpy.allclose(data, 10.**(refdata / 20.))
def test_pixfun_sqrt():
filename = 'data/vrt/pixfun_sqrt.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
assert ds is not None, ('Unable to open "%s" dataset.' % filename)
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/float32.tif'
refds = gdal.Open(reffilename)
assert refds is not None, ('Unable to open "%s" dataset.' % reffilename)
refdata = refds.GetRasterBand(1).ReadAsArray()
assert numpy.alltrue(data == numpy.sqrt(refdata))
def test_pixfun_intensity_c():
filename = 'data/vrt/pixfun_intensity_c.vrt'
ds = gdal.OpenShared(filename, gdal.GA_ReadOnly)
assert ds is not None, ('Unable to open "%s" dataset.' % filename)
data = ds.GetRasterBand(1).ReadAsArray()
reffilename = 'data/cint_sar.tif'
refds = gdal.Open(reffilename)
assert refds is not None, ('Unable to open "%s" dataset.' % reffilename)
refdata = refds.GetRasterBand(1).ReadAsArray()
assert numpy.alltrue(data == (refdata * refdata.conj()).real)
