def draw(file):
# 1) opening maido geotiff as an array
raster = gdal.OpenShared(file)
data = raster.ReadAsArray()
# 2) transformation of coordinates
cols = raster.RasterXSize
rows = raster.RasterYSize
gt = raster.GetGeoTransform()
x = (cols * gt[1]) + gt[0]
y = (rows * gt[5]) + gt[3]
X = np.arange(gt[0], x, gt[1] * 600)
Y = np.arange(gt[3], y, gt[5] * 600)
# 3) creation of a simple grid
X, Y = np.meshgrid(X, Y)
plt.title('2000')
parameters = np.linspace(0, 110, 10)
norm = matplotlib.colors.Normalize(vmin=np.min(parameters),
vmax=np.max(parameters))
# choose a colormap
c_m = matplotlib.cm.cool
# create a ScalarMappable and initialize a data structure
s_m = matplotlib.cm.ScalarMappable(cmap=c_m, norm=norm)
s_m.set_array([])
fig = plt.figure(figsize=(12, 8))
plt.imshow(data, cmap=c_m)
plt.colorbar(s_m)
def rststats(time,rasterfile):
dataset = gdal.OpenShared(rasterfile)
if dataset is None:
print("Failed to open file: " + rasterfile)
sys.exit(1)
band = dataset.GetRasterBand(1)
xsize = dataset.RasterXSize
ysize = dataset.RasterYSize
print "Output file %s size:" % rasterfile, xsize, ysize
rastervalue = band.ReadAsArray(xoff=0, yoff=0, win_xsize=xsize, win_ysize=ysize)
count1 = np.sum(rastervalue == 1)
count2 = np.sum(rastervalue == 2)
count3 = np.sum(rastervalue == 3)
count4 = np.sum(rastervalue == 4)
count5 = np.sum(rastervalue == 5)
data = {}
data["time"] = time
data["class1"] = count1
data["class2"] = count2
data["class3"] = count3
data["class4"] = count4
data["class5"] = count5
stats_str = json.dumps(data)
return stats_str
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 test():
tif = '/root/PycharmProjects/ANNRK/data/ok_china_40km.tif'
raster = gdal.OpenShared(tif)
arr = raster.ReadAsArray()
max = np.max(arr)
min = np.min(arr)
misc.toimage(arr, high=max, low=min).save('/tmp/test.jpg')
def gdal_read_rs2_dim_format(data_dir_path, roi=None):
rbs0 = {}
rb_keys = defs.S2_SLC_IDX
if roi is not None:
x0 = roi[0]
y0 = roi[1]
w = roi[2]
h = roi[3]
ds_list = []
for k, key in enumerate(rb_keys.keys()):
file_path = os.path.join(data_dir_path, f"{key}.img")
ds_list.append(gdal.OpenShared(file_path, gdal.GA_ReadOnly))
rb = ds_list[k]
rbs0[key] = rb
rbs = []
rbs.append(rbs0['i_HH'].ReadAsArray(x0, y0, w, h) +
1j * rbs0['q_HH'].ReadAsArray(x0, y0, w, h))
rbs.append(rbs0['i_HV'].ReadAsArray(x0, y0, w, h) +
1j * rbs0['q_HV'].ReadAsArray(x0, y0, w, h))
rbs.append(rbs0['i_VH'].ReadAsArray(x0, y0, w, h) +
1j * rbs0['q_VH'].ReadAsArray(x0, y0, w, h))
rbs.append(rbs0['i_VV'].ReadAsArray(x0, y0, w, h) +
1j * rbs0['q_VV'].ReadAsArray(x0, y0, w, h))
data = {}
data['BANDS_IDX'] = defs.S2_IDX
data['X0_ORIGINAL'] = x0
data['Y0_ORIGINAL'] = y0
data['W_ORIGINAL'] = w
data['H_ORIGINAL'] = h
data['RASTER_BANDS'] = np.dstack(rbs).transpose(2, 0, 1)
ds_list = None
return data
def tif2png(tif):
# rst_file = '/root/PycharmProjects/ANNRK/AT_2016_year_2016.tif'
raster = gdal.OpenShared(tif)
data = raster.ReadAsArray()
# cmap = plt.cm.jet
png = tif.replace('tif', 'png')
# plt.imsave(png, data, cmap=cmap)
min = np.nanmin(data)
max = np.nanmax(data)
print('当前处理数据：', tif)
print('最小值和最大值：', min, max)
if min < max:
try:
cmap = matplotlib.colors.LinearSegmentedColormap.from_list(
'cmap', [
'#FFFFFF', '#98F5FF', '#00FF00', '#FFFF00', '#FF0000',
'#8B0000'
], 256)
plt.imshow(data, cmap=cmap)
plt.colorbar(ticks=[min, max])
plt.savefig(png)
plt.close()
except:
print('绘图失败！')
else:
print('最小值大于等于最大值，数据不对，无法绘图')
return
def process_tile(tile, items):
data = {}
template = None
print 'Processing', tile
for year, filename in items.items():
ds = gdal.OpenShared(filename)
if template is None:
template = ds
band = ds.GetRasterBand(1)
data[year] = band.ReadAsArray()
# calculate trend
years = data.keys()
dim = data[years[0]].shape
height, width = dim
slope = np.ndarray(dim, dtype=np.float32)
correl = np.ndarray(dim, dtype=np.float32)
stderr = np.ndarray(dim, dtype=np.float32)
pval = np.ndarray(dim, dtype=np.float32)
for i in range(height):
#sys.stderr.write('\r%d ' % (height-i))
for j in range(width):
values = [data[y][i][j] for y in years]
rc, intercept, rvalue, pvalue, evalue = linregress(years, values)
slope[i][j] = rc
correl[i][j] = rvalue
stderr[i][j] = evalue
pval[i][j] = pvalue
save(SRC, 'slope/NDVI.{tile}.slope'.format(tile=tile), slope, template)
save(SRC, 'correl/NDVI.{tile}.correl'.format(tile=tile), correl, template)
save(SRC, 'stderr/NDVI.{tile}.stderr'.format(tile=tile), stderr, template)
save(SRC, 'pvalue/NDVI.{tile}.pvalue'.format(tile=tile), pval, template)
return tile
def gdal_read_rs2_array(file_path, roi=None, preprocessing=UNCALIB):
if os.path.isdir(file_path):
logger.debug("trying to load a beam-dimap")
data = gdal_read_rs2_dim_format(file_path, roi=roi)
return data
file_path0 = file_path
if preprocessing != UNCALIB:
file_path0 = f"{RSAT2_PROCESSING[preprocessing]}:{file_path}"
print(file_path0)
ds = gdal.OpenShared(file_path0, gdal.GA_ReadOnly)
if ds is None:
raise Exception(f"unable to read product {file_path}")
driver_name = ds.GetDriver().ShortName
x0 = 0
y0 = 0
w = ds.RasterXSize
h = ds.RasterYSize
chs = ds.RasterCount
rbs = []
idx = {}
data = None
if driver_name == "RS2":
data = {}
rbs0 = {}
for k in range(chs):
rb = ds.GetRasterBand(k + 1)
metadata = rb.GetMetadata()
id = metadata["POLARIMETRIC_INTERP"]
rbs0[id] = rb
for key, chn in zip(defs.S2_IDX.keys(), defs.S2_IDX.values()):
rbs.append(read_as_array(rbs0[key], roi))
idx = defs.S2_IDX.keys()
elif driver_name == "GTiff":
data = {}
for key, k in zip(defs.S2_IDX.keys(), defs.S2_IDX.values()):
i = 2 * k + 1
q = 2 * k + 2
rb_i = ds.GetRasterBand(i)
rb_q = ds.GetRasterBand(q)
rbs.append(
read_as_array(rb_i, roi) + 1j * read_as_array(rb_q, roi))
idx = defs.S2_IDX.keys()
else:
return data
data['BANDS_IDX'] = idx
data['X0_ORIGINAL'] = x0
data['Y0_ORIGINAL'] = y0
data['W_ORIGINAL'] = w
data['H_ORIGINAL'] = h
data['RASTER_BANDS'] = np.dstack(rbs).transpose(2, 0, 1)
ds = None
return data
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 checkds(filepath,forcegeo):
ds = gdal.OpenShared(filepath)
if ds is not None:
if forcegeo == 1 and ds.GetGeoTransform() == (0, 1, 0, 0, 0, 1):
return False
else:
return True
else:
return False
def getdsdetails(filepath): ds = gdal.OpenShared(filepath) print "*Calculating dataset stats for raster ",filepath bandcount = ds.RasterCount geotrans = ds.GetGeoTransform() driver = ds.GetDriver().LongName wkt = ds.GetProjection() rasterx = ds.RasterXSize rastery = ds.RasterYSize dsstring = '|'.join([filepath, str(bandcount), str(geotrans),str(driver),str(rasterx),str(rastery),wkt]) return dsstring, bandcount, ds
def read_raster(tif):
raster = gdal.OpenShared(tif)
if raster is None:
print("Failed to open file:" + tif)
sys.exit()
cols = raster.RasterXSize
rows = raster.RasterYSize
print "the tif size is cols: %s, rows: %s" % (cols, rows)
gt = raster.GetGeoTransform()
extent = GetExtent(gt, cols, rows)
print 'the extent of the coordinates of the image is %s' % extent
return raster
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 create_cb(self, *args):
bands = self.input_frame.get_output_bands()
if len(bands) == 0:
gvutils.error('No output bands specified!')
return
vrtbase = [gdal.CXT_Element, 'VRTDataset']
vrtbase.append([
gdal.CXT_Attribute, 'rasterXSize',
[gdal.CXT_Text, str(bands[0][0].RasterXSize)]
])
vrtbase.append([
gdal.CXT_Attribute, 'rasterYSize',
[gdal.CXT_Text, str(bands[0][0].RasterYSize)]
])
# Metadata is currently taken from first output band.
# This may be updatable later.
mbase = vrtutils.serializeMetadata(bands[0][0])
if mbase is not None:
vrtbase.append(mbase)
gbase = self.geo_frame.get_geocoding()
for item in gbase:
vrtbase.append(item)
outband = 1
for item in bands:
dict = {}
dict['band'] = outband
dict['SourceBand'] = item[1]
dict['ColorInterp'] = 'Undefined'
bbase = vrtutils.serializeBand(item[0], opt_dict=dict)
vrtbase.append(bbase)
outband = outband + 1
vrtlines = gdal.SerializeXMLTree(vrtbase)
vrtds = gdal.OpenShared(vrtlines)
if args[1] == 'Save':
fname = GtkExtra.file_sel_box(title="Save File")
if fname is None:
return
driver = gdal.GetDriverByName('VRT')
driver.CreateCopy(fname, vrtds)
elif args[1] == 'New':
self.app.new_view()
self.app.open_gdal_dataset(vrtds)
else:
self.app.open_gdal_dataset(vrtds)
def get_cached_value(self, filename, lon, lat):
""" Get a single value at (lon,lat) from cache """
path = os.path.join(self.cache, filename)
ds = gdal.OpenShared(path)
fwd = ds.GetGeoTransform()
inv = gdal.InvGeoTransform(fwd)
# older versions of gdal have a different signature of InvGeoTransform()
if inv and len(inv) == 2:
_success, inv = inv
x, y = gdal.ApplyGeoTransform(inv, lon, lat)
x = int(max(0, min(ds.RasterXSize - 1, x)))
y = int(max(0, min(ds.RasterYSize - 1, y)))
value = ds.GetRasterBand(1).ReadAsArray(x, y, 1, 1)
return value[0][0]
def get_dataset(self, name):
sets = self.hdf.GetMetadata('SUBDATASETS')
i = 1
while True:
key = 'SUBDATASET_%d_DESC' % i
if not key in sets:
break
desc = sets[key]
if name in desc:
key = 'SUBDATASET_%d_NAME' % i
name = sets[key]
return gdal.OpenShared(name)
i += 1
return None
def rst2arr(rasterfile):
dataset = gdal.OpenShared(rasterfile)
if dataset is None:
print("Failed to open file: " + rasterfile)
sys.exit(1)
band = dataset.GetRasterBand(1)
xsize = dataset.RasterXSize #xsize means number of columns
ysize = dataset.RasterYSize # ysize means number of rows
#proj = dataset.GetProjection()
#geotrans = dataset.GetGeoTransform()
#noDataValue = band.GetNoDataValue()
print "Output file %s size:" % rasterfile, xsize, ysize
rastervalue = band.ReadAsArray(xoff=0, yoff=0, win_xsize=xsize, win_ysize=ysize)
return rastervalue
def arr2rst(ref_tif, arr, dst_file):
dataset = gdal.OpenShared(ref_tif)
proj = dataset.GetProjection()
geotrans = dataset.GetGeoTransform()
# noDataValue = band.GetNoDataValue()
# output the array in geotiff format
xsize, ysize = arr.shape
dst_format = 'GTiff'
dst_nbands = 1
dst_datatype = gdal.GDT_Float32
driver = gdal.GetDriverByName(dst_format)
dst_ds = driver.Create(dst_file, ysize, xsize, dst_nbands, dst_datatype)
dst_ds.SetGeoTransform(geotrans)
dst_ds.SetProjection(proj)
# dst_ds.GetRasterBand(1).SetNoDataValue(noDataValue)
dst_ds.GetRasterBand(1).WriteArray(arr)
def update_default_frame(self, fname):
nchars = self.default_scrolled_text.get_length()
self.default_scrolled_text.backward_delete(nchars)
if fname is None:
self.default_fname = None
self.default_geotransform = None
self.default_gcps = None
self.default_prj = ''
return
sr = osr.SpatialReference()
fh = gdal.OpenShared(fname)
prj = ''
geot = fh.GetGeoTransform()
if ((tuple(geot) == (0, 1, 0, 0, 0, 1))
or (tuple(geot) == (0.0, 1.0, 0.0, 0.0, 0.0, 1.0))):
self.default_geotransform = None
gcps = fh.GetGCPs()
if len(gcps) > 0:
self.default_gcps = gcps
txt = 'Type of Geocoding: GCPs (' + str(len(gcps)) + ')\n\n'
prj = fh.GetGCPProjection()
if sr.ImportFromWkt(prj) == 0:
prjtxt = sr.ExportToPrettyWkt(simplify=1)
else:
prjtxt = ''
txt = txt + 'Projection: ' + prjtxt
else:
self.default_gcps = None
txt = 'Type of Geocoding: None\n\nProjection: None'
else:
self.default_geotransform = geot
self.default_gcps = None
txt = 'Type of Geocoding: Geotransform\n\n'
prj = fh.GetProjection()
if sr.ImportFromWkt(prj) == 0:
prjtxt = sr.ExportToPrettyWkt(simplify=1)
else:
prjtxt = ''
txt = txt + 'Projection: ' + prjtxt
self.default_scrolled_text.insert_defaults(txt)
self.default_prj = prj
self.default_fname = fname
def arr2rst(arr, dst_file):
rst = "/mnt/mfs/zjh/rspm25/PM25_CIESIN/china/cnPM25_199801_200012.tif"
dataset = gdal.OpenShared(rst)
proj = dataset.GetProjection()
geotrans = dataset.GetGeoTransform()
#noDataValue = band.GetNoDataValue()
# output the array in geotiff format
xsize, ysize = arr.shape
dst_format = 'GTiff'
dst_nbands = 1
dst_datatype = gdal.GDT_UInt32
driver = gdal.GetDriverByName(dst_format)
dst_ds = driver.Create(dst_file, ysize, xsize, dst_nbands, dst_datatype)
dst_ds.SetGeoTransform(geotrans)
dst_ds.SetProjection(proj)
#dst_ds.GetRasterBand(1).SetNoDataValue(noDataValue)
dst_ds.GetRasterBand(1).WriteArray(arr)
def __gdal_dataset_default(self):
"""DiskReader implementation."""
if not os.path.exists(self.file_name):
return None
if os.path.splitext(self.file_name)[1].lower() not in self.file_types:
raise RuntimeError('Filename %s does not have extension type %s.' %
(self.file_name, self.file_types))
dataset = gdal.OpenShared(self.file_name, gdalconst.GA_ReadOnly)
if dataset is None:
raise ValueError('Dataset %s did not load properly.' %
self.file_name)
# Sanity checks.
assert dataset.RasterCount > 0
# Seems okay...
return dataset
def import_cb(self, *args):
# Check if the parameters valid
filename = self.open_entry.get_text()
if filename is '':
gvutils.error('You should select a raw file to load!')
return
if not os.path.isfile(filename):
gvutils.error('Unable to load '+ filename)
return
if args[1] == 'Save':
self.create_header(filename)
else:
lines=self.create_vrt_lines(filename)
vrtds=gdal.OpenShared(lines)
if args[1] == 'New':
self.app.new_view()
self.app.open_gdal_dataset(vrtds)
def vrtwarp_2():
try:
os.remove('tmp/warp.vrt')
except:
pass
gcp_ds = gdal.OpenShared('data/rgb_gcp.vrt', gdal.GA_ReadOnly)
gdaltest.vrtwarp_ds = gdal.AutoCreateWarpedVRT(gcp_ds)
gcp_ds = None
checksum = gdaltest.vrtwarp_ds.GetRasterBand(2).Checksum()
expected = 21504
if checksum != expected:
gdaltest.post_reason( 'Got checksum of %d instead of expected %d.' \
% (checksum, expected) )
return 'fail'
return 'success'
def grid_feature(gridx, gridy, grid_proj, feat_file):
'''
根据格网位置读取对应的栅格数据的数值
:param gridx: 横坐标数组
:param gridy: 纵坐标数组
:param grid_proj: 格网投影
:param feat_file: 栅格数据
:return: 格网数据
'''
feat_rst = gdal.OpenShared(feat_file)
feat_proj = feat_rst.GetProjectionRef()
grid_X = []
for x in gridx:
for y in gridy:
x_c, y_c = point_geotransform(grid_proj, feat_proj, x, y)
feat = read_value_fcoord(feat_file, x_c, y_c)
# print feat
if feat is None or feat == 0:
continue
grid_X.append([x, y, feat])
return np.array(grid_X)
def _fromFile(fname):
"""
Parameters
----------
fname : str # file name
Returns
-------
GeoArray
Purpose
-------
Create GeoArray from file
"""
# fobj = gdal.OpenShared(fname, gdal.GA_Update)
fobj = gdal.OpenShared(fname)
if fobj:
return _fromDataset(fobj)
raise IOError("Could not open file: {:}".format(fname))
def copy_gcps_cb(self, *args):
""" Copy gcps from an existing gdal dataset. """
fname = GtkExtra.file_sel_box(title="Select GDAL Dataset")
if fname is None:
return
try:
fh = gdal.OpenShared(fname)
except:
gvutils.error('Unable to open ' + fname + ' as a GDAL dataset!')
return
gcps = fh.GetGCPs()
prj = fh.GetGCPProjection()
self.clear_gcps()
for gcp in gcps:
ngcp = CopyGDALGCP(gcp)
self.gcplist.append(ngcp)
self.gcpgrid.refresh()
self.gcpprjbox.set_input_projection(prj)
def stats():
for k in range(8):
statfile = os.path.join(dst_dir, 'stats' + '_c' + str(k) + '.csv')
stat_arr = np.array([])
for t in range(t_num):
rstname = os.path.join(dst_dir,
t_series[t] + '_c' + str(k) + '.tif')
print("file %s will be statisticed" % rstname)
dataset = gdal.OpenShared(rstname)
if dataset is None:
print("Failed to open file: " + rstname)
sys.exit(1)
band = dataset.GetRasterBand(1)
xsize = dataset.RasterXSize
ysize = dataset.RasterYSize
rv = band.ReadAsArray(xoff=0,
yoff=0,
win_xsize=xsize,
win_ysize=ysize)
if np.sum(rv) == 0:
break
max = np.max(rv[(rv > 0)])
min = np.min(rv[(rv > 0)])
mean = np.mean(rv[(rv > 0)])
median = np.median(rv[(rv > 0)])
var = np.var(rv[(rv > 0)])
arr = np.array([max, min, mean, median, var])
stat_arr = np.append(stat_arr, arr)
stat_arr = stat_arr.reshape(-1, 5)
frame = DataFrame(stat_arr)
frame.to_csv(statfile)
print("file %s has been statisticed successfully" % rstname)
def rststats(rasterfile):
dataset = gdal.OpenShared(rasterfile)
if dataset is None:
print("Failed to open file: " + rasterfile)
sys.exit(1)
band = dataset.GetRasterBand(1)
xsize = dataset.RasterXSize
ysize = dataset.RasterYSize
print "Output file %s size:" % rasterfile, xsize, ysize
rastervalue = band.ReadAsArray(xoff=0,
yoff=0,
win_xsize=xsize,
win_ysize=ysize)
data = np.array([])
count1 = np.sum(rastervalue == 1)
count2 = np.sum(rastervalue == 2)
count3 = np.sum(rastervalue == 3)
count4 = np.sum(rastervalue == 4)
count5 = np.sum(rastervalue == 5)
count6 = np.sum(rastervalue == 6)
data = np.append(data, [count1, count2, count3, count4, count5, count6])
return data
def read_by_point(self, x, y, tif_file):
'''
获取坐标点的数据。
tif_file ：数据产品
bandid ：波段名称
x, y：坐标,坐标对应投影信息默认为：EPSG:4326
'''
raster = gdal.OpenShared(tif_file)
if raster is None:
print("Failed to open file: " + tif_file)
sys.exit()
feat_proj = raster.GetProjectionRef()
gt = raster.GetGeoTransform()
# transform geographic coordinates of monitor points into projected coordinate system
inSpatialRef = osr.SpatialReference()
inSpatialRef.SetFromUserInput("EPSG:4326")
outSpatialRef = osr.SpatialReference()
outSpatialRef.SetFromUserInput(feat_proj)
transform = osr.CoordinateTransformation(inSpatialRef, outSpatialRef)
# point coordinate transformation
geom = ogr.Geometry(ogr.wkbPoint)
geom.AddPoint(x, y)
geom.Transform(transform)
x_c = geom.GetX()
y_c = geom.GetY()
# read feature value of the point from related data
col = int((x_c - gt[0]) / gt[1])
row = int((y_c - gt[3]) / gt[5])
# print(col, row)
if col < raster.RasterXSize and row < raster.RasterYSize:
return raster.ReadAsArray(col, row, 1, 1)[0][0]
# print(feat_value)
else:
return None
def file_selection_ok(self, *args):
self.source_name = self.o_s_d.get_filename()
self.o_s_d.hide()
rast = gdal.OpenShared(self.source_name, gdalconst.GA_ReadOnly)
self.input_rast = rast
self.pixsubarea = [0, 0, rast.RasterYSize, rast.RasterXSize]
SetInitialCoord(self.frame_dict['pixcoord'], self.pixsubarea)
self.geotransform = rast.GetGeoTransform()
if EmptyGeotransform(self.geotransform):
self.coord_system.set_history(0)
self.update_gui()
self.coord_system.hide()
else:
self.projsubarea = GetProjRect(self.pixsubarea, self.geotransform)
SetInitialCoord(self.frame_dict['geocoord'], self.projsubarea)
self.geogsubarea = GetGeogrRect(rast, self.projsubarea)
SetInitialCoord(self.frame_dict['geodetic'], self.geogsubarea)
self.band_list = []
for i in range(rast.RasterCount):
item = ["Band " + str(i), "Yes"]
self.band_list.append(item)
if len(self.band_list) > 1:
self.band_grid.set_source(self.band_list, expose=0)
grid_titles = ['Band number', 'Load']
self.band_grid.define_columns(titles=grid_titles, editables=[0, 1])
self.band_grid.resize_to_default()
for i in range(len(self.band_list)):
self.band_num_list.append(i + 1)
self.band_grid.show_all()
else:
self.band_grid.hide()
self.dialog.show()
