print('x extent {} : y extent {}'.format(str(x_extent), str(y_extent)))
print('Num of 30m pixels in x {} | Num of 30m pixels in y {}'.format(
str(xsize), str(ysize)))
wkt_list = list(
Vector.wkt_from_coords(coords, geom_type='point')
for coords in pos_arr.tolist())
attrib = {'cover': 'float', 'cover_error': 'float'}
attr_list = list({
'cover': cover[0],
'cover_error': cover[1]
} for cover in zip(cover_arr, cover_err_arr))
vector = Vector.vector_from_string(wkt_list,
geom_string_type='wkt',
out_epsg=4326,
vector_type='point',
attributes=attr_list,
attribute_types=attrib,
verbose=False)
print(vector)
vector.rasterize(outfile=outfile,
pixel_size=[xpixel, ypixel],
out_dtype=gdal.GDT_Float32,
compress='lzw',
attribute='cover')
attr_list.append(elem)
count += 1
uniq, indices, inverse, count = np.unique(ar=latlon,
axis=0,
return_index=True,
return_counts=True,
return_inverse=True)
print(uniq.shape)
exit()
vector = Vector.vector_from_string(wkt_list,
spref_string=spref_str,
spref_string_type='proj4',
vector_type='point',
attributes=attr_list,
attribute_types=attr,
verbose=True)
print(vector)
vector.write_vector(outfilename)
'''
file0 = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/albedo_data/albedo_data_2000_2010_full_by_tc.csv"
infile1 = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/FIRE/ak_fire/FireAreaHistory_gt500ha.shp"
infile2 = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/FIRE/can_fire/NFDB_poly_20171106_gt500ha_ABoVE_geo.shp"
vec1 = Vector(infile1)
vec2 = Vector(infile2)
str(year), str(nfeat)))
wkt_list = list()
count = 0
feat = layer.GetNextFeature()
while feat:
new_geom = feat.GetGeometryRef()
if new_geom.GetGeometryType() < 0:
new_geom.FlattenTo2D()
wkt_list.append(new_geom.ExportToWkt())
feat = layer.GetNextFeature()
count += 1
vec.datasource.ReleaseResultSet(layer)
temp_vec = Vector.vector_from_string(wkt_list,
spref=vec.spref,
vector_type='multipolygon')
temp_lyr = temp_vec.layer
temp_vec.rasterize(outfile=outfile,
pixel_size=(pixel_size, pixel_size),
extent=(x_min, y_max, x_max, y_min),
burn_values=[year],
all_touched=True,
nodatavalue=0,
compress='lzw')
sys.stdout.write('Written {}!\n\n'.format(outfile))
attr_list = list()
for i, row in enumerate(decid_frac_samp):
elem = dict()
for header in list(attribute_types):
elem[header] = row[header]
wkt = Vector.wkt_from_coords([row['longitude'], row['latitude']],
geom_type='point')
wkt_list.append(wkt)
attr_list.append(elem)
vector = Vector.vector_from_string(wkt_list,
out_epsg=4326,
vector_type='point',
attributes=attr_list,
attribute_types=attribute_types,
verbose=True)
print(vector)
vector.write_vector(ini_outfile)
exit()
# extract all decid frac values for calculating histogram
decid_frac_list = list(samp['decid_frac'] for samp in decid_frac_samp)
# histogram calculation
step = 1.0 / float(nbins)
hist, bin_edges = np.histogram(decid_frac_list, bins=nbins)
hist = hist.tolist()