def test_read_to_grid(self):
g = GeoTiff(utils.get_demo_file('hef_srtm.tif'))
sf = utils.get_demo_file('Hintereisferner_UTM.shp')
df1 = read_shapefile_to_grid(sf, g.grid)
df2 = transform_geopandas(read_shapefile(sf), to_crs=g.grid)
assert_allclose(df1.geometry[0].exterior.coords,
df2.geometry[0].exterior.coords)
# test for caching
d = g.grid.to_dict()
# change key ordering by chance
d2 = dict((k, v) for k, v in d.items())
from salem.sio import _memory_shapefile_to_grid, cached_shapefile_path
shape_cpath = cached_shapefile_path(sf)
res = _memory_shapefile_to_grid.call_and_shelve(shape_cpath,
grid=g.grid,
**d)
h1 = res.argument_hash
res = _memory_shapefile_to_grid.call_and_shelve(shape_cpath,
grid=g.grid,
**d2)
h2 = res.argument_hash
self.assertEqual(h1, h2)
def test_read_to_grid(self):
g = GeoTiff(utils.get_demo_file("hef_srtm.tif"))
sf = utils.get_demo_file("Hintereisferner_UTM.shp")
df1 = read_shapefile_to_grid(sf, g.grid)
df2 = transform_geopandas(read_shapefile(sf), to_crs=g.grid)
assert_allclose(df1.geometry[0].exterior.coords, df2.geometry[0].exterior.coords)
def test_read_to_grid(self):
g = GeoTiff(utils.get_demo_file('hef_srtm.tif'))
sf = utils.get_demo_file('Hintereisferner_UTM.shp')
df1 = read_shapefile_to_grid(sf, g.grid)
df2 = transform_geopandas(read_shapefile(sf), to_crs=g.grid)
assert_allclose(df1.geometry[0].exterior.coords,
df2.geometry[0].exterior.coords)
def test_text():
# UL Corner
g = Grid(nxny=(5, 4),
dxdy=(10, 10),
x0y0=(-20, -15),
proj=wgs84,
pixel_ref='corner')
c = Map(g, ny=4, countries=False)
c.set_lonlat_contours(interval=5., colors='crimson', linewidths=1)
c.set_text(-5, -5, 'Less Middle', color='green', style='italic', size=25)
c.set_geometry(shpg.Point(-10, -10),
s=500,
marker='o',
text='My point',
text_delta=[0, 0])
shape = read_shapefile_to_grid(shapefiles['world_borders'], c.grid)
had_c = set()
for index, row in shape.iloc[::-1].iterrows():
if row.CNTRY_NAME in had_c:
c.set_geometry(row.geometry, crs=c.grid)
else:
c.set_geometry(row.geometry,
text=row.CNTRY_NAME,
crs=c.grid,
text_kwargs=dict(horizontalalignment='center',
verticalalignment='center',
clip_on=True,
color='gray'),
text_delta=[0, 0])
had_c.add(row.CNTRY_NAME)
c.set_points([20, 20, 10], [10, 20, 20],
s=250,
marker='s',
c='purple',
hatch='||||',
text='baaaaad',
text_delta=[0, 0],
text_kwargs=dict(horizontalalignment='center',
verticalalignment='center',
color='red'))
fig, ax = plt.subplots(1, 1)
c.visualize(ax=ax, addcbar=False)
plt.tight_layout()
c.set_text()
assert len(c._text) == 0
c.set_geometry()
assert len(c._geometries) == 0
return fig
def test_text():
# UL Corner
g = Grid(nxny=(5, 4), dxdy=(10, 10), ll_corner=(-20, -15), proj=wgs84,
pixel_ref='corner')
c = Map(g, ny=4, countries=False)
c.set_lonlat_contours(interval=5., colors='crimson')
c.set_text(-5, -5, 'Less Middle', color='green', style='italic', size=25)
c.set_geometry(shpg.Point(-10, -10), s=500, marker='o',
text='My point', text_delta=[0, 0])
shape = read_shapefile_to_grid(shapefiles['world_borders'], c.grid)
had_c = set()
for index, row in shape.iloc[::-1].iterrows():
if row.CNTRY_NAME in had_c:
c.set_geometry(row.geometry, crs=c.grid)
else:
c.set_geometry(row.geometry, text=row.CNTRY_NAME, crs=c.grid,
text_kwargs=dict(horizontalalignment='center',
verticalalignment='center',
clip_on=True,
color='gray'), text_delta=[0, 0])
had_c.add(row.CNTRY_NAME)
c.set_points([20, 20, 10], [10, 20, 20], s=250, marker='s',
c='purple', hatch='||||', text='baaaaad', text_delta=[0, 0],
text_kwargs=dict(horizontalalignment='center',
verticalalignment='center', color='red'))
fig, ax = plt.subplots(1, 1)
c.visualize(ax=ax, addcbar=False)
plt.tight_layout()
c.set_text()
assert len(c._text) == 0
c.set_geometry()
assert len(c._geometries) == 0
return fig
cfg.initialize()
cfg.PATHS['working_dir'] = utils.get_temp_dir('racmo')
gdirs = workflow.init_glacier_regions(['RGI60-05.10315'],
from_prepro_level=3, prepro_border=10)
gdir = gdirs[0]
#Reading RACMO mask
# The mask and geo reference data
ds_geo = xr.open_dataset(mask_file, decode_times=False)
proj = pyproj.Proj('+init=EPSG:3413')
ds_geo.attrs['pyproj_srs'] = proj.srs
# Reading coastline
coast_line = salem.read_shapefile_to_grid(filename_coastline, gdir.grid)
# Selecting a zoom portion of the topo data fitting the ice cap
ds_geo_sel = ds_geo.salem.subset(grid=gdir.grid, margin=2)
# Reading ice cap outline and assinging the rgi grid
shape_cap = salem.read_shapefile_to_grid(ice_cap, gdir.grid)
# Processing vel data
src = rasterio.open(vel_file)
# Retrieve the affine transformation
if isinstance(src.transform, Affine):
transform = src.transform
else:
