def grid(self, tiles=False, **kwargs):
x = kwargs.get("x", self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get("y", self._obj.SCHISM_hgrid_node_y[:].values)
tes = kwargs.get("tri3", self._obj.SCHISM_hgrid_face_nodes.values)
width = kwargs.get("width", 800)
height = kwargs.get("height", 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS("https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png")
nodes = pd.DataFrame({"longitude": x, "latitude": y})
points = gv.operation.project_points(gv.Points(nodes))
if tes.shape[1] == 3:
elems = pd.DataFrame(tes, columns=["a", "b", "c"])
trimesh = gv.TriMesh((elems, points)).edgepaths
if tiles:
return tile * datashade(
trimesh, precompute=True, cmap=["black"])
else:
return datashade(trimesh, precompute=True,
cmap=["green"]).opts(width=width,
height=height)
else: # there are quads
elems = pd.DataFrame(tes, columns=["a", "b", "c", "d"])
quads = elems.loc[~elems.d.isna()].copy()
quads = quads.reset_index(drop=True)
ap = nodes.loc[quads.a, ["longitude", "latitude"]]
bp = nodes.loc[quads.b, ["longitude", "latitude"]]
cp = nodes.loc[quads.c, ["longitude", "latitude"]]
dp = nodes.loc[quads.d, ["longitude", "latitude"]]
quads["ap"] = ap.values.tolist()
quads["bp"] = bp.values.tolist()
quads["cp"] = cp.values.tolist()
quads["dp"] = dp.values.tolist()
q = gv.Polygons([
quads.loc[i, ["ap", "bp", "cp", "dp"]].tolist()
for i in range(quads.shape[0])
]).options(fill_alpha=0, line_color="black")
triangles = elems.loc[elems.d.isna()]
trimesh = gv.TriMesh((triangles, points)).edgepaths
g1 = datashade(trimesh, precompute=True, cmap=["black"])
if tiles:
return tile * g1 * q
else:
return g1 * q
def elevation_max(data_dir: pathlib.Path):
# load data
grid_path = data_dir / "grid.npz"
elevation_max_path = data_dir / "elevation.max.npz"
x, y, simplices = load_grid_from_disk(grid_path)
z = load_elevation_from_disk(elevation_max_path)
# create panel objects
xyz_points = pd.DataFrame(dict(x=x, y=y, z=z))
points = hv.Points(xyz_points, kdims=["x", "y"], vdims="z")
trimesh = hv.TriMesh((simplices, points))
opts.defaults(opts.WMTS(width=1200, height=900))
datashaded_trimesh = (rasterize(trimesh,
aggregator='mean').opts(colorbar=True,
cmap='Viridis',
clim=(z.min(),
z.max()),
clabel='meters',
tools=["hover"]))
tiles = gv.WMTS('https://maps.wikimedia.org/osm-intl/{Z}/{X}/{Y}@2x.png')
layout = tiles * datashaded_trimesh
header = get_header(title="## Max elevation for the next 72 hours")
disclaimer = get_disclaimer()
return pn.Column(header, layout, disclaimer)
def contourf(self, var='depth', it=None, **kwargs):
x = kwargs.get('x', self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get('y', self._obj.SCHISM_hgrid_node_y[:].values)
try:
t = kwargs.get('t', self._obj.time.values)
except:
pass
tri3 = kwargs.get(
'tri3',
self._obj.SCHISM_hgrid_face_nodes.values[:, :3].astype(int))
z = kwargs.get('z', self._obj[var].values[it, :].flatten())
nodes = pd.DataFrame({
'longitude': x,
'latitude': y,
'{}'.format(var): z
})
elems = pd.DataFrame(tri3, columns=['a', 'b', 'c'])
opts.defaults(opts.WMTS(width=800, height=400))
tiles = gv.WMTS(
'https://maps.wikimedia.org/osm-intl/{Z}/{X}/{Y}@2x.png')
points = gv.operation.project_points(
gv.Points(nodes, vdims=['{}'.format(var)]))
trimesh = gv.TriMesh((elems, points))
return tiles * rasterize(trimesh, aggregator='mean').opts(
colorbar=True, cmap='Viridis', padding=.1, tools=['hover'])
def show(self, **kwargs):
width = kwargs.get("width", 800)
height = kwargs.get("height", 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS("https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png")
ps = [tile]
# external
ds = self._obj.loc["line0"]
ds = ds.append(ds.iloc[0]).reset_index(drop=True)
dland = ds.loc[ds.tag == "land"]
dland_ = np.split(dland, np.flatnonzero(np.diff(dland.index) != 1) + 1)
for seg in dland_:
ps.append(
seg.hvplot.paths(x="lon", y="lat", geo=True, color="brown"))
dwater = ds.loc[ds.tag == "open"]
dwater_ = np.split(dwater,
np.flatnonzero(np.diff(dwater.index) != 1) + 1)
for seg in dwater_:
ps.append(
seg.hvplot.paths(x="lon", y="lat", geo=True, color="blue"))
# islands
for line in self._obj.index.levels[0][1:]:
ds = self._obj.loc[line]
ds = ds.append(ds.iloc[0]).reset_index(drop=True)
ps.append(
ds.hvplot.paths(x="lon", y="lat", geo=True, color="green"))
return hv.Overlay(ps)
def elevation_max(dataset: xr.Dataset):
#extract data
x, y, simplices = extract_grid(dataset)
w = dataset
z = dataset.elev.max(dim='time').values
# create panel objects
xyz_points = pd.DataFrame(dict(longitude=x, latitude=y, elevation=z))
points = hv.Points(xyz_points,
kdims=["longitude", "latitude"],
vdims="elevation")
trimesh = hv.TriMesh((simplices, points))
opts.defaults(opts.WMTS(width=1200, height=900))
datashaded_trimesh = (rasterize(trimesh,
aggregator='mean').opts(colorbar=True,
cmap='Viridis',
clim=(z.min(),
z.max()),
clabel='meters',
tools=["hover"]))
tiles = gv.WMTS('https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png')
layout = tiles * datashaded_trimesh
t0 = pd.to_datetime(w.time.values.min()).strftime(format='%Y-%m-%d:%H')
t1 = pd.to_datetime(w.time.values.max()).strftime(format='%Y-%m-%d:%H')
header = get_header(
title="## Maximum forecasted elevation between {} and {}".format(
t0, t1))
disclaimer = get_disclaimer()
return pn.Column(header, layout, disclaimer)
def contourf(self, var="depth", it=None, tiles=False, **kwargs):
x = kwargs.get("x", self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get("y", self._obj.SCHISM_hgrid_node_y[:].values)
try:
t = kwargs.get("t", self._obj.time.values)
except:
pass
tes = kwargs.get("tri3",
self._obj.SCHISM_hgrid_face_nodes.values[:, :4])
# sort out quads
try:
mask = np.isnan(tes)[:, 3]
tr3 = tes[mask][:, :3]
tr3_ = quads_to_tris(tes[~mask])
if tr3_:
tri3 = np.append(tr3, tr3_, axis=0).astype(int)
else:
tri3 = tr3.astype(int)
except:
tri3 = tes.astype(int)
if tri3.min() > 0:
tri3 = tri3 - 1
z = kwargs.get("z", self._obj[var].values[it, :].flatten())
nodes = pd.DataFrame({
"longitude": x,
"latitude": y,
"{}".format(var): z
})
elems = pd.DataFrame(tri3, columns=["a", "b", "c"])
width = kwargs.get("width", 800)
height = kwargs.get("height", 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS("https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png")
points = gv.operation.project_points(
gv.Points(nodes, vdims=["{}".format(var)]))
trimesh = gv.TriMesh((elems, points))
if tiles:
return tile * rasterize(trimesh, aggregator="mean").opts(
colorbar=True, cmap="Viridis", padding=0.1, tools=["hover"])
else:
return rasterize(trimesh, aggregator="mean").opts(
colorbar=True,
cmap="Viridis",
padding=0.1,
tools=["hover"],
width=width,
height=height,
)
def grid(self, tiles=False, **kwargs):
x = kwargs.get('x',self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get('y',self._obj.SCHISM_hgrid_node_y[:].values)
tes = kwargs.get('tri3',self._obj.SCHISM_hgrid_face_nodes.values)
width = kwargs.get('width', 800)
height = kwargs.get('height', 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS('https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png')
nodes = pd.DataFrame({'longitude':x,'latitude':y})
points = gv.operation.project_points(gv.Points(nodes))
if tes.shape[1] == 3 :
elems = pd.DataFrame(tes, columns=['a', 'b', 'c'])
trimesh=gv.TriMesh((elems, points)).edgepaths
if tiles:
return tile * datashade(trimesh, precompute=True, cmap=['black'])
else:
return datashade(trimesh, precompute=True, cmap=['green']).opts(width=width,height=height)
else: # there are quads
elems = pd.DataFrame(tes, columns=['a', 'b', 'c', 'd'])
quads = elems.loc[~elems.d.isna()].copy()
quads = quads.reset_index(drop=True)
ap = nodes.loc[quads.a,['longitude','latitude']]
bp = nodes.loc[quads.b,['longitude','latitude']]
cp = nodes.loc[quads.c,['longitude','latitude']]
dp = nodes.loc[quads.d,['longitude','latitude']]
quads['ap'] = ap.values.tolist()
quads['bp'] = bp.values.tolist()
quads['cp'] = cp.values.tolist()
quads['dp'] = dp.values.tolist()
q = gv.Polygons([quads.loc[i,['ap','bp','cp','dp']].tolist() for i in range(quads.shape[0])]).options(fill_alpha=0, line_color='black')
triangles = elems.loc[elems.d.isna()]
trimesh=gv.TriMesh((triangles, points)).edgepaths
g1 = datashade(trimesh, precompute=True, cmap=['black'])
if tiles :
return tile * g1 * q
else:
return g1 * q
def frames(self,var='depth', tiles=False, **kwargs):
x = kwargs.get('x',self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get('y',self._obj.SCHISM_hgrid_node_y[:].values)
try:
t = kwargs.get('t',self._obj.time.values)
except:
pass
tes = kwargs.get('tri3',self._obj.SCHISM_hgrid_face_nodes.values[:,:4])
# sort out quads
try:
mask = np.isnan(tes)[:,3]
tr3 = tes[mask][:,:3]
tr3_ = quads_to_tris(tes[~mask])
if tr3_ :
tri3 = np.append(tr3,tr3_,axis=0).astype(int)
else:
tri3 = tr3.astype(int)
except:
tri3 = tes.astype(int)
times=kwargs.get('times',self._obj.time.values)
z = kwargs.get('z',self._obj[var].values[0,:].flatten())
zmin = self._obj[var].values.min()
zmax = self._obj[var].values.max()
nodes = pd.DataFrame({'longitude':x,'latitude':y, '{}'.format(var):z})
elems = pd.DataFrame(tri3, columns=['a', 'b', 'c'])
width = kwargs.get('width', 800)
height = kwargs.get('height', 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS('https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png')
points = gv.operation.project_points(gv.Points(nodes, vdims=['{}'.format(var)]))
trimesh = gv.TriMesh((elems, points))
def time_mesh(time):
points.data[var] = self._obj[var].sel(time=time).values
return gv.TriMesh((elems, points))#, crs=ccrs.GOOGLE_MERCATOR)
meshes = hv.DynamicMap(time_mesh, kdims=['Time']).redim.values(Time=times)
imesh = rasterize(meshes, aggregator='mean').opts(cmap='viridis', colorbar=True, padding=.1, tools=['hover'], clim=(zmin, zmax))
if tiles:
return hv.output(tile*imesh, holomap='scrubber', fps=1)
else:
return hv.output(imesh.opts(width=width,height=height), holomap='scrubber', fps=1)
def elevation(dataset: xr.Dataset):
# extract data
z = dataset
x, y, simplices = extract_grid(dataset)
# create panel objects
xyz_points = pd.DataFrame(
dict(longitude=x, latitude=y, elevation=z.elev.isel(time=0).values))
points = hv.Points(xyz_points,
kdims=["longitude", "latitude"],
vdims="elevation")
opts.defaults(opts.WMTS(width=1200, height=900))
def time_mesh(time):
points.data.elevation = z.elev.sel(time=time).values
return hv.TriMesh((simplices, points)) #, crs=ccrs.GOOGLE_MERCATOR)
meshes = hv.DynamicMap(time_mesh,
kdims='Time').redim.values(Time=z.time.values)
datashaded_trimesh = (rasterize(meshes, aggregator='mean').opts(
colorbar=True,
cmap='Viridis',
clim=(z.elev.values.min(), z.elev.values.max()),
clabel='meters',
tools=["hover"]))
tiles = gv.WMTS('https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png')
t_widget = pn.widgets.Select()
@pn.depends(t_widget)
def t_plot(time):
return tiles * datashaded_trimesh
tref_ = pd.to_datetime(z.time.values.min()) - pd.to_timedelta('1H')
tref = tref_.strftime(format='%Y-%m-%d:%H')
header = get_header(
title="## Hourly sea level for 72 hours based on the {} forecast".
format(tref))
text = '''
# USAGE
Use the toolbox on the right to zoom in/out.
'''
footer = pn.Row(pn.pane.Markdown(text))
disclaimer = get_disclaimer()
return pn.Column(header, t_plot, footer, disclaimer)
def frames(self, var='depth', **kwargs):
x = kwargs.get('x', self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get('y', self._obj.SCHISM_hgrid_node_y[:].values)
try:
t = kwargs.get('t', self._obj.time.values)
except:
pass
tri3 = kwargs.get(
'tri3',
self._obj.SCHISM_hgrid_face_nodes.values[:, :3].astype(int))
times = kwargs.get('times', self._obj.time.values)
z = kwargs.get('z', self._obj[var].values[0, :].flatten())
nodes = pd.DataFrame({
'longitude': x,
'latitude': y,
'{}'.format(var): z
})
elems = pd.DataFrame(tri3, columns=['a', 'b', 'c'])
opts.defaults(opts.WMTS(width=800, height=400))
tiles = gv.WMTS(
'https://maps.wikimedia.org/osm-intl/{Z}/{X}/{Y}@2x.png')
points = gv.operation.project_points(
gv.Points(nodes, vdims=['{}'.format(var)]))
trimesh = gv.TriMesh((elems, points))
def time_mesh(time):
points.data[var] = self._obj[var].sel(time=time).values
return gv.TriMesh((elems, points)) #, crs=ccrs.GOOGLE_MERCATOR)
meshes = hv.DynamicMap(time_mesh,
kdims=['Time']).redim.values(Time=times)
imesh = rasterize(meshes, aggregator='mean').opts(cmap='viridis',
colorbar=True,
padding=.1,
tools=['hover'])
return hv.output(tiles * imesh, holomap='scrubber', fps=1)
def elevation(data_dir: pathlib.Path):
# load data
grid_path = data_dir / "grid.npz"
elevation_path = data_dir / "elevation.nc"
x, y, simplices = load_grid_from_disk(grid_path)
z = get_dataset(elevation_path)
# create panel objects
xyz_points = pd.DataFrame(dict(x=x, y=y, z=z.elev.isel(time=0).values))
points = hv.Points(xyz_points, kdims=["x", "y"], vdims="z")
opts.defaults(opts.WMTS(width=1200, height=900))
def time_mesh(time):
points.data.z = z.elev.sel(time=time).values
return hv.TriMesh((simplices, points)) #, crs=ccrs.GOOGLE_MERCATOR)
meshes = hv.DynamicMap(time_mesh,
kdims='Time').redim.values(Time=z.time.values)
datashaded_trimesh = (rasterize(meshes, aggregator='mean').opts(
colorbar=True,
cmap='Viridis',
clim=(z.elev.values.min(), z.elev.values.max()),
clabel='meters',
tools=["hover"]))
tiles = gv.WMTS('https://maps.wikimedia.org/osm-intl/{Z}/{X}/{Y}@2x.png')
t_widget = pn.widgets.Select()
@pn.depends(t_widget)
def t_plot(time):
return tiles * datashaded_trimesh
header = get_header(title="## Time Steps")
text = '''
# USAGE
Use the toolbox on the right to zoom in/out.
'''
footer = pn.Row(pn.pane.Markdown(text))
disclaimer = get_disclaimer()
return pn.Column(header, t_plot, footer, disclaimer)
def grid(self, **kwargs):
x = kwargs.get('x', self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get('y', self._obj.SCHISM_hgrid_node_y[:].values)
tri3 = kwargs.get(
'tri3',
self._obj.SCHISM_hgrid_face_nodes.values[:, :3].astype(int))
opts.defaults(opts.WMTS(width=800, height=400))
tiles = gv.WMTS(
'https://maps.wikimedia.org/osm-intl/{Z}/{X}/{Y}@2x.png')
nodes = pd.DataFrame({'longitude': x, 'latitude': y})
elems = pd.DataFrame(tri3, columns=['a', 'b', 'c'])
points = gv.operation.project_points(gv.Points(nodes))
trimesh = gv.TriMesh((elems, points)).edgepaths
return tiles * datashade(trimesh, precompute=True, cmap=['black'])
def contourf(self, var='depth', it=None, tiles=False, **kwargs):
x = kwargs.get('x',self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get('y',self._obj.SCHISM_hgrid_node_y[:].values)
try:
t = kwargs.get('t',self._obj.time.values)
except:
pass
tes = kwargs.get('tri3',self._obj.SCHISM_hgrid_face_nodes.values[:,:4])
# sort out quads
try:
mask = np.isnan(tes)[:,3]
tr3 = tes[mask][:,:3]
tr3_ = quads_to_tris(tes[~mask])
if tr3_ :
tri3 = np.append(tr3,tr3_,axis=0).astype(int)
else:
tri3 = tr3.astype(int)
except:
tri3 = tes.astype(int)
z = kwargs.get('z',self._obj[var].values[it,:].flatten())
nodes = pd.DataFrame({'longitude':x,'latitude':y, '{}'.format(var):z})
elems = pd.DataFrame(tri3, columns=['a', 'b', 'c'])
width = kwargs.get('width', 800)
height = kwargs.get('height', 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS('https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png')
points = gv.operation.project_points(gv.Points(nodes, vdims=['{}'.format(var)]))
trimesh = gv.TriMesh((elems, points))
if tiles:
return tile * rasterize(trimesh, aggregator='mean').opts(colorbar=True, cmap='Viridis', padding=.1, tools=['hover'])
else:
return rasterize(trimesh, aggregator='mean').opts(colorbar=True, cmap='Viridis', padding=.1, tools=['hover'],width=width,height=height)
def frames(self, var="depth", tiles=False, **kwargs):
x = kwargs.get("x", self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get("y", self._obj.SCHISM_hgrid_node_y[:].values)
try:
t = kwargs.get("t", self._obj.time.values)
except:
pass
tes = kwargs.get("tri3",
self._obj.SCHISM_hgrid_face_nodes.values[:, :4])
# sort out quads
try:
mask = np.isnan(tes)[:, 3]
tr3 = tes[mask][:, :3]
tr3_ = quads_to_tris(tes[~mask])
if tr3_:
tri3 = np.append(tr3, tr3_, axis=0).astype(int)
else:
tri3 = tr3.astype(int)
except:
tri3 = tes.astype(int)
times = kwargs.get("times", self._obj.time.values)
z = kwargs.get("z", self._obj[var].values[0, :].flatten())
zmin = self._obj[var].values.min()
zmax = self._obj[var].values.max()
nodes = pd.DataFrame({
"longitude": x,
"latitude": y,
"{}".format(var): z
})
elems = pd.DataFrame(tri3, columns=["a", "b", "c"])
width = kwargs.get("width", 800)
height = kwargs.get("height", 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS("https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png")
points = gv.operation.project_points(
gv.Points(nodes, vdims=["{}".format(var)]))
trimesh = gv.TriMesh((elems, points))
def time_mesh(time):
points.data[var] = self._obj[var].sel(time=time).values
return gv.TriMesh((elems, points)) # , crs=ccrs.GOOGLE_MERCATOR)
meshes = hv.DynamicMap(time_mesh,
kdims=["Time"]).redim.values(Time=times)
imesh = rasterize(meshes, aggregator="mean").opts(cmap="viridis",
colorbar=True,
padding=0.1,
tools=["hover"],
clim=(zmin, zmax))
if tiles:
return hv.output(tile * imesh, holomap="scrubber", fps=1)
else:
return hv.output(imesh.opts(width=width, height=height),
holomap="scrubber",
fps=1)
def mesh(self, tiles=False, **kwargs):
x = kwargs.get("x", self._obj.SCHISM_hgrid_node_x[:].values)
y = kwargs.get("y", self._obj.SCHISM_hgrid_node_y[:].values)
tes = kwargs.get("tri3", self._obj.SCHISM_hgrid_face_nodes.values)
width = kwargs.get("width", 800)
height = kwargs.get("height", 600)
opts.defaults(opts.WMTS(width=width, height=height))
tile = gv.WMTS("https://b.tile.openstreetmap.org/{Z}/{X}/{Y}.png")
nodes = pd.DataFrame({"longitude": x, "latitude": y})
points = gv.operation.project_points(gv.Points(nodes),
projection=ccrs.PlateCarree())
if tes.shape[1] == 3:
elems = pd.DataFrame(tes, columns=["a", "b", "c"])
if elems.min().min() > 0:
elems = elems - 1
trimesh = gv.TriMesh((elems, points)).edgepaths
if tiles:
return tile * datashade(
trimesh, precompute=True, cmap=["black"])
else:
return datashade(trimesh, precompute=True,
cmap=["green"]).opts(width=width,
height=height)
else: # there are quads
elems = pd.DataFrame(tes, columns=["a", "b", "c", "d"])
if elems.min().min() > 0:
elems = elems - 1
quads = elems.loc[~elems.d.isna()].copy()
quads = quads.reset_index(drop=True)
ap = nodes.loc[quads.a, ["longitude", "latitude"]]
bp = nodes.loc[quads.b, ["longitude", "latitude"]]
cp = nodes.loc[quads.c, ["longitude", "latitude"]]
dp = nodes.loc[quads.d, ["longitude", "latitude"]]
quads["ap"] = ap.values.tolist()
quads["bp"] = bp.values.tolist()
quads["cp"] = cp.values.tolist()
quads["dp"] = dp.values.tolist()
n = 2
al = quads.ap + quads.bp + quads.cp + quads.dp + quads.ap
coords = [[l[i:i + n] for i in range(0, len(l), n)] for l in al]
quads["coordinates"] = coords
qpolys = pygeos.polygons(quads.coordinates.to_list())
df = gp.GeoDataFrame(geometry=qpolys)
df_ = spatialpandas.GeoDataFrame(df)
q = gv.Path(df_)
qdf = dynspread(
rasterize(q, precompute=True).options(cmap=["black"]))
triangles = elems.loc[elems.d.isna()]
trimesh = gv.TriMesh((triangles, points)).edgepaths
wireframe = dynspread(
rasterize(trimesh, precompute=True).opts(cmap=["black"]))
if tiles:
return tile * wireframe * qdf
else:
return wireframe.opts(cmap=["green"]) * qdf.opts(
cmap=["green"])
