def get_legend(ctx: ServiceContext, ds_id: str, var_name: str,
params: RequestParams):
cmap_name = params.get_query_argument('cbar', default=None)
cmap_vmin = params.get_query_argument_float('vmin', default=None)
cmap_vmax = params.get_query_argument_float('vmax', default=None)
cmap_w = params.get_query_argument_int('width', default=None)
cmap_h = params.get_query_argument_int('height', default=None)
if cmap_name is None or cmap_vmin is None or cmap_vmax is None or cmap_w is None or cmap_h is None:
default_cmap_cbar, (default_cmap_vmin,
default_cmap_vmax) = ctx.get_color_mapping(
ds_id, var_name)
cmap_name = cmap_name or default_cmap_cbar
cmap_vmin = cmap_vmin or default_cmap_vmin
cmap_vmax = cmap_vmax or default_cmap_vmax
cmap_w = cmap_w or DEFAULT_CMAP_WIDTH
cmap_h = cmap_h or DEFAULT_CMAP_HEIGHT
try:
_, cmap = get_cmap(cmap_name)
except ValueError:
raise ServiceResourceNotFoundError(
f"color bar {cmap_name!r} not found")
fig = matplotlib.figure.Figure(figsize=(cmap_w, cmap_h))
ax1 = fig.add_subplot(1, 1, 1)
if '.cpd' in cmap_name:
norm, ticks = get_norm(cmap_name)
else:
norm = matplotlib.colors.Normalize(vmin=cmap_vmin, vmax=cmap_vmax)
ticks = None
image_legend = matplotlib.colorbar.ColorbarBase(ax1,
format='%.1f',
ticks=ticks,
cmap=cmap,
norm=norm,
orientation='vertical')
image_legend_label = ctx.get_legend_label(ds_id, var_name)
if image_legend_label is not None:
image_legend.set_label(image_legend_label)
fig.patch.set_facecolor('white')
fig.patch.set_alpha(0.0)
fig.tight_layout()
buffer = io.BytesIO()
fig.savefig(buffer, format='png')
return buffer.getvalue()
def get_dataset_tile(ctx: ServiceContext, ds_id: str, var_name: str, x: str,
y: str, z: str, params: RequestParams):
x = RequestParams.to_int('x', x)
y = RequestParams.to_int('y', y)
z = RequestParams.to_int('z', z)
tile_comp_mode = params.get_query_argument_int('mode', ctx.tile_comp_mode)
trace_perf = params.get_query_argument_int('debug', ctx.trace_perf) != 0
cmap_name = params.get_query_argument('cbar', default=None)
cmap_vmin = params.get_query_argument_float('vmin', default=None)
cmap_vmax = params.get_query_argument_float('vmax', default=None)
if cmap_name is None or cmap_vmin is None or cmap_vmax is None:
default_cmap_name, default_cmap_vmin, default_cmap_vmax = ctx.get_color_mapping(
ds_id, var_name)
cmap_name = cmap_name or default_cmap_name
cmap_vmin = cmap_vmin or default_cmap_vmin
cmap_vmax = cmap_vmax or default_cmap_vmax
ml_dataset = ctx.get_ml_dataset(ds_id)
var = ml_dataset.base_dataset[var_name]
labels = parse_non_spatial_labels(params.get_query_arguments(),
var.dims,
var.coords,
allow_slices=False,
exception_type=ServiceBadRequestError)
return get_ml_dataset_tile(ml_dataset,
var_name,
x,
y,
z,
labels=labels,
cmap_name=cmap_name,
cmap_vmin=cmap_vmin,
cmap_vmax=cmap_vmax,
image_cache=ctx.image_cache,
tile_cache=ctx.tile_cache,
tile_comp_mode=tile_comp_mode,
trace_perf=trace_perf,
exception_type=ServiceBadRequestError)
def get_var_indexers(cls, ds_name: str, var_name: str, var: xr.DataArray,
dim_names: List[str],
params: RequestParams) -> Dict[str, Any]:
var_indexers = dict()
for dim_name in dim_names:
if dim_name not in var.coords:
raise ServiceBadRequestError(
f'dimension {dim_name!r} of variable {var_name!r} of dataset {ds_name!r} has no coordinates'
)
coord_var = var.coords[dim_name]
dim_value_str = params.get_query_argument(dim_name, None)
try:
if dim_value_str is None:
var_indexers[dim_name] = coord_var.values[0]
elif dim_value_str == 'current':
var_indexers[dim_name] = coord_var.values[-1]
elif np.issubdtype(coord_var.dtype, np.floating):
var_indexers[dim_name] = float(dim_value_str)
elif np.issubdtype(coord_var.dtype, np.integer):
var_indexers[dim_name] = int(dim_value_str)
elif np.issubdtype(coord_var.dtype, np.datetime64):
if '/' in dim_value_str:
date_str_1, date_str_2 = dim_value_str.split(
'/', maxsplit=1)
var_indexer_1 = pd.to_datetime(date_str_1)
var_indexer_2 = pd.to_datetime(date_str_2)
var_indexers[dim_name] = var_indexer_1 + (
var_indexer_2 - var_indexer_1) / 2
else:
date_str = dim_value_str
var_indexers[dim_name] = pd.to_datetime(date_str)
else:
raise ValueError(
f'unable to convert value {dim_value_str!r} to {coord_var.dtype!r}'
)
except ValueError as e:
raise ServiceBadRequestError(
f'{dim_value_str!r} is not a valid value for dimension {dim_name!r} '
f'of variable {var_name!r} of dataset {ds_name!r}') from e
return var_indexers
def test_to_int(self):
self.assertEqual(2123, RequestParams.to_int('x', '2123'))
with self.assertRaises(ServiceBadRequestError):
RequestParams.to_int('x', None)
with self.assertRaises(ServiceBadRequestError):
RequestParams.to_int('x', 'bibo')
def test_to_float(self):
self.assertEqual(-0.2, RequestParams.to_float('x', '-0.2'))
with self.assertRaises(ServiceBadRequestError):
RequestParams.to_float('x', None)
with self.assertRaises(ServiceBadRequestError):
RequestParams.to_float('x', 'bibo')
def get_dataset_tile(ctx: ServiceContext, ds_id: str, var_name: str, x: str,
y: str, z: str, params: RequestParams):
x = RequestParams.to_int('x', x)
y = RequestParams.to_int('y', y)
z = RequestParams.to_int('z', z)
tile_comp_mode = params.get_query_argument_int('mode', ctx.tile_comp_mode)
trace_perf = params.get_query_argument_int('debug', ctx.trace_perf) != 0
ml_dataset = ctx.get_ml_dataset(ds_id)
if var_name == 'rgb':
norm_vmin = params.get_query_argument_float('vmin', default=0.0)
norm_vmax = params.get_query_argument_float('vmax', default=1.0)
var_names, norm_ranges = ctx.get_rgb_color_mapping(
ds_id, norm_range=(norm_vmin, norm_vmax))
components = ('r', 'g', 'b')
for i in range(3):
c = components[i]
var_names[i] = params.get_query_argument(c, default=var_names[i])
norm_ranges[i] = params.get_query_argument_float(f'{c}vmin', default=norm_ranges[i][0]), \
params.get_query_argument_float(f'{c}vmax', default=norm_ranges[i][1])
cmap_name = tuple(var_names)
cmap_range = tuple(norm_ranges)
for name in var_names:
if name and name not in ml_dataset.base_dataset:
raise ServiceBadRequestError(
f'Variable {name!r} not found in dataset {ds_id!r}')
var = None
for name in var_names:
if name and name in ml_dataset.base_dataset:
var = ml_dataset.base_dataset[name]
break
if var is None:
raise ServiceBadRequestError(
f'No variable in dataset {ds_id!r} specified for RGB')
else:
cmap_name = params.get_query_argument('cbar', default=None)
cmap_vmin = params.get_query_argument_float('vmin', default=None)
cmap_vmax = params.get_query_argument_float('vmax', default=None)
if cmap_name is None or cmap_vmin is None or cmap_vmax is None:
default_cmap_name, (default_cmap_vmin,
default_cmap_vmax) = ctx.get_color_mapping(
ds_id, var_name)
cmap_name = cmap_name or default_cmap_name
cmap_vmin = cmap_vmin or default_cmap_vmin
cmap_vmax = cmap_vmax or default_cmap_vmax
cmap_range = cmap_vmin, cmap_vmax
if var_name not in ml_dataset.base_dataset:
raise ServiceBadRequestError(
f'Variable {var_name!r} not found in dataset {ds_id!r}')
var = ml_dataset.base_dataset[var_name]
labels = parse_non_spatial_labels(params.get_query_arguments(),
var.dims,
var.coords,
allow_slices=False,
exception_type=ServiceBadRequestError)
return get_ml_dataset_tile(ml_dataset,
var_name,
x,
y,
z,
labels=labels,
cmap_name=cmap_name,
cmap_range=cmap_range,
image_cache=ctx.image_cache,
tile_cache=ctx.tile_cache,
tile_comp_mode=tile_comp_mode,
trace_perf=trace_perf,
exception_type=ServiceBadRequestError)
def get_ne2_tile(ctx: ServiceContext, x: str, y: str, z: str,
params: RequestParams):
x = params.to_int('x', x)
y = params.to_int('y', y)
z = params.to_int('z', z)
return NaturalEarth2Image.get_pyramid().get_tile(x, y, z)
def get_dataset_tile(ctx: ServiceContext, ds_id: str, var_name: str, x: str,
y: str, z: str, params: RequestParams):
x = RequestParams.to_int('x', x)
y = RequestParams.to_int('y', y)
z = RequestParams.to_int('z', z)
tile_comp_mode = params.get_query_argument_int('mode', ctx.tile_comp_mode)
trace_perf = params.get_query_argument_int('debug', ctx.trace_perf) != 0
measure_time = measure_time_cm(logger=_LOG, disabled=not trace_perf)
var = ctx.get_variable_for_z(ds_id, var_name, z)
dim_names = list(var.dims)
if 'lon' not in dim_names or 'lat' not in dim_names:
raise ServiceBadRequestError(
f'Variable "{var_name}" of dataset "{ds_id}" is not geo-spatial')
dim_names.remove('lon')
dim_names.remove('lat')
var_indexers = ctx.get_var_indexers(ds_id, var_name, var, dim_names,
params)
cmap_cbar = params.get_query_argument('cbar', default=None)
cmap_vmin = params.get_query_argument_float('vmin', default=None)
cmap_vmax = params.get_query_argument_float('vmax', default=None)
if cmap_cbar is None or cmap_vmin is None or cmap_vmax is None:
default_cmap_cbar, default_cmap_vmin, default_cmap_vmax = ctx.get_color_mapping(
ds_id, var_name)
cmap_cbar = cmap_cbar or default_cmap_cbar
cmap_vmin = cmap_vmin or default_cmap_vmin
cmap_vmax = cmap_vmax or default_cmap_vmax
image_id = '-'.join(
map(str, [ds_id, z, var_name, cmap_cbar, cmap_vmin, cmap_vmax] + [
f'{dim_name}={dim_value}'
for dim_name, dim_value in var_indexers.items()
]))
if image_id in ctx.image_cache:
image = ctx.image_cache[image_id]
else:
no_data_value = var.attrs.get('_FillValue')
valid_range = var.attrs.get('valid_range')
if valid_range is None:
valid_min = var.attrs.get('valid_min')
valid_max = var.attrs.get('valid_max')
if valid_min is not None and valid_max is not None:
valid_range = [valid_min, valid_max]
# Make sure we work with 2D image arrays only
if var.ndim == 2:
assert len(var_indexers) == 0
array = var
elif var.ndim > 2:
assert len(var_indexers) == var.ndim - 2
array = var.sel(method='nearest', **var_indexers)
else:
raise ServiceBadRequestError(
f'Variable "{var_name}" of dataset "{var_name}" '
'must be an N-D Dataset with N >= 2, '
f'but "{var_name}" is only {var.ndim}-D')
cmap_vmin = np.nanmin(
array.values) if np.isnan(cmap_vmin) else cmap_vmin
cmap_vmax = np.nanmax(
array.values) if np.isnan(cmap_vmax) else cmap_vmax
tile_grid = ctx.get_tile_grid(ds_id)
if not tile_comp_mode:
image = NdarrayImage(
array,
image_id=f'ndai-{image_id}',
tile_size=tile_grid.tile_size,
# tile_cache=ctx.tile_cache,
trace_perf=trace_perf)
image = TransformArrayImage(
image,
image_id=f'tai-{image_id}',
flip_y=tile_grid.inv_y,
force_masked=True,
no_data_value=no_data_value,
valid_range=valid_range,
# tile_cache=ctx.tile_cache,
trace_perf=trace_perf)
image = ColorMappedRgbaImage(image,
image_id=f'rgb-{image_id}',
value_range=(cmap_vmin, cmap_vmax),
cmap_name=cmap_cbar,
encode=True,
format='PNG',
tile_cache=ctx.tile_cache,
trace_perf=trace_perf)
else:
image = ColorMappedRgbaImage2(array,
image_id=f'rgb-{image_id}',
tile_size=tile_grid.tile_size,
cmap_range=(cmap_vmin, cmap_vmax),
cmap_name=cmap_cbar,
encode=True,
format='PNG',
flip_y=tile_grid.inv_y,
no_data_value=no_data_value,
valid_range=valid_range,
tile_cache=ctx.tile_cache,
trace_perf=trace_perf)
ctx.image_cache[image_id] = image
if trace_perf:
_LOG.info(
f'Created tiled image {image_id!r} of size {image.size} with tile grid:'
)
_LOG.info(f' num_levels: {tile_grid.num_levels}')
_LOG.info(f' num_level_zero_tiles: {tile_grid.num_tiles(0)}')
_LOG.info(f' tile_size: {tile_grid.tile_size}')
_LOG.info(f' geo_extent: {tile_grid.geo_extent}')
_LOG.info(f' inv_y: {tile_grid.inv_y}')
if trace_perf:
_LOG.info(f'>>> tile {image_id}/{z}/{y}/{x}')
with measure_time() as measured_time:
tile = image.get_tile(x, y)
if trace_perf:
_LOG.info(f'<<< tile {image_id}/{z}/{y}/{x}: took ' +
'%.2f seconds' % measured_time.duration)
return tile
