def plot_results(
figsize: Tuple[int, int] = (8, 8),
filepaths: List[Union[str, Path]] = None,
titles: List[str] = None,
) -> None:
tools = Tools(auth=_auth)
tools.plot_results(figsize, filepaths, titles)
def get_blocks(
block_type=None,
basic: bool = True,
as_dataframe=False,
):
tools = Tools(auth=_auth)
return tools.get_blocks(block_type, basic, as_dataframe)
def plot_coverage(
scenes: GeoDataFrame,
aoi: GeoDataFrame = None,
legend_column: str = "scene_id",
figsize=(12, 16),
) -> None:
tools = Tools(auth=_auth)
tools.plot_coverage(scenes, aoi, legend_column, figsize)
def get_block_details(auth, block_name):
"""
Get details of block by block name.
"""
logger.info(
pprint_json(
Tools(auth).get_block_details(
Tools(auth).get_blocks()[block_name])))
def construct_parameters(catalog, geom_file, start_date, end_date, sensors,
limit, max_cloud_cover):
"""
Follows STAC principles and property names to create a filter for
catalog search.
"""
geometry = Tools(catalog.auth).read_vector_file(geom_file)
start_date_str = start_date.strftime("%Y-%m-%d")
end_date_str = end_date.strftime("%Y-%m-%d")
logger.info(
pprint_json(
catalog.construct_parameters(geometry, start_date_str,
end_date_str, sensors, limit,
max_cloud_cover)))
def _construct_full_workflow_tasks_dict(
self, input_tasks: Union[List]) -> List[dict]:
"""
Constructs the full workflow task definition from a simplified version.
Accepts blocks ids, block names, block display names & combinations of them.
Args:
input_tasks: List of block names, block ids, or block display names.
Returns:
The full workflow task definition.
Example:
```python
input_tasks = ["sobloo-s2-l1c-aoiclipped",
"tiling"]
```
```python
input_tasks = ["a2daaab4-196d-4226-a018-a810444dcad1",
"4ed70368-d4e1-4462-bef6-14e768049471"]
```
```python
input_tasks = ["Sentinel-2 L1C MSI AOI clipped",
"Raster Tiling"]
```
"""
full_input_tasks_definition = []
# Get public + custom blocks.
logging.getLogger("up42.tools").setLevel(logging.CRITICAL)
blocks: dict = Tools(auth=self.auth).get_blocks(
basic=False) # type: ignore
logging.getLogger("up42.tools").setLevel(logging.INFO)
# Get ids of the input tasks, regardless of the specified format.
blocks_id_name = {block["id"]: block["name"] for block in blocks}
blocks_name_id = {block["name"]: block["id"] for block in blocks}
blocks_displaynames_id = {
block["displayName"]: block["id"]
for block in blocks
}
input_tasks_ids = []
for task in input_tasks:
if task in list(blocks_id_name.keys()):
input_tasks_ids.append(task)
elif task in list(blocks_name_id.keys()):
input_tasks_ids.append(blocks_name_id[task])
elif task in list(blocks_displaynames_id.keys()):
input_tasks_ids.append(blocks_displaynames_id[task])
else:
raise ValueError(
f"The specified input task {task} does not match any "
f"available block.")
# Add first task, the data block.
data_task = {
"name": f"{blocks_id_name[input_tasks_ids[0]]}:1",
"parentName": None,
"blockId": input_tasks_ids[0],
}
full_input_tasks_definition.append(data_task)
previous_task_name = data_task["name"]
# All following (processing) blocks.
for block_id in input_tasks_ids[1:]:
# Check if multiple of the same block are in the input tasks definition,
# so that is does not get skipped as it has the same id.
counts = Counter(
[x["blockId"] for x in full_input_tasks_definition])
try:
count_block = int(counts[block_id]) + 1
except KeyError:
count_block = 1
next_task = {
"name": f"{blocks_id_name[block_id]}:{count_block}",
"parentName": previous_task_name,
"blockId": block_id,
}
full_input_tasks_definition.append(next_task)
previous_task_name = next_task["name"]
return full_input_tasks_definition
def plot_quicklooks(figsize: Tuple[int, int] = (8, 8),
filepaths: List = None) -> None:
tools = Tools(auth=_auth)
tools.plot_quicklooks(figsize, filepaths)
def read_vector_file(
filename: str = "aoi.geojson", as_dataframe: bool = False
) -> Union[Dict, GeoDataFrame]:
return Tools().read_vector_file(filename, as_dataframe)
def get_example_aoi(
location: str = "Berlin", as_dataframe: bool = False
) -> FeatureCollection:
return Tools().get_example_aoi(location, as_dataframe)
def validate_manifest(path_or_json: Union[str, Path, Dict]) -> Dict:
tools = Tools(auth=_auth)
return tools.validate_manifest(path_or_json)
def validate_manifest(auth, manifest_json):
"""
Validate a block manifest.
"""
logger.info(pprint_json(Tools(auth).validate_manifest(manifest_json)))
def full_process_value(self, ctx, value):
self.type = click.Choice(Tools(ctx.obj).get_blocks().keys())
return super().full_process_value(ctx, value) # pylint: disable=no-member
def get_blocks(auth, block_type, basic):
"""
Get public blocks information.
"""
logger.info(pprint_json(Tools(auth).get_blocks(block_type, basic)))
def get_example_aoi(
location: str = "Berlin", as_dataframe: bool = False
) -> Union[Dict, GeoDataFrame]:
return Tools().get_example_aoi(location, as_dataframe)
def read_vector_file(filename: str = "aoi.geojson",
as_dataframe: bool = False) -> FeatureCollection:
tools = Tools(auth=_auth)
return tools.read_vector_file(filename, as_dataframe)
def get_block_details(block_id: str, as_dataframe=False) -> Dict:
tools = Tools(auth=_auth)
return tools.get_block_details(block_id, as_dataframe)
def get_example_aoi(location: str = "Berlin",
as_dataframe: bool = False) -> FeatureCollection:
tools = Tools(auth=_auth)
return tools.get_example_aoi(location, as_dataframe)
def read_vector_file(
filename: str = "aoi.geojson", as_dataframe: bool = False
) -> FeatureCollection:
return Tools().read_vector_file(filename, as_dataframe)
def draw_aoi() -> None:
tools = Tools(auth=_auth)
tools.draw_aoi()
def draw_aoi() -> None:
return Tools().draw_aoi()
def full_process_value(self, ctx, value):
self.type = click.Choice(Tools(ctx.obj).get_blocks().keys())
return super(OptionChoiceFromContext,
self).full_process_value(ctx, value)