Skip to content

Commit

Permalink
add mr_time_series from MPV5
Browse files Browse the repository at this point in the history 
- test unit
- removing mr_time_series from processor api
- cleaning notebook
  • Loading branch information
@jpn-geo6
Julien Papon authored and jpn-geo6 committed Oct 11, 2024
1 parent 28a1f62 commit 3a9fe8e
Show file tree
Hide file tree
Showing 7 changed files with 686 additions and 5,536 deletions.
5,035 changes: 69 additions & 4,966 deletions examples.ipynb
View file

Large diffs are not rendered by default.

149 changes: 70 additions & 79 deletions geosyspy/geosys.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -501,6 +501,70 @@ def get_coordinates_by_pixel(raster):
)
return dataset

def get_mr_time_series(
self,
start_date: datetime,
end_date: datetime,
indicator,
sensors_collection: Optional[list[SatelliteImageryCollection]] = [
SatelliteImageryCollection.SENTINEL_2,
],
aggregation: str = "Median",
smoothing_method: str = "Whittaker",
apply_denoiser: bool = True,
apply_end_of_curve: bool = True,
output_saturation: bool = False,
extract_raw_datasets: bool = False,
polygon: Optional[str] = None,
season_field_id: Optional[str] = None,
coverage_percent: Optional[int] = 80,
):
"""
Retrieves MR time series a given season field or geometry within the specified time range.
Args:
start_date (datetime): The start date of the time range for satellite coverage.
end_date (datetime): The end date of the time range for satellite coverage.
indicator (str): The indicator for which satellite imagery is requested.
sensors_collection (Optional[List[SatelliteImageryCollection]], optional):
A list of satellite imagery collections to consider.
Defaults to [SatelliteImageryCollection.SENTINEL_2].
coverage_percent (int, optional): Minimum clear cover percentage. Defaults to 80.
aggregation (str, optional): Method to aggregate data. Defaults to "Median".
smoothing_method (str, optional): Method to smooth data. Defaults to "Whittaker".
apply_denoiser (bool, optional): Whether to apply denoiser. Defaults to True.
apply_end_of_curve (bool, optional): Whether to apply end of curve. Defaults to True.
output_saturation (bool, optional): Whether to output saturation. Defaults to False.
extract_raw_datasets (bool, optional): Whether to extract raw datasets. Defaults to False.
season_field_id (Optional[str]): The identifier for the season field.
polygon (Optional[str]): The polygon geometry in WKT format.
Returns:
pd.DataFrame: DataFrame containing the satellite coverage data.
"""
if not season_field_id and not polygon:
raise ValueError(
"Parameters 'season_field_id' and 'polygon' cannot be both None or empty."
)

df = self.__map_product_service.get_mr_time_series(
season_field_id,
polygon,
start_date,
end_date,
indicator,
sensors_collection,
coverage_percent,
aggregation,
smoothing_method,
apply_denoiser,
apply_end_of_curve,
output_saturation,
extract_raw_datasets,
)

return df

###########################################
# ANALYTICS FABRIC #
###########################################
Expand Down Expand Up @@ -768,79 +832,6 @@ def check_status_and_metrics(self, task_id, schema, sf_unique_id):
self.__analytics_processor_service.wait_and_check_task_status(task_id)
return self.__analytics_fabric_service.get_lastest_metrics(sf_unique_id, schema)

def get_mr_time_series(
self,
polygon,
start_date: str = "2010-01-01",
end_date=None,
list_sensors=None,
denoiser: bool = True,
smoother: str = "ww",
eoc: bool = True,
aggregation: str = "mean",
index: str = "ndvi",
raw_data: bool = False,
):
"""Retrieve mr time series on the collection targeted.
Args:
start_date : The start date of the time series
end_date : The end date of the time series
list_sensors : The Satellite Imagery Collection targeted
denoiser : A boolean value indicating whether a denoising operation should be applied or not.
smoother : The type or name of the smoothing technique or algorithm to be used.
eoc : A boolean value indicating whether the "end of curve" detection should be performed.
func : The type or name of the function to be applied to the data.
index : The type or name of the index used for data manipulation or referencing
raw_data : A boolean value indicating whether the data is in its raw/unprocessed form.
polygon : A string representing a polygon.
Returns:
string : s3 bucket path
"""
if list_sensors is None:
list_sensors = [
"micasense",
"sequoia",
"m4c",
"sentinel_2",
"landsat_8",
"landsat_9",
"cbers4",
"kazstsat",
"alsat_1b",
"huanjing_2",
"deimos",
"gaofen_1",
"gaofen_6",
"resourcesat2",
"dmc_2",
"landsat_5",
"landsat_7",
"spot",
"rapideye_3a",
"rapideye_1b",
]
task_id = self.__analytics_processor_service.launch_mr_time_series_processor(
start_date=start_date,
end_date=end_date,
polygon=polygon,
raw_data=raw_data,
denoiser=denoiser,
smoother=smoother,
aggregation=aggregation,
list_sensors=list_sensors,
index=index,
eoc=eoc,
)

# check the task status to continue or not the process
self.__analytics_processor_service.wait_and_check_task_status(task_id)

return self.__analytics_processor_service.get_s3_path_from_task_and_processor(
task_id, processor_name="mrts"
)

def get_harvest_analytics(
self,
season_duration: int,
Expand Down Expand Up @@ -1291,13 +1282,13 @@ def get_farm_info_from_location(self, latitude: str, longitude: str):

return self.__gis_service.get_farm_info_from_location(latitude, longitude)

def get_municipio_id_from_geometry(self, geometry:str):
def get_municipio_id_from_geometry(self, geometry: str):
"""get Municipio id from a geometry
Args:
geometry (str): the geometry (WKT or GeosJson) to retrieve the municipio Id
Returns:
the internal id of the municipio
Args:
geometry (str): the geometry (WKT or GeosJson) to retrieve the municipio Id
Returns:
the internal id of the municipio
"""

return self.__gis_service.get_municipio_id_from_geometry(geometry)
return self.__gis_service.get_municipio_id_from_geometry(geometry)
Loading

0 comments on commit 3a9fe8e

Please sign in to comment.