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Input product protocols

Input product extended protocol.

Attributes

ALECorrectionFunctionType module-attribute

Python
ALECorrectionFunctionType = Callable[[SCTInputProduct, pd.DataFrame], pd.DataFrame]

Classes

SCTInputProduct

Bases: QualityInputProduct, Protocol

SCT extended version of QualityInputProduct protocol

Attributes

footprint property
Python
footprint: Polygon | None

Get product scene footprint as a Shapely Polygon

Inputs managers

Input/Output utilities.

Attributes

Classes

InvalidProductType

Bases: RuntimeError

Invalid input product type

Functions:

product_loader

Python
product_loader(product_path: Path, external_orbit: Path | None = None, external_corrections_product: Path | None = None) -> tuple[SCTInputProduct, ALECorrectionFunctionType | None]

Load any supported product

Parameters:

Name Type Description Default
product_path Path

Path to the product to be loaded

 required
external_orbit Path | None

Path to external orbit file, if needed, by default None

 None
external_corrections_product Path | None

Path to external ALE corrections product, if needed, by default None

 None

Returns:

Type Description
SCTInputProduct

SCTInputProduct compliant object
ALECorrectionFunctionType | None

range and azimuth ale corrections function (if available)

Point Target and Calibration Sites utilities.

Attributes

Classes

UnsupportedPointTargetSource

Bases: RuntimeError

External point target source provided is not supported

Functions:

extract_point_target_data_from_source

Python
extract_point_target_data_from_source(source: str | Path) -> pd.DataFrame

Managing external point target data source based on its type, unifying the output to the SCT standard.

Parameters:

Name Type Description Default
source str | Path

Path to the external source of point target files

 required

Returns:

Type Description
DataFrame

pandas dataframe corresponding to the input point target file

read_csv_point_targets_file

Python
read_csv_point_targets_file(source: Path) -> pd.DataFrame

Reading the input .csv file containing Point Target locations and info and converting it to a Pandas DataFrame.

Parameters:

Name Type Description Default
source Path

path to the .csv file

 required

Returns:

Type Description
DataFrame

Point Targets DataFrame

read_geojson_point_targets_file

Python
read_geojson_point_targets_file(surveys: Path, product_date: PreciseDateTime | None = None) -> pd.DataFrame

Reading the input .geojson file containing Point Target locations and info and converting it to Pandas DataFrame.

Parameters:

Name Type Description Default
surveys Path

path to the surveys .json file

 required
product_date PreciseDateTime | None

product acquisition date, this date is needed to select the proper survey data in case several surveys are available, if None, the latest survey is selected, by default None

 None

Returns:

Type Description
DataFrame

Point Targets DataFrame

convert_df_to_nominal_point_target

Python
convert_df_to_nominal_point_target(data_df: DataFrame) -> list[PointTarget]

Convert dataframe to dictionary of NominalPointTarget values.

Parameters:

Name Type Description Default
data_df DataFrame

point target dataframe

 required

Returns:

Type Description
list[PointTarget]

list of Point Target objects

convert_rosamond_file_to_compliant_csv

Python
convert_rosamond_file_to_compliant_csv(df: str | Path | DataFrame, measurement_date: PreciseDateTime) -> pd.DataFrame

Formatting downloaded Rosamond Point Target Dataset to be compliant with the SCT input .csv format.

Parameters:

Name Type Description Default
df str | Path | DataFrame

downloaded Rosamond Point Target dataset, can be a path to the .csv file or the corresponding pandas dataframe

 required
measurement_date PreciseDateTime

measurement date of the current dataset

 required

Returns:

Type Description
DataFrame

SCT compliant Rosamond dataframe

Antenna Pattern Data reader for the supported antenna pattern data model.

Functions:

read_antenna_pattern_netcdf

Python
read_antenna_pattern_netcdf(path: Path) -> dict[str, dict[str, xr.Dataset]]

Reading Antenna Pattern data from NetCDF file and returning a dictionary containing the content divided by swath and polarization.

Hierarchy:

Text Only
root/
└── swath
    └── direction (e.g. `TW`)
        └──polarization (e.g. `HH`, `VV`)
            ├── gain (in dB)
            ├── phase (optional, in rad)
            ├── azimuth_angles (in deg)
            └── elevation_angles (in deg)

Supported Products

Only Two Way Antenna Patterns are supported, so only one direction group is expected.

Parameters:

Name Type Description Default
path Path

Path to the NetCDF file containing the antenna pattern data. The structure of the file must adhere to the following structure:

 required

Returns:

Type Description
dict[str, dict[str, Dataset]]

nested dictionary containing the antenna pattern data divided by swath and polarization