7.5.1.1. Abstract Look Up Table Dataloader

class meshiphi.dataloaders.lut.abstract_lut.LutDataLoader(bounds, params)

Abstract class for all LookUp Table Datasets.

__init__(bounds, params)

This is where large-scale operations are performed, such as importing data, downsampling, reprojecting, and renaming variables

Parameters:

  • bounds (Boundary) – Initial mesh boundary to limit scope of data ingest

  • params (dict) – Values needed by dataloader to initialise. Unique to each dataloader

self.data

Data stored by dataloader to use when called upon by the mesh. Must be saved in mercator projection (EPSG:4326), with columns ‘geometry’ and data_name.

Type:

gpd.DataFrame

self.data_name

Name of scalar variable. Must be the column name in the dataframe

Type:

str

Raises:

ValueError – If no data lies within the parsed boundary

add_default_params(params)

Set default values for all LUT dataloaders. This function should be overloaded to include any extra params for a specific dataloader

Parameters:

params (dict) – Dictionary containing attributes that are required for each dataloader.

Returns:

Dictionary of attributes the dataloader will require, completed with default values if not provided in config.

Return type:

(dict)

calculate_coverage(bounds, data=None)

Calculates percentage of boundary covered by dataset

Parameters:

  • bounds (Boundary) – Boundary being compared against

  • data (pd.DataFrame) – Dataset with shapely polygons in ‘geometry’ column Defaults to objects internal dataset.

Returns:

Decimal fraction of boundary covered by the dataset

Return type:

float

downsample()

Downsampling not supported by LookUpTable Dataloader

get_data_col_name()

Retrieve name of data column. Used for when data_name not defined in params.

Returns:

Name of data column

Return type:

str

Raises:

AssertionError – If multiple possible data columns found, can’t retrieve data name

get_hom_condition(bounds, splitting_conds, data=None)

Retrieves homogeneity condition of data within boundary.

Parameters:

  • bounds (Boundary) – Boundary object with limits of datarange to analyse

  • splitting_conds (dict) –

    Containing the following keys:

    ’boundary’:

    (boolean) True if user wants to split when polygon boundary goes through bounds

Returns:

The homogeniety condtion returned is of the form:

’CLR’ = the boundary is completely contained within the LUT regions, no need to split

’MIN’ = the boundary contains no LUT data, can’t split

’HET’ = the boundary contains an edge within the LUT data, should split

Return type:

str

get_value(bounds, agg_type=None, skipna=False, data=None)

Retrieve aggregated value from within bounds

Parameters:

  • aggregation_type (str) – Method of aggregation of datapoints within bounds. Can be upper or lower case. Accepts ‘MIN’, ‘MAX’, ‘MEAN’, ‘MEDIAN’, ‘STD’, ‘COUNT’

  • bounds (Boundary) – Boundary object with limits of lat/long

  • skipna (bool) – Defines whether to propogate NaN’s or not Default = False (includes NaN’s)

Returns:

{variable (str): aggregated_value (float)} Aggregated value within bounds following aggregation_type

Return type:

dict

Raises:

ValueError – aggregation type not in list of available methods

abstract import_data(bounds)

User defined method for importing data from files, or even generating data from scratch

Returns:

Coordinates and data being imported from file

if pd.DataFrame,

  • Must have columns ‘geometry’ and data_name

  • Must have single data column

Return type:

pd.DataFrame

reproject()

Reprojection not supported by LookUpTable Dataloader

set_data_col_name(new_name)

Sets name of data column/data variable

Parameters:

name (str) – Name to replace currently stored name with

Returns:

Data with variable name changed

Return type:

pd.DataFrame

trim_datapoints(bounds, data=None)

Trims datapoints from self.data within boundary defined by ‘bounds’. self.data can be pd.DataFrame or xr.Dataset

Parameters:

bounds (Boundary) – Limits of lat/long/time to select data from

Returns:

Trimmed dataset in same format as self.data

Return type:

pd.DataFrame

verify_data(data=None)

Verifies that all geometries read in are Polygons or MultiPolygons If MultiPolygon, then split out into multiple Polygons

Parameters:

data (pd.DataFrame, optional) – DataFrame with at least columns ‘geometry’ and a variable. Defaults to dataloader’s data attribute.

Raises:

ValueError – If read in a geometry that is not Polygon or MultiPolygon