easy_vic_build.build_Param

build_Param - A Python module for building VIC parameter file.

This module provides functions for constructing the Parameter file of the VIC model. It includes capabilities to: - Build the basic params_dataset_level0 - Build the params_dataset_level0 by g parameters and TF - Build the params_dataset_level1 - Searching grids for scaling grids from level 0 to level 1 - Scaling params_dataset_level0 to params_dataset_level1

Functions:

  • buildParam_level0: Build the parameter dataset for level 0, consisting of two components: buildParam_level0_basic and buildParam_level0_by_g.

  • buildParam_level0_basic: Build the basic parameter dataset for level 0.

  • buildParam_level0_by_g: Use global parameter lists and TF to generate the parameter dataset.

  • buildParam_level1: Build Level 1 parameters based on TF and dpc information.

  • scaling_level0_to_level1_search_grids: Searching grids for scaling grids from level 0 to level 1 (Matching).

  • scaling_level0_to_level1: Scaling the grid parameters from level 0 to level 1 based on matching grids.

Usage:

  1. Call buildParam_level0 and provide g_list as well as dpc instances to generate basic params_dataset_level0.

  2. Call buildParam_level1 to generate params_dataset_level1.

  3. Call scaling_level0_to_level1_search_grids to search grids for match grids at level 0 and level 1.

4. Call scaling_level0_to_level1 to scale params_dataset_level0 to params_dataset_level1. Note: The Transfer function and scaling operator is set in params_func.TransferFunction and params_func.Scaling_operator module.

Example:

basin_index = 213 model_scale = “6km” date_period = [“19980101”, “19981231”] case_name = f”{basin_index}_{model_scale}”

evb_dir = Evb_dir(cases_home=”./examples”) # cases_home=”/home/xdz/code/VIC_xdz/cases” evb_dir.builddir(case_name)

dpc_VIC_level0, dpc_VIC_level1, dpc_level2 = readdpc(evb_dir)

domain_dataset = readDomain(evb_dir)

params_dataset_level0, stand_grids_lat, stand_grids_lon, rows_index, cols_index = buildParam_level0(evb_dir, default_g_list, dpc_VIC_level0, reverse_lat=True) params_dataset_level1, stand_grids_lat, stand_grids_lon, rows_index, cols_index = buildParam_level1(evb_dir, dpc_VIC_level1, reverse_lat=True, domain_dataset=domain_dataset) params_dataset_level1, searched_grids_bool_index = scaling_level0_to_level1(params_dataset_level0, params_dataset_level1)

domain_dataset.close() params_dataset_level0.close() params_dataset_level1.close()

Dependencies:

  • numpy: For numerical computations and array manipulations.

  • bulid_Domain.cal_mask_frac_area_length: For calculating mask fraction, area, and length within a domain.

  • tools.decoractors: For measuring function execution time.

  • tools.dpc_func: For data processing and computation functions.

  • tools.geo_func: For geometric calculations and spatial operations.

  • tools.params_func: Custom utility functions for parameter handling.

  • tools.utilities: Custom utility functions.

  • tools.decoractors: For measuring function execution time (duplicate entry, consider consolidating).

Functions

buildParam_level0(evb_dir, g_params, ...[, ...])

Build the parameter dataset for level 0, consisting of two components: buildParam_level0_basic and buildParam_level0_by_g.

buildParam_level1(evb_dir, dpc_VIC_level1[, ...])

Build Level 1 parameters.

scaling_level0_to_level1(...[, ...])

Scaling the parameters from level 0 to level 1 based on matching grids.

scaling_level0_to_level1_search_grids(...)

Searching grids for scaling grids from level 0 to level 1 (Matching grids at different levels).
easy_vic_build.build_Param.buildParam_level0(evb_dir, g_params, soillayerresampler, dpc_VIC_level0, TF_VIC_class=<class 'easy_vic_build.tools.params_func.TransferFunction.TF_VIC'>, buildParam_level0_interface_class=<class 'easy_vic_build.tools.params_func.build_Param_interface.buildParam_level0_interface'>, reverse_lat=True, stand_grids_lat_level0=None, stand_grids_lon_level0=None, rows_index_level0=None, cols_index_level0=None)[source]

Build the parameter dataset for level 0, consisting of two components: buildParam_level0_basic and buildParam_level0_by_g.

Parameters:

evb_dirEvb_dir

An instance of the Evb_dir class, containing paths for VIC deployment.

g_listlist

A list of global parameters (g-parameters).

dpc_VIC_level0dpc_VIC_level0

An instance of the dpc_VIC_level0 class to process data at level 0 of the VIC model.

reverse_latbool

Boolean flag to indicate whether to reverse latitudes (Northern Hemisphere: large -> small, set as True).

stand_grids_latlist, optional

A list of standard latitudes. If not provided, will be calculated based on the grid shape.

stand_grids_lonlist, optional

A list of standard longitudes. If not provided, will be calculated based on the grid shape.

rows_indexlist, optional

A list of row indices for the grid. If not provided, will be calculated based on the grid shape.

cols_indexlist, optional

A list of column indices for the grid. If not provided, will be calculated based on the grid shape.

Returns:

params_dataset_level0netCDF.Dataset

The parameter dataset for level 0.

stand_grids_latlist

A list of standard latitudes.

stand_grids_lonlist

A list of standard longitudes.

rows_indexlist

A list of row indices for the grid.

cols_indexlist

A list of column indices for the grid.

Notes:

The function generates the parameter dataset for level 0, integrating two sub-components: buildParam_level0_basic for basic parameter generation and buildParam_level0_by_g for parameter adjustments based on global parameters.

easy_vic_build.build_Param.buildParam_level1(evb_dir, dpc_VIC_level1, TF_VIC_class=<class 'easy_vic_build.tools.params_func.TransferFunction.TF_VIC'>, buildParam_level1_interface_class=<class 'easy_vic_build.tools.params_func.build_Param_interface.buildParam_level1_interface'>, reverse_lat=True, domain_dataset=None, stand_grids_lat_level1=None, stand_grids_lon_level1=None, rows_index_level1=None, cols_index_level1=None)[source]

Build Level 1 parameters.

Parameters:

  • evb_dir (Evb_dir) – An instance of the Evb_dir class, containing paths for VIC deployment.

  • dpc_VIC_level1 (dpc_VIC_level1) – An instance of the dpc_VIC_level1 class to process data at level 0 of the VIC model.

  • reverse_lat (bool) – Boolean flag to indicate whether to reverse latitudes (Northern Hemisphere: large -> small, set as True).

  • domain_dataset (netCDF.Dataset, optional) – Domain dataset containing terrain and mask information. If not provided, mask will be computed based on dpc_VIC_level1.

  • stand_grids_lat (list of float, optional) – A list of standard grid latitudes. If not provided, will be calculated based on the grid shape.

  • stand_grids_lon (list of float, optional) – A list of standard grid longitudes. If not provided, will be calculated based on the grid shape.

  • rows_index (list of int, optional) – A list of row indices specifying grid positions. If not provided, will be calculated based on the grid shape.

  • cols_index (list of int, optional) – A list of column indices specifying grid positions. If not provided, will be calculated based on the grid shape.

Returns:

  • params_dataset_level1 (netCDF.Dataset) – The parameter dataset for level 1.

  • stand_grids_lat (list of float) – The list of standard grid latitudes used in the dataset.

  • stand_grids_lon (list of float) – The list of standard grid longitudes used in the dataset.

  • rows_index (list of int) – The list of row indices used in the grid.

  • cols_index (list of int) – The list of column indices used in the grid.

easy_vic_build.build_Param.scaling_level0_to_level1(params_dataset_level0, params_dataset_level1, searched_grids_bool_index=None, nlayer_list=[1, 2, 3])[source]

Scaling the parameters from level 0 to level 1 based on matching grids.

This function takes the parameters from the level 0 and level 1 datasets, and scales the grid parameters from the level 0 resolution to the level 1 resolution. It searches for the matching grids between the two levels and then returns the level 1 dataset with the corresponding data mapped from level 0, along with a boolean index indicating which grids in level 0 correspond to the grids in level 1. The scaling operators are applied.

Parameters:

  • params_dataset_level0 (netCDF.Dataset) – The parameter dataset for level 0.

  • params_dataset_level1 (netCDF.Dataset) – The parameter dataset for level 1.

  • searched_grids_bool_index (array-like, optional, default=None) – Boolean indices indicating which grids from level 0 match the grids from level 1. If not provided, it is calculated within the function.

Returns:

  • params_dataset_level1 (netCDF.Dataset) – The parameter dataset for level 1, with values from level 0 mapped onto the grids of level 1.

  • searched_grids_bool_index (array) – Boolean indices indicating which grids from level 0 correspond to grids from level 1.

Notes

  • This function performs a search for the closest grids between level 0 and level 1.

  • The mapping process takes into account the resolution of both grids and the spatial alignment.

easy_vic_build.build_Param.scaling_level0_to_level1_search_grids(params_dataset_level0, params_dataset_level1)[source]

Searching grids for scaling grids from level 0 to level 1 (Matching grids at different levels).

This function reads longitude and latitude values from the parameter datasets of level 0 and level 1, calculates the grid resolutions, creates 2D mesh grids for level 1, and searches for the closest matching grid indices between level 0 and level 1 with search_grids.search_grids_radius_rectangle. The function then converts the results into boolean indices for the corresponding grids.

Parameters:

  • params_dataset_level0 (object) – The parameter dataset for level 0, containing the longitude and latitude values of the original grid.

  • params_dataset_level1 (object) – The parameter dataset for level 1, containing the longitude and latitude values of the target grid.

Returns:

  • searched_grids_index (array) – The indices of the grids from level 0 that correspond to the grids of level 1.

  • searched_grids_bool_index (array) – Boolean indices indicating which grids from level 0 match the grids from level 1.