reVX.config.least_cost_xmission.LeastCostXmissionConfig

class LeastCostXmissionConfig(config)[source]

Bases: AnalysisConfig

Config framework for Least Cost Xmission

Parameters:: config (str | dict) – Path to config .json or pre-extracted config input dictionary.

Methods

`check_files`(flist)	Make sure all files in the input file list exist.
`check_overwrite_keys`(primary_key, ...)	Check for overwrite keys and raise a ConfigError if present
`clear`()
`copy`()
`fromkeys`([value])	Create a new dictionary with keys from iterable and values set to value.
`get`(key[, default])	Return the value for key if key is in the dictionary, else default.
`items`()
`keys`()
`pop`(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised
`popitem`()	Remove and return a (key, value) pair as a 2-tuple.
`resolve_path`(path)	Resolve a file path represented by the input string.
`set_self_dict`(dictlike)	Save a dict-like variable as object instance dictionary items.
`setdefault`(key[, default])	Insert key with a value of default if key is not in the dictionary.
`str_replace_and_resolve`(d, str_rep)	Perform a deep string replacement and path resolve in d.
`update`([E, ]**F)	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
`values`()

Attributes

`NAME`
`REQUIREMENTS`	Required keys for config
`STR_REP`	Mapping of config inputs (keys) to desired replacements (values) in addition to relative file paths as demarcated by ./ and ../
`analysis_years`	Get the analysis years.
`barrier_mult`	Transmission barrier multiplier to use for MCP costs
`capacity_class`	Capacity class, either {capacity}MW or capacity value in MW
`cell_size`	Side length of each cell, in meters.
`clipping_buffer`	Buffer to add to clipping radius
`config_dir`	Get the directory that the config file is in.
`config_keys`	List of valid config keys
`cost_fpath`	.h5 file with cost and required layers
`cost_layers`	List of H5 layers that are summed to determine total costs raster used for routing.
`execution_control`	Get the execution control object.
`expand_radius`	Optional flag to expand radius until at least one transmission feature is available for connection.
`features_fpath`	Tranmission feature .gpkg
`iso_regions_layer_name`	Name of ISO regions layer in cost_fpath file.
`length_invariant_cost_layers`	Layers to be added to the cost raster whose costs do not scale with distance traversed (i.e.
`length_mult_kind`	Type of length multiplier calcualtion.
`log_directory`	Get the logging directory, look for key "log_directory" in the config.
`log_level`	Get user-specified "log_level" (DEBUG, INFO, WARNING, etc...).
`min_line_length`	Minimum Tie-line length config input
`mp_delay`	Delay in seconds between starting multi-process workers.
`name`	Get the job name, defaults to the output directory name.
`nn_sinks`	Number of nearest neighbor sinks to use for clipping radius
`radius`	Optional radius to use for clipping
`region_identifier_column`	Name of column containing unique region identifier
`regions_fpath`	Reinforcement regions .gpkg
`resolution`	SC point resolution
`save_paths`	Save paths as GPKG if true
`sc_point_gids`	List of sc_point_gids to compute Least Cost Xmission for
`simplify_geo`	Optional float to use to simplify path geometries before saving to geopackage
`tb_layer_name`	Name of transmission barrier layer in cost_fpath file.
`tracked_layers`	Dictionary mapping layer names to strings, where the strings are numpy methods that should be applied to the layer along the LCP.
`xmission_config`	Xmission config input

REQUIREMENTS = ('cost_fpath', 'features_fpath', 'capacity_class', 'cost_layers'): Required keys for config

property name

Get the job name, defaults to the output directory name.

Returns:: _name (str) – Job name.

property radius: Optional radius to use for clipping

property expand_radius: Optional flag to expand radius until at least one transmission feature is available for connection.

property mp_delay: Delay in seconds between starting multi-process workers. Useful for reducing memory spike at working startup. By default, 3.0.

property simplify_geo: Optional float to use to simplify path geometries before saving to geopackage

property save_paths: Save paths as GPKG if true

property cost_fpath: .h5 file with cost and required layers

property features_fpath: Tranmission feature .gpkg

property regions_fpath: Reinforcement regions .gpkg

property region_identifier_column: Name of column containing unique region identifier

property capacity_class: Capacity class, either {capacity}MW or capacity value in MW

property resolution: SC point resolution

property xmission_config: Xmission config input

property length_mult_kind

Type of length multiplier calcualtion.

“step” computes length multipliers using a step function, while “linear” computes the length multiplier using a linear interpolation between 0 amd 10 mile spur-line lengths. By default, "linear".

property min_line_length: Minimum Tie-line length config input

property nn_sinks: Number of nearest neighbor sinks to use for clipping radius

property clipping_buffer: Buffer to add to clipping radius

property tb_layer_name: Name of transmission barrier layer in cost_fpath file.

property barrier_mult: Transmission barrier multiplier to use for MCP costs

property iso_regions_layer_name: Name of ISO regions layer in cost_fpath file.

property cost_layers: List[str]: List of H5 layers that are summed to determine total costs raster used for routing. Costs and distances for each individual layer are also reported (e.g. wet and dry costs).

property length_invariant_cost_layers: Layers to be added to the cost raster whose costs do not scale with distance traversed (i.e. fixed one-time costs for crossing these cells).

property tracked_layers: Dictionary mapping layer names to strings, where the strings are numpy methods that should be applied to the layer along the LCP.

property cell_size: Side length of each cell, in meters.

property sc_point_gids: List of sc_point_gids to compute Least Cost Xmission for

STR_REP = {'REVDIR': '/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/reV', 'TESTDATADIR': '/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/tests/data'}: Mapping of config inputs (keys) to desired replacements (values) in addition to relative file paths as demarcated by ./ and ../

property analysis_years

Get the analysis years.

Returns:: analysis_years (list) – List of years to analyze. If this is a single year run, this return value is a single entry list. If no analysis_years are specified, the code will look anticipate a year in the input files.

static check_files(flist)

Make sure all files in the input file list exist.

Parameters:: flist (list) – List of files (with paths) to check existance of.

check_overwrite_keys(primary_key, *overwrite_keys)

Check for overwrite keys and raise a ConfigError if present

Parameters:

primary_key (str) – Primary key that overwrites overwrite_keys, used for error message
overwrite_keys (str) – Key(s) to overwrite

clear() → None. Remove all items from D.

property config_dir

Get the directory that the config file is in.

Returns:: config_dir (str) – Directory path that the config file is in.

property config_keys

List of valid config keys

Returns:: list

copy() → a shallow copy of D

property execution_control

Get the execution control object.

Returns:: _ec (BaseExecutionConfig | EagleConfig) – reV execution config object specific to the execution_control option.

fromkeys(value=None, /): Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /): Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

property log_directory: Get the logging directory, look for key “log_directory” in the config. :returns: log_directory (str) – Target path for reV log files.

property log_level

Get user-specified “log_level” (DEBUG, INFO, WARNING, etc…).

Returns:: log_level (int) – Python logging module level (integer format) corresponding to the config-specified log level string.

pop(k[, d]) → v, remove specified key and return the corresponding value.: If key is not found, d is returned if given, otherwise KeyError is raised

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

resolve_path(path)

Resolve a file path represented by the input string.

This function resolves the input string if it resembles a path. Specifically, the string will be resolved if it starts with “./” or “..”, or it if it contains either “./” or “..” somewhere in the string body. Otherwise, the string is returned unchanged, so this function is safe to call on any string, even ones that do not resemble a path.

This method delegates the “resolving” logic to pathlib.Path.resolve(). This means the path is made absolute, symlinks are resolved, and “..” components are eliminated. If the path input starts with “./” or “..”, it is assumed to be w.r.t the config directory, not the run directory.

Parameters:: path (str) – Input file path.
Returns:: str – The resolved path.

set_self_dict(dictlike)

Save a dict-like variable as object instance dictionary items.

Parameters:: dictlike (dict) – Python namespace object to set to this dictionary-emulating class.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

str_replace_and_resolve(d, str_rep)

Perform a deep string replacement and path resolve in d.

Parameters:

d (dict) – Config dictionary potentially containing strings to replace and/or paths to resolve.
str_rep (dict) – Replacement mapping where keys are strings to search for and values are the new values.

Returns:

d (dict) – Config dictionary with updated strings.

update([E, ]**F) → None. Update D from dict/iterable E and F.: If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values