NRWAL.handlers.directories.EquationDirectory
- class EquationDirectory(eqn_dir, interp_extrap_power=False, use_nearest_power=False, interp_extrap_year=False, use_nearest_year=False)[source]
Bases:
objectClass to handle a directory with one or more equation files or a directory containing subdirectories with one or more equation files.
Examples
The NRWAL EquationDirectory object is instantiated from a directory input arg that contains nested equation yaml or json files.
>>> from NRWAL import EquationDirectory >>> >>> obj = EquationDirectory('./NRWAL') >>> >>> obj 2015 variables.yaml transmission_cost: 6536 tower_cost: 3960 pile_cost: 2250 monopile_tp_cost: 3230 lattice_cost: 4680 jacket_tp_cost: 4599 stiffened_column_cost: 3120 tapered_column_cost: 4220 truss_cost: 6250 heave_plate_cost: 5250 outfitting_cost: 7250 perm_ballast_cost: 150 operations_cost: 18880383 port_cost: 25000000 hz_turbine_factor: 0.05 windflip_CAPEX: 50000000 vertical_tow_OM_equip: 13400000 lease_price: 50000000 array.yaml fixed(depth, num_turbines) floating(depth, num_turbines) ... turbine_install.yaml jacket_3MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) jacket_6MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) jacket_10MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) jacket_12MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) jacket_15MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) monopile_3MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) monopile_6MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) monopile_10MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) monopile_12MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) monopile_15MW(depth, dist_p_to_s, fixed_downtime, turbine_capacity) semi_3MW(dist_p_to_s_nolimit, floating_downtime) semi_6MW(dist_p_to_s_nolimit, floating_downtime) semi_10MW(dist_p_to_s_nolimit, floating_downtime) semi_12MW(dist_p_to_s_nolimit, floating_downtime) semi_15MW(dist_p_to_s_nolimit, floating_downtime) spar_3MW(dist_a_to_s, dist_p_to_a, floating_downtime) spar_6MW(dist_a_to_s, dist_p_to_a, floating_downtime) spar_10MW(dist_a_to_s, dist_p_to_a, floating_downtime) spar_12MW(dist_a_to_s, dist_p_to_a, floating_downtime) spar_15MW(dist_a_to_s, dist_p_to_a, floating_downtime)
Nested EquationDirectory, EquationGroup, and Equation objects can be retrieved using the python bracket syntax similar to a python dictionary. Nested retrievals are delimited by two colons.
>>> type(obj['2015']) NRWAL.handlers.directories.EquationDirectory
>>> type(obj['2015::array']) NRWAL.handlers.groups.EquationGroup
>>> eqn = obj['2015::array::fixed'] >>> type(eqn) NRWAL.handlers.equations.Equation
>>> eqn fixed(depth, num_turbines)
NRWAL Equation objects can be evaluated using kwargs.
>>> import numpy as np >>> eqn.variables ['depth', 'num_turbines']
>>> eqn.eval(**{k: np.ones(2) for k in eqn.variables}) array([1.48410044e+08, 1.48410044e+08])
>>> eqn.eval(depth=np.ones(2), num_turbines=np.ones(2)) array([1.48410044e+08, 1.48410044e+08])
NRWAL Equation objects can be operated on using the usual python math operators. Note that the tower_cost input arg in this equation group is set to a default value of 3960 based on the variables.yaml file present in the 2015 directory. As a result, this argument does not need to be input in the eval() call, but can still be overwritten at runtime if desired.
>>> group = obj['2015::turbine'] >>> group EquationGroup object from "turbine.yaml" with heirarchy: rna(turbine_capacity) horiz_spar_rna(turbine_capacity, hz_turbine_factor=0.05) jacket_tower(depth, turbine_capacity, tower_cost=3960) monopile_tower(depth, turbine_capacity, tower_cost=3960) spar_tower(turbine_capacity) horiz_spar_tower(turbine_capacity, hz_turbine_factor=0.05) semi_tower(turbine_capacity)
>>> eqn = group['rna'] + group['monopile_tower'] >>> eqn (rna(turbine_capacity) + monopile_tower(depth, turbine_capacity, tower_cost=3960))
>>> eqn = group['rna'] - group['monopile_tower'] >>> eqn (rna(turbine_capacity) - monopile_tower(depth, turbine_capacity, tower_cost=3960))
>>> eqn = group['rna'] * group['monopile_tower'] >>> eqn (rna(turbine_capacity) * monopile_tower(depth, turbine_capacity, tower_cost=3960))
>>> eqn = group['rna'] / group['monopile_tower'] >>> eqn (rna(turbine_capacity) / monopile_tower(depth, turbine_capacity, tower_cost=3960))
>>> eqn = group['rna'] ** group['monopile_tower'] >>> eqn (rna(turbine_capacity) ** monopile_tower(depth, turbine_capacity, tower_cost=3960))
>>> eqn = group['rna'] + group['monopile_tower'] ** 2 >>> eqn (rna(turbine_capacity) + (monopile_tower(depth, turbine_capacity, tower_cost=3960) ** 2))
The new Equation objects resulting from math operations can be evaluated just like the original Equation objects.
>>> eqn = group['rna + monopile_tower'] >>> eqn (rna(turbine_capacity) + monopile_tower(depth, turbine_capacity, tower_cost=3960))
>>> eqn.variables ['depth', 'tower_cost', 'turbine_capacity']
>>> eqn.eval(**{k: np.ones(2) for k in eqn.variables}) array([1037835.27761686, 1037835.27761686])
>>> eqn.eval(depth=np.ones(2), turbine_capacity=np.ones(2)) array([1256782.29675191, 1256782.29675191])
The EquationDirectory object can parse power-dependent equations by searching for the “_10MW” string in the equation name request and the equations present in the directory (10 is an example and can be any integer). By default, only an exact match is returned, but the EquationDirectory object can also be set to perform interpolation + extrapolation or nearest neighbor lookup. Interpolation and extrapolation take priority over the use_nearest_power kwarg.
>>> obj['2015::spar'] EquationGroup object from "spar.yaml" with heirarchy: install_3MW(dist_p_to_a, dist_p_to_s, floating_downtime) install_6MW(dist_p_to_a, dist_p_to_s, floating_downtime) install_10MW(dist_p_to_a, dist_p_to_s, floating_downtime) spar_3MW(dist_a_to_s, dist_p_to_a) spar_6MW(dist_a_to_s, dist_p_to_a) spar_10MW(dist_a_to_s, dist_p_to_a) stiffened_column(depth, turbine_capacity, stiffened_column_cost=3120) tapered_column(turbine_capacity, tapered_column_cost=4220) outfitting(depth, turbine_capacity, outfitting_cost=7250) perm_ballast(turbine_capacity, perm_ballast_cost=150) stiffened_column_gt10MW(depth, stiffened_column_cost=3120) tapered_column_gt10MW(tapered_column_cost=4220) outfitting_gt10MW(depth, outfitting_cost=7250) perm_ballast_gt10MW(perm_ballast_cost=150)
>>> obj['2015::spar::spar_3MW'] spar_3MW(dist_a_to_s, dist_p_to_a)
>>> obj['2015::spar::spar_4MW'] KeyError: 'Could not retrieve equation key "2015::spar::spar_4MW"
>>> obj = EquationDirectory('./NRWAL', use_nearest_power=True) >>> obj['2015::spar::spar_4MW'] spar_3MW(dist_a_to_s, dist_p_to_a)
>>> obj = EquationDirectory('./NRWAL', interp_extrap_power=True) >>> obj['2015::spar::spar_4MW'] ((((spar_6MW(dist_a_to_s, dist_p_to_a) - spar_3MW(dist_a_to_s, dist_p_to_a)) * 1.0) / 3.0) + spar_3MW(dist_a_to_s, dist_p_to_a))
- Parameters:
eqn_dir (str) – Path to a directory with one or more equation files or a path to a directory containing subdirectories with one or more equation files.
interp_extrap_power (bool) – Flag to interpolate and extrapolate power (MW) dependent equations based on the case-insensitive regex pattern: “_[0-9]*MW$” This takes preference over the use_nearest_power flag. If both interp_extrap_power & use_nearest_power are False, a KeyError will be raised if the exact equation name request is not found.
use_nearest_power (bool) – Flag to use the nearest valid power (MW) dependent equation based on the case-insensitive regex pattern: “_[0-9]*MW$” This is second priority to the interp_extrap_power flag. If both interp_extrap_power & use_nearest_power are False, a KeyError will be raised if the exact equation name request is not found.
interp_extrap_year (bool) – Flag to interpolate and extrapolate equations keyed by year. This takes preference over the use_nearest_year flag. If both interp_extrap_year & use_nearest_year are False, a KeyError will be raised if the exact equation name request is not found.
use_nearest_year (bool) – Flag to use the nearest valid equation keyed by year. This is second priority to the interp_extrap_year flag. If both interp_extrap_year & use_nearest_year are False, a KeyError will be raised if the exact equation name request is not found.
Methods
Attempt to get a key from the EquationDirectory, return default_value if the key could not be retrieved
Return the first n lines of the directory string representation
Get the 1st level of equation (keys, values), same as dict.items().
Get the 1st level of equation keys, same as dict.keys()
Set default variables available to this object and all sub-directories, sub-groups, and equations within this object.
Return the last n lines of the directory string representation
Get the 1st level of equation values, same as dict.values()
Attributes
List of all Equation objects from this object.
Get a dictionary of default variables from a variables.yaml file accessible to this object
- __add__(other)[source]
Add another equation dir to this instance of EquationDirectory (self) and return a new EquationDirectory object that updates this instance with the new input. Note that overlapping sub directories or EquationGroups in the original EquationDirectory can be overwritten by the new input if a duplicate key exists.
- Parameters:
other (EquationDirectory | str) – Another EquationDirectory object or path to an EquationDirectory to add to this instance of EquationDirectory (self).
- Returns:
out (EquationDirectory) – A new EquationDirectory instance with this instance of EquationDirectory (self) updated with the input EquationDirectory. Note that overlapping sub directories or EquationGroups in the original EquationDirectory may be overwritten by the new input if a duplicate key exists.
- set_default_variables(var_group=None, force_update=False)[source]
Set default variables available to this object and all sub-directories, sub-groups, and equations within this object.
- Parameters:
var_group (dict | None) – Default variables namespace that will be set to the EquationGroup objects in this EquationDirectory unless other variables.yaml files are found on the local level in sub-directories. These variables can always be overwritten when Equation.evaluate() is called.
force_update (bool) – Flag to force updates to local VariableGroup objects (variables.yaml files) contained in lower level directories. Default is False so that lower level directories will maintain their locally-defined default variables.
- property default_variables
Get a dictionary of default variables from a variables.yaml file accessible to this object
- Returns:
dict
- property all_equations
List of all Equation objects from this object.