Parameter Exploration

Parameter exploration tools for PDEVisualizer.

This module provides tools for exploring how different parameters affect PDE solutions, including parameter sweeps, comparison grids, and sensitivity analysis.

class pdevisualizer.parameter_exploration.ParameterSweepResult(parameter_name, parameter_values, solutions, metrics, solver_config, execution_time)[source]

Bases: object

Results from a parameter sweep experiment.

Parameters:

parameter_name (str)
parameter_values (ndarray)
solutions (List[ndarray])
metrics (Dict[str, ndarray])
solver_config (Dict[str, Any])
execution_time (float)

parameter_name: str

parameter_values: ndarray

solutions: List[ndarray]

metrics: Dict[str, ndarray]

solver_config: Dict[str, Any]

execution_time: float

class pdevisualizer.parameter_exploration.ParameterExplorer(equation, grid_shape=(50, 50), boundary=None)[source]

Bases: object

Tool for exploring parameter spaces in PDE solutions.

This class provides methods for systematic parameter exploration, comparison studies, and sensitivity analysis.

Methods

`compare_parameters`(param_configs[, labels])	Compare solutions with different parameter configurations.
`parameter_sweep`(parameter_name, parameter_values)	Perform a parameter sweep across a range of values.
`sensitivity_analysis`(parameter_name, base_value)	Analyze sensitivity to parameter changes.
`set_initial_conditions`(u0[, v0])	Set initial conditions for parameter exploration.

Initialize parameter explorer.

Methods

`compare_parameters`(param_configs[, labels])	Compare solutions with different parameter configurations.
`parameter_sweep`(parameter_name, parameter_values)	Perform a parameter sweep across a range of values.
`sensitivity_analysis`(parameter_name, base_value)	Analyze sensitivity to parameter changes.
`set_initial_conditions`(u0[, v0])	Set initial conditions for parameter exploration.

Parameters:

equation (str)
grid_shape (Tuple[int, int])
boundary (BoundaryCondition | None)

__init__(equation, grid_shape=(50, 50), boundary=None)[source]

Initialize parameter explorer.

Parameters:

equation (str)
grid_shape (Tuple[int, int])
boundary (BoundaryCondition | None)

set_initial_conditions(u0, v0=None)[source]

Set initial conditions for parameter exploration.

Parameters:

u0 (ndarray)
v0 (ndarray | None)

parameter_sweep(parameter_name, parameter_values, custom_params=None, compute_metrics=True)[source]

Perform a parameter sweep across a range of values.

Parameters:

parameter_name (str)
parameter_values (ndarray | List[float])
custom_params (Dict[str, Any] | None)
compute_metrics (bool)

Return type:

ParameterSweepResult

compare_parameters(param_configs, labels=None)[source]

Compare solutions with different parameter configurations.

Parameters:

param_configs (List[Dict[str, Any]])
labels (List[str] | None)

Return type:

Dict[str, ndarray]

sensitivity_analysis(parameter_name, base_value, perturbation_percent=10.0, n_samples=5)[source]

Analyze sensitivity to parameter changes.

Parameters:

parameter_name (str)
base_value (float)
perturbation_percent (float)
n_samples (int)

Return type:

Dict[str, Any]

class pdevisualizer.parameter_exploration.ParameterVisualizer[source]

Bases: object

Visualization tools for parameter exploration results.

Methods

`plot_parameter_grid`(explorer, param1_name, ...)	Create a grid of solutions for two parameters.
`plot_parameter_sweep`(sweep_result[, ...])	Plot parameter sweep results.
`plot_sensitivity_analysis`(sensitivity_result)	Plot sensitivity analysis results.
`plot_solution_comparison`(solutions[, ...])	Plot multiple solutions side by side.

static plot_parameter_sweep(sweep_result, metric_names=None, figsize=(12, 8))[source]

Plot parameter sweep results.

Parameters:

sweep_result (ParameterSweepResult)
metric_names (List[str] | None)
figsize (Tuple[int, int])

Return type:

Figure

static plot_solution_comparison(solutions, figsize=(15, 5), cmap='viridis')[source]

Plot multiple solutions side by side.

Parameters:

solutions (Dict[str, ndarray])
figsize (Tuple[int, int])
cmap (str)

Return type:

Figure

static plot_parameter_grid(explorer, param1_name, param1_values, param2_name, param2_values, figsize=(12, 10), cmap='viridis')[source]

Create a grid of solutions for two parameters.

Parameters:

explorer (ParameterExplorer)
param1_name (str)
param1_values (ndarray | List[float])
param2_name (str)
param2_values (ndarray | List[float])
figsize (Tuple[int, int])
cmap (str)

Return type:

Figure

static plot_sensitivity_analysis(sensitivity_result, figsize=(12, 6))[source]

Plot sensitivity analysis results.

Parameters:

sensitivity_result (Dict[str, Any])
figsize (Tuple[int, int])

Return type:

Figure

ParameterExplorer

class pdevisualizer.parameter_exploration.ParameterExplorer(equation, grid_shape=(50, 50), boundary=None)[source]

Bases: object

Tool for exploring parameter spaces in PDE solutions.

This class provides methods for systematic parameter exploration, comparison studies, and sensitivity analysis.

Methods

`compare_parameters`(param_configs[, labels])	Compare solutions with different parameter configurations.
`parameter_sweep`(parameter_name, parameter_values)	Perform a parameter sweep across a range of values.
`sensitivity_analysis`(parameter_name, base_value)	Analyze sensitivity to parameter changes.
`set_initial_conditions`(u0[, v0])	Set initial conditions for parameter exploration.

Initialize parameter explorer.

Methods

`compare_parameters`(param_configs[, labels])	Compare solutions with different parameter configurations.
`parameter_sweep`(parameter_name, parameter_values)	Perform a parameter sweep across a range of values.
`sensitivity_analysis`(parameter_name, base_value)	Analyze sensitivity to parameter changes.
`set_initial_conditions`(u0[, v0])	Set initial conditions for parameter exploration.

Parameters:

equation (str)
grid_shape (Tuple[int, int])
boundary (BoundaryCondition | None)

__init__(equation, grid_shape=(50, 50), boundary=None)[source]

Initialize parameter explorer.

Parameters:

equation (str)
grid_shape (Tuple[int, int])
boundary (BoundaryCondition | None)

set_initial_conditions(u0, v0=None)[source]

Set initial conditions for parameter exploration.

Parameters:

u0 (ndarray)
v0 (ndarray | None)

parameter_sweep(parameter_name, parameter_values, custom_params=None, compute_metrics=True)[source]

Perform a parameter sweep across a range of values.

Parameters:

parameter_name (str)
parameter_values (ndarray | List[float])
custom_params (Dict[str, Any] | None)
compute_metrics (bool)

Return type:

ParameterSweepResult

compare_parameters(param_configs, labels=None)[source]

Compare solutions with different parameter configurations.

Parameters:

param_configs (List[Dict[str, Any]])
labels (List[str] | None)

Return type:

Dict[str, ndarray]

sensitivity_analysis(parameter_name, base_value, perturbation_percent=10.0, n_samples=5)[source]

Analyze sensitivity to parameter changes.

Parameters:

parameter_name (str)
base_value (float)
perturbation_percent (float)
n_samples (int)

Return type:

Dict[str, Any]

ParameterVisualizer

class pdevisualizer.parameter_exploration.ParameterVisualizer[source]

Bases: object

Visualization tools for parameter exploration results.

Methods

`plot_parameter_grid`(explorer, param1_name, ...)	Create a grid of solutions for two parameters.
`plot_parameter_sweep`(sweep_result[, ...])	Plot parameter sweep results.
`plot_sensitivity_analysis`(sensitivity_result)	Plot sensitivity analysis results.
`plot_solution_comparison`(solutions[, ...])	Plot multiple solutions side by side.

static plot_parameter_sweep(sweep_result, metric_names=None, figsize=(12, 8))[source]

Plot parameter sweep results.

Parameters:

sweep_result (ParameterSweepResult)
metric_names (List[str] | None)
figsize (Tuple[int, int])

Return type:

Figure

static plot_solution_comparison(solutions, figsize=(15, 5), cmap='viridis')[source]

Plot multiple solutions side by side.

Parameters:

solutions (Dict[str, ndarray])
figsize (Tuple[int, int])
cmap (str)

Return type:

Figure

static plot_parameter_grid(explorer, param1_name, param1_values, param2_name, param2_values, figsize=(12, 10), cmap='viridis')[source]

Create a grid of solutions for two parameters.

Parameters:

explorer (ParameterExplorer)
param1_name (str)
param1_values (ndarray | List[float])
param2_name (str)
param2_values (ndarray | List[float])
figsize (Tuple[int, int])
cmap (str)

Return type:

Figure

static plot_sensitivity_analysis(sensitivity_result, figsize=(12, 6))[source]

Plot sensitivity analysis results.

Parameters:

sensitivity_result (Dict[str, Any])
figsize (Tuple[int, int])

Return type:

Figure

ParameterSweepResult

class pdevisualizer.parameter_exploration.ParameterSweepResult(parameter_name, parameter_values, solutions, metrics, solver_config, execution_time)[source]

Results from a parameter sweep experiment.

Parameters:

parameter_name (str)
parameter_values (ndarray)
solutions (List[ndarray])
metrics (Dict[str, ndarray])
solver_config (Dict[str, Any])
execution_time (float)

parameter_name: str

parameter_values: ndarray

solutions: List[ndarray]

metrics: Dict[str, ndarray]

solver_config: Dict[str, Any]

execution_time: float