Plots

plot_dynamic_response

plot_dynamic_response(data, variable_name='voltModel')

Create a line plot of dynamic response for multiple designs.

This function generates a Plotly figure that visualizes the dynamic response given the variable name.

Parameters:

Name	Type	Description	Default
data	dict	A dictionary where keys are design names and values are dictionaries containing 'Time' and 'voltModel' data for each design. The structure should be: {design_name: {'Time': [...], 'voltModel': [...]}, ...}	required
variable_name	str	The name of the variable to plot. variable_name can be one of the following: Time, voltModel, voltAnode, voltCathode, ocvModel, ocvAnode, ocvCathode, tempSurfaceModel, socModel, socAnode, socCathode, currModel, heatFluxModel.	'voltModel'

Returns:

Type	Description
Figure	A Plotly Figure object representing the line plot of dynamic KPI performance, which can be displayed or further modified.

plot_kpis

plot_kpis(results, plot_type)

Create a horizontal bar plot comparing KPI values of different designs to a baseline.

This function generates a plotly figure that visualizes the performance of various design alternatives compared to a baseline design for different Key Performance Indicators (KPIs).

Parameters:

Name	Type	Description	Default
results	DataFrame	A DataFrame containing KPI values for different designs. It should have columns for 'KPI', 'Baseline', and other design alternatives.	required
plot_type	str	A string indicating the type of plot to generate. It can be either "relative" or "delta".	required

Returns:

Type	Description
Figure	A Plotly Figure object representing the horizontal bar chart of KPI values, which can be displayed or further modified.

plot_ocv

plot_ocv(battery)

Create a scatter plot of OCV data for a battery. This function generates a plotly figure that visualizes the OCV data for a battery.

Parameters:

Name	Type	Description	Default
battery	dict	A dictionary containing OCV data for a battery. The structure should be: { "SoC": [...], "ChargeVoltage_V_": [...], "DischargeVoltage_V_": [...], "AnodeChargeVoltage_V_": [...]	required

Returns:

Type	Description
Figure	A Plotly Figure object representing the scatter plot of OCV data, which can be displayed or further modified.

plot_sensitivities

plot_sensitivities(kpi_names, sensitivities)

Create a heatmap plot of sensitivities for different KPIs and parameters.

This function generates a heatmap visualization of the sensitivity values for various Key Performance Indicators (KPIs) with respect to different parameters. The heatmap is normalized for each KPI to enhance visual comparison.

Parameters:

Name	Type	Description	Default
kpi_names	list	A list of strings representing the names of the KPIs.	required
sensitivities	dict	A dictionary where keys are parameter names and values are lists of sensitivity values corresponding to each KPI.	required

Returns:

Type	Description
Figure	A Plotly Figure object representing the sensitivity heatmap, which can be displayed or further modified.

plot_voltage_response

plot_voltage_response(data)

Create a line plot of voltage response for multiple designs.

This function generates a Plotly figure that visualizes the voltage response of various designs over time, specifically focusing on voltage models.

Parameters:

Name	Type	Description	Default
data	dict	A dictionary where keys are design names and values are dictionaries containing 'Time' and 'voltModel' data for each design. The structure should be: {design_name: {'Time': [...], 'voltModel': [...]}, ...}	required

Returns:

Type	Description
Figure	A Plotly Figure object representing the line plot of dynamic KPI performance, which can be displayed or further modified.

radar_plot

radar_plot(results)

Create a radar plot to visualize the performance of various designs.

Parameters:

Name	Type	Description	Default
results	DataFrame	A DataFrame containing the performance metrics of various designs.	required

Returns:

Type	Description
Figure	A radar plot representing the performance of various designs.