Solutions#
- class pybamm.Solution(all_ts, all_ys, all_models, all_inputs, t_event=None, y_event=None, termination='final time', all_sensitivities=False, all_yps=None, variables_returned=False, check_solution=True)[source]#
Class containing the solution of, and various attributes associated with, a PyBaMM model.
- Parameters:
all_ts (
numpy.array
, size (n,) (or list of these)) – A one-dimensional array containing the times at which the solution is evaluated. A list of times can be provided instead to initialize a solution with sub-solutions.all_ys (
numpy.array
, size (m, n) (or list of these)) – A two-dimensional array containing the values of the solution. y[i, :] is the vector of solutions at time t[i]. A list of ys can be provided instead to initialize a solution with sub-solutions.all_models (
pybamm.BaseModel
) – The model that was used to calculate the solution. A list of models can be provided instead to initialize a solution with sub-solutions that have been calculated using those models.all_inputs (dict (or list of these)) – The inputs that were used to calculate the solution A list of inputs can be provided instead to initialize a solution with sub-solutions.
t_event (
numpy.array
, size (1,)) – A zero-dimensional array containing the time at which the event happens.y_event (
numpy.array
, size (m,)) – A one-dimensional array containing the value of the solution at the time when the event happens.termination (str) – String to indicate why the solution terminated
all_sensitivities (bool or dict of lists) – True if sensitivities included as the solution of the explicit forwards equations. False if no sensitivities included/wanted. Dict if sensitivities are provided as a dict of {parameter: [sensitivities]} pairs.
variables_returned (bool) – Bool to indicate if all_ys contains the full state vector, or is empty because only requested variables have been returned. True if output_variables is used with a solver, otherwise False.
- property all_models#
Model(s) used for solution
- property first_state#
A Solution object that only contains the first state. This is faster to evaluate than the full solution when only the first state is needed (e.g. to initialize a model with the solution)
- get_data_dict(variables=None, short_names=None, cycles_and_steps=True)[source]#
Construct a (standard python) dictionary of the solution data containing the variables in variables. If variables is None then all variables are returned. Any variable names in short_names are replaced with the corresponding short name.
If the solution has cycles, then the cycle numbers and step numbers are also returned in the dictionary.
- Parameters:
- Returns:
A dictionary of the solution data
- Return type:
- property last_state#
A Solution object that only contains the final state. This is faster to evaluate than the full solution when only the final state is needed (e.g. to initialize a model with the solution)
- plot(output_variables=None, **kwargs)[source]#
A method to quickly plot the outputs of the solution. Creates a
pybamm.QuickPlot
object (with keyword arguments ‘kwargs’) and then callspybamm.QuickPlot.dynamic_plot()
.- Parameters:
output_variables (list, optional) – A list of the variables to plot.
**kwargs – Additional keyword arguments passed to
pybamm.QuickPlot.dynamic_plot()
. For a list of all possible keyword arguments seepybamm.QuickPlot
.
- plot_voltage_components(ax=None, show_legend=True, split_by_electrode=False, show_plot=True, **kwargs_fill)[source]#
Generate a plot showing the component overpotentials that make up the voltage
- Parameters:
ax (matplotlib Axis, optional) – The axis on which to put the plot. If None, a new figure and axis is created.
show_legend (bool, optional) – Whether to display the legend. Default is True.
split_by_electrode (bool, optional) – Whether to show the overpotentials for the negative and positive electrodes separately. Default is False.
show_plot (bool, optional) – Whether to show the plots. Default is True. Set to False if you want to only display the plot after plt.show() has been called.
kwargs_fill – Keyword arguments, passed to ax.fill_between.
- save_data(filename=None, variables=None, to_format='pickle', short_names=None)[source]#
Save solution data only (raw arrays)
- Parameters:
filename (str, optional) – The name of the file to save data to. If None, then a str is returned
variables (list, optional) – List of variables to save. If None, saves all of the variables that have been created so far
to_format (str, optional) –
The format to save to. Options are:
’pickle’ (default): creates a pickle file with the data dictionary
’matlab’: creates a .mat file, for loading in matlab
’csv’: creates a csv file (0D variables only)
’json’: creates a json file
short_names (dict, optional) – Dictionary of shortened names to use when saving. This may be necessary when saving to MATLAB, since no spaces or special characters are allowed in MATLAB variable names. Note that not all the variables need to be given a short name.
- Returns:
data – str if ‘csv’ or ‘json’ is chosen and filename is None, otherwise None
- Return type:
str, optional
- property sensitivities#
np_array
- Type:
Values of the sensitivities. Returns a dict of param_name
- property sub_solutions#
List of sub solutions that have been concatenated to form the full solution
- property t#
Times at which the solution is evaluated
- property t_event#
Time at which the event happens
- property termination#
Reason for termination
- property y#
Values of the solution
- property y_event#
Value of the solution at the time of the event