pycotools3.model.InsertParameters¶
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class
pycotools3.model.
InsertParameters
(model, parameter_dict=None, df=None, parameter_path=None, index=0, quantity_type='concentration', inplace=False)[source]¶ Parse parameters into a copasi model
Insert parameters from a file, dictionary or a pandas dataframe into a copasi file.
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__init__
(model, parameter_dict=None, df=None, parameter_path=None, index=0, quantity_type='concentration', inplace=False)[source]¶ Parameters: - model (
Model
) – The model to parse parameters into - parameter_dict (dict) – Default None. If not None, dict[parameter_name] = parameter_value
- df (pandas.DataFrame) – Default None. If not None, a dataframe containing parameters to insert
- parameter_path (str) – Default None. If not None a path to parameter estimation output file
- index (int) – Default 0 (best RSS). When multiple parameter sets available, rank of best fit you want to insert
- quantity_type (str) – concentration (default) or particle_numbers
- inplace (bool) – Whether to operate inplace or return a new model
- model (
Methods
__init__
(model[, parameter_dict, df, …])param model: The model to parse parameters into insert
()User other methods defined in this class to insert parameters into the model :return: insert_compartments
()insert new parameters into compartment :return: insert_global_quantities
()insert new parameters into compartment :return: insert_locals
()return: insert_metabolites
()insert new parameters into compartment :return: read_model
(m)param m: to_dict
()Args: Attributes
parameters
Get parameters depending on the type of input. -
insert
()[source]¶ User other methods defined in this class to insert parameters into the model :return:
Args:
Returns:
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parameters
¶ Get parameters depending on the type of input. Converge on a pandas dataframe. Columns = parameters, rows = parameter sets
Use check parameter consistency to see whether headers have been pruned or not. If not try pruning them
Args:
Returns:
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