"""
pysd.py
Contains all the code that will be directly accessed by the user in
normal operation.
"""
import sys
from pysd.py_backend.model import Model
if sys.version_info[:2] < (3, 7): # pragma: no cover
raise RuntimeError(
"\n\n"
+ "Your Python version is no longer supported by PySD.\n"
+ "The current version needs to run at least Python 3.7."
+ " You are running:\n\tPython "
+ sys.version
+ "."
+ "\nPlease update your Python version or use the last "
+ " supported version:\n\t"
+ "https://github.com/SDXorg/pysd/releases/tag/LastPy2"
)
[docs]def read_xmile(xmile_file, data_files=None, initialize=True,
missing_values="warning"):
"""
Construct a model from a Xmile file.
Parameters
----------
xmile_file: str or pathlib.Path
The relative path filename for a raw Xmile file.
initialize: bool (optional)
If False, the model will not be initialize when it is loaded.
Default is True.
data_files: list or str or None (optional)
If given the list of files where the necessary data to run the model
is given. Default is None.
missing_values: str ("warning", "error", "ignore", "keep") (optional)
What to do with missing values. If "warning" (default)
shows a warning message and interpolates the values.
If "raise" raises an error. If "ignore" interpolates
the values without showing anything. If "keep" it will keep
the missing values, this option may cause the integration to
fail, but it may be used to check the quality of the data.
Returns
-------
model: a PySD class object
Elements from the Python model are loaded into the PySD class
and ready to run
Examples
--------
>>> model = read_xmile('../tests/test-models/samples/teacup/teacup.xmile')
"""
from pysd.translators.xmile.xmile_file import XmileFile
from pysd.builders.python.python_model_builder import ModelBuilder
# Read and parse Xmile file
xmile_file_obj = XmileFile(xmile_file)
xmile_file_obj.parse()
# get AbstractModel
abs_model = xmile_file_obj.get_abstract_model()
# build Python file
py_model_file = ModelBuilder(abs_model).build_model()
# load Python file
model = load(py_model_file, data_files, initialize, missing_values)
model.xmile_file = str(xmile_file)
return model
[docs]def read_vensim(mdl_file, data_files=None, initialize=True,
missing_values="warning", split_views=False,
encoding=None, **kwargs):
"""
Construct a model from Vensim `.mdl` file.
Parameters
----------
mdl_file: str or pathlib.Path
The relative path filename for a raw Vensim `.mdl` file.
initialize: bool (optional)
If False, the model will not be initialize when it is loaded.
Default is True.
data_files: list or str or None (optional)
If given the list of files where the necessary data to run the model
is given. Default is None.
missing_values: str ("warning", "error", "ignore", "keep") (optional)
What to do with missing values. If "warning" (default)
shows a warning message and interpolates the values.
If "raise" raises an error. If "ignore" interpolates
the values without showing anything. If "keep" it will keep
the missing values, this option may cause the integration to
fail, but it may be used to check the quality of the data.
split_views: bool (optional)
If True, the sketch is parsed to detect model elements in each
model view, and then translate each view in a separate Python
file. Setting this argument to True is recommended for large
models split in many different views. Default is False.
encoding: str or None (optional)
Encoding of the source model file. If None, the encoding will be
read from the model, if the encoding is not defined in the model
file it will be set to 'UTF-8'. Default is None.
subview_sep: list
Characters used to separate views and subviews (e.g. [",", "."]).
If provided, and split_views=True, each submodule will be placed
inside the directory of the parent view.
**kwargs: (optional)
Additional keyword arguments for translation.
Returns
-------
model: a PySD class object
Elements from the Python model are loaded into the PySD class
and ready to run
Examples
--------
>>> model = read_vensim('../tests/test-models/samples/teacup/teacup.mdl')
"""
from pysd.translators.vensim.vensim_file import VensimFile
from pysd.builders.python.python_model_builder import ModelBuilder
# Read and parse Vensim file
ven_file = VensimFile(mdl_file, encoding=encoding)
ven_file.parse()
if split_views:
# split variables per views
subview_sep = kwargs.get("subview_sep", "")
ven_file.parse_sketch(subview_sep)
# get AbstractModel
abs_model = ven_file.get_abstract_model()
# build Python file
py_model_file = ModelBuilder(abs_model).build_model()
# load Python file
model = load(py_model_file, data_files, initialize, missing_values)
model.mdl_file = str(mdl_file)
return model
[docs]def load(py_model_file, data_files=None, initialize=True,
missing_values="warning"):
"""
Load a Python-converted model file.
Parameters
----------
py_model_file : str
Filename of a model which has already been converted into a
Python format.
initialize: bool (optional)
If False, the model will not be initialize when it is loaded.
Default is True.
data_files: dict or list or str or None
The dictionary with keys the name of file and variables to
load the data from there. Or the list of names or name of the
file to search the data in. Only works for TabData type object
and it is neccessary to provide it. Default is None.
missing_values : str ("warning", "error", "ignore", "keep") (optional)
What to do with missing values. If "warning" (default)
shows a warning message and interpolates the values.
If "raise" raises an error. If "ignore" interpolates
the values without showing anything. If "keep" it will keep
the missing values, this option may cause the integration to
fail, but it may be used to check the quality of the data.
Examples
--------
>>> model = load('../tests/test-models/samples/teacup/teacup.py')
"""
return Model(py_model_file, data_files, initialize, missing_values)