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murrayrmmurrayrm
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refactor config module to use local dictionaries + better helper functions
1 parent 44de990 commit d66db80

10 files changed

Lines changed: 406 additions & 172 deletions

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‎control/__init__.py‎

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Original file line numberDiff line numberDiff line change
@@ -84,3 +84,6 @@
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from numpy.testing import Tester
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test = Tester().test
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bench = Tester().bench
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# Initialize default parameter values
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reset_defaults()

‎control/config.py‎

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Original file line numberDiff line numberDiff line change
@@ -9,26 +9,103 @@
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import warnings
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__all__ = ['reset_defaults', 'use_matlab_defaults', 'use_fbs_defaults',
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__all__ = ['defaults', 'set_defaults', 'reset_defaults',
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'use_matlab_defaults', 'use_fbs_defaults',
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'use_numpy_matrix']
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# Dictionary of default values
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defaults = {
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'bode.dB':False, 'bode.deg':True, 'bode.Hz':False, 'bode.grid':True,
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'freqplot.feature_periphery_decades':1, 'freqplot.number_of_samples':None,
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'statesp.use_numpy_matrix':True,
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# Package level default values
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_control_defaults = {
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# No package level defaults (yet)
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}
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defaults = dict(_control_defaults)
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def set_defaults(module, **keywords):
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"""Set default values of parameters for a module.
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The set_defaults() function can be used to modify multiple parameter
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values for a module at the same time, using keyword arguments:
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control.set_defaults('module', param1=val, param2=val)
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"""
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if not isinstance(module, str):
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raise ValueError("module must be a string")
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for key, val in keywords.items():
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defaults[module + '.' + key] = val
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def reset_defaults():
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"""Reset configuration values to their default values."""
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defaults['bode.dB'] = False
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defaults['bode.deg'] = True
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defaults['bode.Hz'] = False
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defaults['bode.grid'] = True
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defaults['freqplot.number_of_samples'] = None
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defaults['freqplot.feature_periphery_decades'] = 1.0
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defaults['statesp.use_numpy_matrix'] = True
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"""Reset configuration values to their default (initial) values."""
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# System level defaults
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defaults.update(_control_defaults)
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from .freqplot import _bode_defaults, _freqplot_defaults
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defaults.update(_bode_defaults)
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defaults.update(_freqplot_defaults)
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from .nichols import _nichols_defaults
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defaults.update(_nichols_defaults)
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from .pzmap import _pzmap_defaults
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defaults.update(_pzmap_defaults)
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from .rlocus import _rlocus_defaults
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defaults.update(_rlocus_defaults)
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from .statesp import _statesp_defaults
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defaults.update(_statesp_defaults)
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def _get_param(module, param, argval=None, defval=None, pop=False):
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"""Return the default value for a configuration option.
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The _get_param() function is a utility function used to get the value of a
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parameter for a module based on the default parameter settings and any
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arguments passed to the function. The precedence order for parameters is
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the value passed to the function (as a keyword), the value from the
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config.defaults dictionary, and the default value `defval`.
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Parameters
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----------
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module : str
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Name of the module whose parameters are being requested.
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param : str
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Name of the parameter value to be determeind.
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argval : object or dict
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Value of the parameter as passed to the function. This can either be
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an object or a dictionary (i.e. the keyword list from the function
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call). Defaults to None.
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defval : object
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Default value of the parameter to use, if it is not located in the
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`config.defaults` dictionary. If a dictionary is provided, then
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`module.param` is used to determine the default value. Defaults to
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None.
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pop : bool
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If True and if argval is a dict, then pop the remove the parameter
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entry from the argval dict after retreiving it. This allows the use
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of a keyword argument list to be passed through to other functions
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internal to the function being called.
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"""
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# Make sure that we were passed sensible arguments
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if not isinstance(module, str) or not isinstance(param, str):
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raise ValueError("module and param must be strings")
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# Construction the name of the key, for later use
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key = module + '.' + param
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# If we were passed a dict for the argval, get the param value from there
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if isinstance(argval, dict):
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argval = argval.pop(param, None) if pop else argval.get(param, None)
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# If we were passed a dict for the defval, get the param value from there
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if isinstance(defval, dict):
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defval = defval.get(key, None)
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# Return the parameter value to use (argval > defaults > defval)
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return argval if argval is not None else defaults.get(key, defval)
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# Set defaults to match MATLAB
@@ -38,33 +115,23 @@ def use_matlab_defaults():
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The following conventions are used:
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* Bode plots plot gain in dB, phase in degrees, frequency in
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Hertz, with grids
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* State space class and functions use Numpy matrix objects
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"""
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# Bode plot defaults
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from .freqplot import bode_plot
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defaults['bode.dB'] = True
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defaults['bode.deg'] = True
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defaults['bode.Hz'] = True
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defaults['bode.grid'] = True
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defaults['statesp.use_numpy_matrix'] = True
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set_defaults('bode', dB=True, deg=True, Hz=True, grid=True)
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set_defaults('statesp', use_numpy_matrix=True)
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# Set defaults to match FBS (Astrom and Murray)
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def use_fbs_defaults():
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"""Use `Feedback Systems <http://fbsbook.org>`_ (FBS) compatible settings.
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The following conventions are used:
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* Bode plots plot gain in powers of ten, phase in degrees,
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frequency in Hertz, no grid
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"""
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# Bode plot defaults
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from .freqplot import bode_plot
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defaults['bode.dB'] = False
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defaults['bode.deg'] = True
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defaults['bode.Hz'] = False
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defaults['bode.grid'] = False
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set_defaults('bode', dB=False, deg=True, Hz=False, grid=False)
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# Decide whether to use numpy.matrix for state space operations
@@ -87,5 +154,5 @@ class and functions. If flat is `False`, then matrices are
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"""
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if flag and warn:
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warnings.warn("Return type numpy.matrix is soon to be deprecated.",
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stacklevel=2)
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defaults['statesp.use_numpy_matrix'] = flag
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stacklevel=2)
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set_defaults('statesp', use_numpy_matrix=flag)

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