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additional documentation updates + legacy settings for 0.10.1 Nyquist plots
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control/config.py

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@@ -297,7 +297,7 @@ def use_legacy_defaults(version):
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Parameters
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----------
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version : string
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Version number of the defaults desired. Ranges from '0.1' to '0.10.1'.
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Version number of `python-control` to use for setting defaults.
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Examples
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--------
@@ -342,6 +342,14 @@ def use_legacy_defaults(version):
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#
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reset_defaults() # start from a clean slate
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# Version 0.10.2:
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if major == 0 and minor < 10 or (minor == 10 and patch < 2):
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from math import inf
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# Reset Nyquist defaults
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set_defaults('nyquist', arrows=2, max_curve_magnitude=20,
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blend_fraction=0, indent_points=50)
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# Version 0.9.2:
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if major == 0 and minor < 9 or (minor == 9 and patch < 2):
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from math import inf

control/freqplot.py

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@@ -1659,7 +1659,7 @@ def nyquist_plot(
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portions of the contour are plotted using a different line style.
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label : str or array_like of str, optional
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If present, replace automatically generated label(s) with the given
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label(s). If sysdata is a list, strings should be specified for each
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label(s). If `data` is a list, strings should be specified for each
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system.
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label_freq : int, optional
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Label every nth frequency on the plot. If not specified, no labels
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elements is equivalent to providing `omega_limits`.
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omega_num : int, optional
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Number of samples to use for the frequency range. Defaults to
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`config.defaults['freqplot.number_of_samples']`. Ignored if data is
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not a list of systems.
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`config.defaults['freqplot.number_of_samples']`. Ignored if `data`
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is not a system or list of systems.
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plot : bool, optional
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(legacy) If given, `nyquist_plot` returns the legacy return values
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of (counts, contours). If False, return the values with no plot.

control/matlab/__init__.py

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@@ -6,7 +6,7 @@
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This subpackage contains a number of functions that emulate some of
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the functionality of MATLAB. The intent of these functions is to
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provide a simple interface to the python control systems library
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provide a simple interface to the Python Control Systems Library
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(python-control) for people who are familiar with the MATLAB Control
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Systems Toolbox (tm).
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doc/develop.rst

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@@ -110,8 +110,8 @@ Filenames
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* Source files are lower case, usually less than 10 characters (and 8
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or less is better).
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* Unit tests (in `control/tests/`) are of the form `module_test.py` or
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`module_function.py`.
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* Unit tests (in `control/tests/`) are of the form `module_test.py`,
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`module_functionality_test.py`, or `functionality_test.py`.
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Class names

doc/intro.rst

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@@ -126,7 +126,7 @@ some things to keep in mind:
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* Vectors and matrices used as arguments to functions can be written
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using lists, with commas required between elements and column
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vectors implemented as nested list . So [1 2 3] must be written as
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vectors implemented as nested lists. So [1 2 3] must be written as
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[1, 2, 3] and matrices are written using 2D nested lists, e.g., [[1,
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2], [3, 4]].
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* Functions that in MATLAB would return variable numbers of values
@@ -150,12 +150,12 @@ This documentation has a number of notional conventions and functionality:
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Manual, which contains documentation for all functions, classes,
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configurable default parameters, and other detailed information.
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* Class, functions, and methods with additional documentation appear
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* Classes, functions, and methods with additional documentation appear
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in a bold, code font that link to the Reference Manual. Example: `ss`.
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* Links to other sections appear in blue. Example: :ref:`nonlinear-systems`.
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* Parameters appear in a (non-bode) code font, as do code fragments.
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* Parameters appear in a (non-bold) code font, as do code fragments.
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Example: `omega`.
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* Example code is contained in code blocks that can be copied using

doc/releases/0.10.2-notes.rst

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@@ -9,15 +9,16 @@ Version 0.10.2 Release Notes (current)
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* `GitHub release page
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<https://github.com/python-control/python-control/releases/tag/0.10.2>`_
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This release contains numerous bug fixes and improvements, including
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substantial updates to the documentation, including refactoring of the
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online manual into a User Guide and a Reference Manual, as well as
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more consistent and complete docstrings. In addition, signals and
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systems can now be referenced using signal labels in addition to
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offsets, and phase plane plots make use of the matplotlib
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`~matplotlib.pyplot.streamplot` function. Numerous other changes have
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been made to improve consistency of keyword arguments and function
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names, with legacy aliases available.
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This release includes numerous bug fixes and improvements, with major
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changes such as a substantial reorganization of the documentation into
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a User Guide and Reference Manual, more consistent and complete
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docstrings, and support for referencing signals and subsystems by name
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as well as by index. Phase plane plots now use matplotlib’s
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`streamplot` for better visuals. New functions include `combine_tf`
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and `split_tf` for MIMO/SISO conversion and `disk_margins` for
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stability analysis. Additional improvements include consistent keyword
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usage, expanded LTI system methods for plotting and responses, better
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error messages, and legacy aliases to maintain backward compatibility.
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This version of `python-control` requires Python 3.10 or higher, NumPy
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1.23 or higher (2.x recommended), and SciPy 1.8 or higher.

examples/python-control_tutorial.ipynb

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"id": "qMVGK15gNQw2"
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},
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"source": [
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"## Example 1: Open loop analysis of a coupled mass spring system\n",
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"## Example 1: Open Loop Analysis of a Coupled Mass Spring System\n",
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"\n",
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"Consider the spring mass system below:\n",
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"\n",
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"id": "2f27f767-e012-45f9-8b76-cc040cfc89e2",
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"metadata": {},
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"source": [
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"## Example 2: Trajectory tracking for a kinematic vehicle model\n",
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"## Example 2: Trajectory Tracking for a Kinematic Vehicle Model\n",
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"\n",
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"This example illustrates the use of python-control to model, analyze, and design nonlinear control systems.\n",
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"\n",
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"id": "03b1fd75-579c-47da-805d-68f155957084",
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"metadata": {},
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"source": [
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"## Computing environment"
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"## Computing Environment"
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]
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},
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{

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