center figures + small fixes

murrayrm · murrayrm · commit 1506ab060a90 · 2025-02-02T20:40:10.000-08:00
diff --git a/control/frdata.py b/control/frdata.py
@@ -97,7 +97,8 @@ class constructor, using the `frd` factory function, or
     Other Parameters
     ----------------
     plot_type : str, optional
-        Set the type of plot to generate with `plot()` ('bode', 'nichols').
+        Set the type of plot to generate with `~FrequencyResponseData.plot`
+        ('bode', 'nichols').
     title : str, optional
         Set the title to use when plotting.
     plot_magnitude, plot_phase : bool, optional
@@ -857,12 +858,12 @@ def append(self, other):
 
     # Plotting interface
     def plot(self, plot_type=None, *args, **kwargs):
-        """Plot the frequency response using a Bode plot.
+        """Plot the frequency response using Bode or singular values plot.
 
         Plot the frequency response using either a standard Bode plot
-        (default) or using a singular values plot (by setting `plot_type`
-        to 'svplot').  See `bode_plot` and `singular_values_plot` for more
-        detailed descriptions.
+        (``plot_type='bode'``, default) or a singular values plot
+        (``plot_type='svplot'``).  See `bode_plot` and
+        `singular_values_plot` for more detailed descriptions.
 
         """
         from .freqplot import bode_plot, singular_values_plot
diff --git a/control/nichols.py b/control/nichols.py
@@ -194,7 +194,7 @@ def nichols_grid(cl_mags=None, cl_phases=None, line_style='dotted', ax=None,
         :doc:`Matplotlib linestyle \
             <matplotlib:gallery/lines_bars_and_markers/linestyles>`.
     ax : matplotlib.axes.Axes, optional
-        Axes to add grid to.  If None, use `matplotlib.pyplot.gca()`.
+        Axes to add grid to.  If None, use `matplotlib.pyplot.gca`.
     label_cl_phases : bool, optional
         If True, closed-loop phase lines will be labelled.
 
diff --git a/control/optimal.py b/control/optimal.py
@@ -84,7 +84,7 @@ class OptimalControlProblem():
         will be broadcast by extension of the time axis.
     log : bool, optional
         If True, turn on logging messages (using Python logging module).
-        Use `python.logging.basicConfig` to enable logging output
+        Use `logging.basicConfig` to enable logging output
         (e.g., to a file).
 
     Attributes
@@ -1216,7 +1216,7 @@ def create_mpc_iosystem(
         `InputOutputSystem`.
     log : bool, optional
         If True, turn on logging messages (using Python logging module).
-        Use `python.logging.basicConfig` to enable logging output
+        Use `logging.basicConfig` to enable logging output
         (e.g., to a file).
     name : string, optional
         System name (used for specifying signals). If unspecified, a generic
diff --git a/doc/classes.rst b/doc/classes.rst
@@ -33,7 +33,8 @@ some of the functions that can be used to convert objects from one class to
 another:
 
 .. image:: figures/classes.pdf
-  :width: 800
+   :width: 800
+   :align: center
 
 
 Response and plotting classes
diff --git a/doc/conf.py b/doc/conf.py
@@ -104,6 +104,7 @@
     {'scipy': ('https://docs.scipy.org/doc/scipy', None),
      'numpy': ('https://numpy.org/doc/stable', None),
      'matplotlib': ('https://matplotlib.org/stable/', None),
+     'python': ('https://docs.python.org/3/', None),
      }
 
 # If this is True, todo and todolist produce output, else they produce nothing.
diff --git a/doc/config.rst b/doc/config.rst
@@ -159,7 +159,7 @@ System display parameters
    :value: True
 
    If True, show the input, output, and state count when using
-   `iosys_repr()` and the 'eval' format.  Otherwise, the input,
+   `iosys_repr` and the 'eval' format.  Otherwise, the input,
    output, and state values are repressed from the output unless
    non-generic signal names are present.
 
diff --git a/doc/iosys.rst b/doc/iosys.rst
@@ -83,6 +83,7 @@ diagram:
 
 .. image:: figures/bdalg-feedback.png
    :width: 240
+   :align: center
 
 By default a gain of -1 is applied at the output of the second system,
 so the dynamics illustrate above can be created using the command
diff --git a/doc/nlsys.rst b/doc/nlsys.rst
@@ -51,7 +51,8 @@ To illustrate the creation of a nonlinear I/O system model, consider a
 simple model of a spring loaded arm driven by a motor:
 
 .. image:: figures/servomech-diagram.png
-  :width: 240
+   :width: 240
+   :align: center
 
 The dynamics of this system can be modeling using the following code::
 
diff --git a/doc/optimal.rst b/doc/optimal.rst
@@ -84,6 +84,8 @@ length. This process is then repeated, resulting in a sampled data feedback
 law.  This approach is illustrated in the following figure:
 
 .. image:: figures/mpc-overview.png
+   :width: 640
+   :align: center
 
 Every :math:`\Delta T` seconds, an optimal control problem is solved over a
 :math:`T` second horizon, starting from the current state.  The first
@@ -286,7 +288,7 @@ Plotting the results::
 yields
 
 .. image:: figures/steering-optimal.png
-
+   :align: center
 
 An example showing the use of the optimal estimation problem and moving
 horizon estimation (MHE) is given in the :doc:`mhe-pvtol Jupyter
diff --git a/doc/phaseplot.rst b/doc/phaseplot.rst
@@ -19,6 +19,7 @@ The default method for generating a phase plane plot is to provide a
     ct.phase_plane_plot(sys, axis_limits, T)
 
 .. image:: figures/phaseplot-dampedosc-default.png
+   :align: center
 
 By default, the plot includes streamlines generated from starting
 points on limits of the plot, with arrows showing the flow of the
@@ -44,6 +45,7 @@ an inverted pendulum system, which is created using a mesh grid::
     plt.ylabel(r"$\dot\theta$ [rad/sec]")
 
 .. image:: figures/phaseplot-invpend-meshgrid.png
+   :align: center
 
 This figure shows several features of more complex phase plane plots:
 multiple equilibrium points are shown, with saddle points showing
@@ -75,6 +77,7 @@ are part of the :mod:`phaseplot` (pp) module::
     plt.gca().set_aspect('equal')
 
 .. image:: figures/phaseplot-oscillator-helpers.png
+   :align: center
 
 The following helper functions are available:
 
diff --git a/doc/response.rst b/doc/response.rst
@@ -222,6 +222,7 @@ for a two-input, two-output can be plotted using the commands::
 which produces the following plot:
 
 .. image:: figures/timeplot-mimo_step-default.png
+   :align: center
 
 A number of options are available in the :func:`time_response_plot`
 function (and associated :func:`TimeResponseData.plot` method) to
@@ -244,6 +245,7 @@ yields the following plot::
         "[plot_inputs, overlay_signals]")
 
 .. image:: figures/timeplot-mimo_step-pi_cs.png
+   :align: center
 
 Input/output response plots created with either the
 :func:`forced_response` or the
@@ -263,6 +265,7 @@ keyword::
       "[plot_inputs='overlay', legend_map]")
 
 .. image:: figures/timeplot-mimo_ioresp-ov_lm.png
+   :align: center
 
 Another option that is available is to use the `transpose` keyword so that
 instead of plotting the outputs on the top and inputs on the bottom, the
@@ -282,6 +285,7 @@ following figure::
           "[transpose]")
 
 .. image:: figures/timeplot-mimo_ioresp-mt_tr.png
+   :align: center
 
 This figure also illustrates the ability to create "multi-trace" plots
 using the :func:`combine_time_responses` function.  The line
@@ -300,6 +304,7 @@ and styles for various signals and traces::
       trace_props=[{'linestyle': s} for s in ['-', '--']])
 
 .. image:: figures/timeplot-mimo_step-linestyle.png
+   :align: center
 
 
 .. _frequency_response:
@@ -323,6 +328,7 @@ be generated using the :func:`bode_plot` function::
   ct.bode_plot(response, initial_phase=0)
 
 .. image:: figures/freqplot-siso_bode-default.png
+   :align: center
 
 Computing the response for multiple systems at the same time yields a
 common frequency range that covers the features of all listed systems.
@@ -336,6 +342,7 @@ Bode plots can also be created directly using the
   ct.frequency_response(sys_mimo).plot()
 
 .. image:: figures/freqplot-mimo_bode-default.png
+   :align: center
 
 A variety of options are available for customizing Bode plots, for
 example allowing the display of the phase to be turned off or
@@ -345,6 +352,7 @@ overlaying the inputs or outputs::
       plot_phase=False, overlay_inputs=True, overlay_outputs=True)
 
 .. image:: figures/freqplot-mimo_bode-magonly.png
+   :align: center
 
 The :func:`singular_values_response` function can be used to
 generate Bode plots that show the singular values of a transfer
@@ -353,6 +361,7 @@ function::
   ct.singular_values_response(sys_mimo).plot()
 
 .. image:: figures/freqplot-mimo_svplot-default.png
+   :align: center
 
 Different types of plots can also be specified for a given frequency
 response.  For example, to plot the frequency response using a a Nichols
@@ -361,6 +370,7 @@ plot, use ``plot_type='nichols'``::
   response.plot(plot_type='nichols')
 
 .. image:: figures/freqplot-siso_nichols-default.png
+   :align: center
 
 Another response function that can be used to generate Bode plots is the
 :func:`gangof4_response` function, which computes the four primary
@@ -372,6 +382,7 @@ sensitivity functions for a feedback control system in standard form::
   ct.bode_plot(response)	# or response.plot()
 
 .. image:: figures/freqplot-gangof4.png
+   :align: center
 
 Nyquist analysis can be done using the :func:`nyquist_response`
 function, which evaluates an LTI system along the Nyquist contour, and
@@ -381,6 +392,7 @@ the :func:`nyquist_plot` function, which generates a Nyquist plot::
   nyquist_plot(sys)
 
 .. image:: figures/freqplot-nyquist-default.png
+   :align: center
 
 The :func:`nyquist_response` function can be used to compute
 the number of encirclements of the -1 point and can return the Nyquist
@@ -403,6 +415,7 @@ the computation of the Nyquist curve and the way the data are plotted::
   print("Encirclements =", nyqresp.count)
 
 .. image:: figures/freqplot-nyquist-custom.png
+   :align: center
 
 All frequency domain plotting functions will automatically compute the
 range of frequencies to plot based on the poles and zeros of the frequency
@@ -415,6 +428,7 @@ array of frequencies as a second argument (after the list of systems)::
   ct.frequency_response([sys1, sys2], omega).plot(initial_phase=0)
 
 .. image:: figures/freqplot-siso_bode-omega.png
+   :align: center
 
 Alternatively, frequency ranges can be specified by passing a list of the
 form ``[wmin, wmax]``, where `wmin` and `wmax` are the minimum and
@@ -452,13 +466,15 @@ zeros and can be used to generate a pole/zero plot::
   ct.pole_zero_plot(response)
 
 .. image:: figures/pzmap-siso_ctime-default.png
+   :align: center
 
 A root locus plot shows the location of the closed loop poles of a system
 as a function of the loop gain::
 
   ct.root_locus_map(sys).plot()
 
 .. image:: figures/rlocus-siso_ctime-default.png
+   :align: center
 
 The grid in the left hand plane shows lines of constant damping ratio as
 well as arcs corresponding to the frequency of the complex pole.  The grid
@@ -472,6 +488,7 @@ diagram and display the gain and damping ratio for the clicked point below
 the plot title:
 
 .. image:: figures/rlocus-siso_ctime-clicked.png
+   :align: center
 
 Root locus diagrams are also supported for discrete time systems, in which
 case the grid is show inside the unit circle::
@@ -480,6 +497,7 @@ case the grid is show inside the unit circle::
   ct.root_locus_plot(sysd)
 
 .. image:: figures/rlocus-siso_dtime-default.png
+   :align: center
 
 Lists of systems can also be given, in which case the root locus diagram
 for each system is plotted in different colors::
@@ -489,6 +507,7 @@ for each system is plotted in different colors::
   ct.root_locus_plot([sys1, sys2], grid=False)
 
 .. image:: figures/rlocus-siso_multiple-nogrid.png
+   :align: center
 
 
 Customizing control plots
@@ -662,6 +681,7 @@ features::
     plt.tight_layout()
 
 .. image:: figures/ctrlplot-servomech.png
+   :align: center
 
 As this example illustrates, python-control plotting functions and
 Matplotlib plotting functions can generally be intermixed.  One type of
@@ -680,6 +700,7 @@ example::
     cplt.set_plot_title("Root locus plots (w/ specified axes)")
 
 .. image:: figures/ctrlplot-pole_zero_subplots.png
+   :align: center
 
 Alternatively, turning off the omega-damping grid (using ``grid=False`` or
 ``grid='empty'``) allows use of Matplotlib layout commands.

Original file line number	Diff line number	Diff line change
`@@ -104,6 +104,7 @@`
`104`	`104`	`{'scipy': ('https://docs.scipy.org/doc/scipy', None),`
`105`	`105`	`'numpy': ('https://numpy.org/doc/stable', None),`
`106`	`106`	`'matplotlib': ('https://matplotlib.org/stable/', None),`
	`107`	`+ 'python': ('https://docs.python.org/3/', None),`
`107`	`108`	`}`
`108`	`109`
`109`	`110`	`# If this is True, todo and todolist produce output, else they produce nothing.`