Mar 2, 2012 · Jul 1, 2013 · Aug 27, 2012
diff --git a/CHANGELOG b/CHANGELOG
 2013-06-30 Add support for plotting callables via fplot
           Now one can use fplot and pass a callable to plot.  Plotted
 coordinates are dynamically managed based on the bounds of the
 current viewport - Damon McDougall

 2013-06-26 Refactored the axes module: the axes module is now a folder,
   containing the following submodule:
      - _subplots.py, containing all the subplots helper methods
diff --git a/boilerplate.py b/boilerplate.py
        'fill',
        'fill_between',
        'fill_betweenx',
        'fplot',
        'hexbin',
        'hist',
        'hist2d',
diff --git a/doc/users/whats_new.rst b/doc/users/whats_new.rst
 .. contents:: Table of Contents
   :depth: 3

 .. _whats-new-1-4:

 new in matplotlib-1.4
 =====================

 New plotting features
 ---------------------

 Callable plotting via fplot
 ```````````````````````````

 Damon McDougall added :func:`matplotlib.pyplot.fplot` which offers the
 flexibilty of plotting callables.  This is similar to Matlab's fplot.  Zooming
 and panning dynamically adjusts the plotted coordinates, allowing the
 possibilty to explore parts of the function that are less well behaved.  An
 attempt has been made to detect singularities in functions as well.  This
 feature is experimental and is likely to change in the future.

 .. plot:: mpl_examples/pylab_examples/fplot_demo.py

 .. _whats-new-1-3:

 new in matplotlib-1.3
diff --git a/examples/pylab_examples/fplot_demo.py b/examples/pylab_examples/fplot_demo.py
 import numpy as np
 import matplotlib.pyplot as plt

 # Set up figure
 fig, ax = plt.subplots()

 # Plot function
 fp = ax.fplot(np.tan, [0, 2])
 ax.set_xlim([1, 2])
 plt.show()
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
 import matplotlib.contour as mcontour
 import matplotlib.dates as _  # <-registers a date unit converter
 from matplotlib import docstring
 import matplotlib.fplot as mfplot
 import matplotlib.image as mimage
 import matplotlib.legend as mlegend
 import matplotlib.lines as mlines
        return stream_container
    streamplot.__doc__ = mstream.streamplot.__doc__

    def fplot(self, *args, **kwargs):
        return mfplot.fplot(self, *args, **kwargs)
    fplot.__doc__ = mfplot.fplot.__doc__

    @docstring.dedent_interpd
    def barbs(self, *args, **kw):
        """
diff --git a/lib/matplotlib/fplot.py b/lib/matplotlib/fplot.py
 """
 1D Callable function plotting.
 """

 import numpy as np


 __all__ = ['fplot']


 class FPlot(object):
    def __init__(self, axes, *args, **kwargs):
        self._process_args(*args, **kwargs)

        self.axes = axes
        self.axes.set_autoscale_on(False)

        self.n = kwargs.pop('res', 1000)

        self.x = np.linspace(self.limits[0], self.limits[1], self.n)
        self.f_vals = np.asarray([self.f(xi) for xi in self.x])

        self.fline, = self.axes.plot(self.x, self.f_vals)
        self._process_singularities()
        self.axes.set_xlim([self.x[0], self.x[-1]])
        mn, mx = np.nanmin(self.f_vals), np.nanmax(self.f_vals)
        self.axes.set_ylim([mn, mx])

        axes.callbacks.connect('xlim_changed', self._update)
        axes.callbacks.connect('ylim_changed', self._update)

    def _process_args(self, *args, **kwargs):
        # TODO: Check f is callable. If not callable, support array of callables.
        # TODO: Support y limits?
        self.f = args[0]
        self.limits = args[1]

    def _update(self, axes):
        # bounds is (l, b, w, h)
        bounds = axes.viewLim.bounds
        self.x = np.linspace(bounds[0], bounds[0] + bounds[2], self.n)
        self.f_vals = [self.f(xi) for xi in self.x]
        self._process_singularities()
        self.fline.set_data(self.x, self.f_vals)
        self.axes.figure.canvas.draw_idle()

    def _process_singularities(self):
        # Note:  d[i] == f_vals[i+1] - f_vals[i]
        d = np.diff(self.f_vals)

        # 80% is arbitrary.  Perhaps more control could be offered here?
        badness = np.where(d > 0.80 * self.axes.viewLim.bounds[3])[0]

        # We don't draw the signularities
        for b in badness:
            self.f_vals[b] = np.nan
            self.f_vals[b + 1] = np.nan


 def fplot(ax, *args, **kwargs):
    """
    Plots a callable function f.

    Parameters
    ----------
    f : Python callable, the function that is to be plotted.
    limits : 2-element array or list of limits: [xmin, xmax]. The function f
        is to to be plotted between xmin and xmax.

    Returns
    -------
    lines : `matplotlib.collections.LineCollection`
        Line collection with that describes the function *f* between xmin
        and xmax. all streamlines as a series of line segments.
    """
    if not ax._hold:
        ax.cla()
    return FPlot(ax, *args, **kwargs)
diff --git a/lib/matplotlib/pylab.py b/lib/matplotlib/pylab.py
  figure   - create or change active figure
  fill     - make filled polygons
  findobj  - recursively find all objects matching some criteria
  fplot    - a method to plot callables
  gca      - return the current axes
  gcf      - return the current figure
  gci      - get the current image, or None
diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py

    return ret

 # This function was autogenerated by boilerplate.py.  Do not edit as
 # changes will be lost
 @_autogen_docstring(Axes.fplot)
 def fplot(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.fplot(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

 # This function was autogenerated by boilerplate.py.  Do not edit as
 # changes will be lost
 @_autogen_docstring(Axes.hexbin)
Original file line number	Diff line number	Diff line change
		@@ -1,3 +1,8 @@
		2013-06-30 Add support for plotting callables via fplot
		Now one can use fplot and pass a callable to plot. Plotted
		coordinates are dynamically managed based on the bounds of the
		current viewport - Damon McDougall

		2013-06-26 Refactored the axes module: the axes module is now a folder,
		containing the following submodule:
		- _subplots.py, containing all the subplots helper methods
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -112,6 +112,7 @@ def boilerplate_gen():
		'fill',
		'fill_between',
		'fill_betweenx',
		'fplot',
		'hexbin',
		'hist',
		'hist2d',
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -18,6 +18,26 @@ revision, see the :ref:`github-stats`.
		.. contents:: Table of Contents
		:depth: 3

		.. _whats-new-1-4:

		new in matplotlib-1.4
		=====================

		New plotting features
		---------------------

		Callable plotting via fplot
		```````````````````````````

		Damon McDougall added :func:`matplotlib.pyplot.fplot` which offers the
		flexibilty of plotting callables. This is similar to Matlab's fplot. Zooming
		and panning dynamically adjusts the plotted coordinates, allowing the
		possibilty to explore parts of the function that are less well behaved. An
		attempt has been made to detect singularities in functions as well. This
		feature is experimental and is likely to change in the future.

		.. plot:: mpl_examples/pylab_examples/fplot_demo.py

		.. _whats-new-1-3:

		new in matplotlib-1.3
Expand Down
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,10 @@
		import numpy as np
		import matplotlib.pyplot as plt

		# Set up figure
		fig, ax = plt.subplots()

		# Plot function
		fp = ax.fplot(np.tan, [0, 2])
		ax.set_xlim([1, 2])
		plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -15,6 +15,7 @@
		import matplotlib.contour as mcontour
		import matplotlib.dates as _ # <-registers a date unit converter
		from matplotlib import docstring
		import matplotlib.fplot as mfplot
		import matplotlib.image as mimage
		import matplotlib.legend as mlegend
		import matplotlib.lines as mlines
Expand DownExpand Up		@@ -3762,6 +3763,10 @@ def streamplot(self, x, y, u, v, density=1, linewidth=None, color=None,
		return stream_container
		streamplot.__doc__ = mstream.streamplot.__doc__

		def fplot(self, args, *kwargs):
		return mfplot.fplot(self, args, *kwargs)
		fplot.__doc__ = mfplot.fplot.__doc__

		@docstring.dedent_interpd
		def barbs(self, args, *kw):
		"""
Expand Down
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,78 @@
		"""
		1D Callable function plotting.
		"""

		import numpy as np


		__all__ = ['fplot']


		class FPlot(object):
		def __init__(self, axes, args, *kwargs):
		self._process_args(args, *kwargs)

		self.axes = axes
		self.axes.set_autoscale_on(False)

		self.n = kwargs.pop('res', 1000)

		self.x = np.linspace(self.limits[0], self.limits[1], self.n)
		self.f_vals = np.asarray([self.f(xi) for xi in self.x])

		self.fline, = self.axes.plot(self.x, self.f_vals)
		self._process_singularities()
		self.axes.set_xlim([self.x[0], self.x[-1]])
		mn, mx = np.nanmin(self.f_vals), np.nanmax(self.f_vals)
		self.axes.set_ylim([mn, mx])

		axes.callbacks.connect('xlim_changed', self._update)
		axes.callbacks.connect('ylim_changed', self._update)

		def _process_args(self, args, *kwargs):
		# TODO: Check f is callable. If not callable, support array of callables.
Copy link Member pelsonAug 27, 2012 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Seems reasonable. Would be nice to document the args clearly at this point (for devs rather than users).
		# TODO: Support y limits?
		self.f = args[0]
		self.limits = args[1]

		def _update(self, axes):
		# bounds is (l, b, w, h)
		bounds = axes.viewLim.bounds
		self.x = np.linspace(bounds[0], bounds[0] + bounds[2], self.n)
		self.f_vals = [self.f(xi) for xi in self.x]
		self._process_singularities()
		self.fline.set_data(self.x, self.f_vals)
		self.axes.figure.canvas.draw_idle()

		def _process_singularities(self):
		# Note: d[i] == f_vals[i+1] - f_vals[i]
		d = np.diff(self.f_vals)

		# 80% is arbitrary. Perhaps more control could be offered here?
		badness = np.where(d > 0.80 * self.axes.viewLim.bounds[3])[0]

		# We don't draw the signularities
		for b in badness:
		self.f_vals[b] = np.nan
		self.f_vals[b + 1] = np.nan


		def fplot(ax, args, *kwargs):
		"""
		Plots a callable function f.

		Parameters
		----------
		f : Python callable, the function that is to be plotted.
		limits : 2-element array or list of limits: [xmin, xmax]. The function f
		is to to be plotted between xmin and xmax.

		Returns
		-------
		lines : `matplotlib.collections.LineCollection`
		Line collection with that describes the function f between xmin
		and xmax. all streamlines as a series of line segments.
		"""
		if not ax._hold:
		ax.cla()
		return FPlot(ax, args, *kwargs)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -42,6 +42,7 @@
		figure - create or change active figure
		fill - make filled polygons
		findobj - recursively find all objects matching some criteria
		fplot - a method to plot callables
		gca - return the current axes
		gcf - return the current figure
		gci - get the current image, or None
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -2779,6 +2779,24 @@ def fill_betweenx(y, x1, x2=0, where=None, hold=None, **kwargs):

		return ret

		# This function was autogenerated by boilerplate.py. Do not edit as
		# changes will be lost
		@_autogen_docstring(Axes.fplot)
		def fplot(args, *kwargs):
		ax = gca()
		# allow callers to override the hold state by passing hold=True\|False
		washold = ax.ishold()
		hold = kwargs.pop('hold', None)
		if hold is not None:
		ax.hold(hold)
		try:
		ret = ax.fplot(args, *kwargs)
		draw_if_interactive()
		finally:
		ax.hold(washold)

		return ret

		# This function was autogenerated by boilerplate.py. Do not edit as
		# changes will be lost
		@_autogen_docstring(Axes.hexbin)
Expand Down