aerosandbox.tools.pretty_plots.plots.plot_smooth
================================================

.. py:module:: aerosandbox.tools.pretty_plots.plots.plot_smooth


Attributes
----------

.. autoapisummary::

   aerosandbox.tools.pretty_plots.plots.plot_smooth.x


Functions
---------

.. autoapisummary::

   aerosandbox.tools.pretty_plots.plots.plot_smooth.plot_smooth


Module Contents
---------------

.. py:function:: plot_smooth(*args, color=None, label=None, function_of = None, resample_resolution = 500, drop_nans = False, **kwargs)

   Plots a curve that interpolates a 2D dataset. Same as matplotlib.pyplot.plot(), with the following changes:
       * uses B-splines to draw a smooth curve rather than a jagged polyline
       * By default, plots in line format `fmt='.-'` rather than `fmt='-'`.

   Other than that, almost all matplotlib.pyplot.plot() syntax can be used. See syntax here:
   https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html

   Example usage:
       >>> import aerosandbox.numpy as np
       >>>
       >>> t = np.linspace(0, 1, 12)  # Parametric variable
       >>> x = np.cos(2 * np.pi * t)
       >>> y = np.cos(2 * np.pi * t ** 4) - t
       >>>
       >>> plot_smooth(
       >>>     x, y, 'o--', color='purple'
       >>> )
       >>> plt.show()

   * Note: a true 2D interpolation is performed - it is not assumed y is a function of x, or vice versa. This can,
   in rare cases, cause single-valuedness to not be preserved in cases where it logically should. If this is the
   case, you need to perform the interpolation yourself without `plot_smooth()`.

   :param \*args: Same arguments as `matplotlib.pyplot.plot()`.
                  Notes on standard plot() syntax:

                      Call signatures:
                      >>> plot([x], y, [fmt], *, data=None, **kwargs)
                      >>> plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)

                      Examples:
                      >>> plot(x, y)        # plot x and y using default line style and color
                      >>> plot(x, y, 'bo')  # plot x and y using blue circle markers
                      >>> plot(y)           # plot y using x as index array 0..N-1
                      >>> plot(y, 'r+')     # ditto, but with red plusses
   :param color: Specifies the color of any line and/or markers that are plotted (as determined by the `fmt`).
   :param label: Attaches a label to this line. Use `plt.legend()` to display.
   :param resample_resolution: The number of points to use when resampling the interpolated curve.
   :param \*\*kwargs: Same keyword arguments as `matplotlib.pyplot.plot()`.

   Returns: A tuple `(x, y)` of the resampled points on the interpolated curve. Both `x` and `y` are 1D ndarrays.



.. py:data:: x