.. _ch_interactive: ========================================================== Interactive wxmplot displays ========================================================== .. module:: wxmplot.interactive The :ref:`ch_overview` describes the main features of `wxmplot` and shows how `wxmplot` plotting functions give a richer level of customization and interactivity to the end user than is available from the standard `matplotlib.pyplot`. Here, the emphasis is on the immediacy of the interactivity of the data displays especially when used from interactive sessions. An important feature of the :func:`plot`, :func:`imshow` and other functions of the :mod:`interactive` module is that they display their results immediately, without having to execute a `show()` method to render the display. For interactive work from the Python (or one of the Jupyter consoles or notebook) prompt, the displayed windows do not block the Python session. This means that not only can you zoom in, change themes, etc from the Plot window, you can can also easily plot other functions or data, either on the same window or in a new top-level plotting window. While `wxmplot` provides :func:`plot`, :func:`imshow` and other functions that are roughly equivalent to the functions from `matplotlib.pyplot`, the functions are here not exact drop-in replacements for the `pyplot` functions. For one thing, there are many missing plot types and functions. For another, the syntax for specifying options is different. For example, `wxmplot` prefers a long list of keyword arguments to :func:`plot` over a series of separate function calls. The functions in the :mod:`interactive` are described in detail below. Plotting in an interactive session =========================================================== As an example using :mod:`wxmplot.interactive` in a Jupyter-qtconsole session might look like this:: Jupyter QtConsole 4.5.4 Python 3.7.4 (default, Aug 13 2019, 20:35:49) Type 'copyright', 'credits' or 'license' for more information IPython 7.7.0 -- An enhanced Interactive Python. Type '?' for help. In [1]: import numpy as np In [2]: import wxmplot.interactive as wi In [3]: x = np.linspace(0, 20, 101) In [4]: wi.plot(x, np.sin(x), xlabel='t (sec)') Out[4]: In [5]: At this point a plot like this will be displayed: .. image:: images/interactive1.png :width: 50 % As with using `%matplotlib notebook` in a Jupyter notebook, the `wxmplot` display can be zoomed in and out, but as shown in :ref:`ch_overview`, it can also be configured and updated in many more ways. For example, from the Plot Configuration window we could change the theme to 'Seaborn' and set the label for this trace to be 'sine'. Then from the Jupyter console we can continue:: In [5]: wi.plot(x, np.cos(1.5*x), label='cosine', show_legend=True) Out[5]: In [6]: which will now show: .. image:: images/interactive2.png :width: 50 % which is again a fully interactive and configurable display. For example, with the legend displayed, clicking on any of the labels in the legend will toggle the display of that curve. If we want to clear the data and plot something new, we might do something like:: In [6]: wi.plot(x, x*np.log(x+1), label='xlogx', new=True) Out[6]: In [7]: We can also place a text string, arrow, horizontal, or vertical line on the plot, as with:: In [7]: wi.plot_text('hello!', 9.1, 0.87) In [8]: and so forth. If we wanted to bring up a second Line Plot window, we can use the **win=2** option:: In [8]: wi.plot(x, np.sin(x)*np.exp(-x/8) , win=2, theme='ggplot') Out[8]: In [9]: and then control which of the displays any additional plot functions use by passing the `win` option to the plotting functions. The immediacy of the rendering and the ability to customize the plots makes these plotting functions well-suited for exploratory displays of data. Using the :mod:`interactive` functions from a script =========================================================== When using the :mod:`interactive` functions by running a script in a non-interactive way, the display will still appear. It does not block further execution of the script and the display does not disappear when the script is complete. Instead, the plots and images will remain displayed and fully operational until all windows have been closed or until the running script is explicitly closed with Crtl-C. That means that you can add `wi.plot()` and `wi.imshow()` to your short- or long-running scripts and the plots will be displayed until you no longer want to use them. Line Plotting with :func:`plot` and related functions ========================================================================== .. autofunction:: plot More details of Plot Options are given in :ref:`Table of Plot Arguments `. .. autofunction:: hist .. autofunction:: update_trace .. autofunction:: set_data_generator .. autofunction:: plot_setlimits .. autofunction:: plot_text .. autofunction:: plot_arrow .. autofunction:: plot_marker .. autofunction:: plot_axhline .. autofunction:: plot_axvline Displaying images with :func:`imshow` and :func:`contour` ============================================================== .. autofunction:: imshow .. autofunction:: contour Functions for working with the interactive windows ====================================================== .. autofunction:: set_theme .. autofunction:: available_themes .. autofunction:: get_wxapp .. autofunction:: get_plot_window The returned :class:`wx.PlotFrame` will have the heirarchy of attributes described in the table below. This allows access to the underlying matplotlib Axes and Canvas objects. .. _plotframe_objects_table: **Table of PlotFrame attributes** +-----------------+-----------------------------------------------------+ | name | object type | +=================+=====================================================+ | .panel | wxmplot.PlotPanel, a wx.Panel | +-----------------+-----------------------------------------------------+ | .panel.conf | wxmplot.PlotConfig | +-----------------+-----------------------------------------------------+ | .panel.axes | matplotlib.axes.AxesSubPlot | +-----------------+-----------------------------------------------------+ | .panel.fig | matplotlib.figure.Figure | +-----------------+-----------------------------------------------------+ | .panel.canvas | matplotlib.backends.backend_wxagg.FigureCanvasWxAgg | +-----------------+-----------------------------------------------------+ .. autofunction:: get_image_window As with :class:`wx.PlotFrame`, the returned :class:`wx.ImageFrame` will have the same principle attributes to access the matplotlib Axes and Canvas objects.