.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/miscellaneous/plot_histogram_1D.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_miscellaneous_plot_histogram_1D.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_miscellaneous_plot_histogram_1D.py:


===================
Make a 1D Histogram
===================

``tttrlib`` offers some functions and classes for the creation of histograms.
They are part of ``tttrlib`` to offer more performance in direct comparison to
general purpose routines for analysis methods as Photon Distribution Analysis
(PDA) that make heady use of repeated histogram calculations.

.. note::

    These function and ``classes`` are not intended as a substitution for more
    general functions, e.g., offered by `NumPy <https://www.numpy.org/>`_ and
    are less tested. They offer performance advantages for histograms
    calculated on a logarithmic (log10) scale and a linear scale in direct
    comparison to NumPy.

One dimensional histograms
--------------------------

``tttrlib`` supports one dimensional histograms with linear, logarithmic, or
arbitrary spaced bins.

#.. plot:: ../examples/miscellaneous/histogram_1D.py
   :include-source:

In the example shown above, the histograms for the three bin spacings are shown.


Multi dimensional histograms
----------------------------

In addition to simple one dimensional histograms ``tttrlib`` can calculate
multidimensional histograms with an arbitrary number of dimensions. For that,
first a new object of the class ``doubleHistogram`` is created. Here, *double*
refers to the data type double - a floating point number. Next, axes are added
to the Histogram by calling the method ``setAxis``. The first argument is the
number of the axis, the second the name of the axis, the third and the fourth
the range of the axis, the fifth the number of bins, and the sixth the type of
the axis. The ``Histogram`` class support arbitrary axis types. However, when
initializing an axis via ``setAxis`` the axis type must be either *lin* or
*log10* for a linear or an logarithmic axis with base 10. Next, the data are
assigned to the histogram by the ``setData`` method and the histogram is
calculated by the ``update`` method. A working example for 2D normal
distributed data is shown below.

#.. plot:: ../examples/miscellaneous/histogram_2D.py
   :include-source:

Above, a two dimensional histogram with linear spaced bins is shown.

.. GENERATED FROM PYTHON SOURCE LINES 55-87



.. image-sg:: /auto_examples/miscellaneous/images/sphx_glr_plot_histogram_1D_001.png
   :alt: plot histogram 1D
   :srcset: /auto_examples/miscellaneous/images/sphx_glr_plot_histogram_1D_001.png
   :class: sphx-glr-single-img





.. code-block:: Python

    import tttrlib
    import numpy as np
    import pylab as p

    fig, ax = p.subplots(3, 1)

    # Linear histograms
    data = np.random.normal(10, 2, int(2e6))
    bins = np.linspace(0, 20, 32000, dtype=np.float64)
    hist = np.zeros(len(bins), dtype=np.float64)
    weights = np.ones_like(data)
    tttrlib.histogram1D_double(data, weights, bins, hist, 'lin', True)
    ax[0].plot(bins, hist, 'g')

    # Logarithmic histogram
    bins = np.logspace(0, 3.5, 32000, dtype=np.float64)
    data = np.random.lognormal(3.0, 1, int(2e6))
    hist = np.zeros(len(bins), dtype=np.float64)
    weights = np.ones_like(data)
    tttrlib.histogram1D_double(data, weights, bins, hist, '', True)
    ax[1].semilogx(bins, hist, 'r')

    # Histogram with arbitrary spacing
    bins1 = np.linspace(1, 600, 16000, dtype=np.float64)
    bins2 = np.logspace(np.log10(bins1[-1]+0.1), 3.0, 16000, dtype=np.float64)
    bins = np.hstack([bins1, bins2])
    hist = np.zeros(len(bins), dtype=np.float64)
    weights = np.ones_like(data)
    tttrlib.histogram1D_double(data, weights, bins, hist, '', True)
    ax[2].semilogx(bins, hist, 'y')

    p.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 1.392 seconds)


.. _sphx_glr_download_auto_examples_miscellaneous_plot_histogram_1D.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_histogram_1D.ipynb <plot_histogram_1D.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_histogram_1D.py <plot_histogram_1D.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_