Visualizing data
============================

1D and 2D data
********************

After loading data into an :doc:`EprData <EprData>` object. Plots can be made using ``plot`` method, as shown below. 

.. code-block:: python

  # import EPRpy
  import eprpy as epr
  
  # Load data by providing path to .DSC or .DTA file
  epr_data = epr.load('tempo.DSC')

  # plot the data
  epr_data.plot()

For complex data, imaginary part can be be visualized by setting ``plot_imag`` to True.

.. code-block:: python
  
  # import EPRpy and load data
  import eprpy as epr
  epr_t1 = epr.load('tempo_t1.DSC')

  # plot the imaginary part as well
  epr_data.plot(plot_imag=True)

.. image:: images/plt_with_imag.png
   :width: 400px

See more `plotting examples <notebooks/examples.html#Plotting>`_ for 1D data.


2D data can be visualized similarly and has a selection of plot types as shown below. 
Addtionally, for 2D plots, specific slices can be selected by using the ``slices`` keyword and providing a ``range`` object as shown below.


.. code-block:: python
  
  # import EPRpy and load data
  import eprpy as epr
  epr_2d = epr.load('tempo_time.DSC')

  # default is a stacked plot
  # use `spacing` to control vertical spacing between each slice
  # use `slices` to control data slices which should be plot
  epr_data.plot(spacing=5,slices=range(35,48)) # spacing of 5, and slices 35 to 47.


Other plot types can be selected using the ``plot_type`` keyword as shown below.


.. code-block:: python

  # superimposed plot
  epr_data.plot(plot_type='superimposed')

  # pseudo color plot
  epr_data.plot(plot_type='pcolor')

  # surface
  epr_data.plot(plot_type='surf')

See `plotting examples <notebooks/examples.html#id2>`_ for 2D data.

Multiple datasets
***********************

Any number of datasets can be compared on the same plot by using the ``eprplot`` function and provding the datasets as a list as shown below.

.. code-block:: python

  # import EPRpy and load the datasets
  import eprpy as epr
  
  # Load data by providing path to .DSC or .DTA file of each dataset
  data1 = epr.load('tempo10mM.DSC')
  data2 = epr.load('tempo1mM.DSC')

  # use the eprplot function and input the datasets as a list
  fig,ax = epr.eprplot([data1,data2])

.. image:: images/plt_compare.png
   :width: 400px

Interactive Plots
***********************

A **data cursor** for inspecting data on plots can be obtained by setting `interactive` to True while plotting as shown below.
Move the cursor around to display the x-y value pairs in red. 
Left click and hold, and then drag while holding the right click mouse button to measure horizontal distance, shown in blue.
For touchpads use : `Ctrl + Left Click + Drag`

.. code-block:: python

  # import EPRpy
  import eprpy as epr
  
  # Load data by providing path to .DSC or .DTA file
  epr_data = epr.load('tempo.DSC')

  # plot the data
  epr_data.plot(interactive=True)

.. image:: images/interactive_plot.gif

A **slider** for slicing through 2D data can be obtained as shown below for a TEMPO EPR spectrum as a function of time. 
The slider plot shows the value for the corresponding slice below the plot and a 'Swap axes' button to change the axis along which data slices are diplayed. 

.. code-block:: python

  # import EPRpy
  import eprpy as epr
  
  # Load data by providing path to .DSC or .DTA file
  epr_data = epr.load('tempo_time.DSC')

  # plot the data
  epr_data.plot(plot_type='slider',slices=range(35,48))

.. image:: images/interactive_plot2.gif