pyepr.dataset
=============

.. py:module:: pyepr.dataset


Classes
-------

.. toctree::
   :hidden:

   /autoapi/pyepr/dataset/EPRAccessor

.. autoapisummary::

   pyepr.dataset.EPRAccessor


Functions
---------

.. autoapisummary::

   pyepr.dataset.get_all_axes
   pyepr.dataset.get_all_fixed_param
   pyepr.dataset.create_dataset_from_sequence
   pyepr.dataset.create_dataset_from_axes
   pyepr.dataset.create_dataset_from_bruker
   pyepr.dataset.downconvert_dataset
   pyepr.dataset.find_peak


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

.. py:function:: get_all_axes(sequence)

.. py:function:: get_all_fixed_param(sequence)

.. py:function:: create_dataset_from_sequence(data, sequence, extra_params={})

.. py:function:: create_dataset_from_axes(data, axes, params = {}, extra_coords = None, axes_labels=None)

   
   Create an xarray dataset from a numpy array and a list of axes.


   :Parameters:

       **data** : np.ndarray
           The data to be stored in the dataset.

       **axes** : list
           A list of numpy arrays containing the axes for each dimension of the data.

       **params** : dict, optional
           A dictionary containing any additional parameters to be stored in the dataset, by default None

       **axes_labels** : list, optional
           A list of labels for each axis, by default None














   ..
       !! processed by numpydoc !!

.. py:function:: create_dataset_from_bruker(filepath)

.. py:function:: downconvert_dataset(dataset, filter_type='boxcar', IF=None, reduce=True, sampling_rate=None, **kwargs)

   
   Downconvert a dataset to baseband using a filter    
   Parameters
   ----------
   dataset : xr.DataArray
       The dataset to downconvert
   filter_type : str, optional
       The type of filter to use, by default 'boxcar'. Other options are 'cheby' and a Pulse object
   filter_width : float, optional 
       The width of the filter in MHz or ns depending on filter tyre, by default 20 ns for boxcar and 50 MHz for cheby.
   IF : float, optional
       The intermediate frequency to use, by default 0.15
   reduce : bool, optional
       If True, the dataset is reduced to a single point, by default True
   **kwargs : dict
       Extra arguments to pass to the filter function





   :Returns:

       xr.DataArray
           The downconverted dataset











   ..
       !! processed by numpydoc !!

.. py:function:: find_peak(dataset, freq, freq_axis=None, search_range=4)