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        Click :ref:`here <sphx_glr_download_auto_examples_calculate_ODNP.py>`
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.. _sphx_glr_auto_examples_calculate_ODNP.py:


calculate ODNP using DNPLab
===========================

This example demonstrates how to use the dnplab.dnpHydration module

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First import dnplab and numpy,

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.. code-block:: default

    import dnplab
    import numpy as np


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To use the dnpHydration module first create a dictionary with the necessary inputs. Start by creating a workspace and assinging an inputs dictionary to the key **'hydration_inputs'**. For example,

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.. code-block:: default


    Enhancements = [] # list of signal enhancements
    Enhancement_powers = [] # list of powers in Watts corresponding to Enhancements
    T1s = [] # list of T1 values in seconds
    T1_powers = [] # list of powers in Watts corresponding to T1s

    inputs = {
              'E_array' : np.array(Enhancements),
              'E_powers' : np.array(Enhancement_powers),
              'T1_array' : np.array(T1s),
              'T1_powers' : np.array(T1_powers),
              'T10': 2.0, # T1 measured with power=0
              'T100': 2.5, # T1 measured with SL=0 and power=0
              'spin_C': 100, # spin concentration in micromolar
              'field': 350, # magnetic field in mT
              'smax_model': 'tethered', # choice of smax model
              'interpolate_method': 'second_order' # choice of interpolation method
              }

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Now you can either create a workspace and add the dictionary under the key **'hydration_inputs'**,

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.. code-block:: default

    workspace = dnplab.create_workspace('hydration_inputs', inputs)

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Or add to an existing workspace,

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.. code-block:: default

    workspace.add('hydration_inputs', inputs)

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In rare cases the bulk water or second order T1 interpolation constants may need to be altered. This is not necessary for the odnp module to operate, but if needed this can be done by adding the dictionary **'hydration_constants'** to the workspace. For example,

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.. code-block:: default

    constants = {
                 'ksigma_bulk': 95.4, # bulk ksigma value
                 'krho_bulk': 353.4, # bulk krho value
                 'klow_bulk': 366, # bulk klow value
                 'tcorr_bulk': 54, # bulk tcorr value
                 'D_H2O': 2.3e-9, # bulk water diffusivity
                 'D_SL': 4.1e-10, # diffusivity of spin probe in bulk water
                 'delta_T1_water': 1, # change in water proton T1 due to microwaves
                 'T1_water': 2.5, # T1 of bulk water protons
                 'macro_C': 100, # concentration of macromolecule in uM
                 }

    workspace.add('hydration_constants', constants)

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Next, pass the workspace to dnplab.dnpHydration.hydration to perform calculations using,

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.. code-block:: default

    hydration_results = dnplab.dnpHydration.hydration(workspace)

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or operate in-place with:

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.. code-block:: default

    dnplab.dnpHydration.hydration(workspace)

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For use without creating a DNPLab workspace simply skip the above steps and pass the dictionaries to dnpHydration directly,

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.. code-block:: default

    hydration_results = dnplab.dnpHydration.odnp(inputs=inputs, constants=constants)


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   **Total running time of the script:** ( 0 minutes  0.000 seconds)


.. _sphx_glr_download_auto_examples_calculate_ODNP.py:


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