.. only:: html
.. note::
:class: sphx-glr-download-link-note
Click :ref:`here ` to download the full example code
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_auto_examples_1D_1_examples_plot_1_NMR_bloch.py:
Nuclear Magnetic Resonance (NMR) dataset
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The following dataset is a :math:`^{13}\mathrm{C}` time-domain NMR Bloch decay
signal of ethanol.
Let's load this data file and take a quick look at its data
structure. We follow the steps described in the previous example.
.. code-block:: default
import csdmpy as cp
filename = "https://osu.box.com/shared/static/2e4fqm8n8bh4i5wgrinbwcavafa8x7y1.csdf"
NMR_data = cp.load(filename)
print(NMR_data.data_structure)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
{
"csdm": {
"version": "1.0",
"read_only": true,
"timestamp": "2016-03-12T16:41:00Z",
"geographic_coordinate": {
"altitude": "238.9719543457031 m",
"longitude": "-83.05154573892345 °",
"latitude": "39.97968794964322 °"
},
"tags": [
"13C",
"NMR",
"spectrum",
"ethanol"
],
"description": "A time domain NMR 13C Bloch decay signal of ethanol.",
"dimensions": [
{
"type": "linear",
"count": 4096,
"increment": "0.1 ms",
"coordinates_offset": "-0.3 ms",
"quantity_name": "time",
"reciprocal": {
"coordinates_offset": "-3005.363 Hz",
"origin_offset": "75426328.86 Hz",
"quantity_name": "frequency",
"label": "13C frequency shift"
}
}
],
"dependent_variables": [
{
"type": "internal",
"numeric_type": "complex128",
"quantity_type": "scalar",
"components": [
[
"(-8899.40625-1276.7734375j), (-4606.88037109375-742.4124755859375j), ..., (37.548492431640625+20.156890869140625j), (-193.9228515625-67.06524658203125j)"
]
]
}
]
}
}
This particular example illustrates two additional attributes of the CSD model,
namely, the :attr:`~csdmpy.CSDM.geographic_coordinate` and
:attr:`~csdmpy.CSDM.tags`. The `geographic_coordinate` described the
location where the CSDM file was last serialized. You may access this
attribute through,
.. code-block:: default
NMR_data.geographic_coordinate
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
{'altitude': '238.9719543457031 m', 'longitude': '-83.05154573892345 °', 'latitude': '39.97968794964322 °'}
The `tags` attribute is a list of keywords that best describe the dataset.
The `tags` attribute is accessed through,
.. code-block:: default
NMR_data.tags
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
['13C', 'NMR', 'spectrum', 'ethanol']
You may add additional tags, if so desired, using the `append`
method of python's list class, for example,
.. code-block:: default
NMR_data.tags.append("Bloch decay")
NMR_data.tags
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
['13C', 'NMR', 'spectrum', 'ethanol', 'Bloch decay']
The coordinates along the dimension are
.. code-block:: default
x = NMR_data.dimensions
x0 = x[0].coordinates
print(x0)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
[-3.000e-01 -2.000e-01 -1.000e-01 ... 4.090e+02 4.091e+02 4.092e+02] ms
Unlike the previous example, the data structure of an NMR measurement is
a complex-valued dependent variable. The numeric type of the components from
a dependent variable is accessed through the
:attr:`~csdmpy.DependentVariable.numeric_type` attribute.
.. code-block:: default
y = NMR_data.dependent_variables
print(y[0].numeric_type)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
complex128
**Visualizing the dataset**
In the previous example, we illustrated a matplotlib script for plotting 1D data.
Here, we use the csdmpy :meth:`~csdmpy.plot` method, which is a supplementary method
for plotting 1D and 2D datasets only.
.. code-block:: default
cp.plot(NMR_data)
.. image:: /auto_examples/1D_1_examples/images/sphx_glr_plot_1_NMR_bloch_001.png
:class: sphx-glr-single-img
**Reciprocal dimension object**
When closely observing the dimension instance of `NMR_data`,
.. code-block:: default
print(x[0].data_structure)
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
{
"type": "linear",
"count": 4096,
"increment": "0.1 ms",
"coordinates_offset": "-0.3 ms",
"quantity_name": "time",
"reciprocal": {
"coordinates_offset": "-3005.363 Hz",
"origin_offset": "75426328.86 Hz",
"quantity_name": "frequency",
"label": "13C frequency shift"
}
}
notice, there is a reciprocal keyword. The
:attr:`~csdmpy.Dimension.reciprocal` attribute is useful for datasets
that frequently transform to a reciprocal domain, such as the NMR dataset.
The value of the reciprocal attribute is the reciprocal object, which contains metadata
for describing the reciprocal coordinates, such as the `coordinates_offset`,
`origin_offset` of the reciprocal dimension.
You may perform a fourier transform to visualize the NMR spectrum. Use the
:meth:`~csdmpy.CSDM.fft` method on the csdm object ``NMR_data`` as follows
.. code-block:: default
fft_NMR_data = NMR_data.fft()
cp.plot(fft_NMR_data)
.. image:: /auto_examples/1D_1_examples/images/sphx_glr_plot_1_NMR_bloch_002.png
:class: sphx-glr-single-img
To return to time domain signal, use the :meth:`~csdmpy.CSDM.fft` method on the
``fft_NMR_data`` object,
.. code-block:: default
NMR_data_2 = fft_NMR_data.fft()
cp.plot(NMR_data_2)
.. image:: /auto_examples/1D_1_examples/images/sphx_glr_plot_1_NMR_bloch_003.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 1.545 seconds)
.. _sphx_glr_download_auto_examples_1D_1_examples_plot_1_NMR_bloch.py:
.. only :: html
.. container:: sphx-glr-footer
:class: sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: plot_1_NMR_bloch.py `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: plot_1_NMR_bloch.ipynb `
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery `_