.. 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_2D_1_examples_plot_2_TEM.py:
Transmission Electron Microscopy (TEM) dataset
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The following `TEM dataset `_ is
a section of an early larval brain of *Drosophila melanogaster* used in the
analysis of neuronal microcircuitry. The dataset was obtained
from the `TrakEM2 tutorial `_ and
subsequently converted to the CSD model file-format.
Let's import the CSD model data-file and look at its data structure.
.. code-block:: default
import csdmpy as cp
filename = "https://osu.box.com/shared/static/3w5iqkx15fayan1u6g6sn5woc2ublkyh.csdf"
TEM = cp.load(filename)
print(TEM.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",
"description": "TEM image of the early larval brain of Drosophila melanogaster used in the analysis of neuronal microcircuitry.",
"dimensions": [
{
"type": "linear",
"count": 512,
"increment": "4.0 nm",
"quantity_name": "length",
"reciprocal": {
"quantity_name": "wavenumber"
}
},
{
"type": "linear",
"count": 512,
"increment": "4.0 nm",
"quantity_name": "length",
"reciprocal": {
"quantity_name": "wavenumber"
}
}
],
"dependent_variables": [
{
"type": "internal",
"numeric_type": "uint8",
"quantity_type": "scalar",
"components": [
[
"126, 107, ..., 164, 171"
]
]
}
]
}
}
This dataset consists of two linear dimensions and one single-component
dependent variable. The tuple of the dimension and the dependent variable
instances from this example are
.. code-block:: default
x = TEM.dimensions
y = TEM.dependent_variables
and the respective coordinates (viewed only for the first ten coordinates),
.. code-block:: default
print(x[0].coordinates[:10])
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
[ 0. 4. 8. 12. 16. 20. 24. 28. 32. 36.] nm
.. code-block:: default
print(x[1].coordinates[:10])
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
[ 0. 4. 8. 12. 16. 20. 24. 28. 32. 36.] nm
For convenience, let's convert the coordinates from `nm` to `µm` using the
:meth:`~csdmpy.Dimension.to` method of the respective :ref:`dim_api`
instance,
.. code-block:: default
x[0].to("µm")
x[1].to("µm")
and plot the data.
.. code-block:: default
cp.plot(TEM)
.. image:: /auto_examples/2D_1_examples/images/sphx_glr_plot_2_TEM_001.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 1.348 seconds)
.. _sphx_glr_download_auto_examples_2D_1_examples_plot_2_TEM.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_2_TEM.py `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: plot_2_TEM.ipynb `
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery `_