* pycroscopy is a `python <http://www.python.org/>`_ package for processing, analyzing, and visualizing multidimensional imaging and spectroscopy data.
* pycroscopy uses the **Universal Spectroscopy and Imaging Data (USID)** `model <https://pycroscopy.github.io/pyUSID/data_format.html>`_ as its foundation, which:
* pycroscopy uses the **Universal Spectroscopy and Imaging Data (USID)** `model <../../USID/index.html>`_ as its foundation, which:
* facilitates the representation of any spectroscopic or imaging data regardless of its origin, modality, size, or dimensionality.
* enables the development of instrument- and modality- agnostic data processing and analysis algorithms.
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@@ -58,7 +58,7 @@ As we see it, there are a few opportunities in scientific imaging (that surely a
How?
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* pycroscopy uses the `Universal Spectroscopy and Imaging Data model <https://pycroscopy.github.io/pyUSID/data_format.html>`_ that facilitates the storage of data, regardless
* pycroscopy uses the `Universal Spectroscopy and Imaging Data model <../../USID/index.html>`_ that facilitates the storage of data, regardless
of dimensionality (conventional 1D spectra and 2D images to 9D hyperspectral datasets and beyond!) or instrument of origin (AFMs, STEMs, Raman spectroscopy etc.).
* This generalized representation of data allows us to write a single and
generalized version of analysis and processing functions that can be applied to any kind of data.
* See `tutorials <https://pycroscopy.github.io/pyUSID/auto_examples/index.html>`_ to get started on using and writing your own pyUSID functions that power pycroscopy
* We already have `many translators <./translators.html>`_ that transform data from popular microscope data formats to pycroscopy compatible HDF5 files.
* pyUSID also has a `tutorial <https://pycroscopy.github.io/pyUSID/auto_examples/beginner/plot_numpy_translator.html>`_ to get you started on importing your other data to pycroscopy.
* Details regarding the definition and guidelines for the Universal Spectroscopy and Imaging Data `(USID) <https://pycroscopy.github.io/pyUSID/data_format.html>`_ model and implementation in HDF5 are also available in pyUSID's documentation.
* Details regarding the definition and guidelines for the Universal Spectroscopy and Imaging Data `(USID) <../../USID/index.html>`_ model and implementation in HDF5 are also available in pyUSID's documentation.
* Please see our document on the `organization of pycroscopy <./package_organization.html>`_ to find out more on what is where and why.
* If you are interested in contributing your code to pycroscopy, please look at our `guidelines <https://pycroscopy.github.io/pyUSID/contribution_guidelines.html>`_
* If you need detailed documentation on all our classes, functions, etc., please visit our `API <./api.html>`_
* Nov 25-30 2018 - poster at MRS Fall meeting at Boston
* Oct 25 2018 @ 6 PM - 8 PM - poster - NS-ThP19 - Room Hall B - at `American Vacuum Society 2018 meeting <http://www.avssymposium.org/Schedule/SessionSchedule.aspx?sessionCode=NS-ThP>`_
* May 16-18 2018 - Poster at `ORNL Software Expo <https://software.ornl.gov/expo/program>`_
* May 18 2018 - **Invited** `talk <https://github.com/pycroscopy/pycroscopy/blob/master/docs/USID_pyUSID_pycroscopy.pdf>`_ at `ImageXD <http://www.imagexd.org/programs/imagexd2018/>`_
* Feb 28 2018 - Webinar on `Jupyter for Supporting a Materials Imaging User Facility (and beyond) <https://www.exascaleproject.org/event/jupyter/>`_. see this `Youtube video <https://www.youtube.com/watch?v=aKah_O5OZdE&t=31m53s>`_
2017
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* Nov 29 2017 @ 8-10 PM - `Poster <https://mrsfall.zerista.com/event/member/432978>`_ at the Materials Research Society Fall 2017 Meeting
* Oct 31 2017 @ 6:30 PM - American Vacuum Society conference; Session: SP-TuP1; `poster 1641 <http://www2.avs.org/symposium2017/Papers/Paper_SP-TuP1.html>`_
* Aug 8 2017 @ 10:45 AM - Microscopy and Microanalysis conference - `poster <https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C6F6D85EF7367C058B66B4B709AD61ED/S1431927617001805a.pdf/pycroscopy_an_open_source_approach_to_microscopy_and_microanalysis_in_the_age_of_big_data_and_open_science.pdf>`_.
* Apr 2017 - Lecture on `atom finding <https://physics.appstate.edu/events/aberration-corrected-stem-teaching-machines-and-atomic-forge>`_
2016
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* Dec 2016 - Poster + `abstract <https://mrsspring.zerista.com/poster/member/85350>`_ at the 2017 Spring Materials Research Society (MRS) conference
* Pycroscopy uses ``Translators`` to extract data and metadata from files (often measurement data stored in instrument-generated proprietary file formats) and write them into `Universal Spectroscopy and Imaging Data (USID) HDF5 files <../../pyUSID/data_format.html>`_.
* Pycroscopy uses ``Translators`` to extract data and metadata from files (often measurement data stored in instrument-generated proprietary file formats) and write them into `Universal Spectroscopy and Imaging Data (USID) HDF5 files <../../USID/index.html>`_.
* You can write your own ``Translator`` easily by following `this example <https://pycroscopy.github.io/pyUSID/auto_examples/beginner/plot_numpy_translator.html>`_ on our sister project's documentation.
* Below is a list of ``Translators`` already available in pycroscopy to translate data.
* These translators can be accessed via ``pycroscopy.io.translators`` or ``pycroscopy.translators``