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Commit a9bc9ecd authored by Easy Build's avatar Easy Build
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Thu, 04 Jan 2018 13:15:04 +0100

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...@@ -1188,9 +1188,11 @@ phono3py/1.11.13.35-intel-2017a-Python-2.7.13,2 ...@@ -1188,9 +1188,11 @@ phono3py/1.11.13.35-intel-2017a-Python-2.7.13,2
phonopy/1.11.6.7-intel-2015b-Python-2.7.9,2 phonopy/1.11.6.7-intel-2015b-Python-2.7.9,2
phonopy/1.11.12.5-intel-2015b-Python-2.7.9,2 phonopy/1.11.12.5-intel-2015b-Python-2.7.9,2
phonopy/1.11.12.5-Python-2.7.13-base,2 phonopy/1.11.12.5-Python-2.7.13-base,2
cycler/0.10.0-Py-3.6,2
numpy/1.13.3-Py-3.6,2 numpy/1.13.3-Py-3.6,2
pyparsing/2.2.0-Py-3.6,2 pyparsing/2.2.0-Py-3.6,2
python-dateutil/2.6.1-Py-3.6,2 python-dateutil/2.6.1-Py-3.6,2
pytz/2017.3-Py-3.6,2
scipy/1.0.0Py-3.6,2 scipy/1.0.0Py-3.6,2
six/1.11.0-Py-2.7,2 six/1.11.0-Py-2.7,2
six/1.11.0-Py-3.6,2 six/1.11.0-Py-3.6,2
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...@@ -354,9 +354,11 @@ ...@@ -354,9 +354,11 @@
| Module | Description | | Module | Description |
| ------ | ----------- | | ------ | ----------- |
| [cycler](https://matplotlib.org/cycler) | Composable style cycles. |
| [numpy](http://www.numpy.org) | NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. | | [numpy](http://www.numpy.org) | NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. |
| [pyparsing](http://pyparsing.wikispaces.com) | The pyparsing module provides a library of classes that client code uses to construct the grammar directly in Python code. | | [pyparsing](http://pyparsing.wikispaces.com) | The pyparsing module provides a library of classes that client code uses to construct the grammar directly in Python code. |
| [python-dateutil](https://github.com/dateutil/dateutil) | Useful extensions to the standard Python datetime features | | [python-dateutil](https://github.com/dateutil/dateutil) | Useful extensions to the standard Python datetime features |
| [pytz](http://pytz.sourceforge.net/) | pytz brings the Olson tz database into Python. This library allows accurate and cross platform timezone calculations using Python 2.4 or higher. |
| [scipy](https://github.com/jupyter/testpath) | Test utilities for code working with files and commands | | [scipy](https://github.com/jupyter/testpath) | Test utilities for code working with files and commands |
| [six](https://github.com/benjaminp/six) | Python 2 and 3 compatibility library. | | [six](https://github.com/benjaminp/six) | Python 2 and 3 compatibility library. |
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