For Python lesson 08/23/2016
Short link: http://bit.ly/2bQTRBH
For Python lesson 08/23/2016
Short link: http://bit.ly/2bQTRBH
The user and channel is, https://anaconda.org/wd15/sfepy.
Remember to change the version and git_rev.
To build and upload use,
$ conda config --add channels conda-forge
$ conda install -n root conda-build
| time | TotalEnergy | |
|---|---|---|
| 0 | 0 | |
| 1 | 933.5539904727 | |
| 1.1407100423 | 931.7990362438 | |
| 2.9990376221 | 900.9723236116 | |
| 5 | 848.4660711059 | |
| 5.6611454885 | 826.9131473404 | |
| 10 | 674.1116285695 | |
| 16.568796683 | 560.2503712909 | |
| 20 | 532.7331081155 |
This year's SciPy 2017 conference will include a minisymposium on Materials Science, the goal of which is to capture a cross-section of computational materials science activities relating to the SciPy tools and the scientific Python community at a variety of levels.
We welcome presentation proposals from individuals or teams who directly
There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data-driven process-structure-property (PSP) linkages provide a systemic, modular, and hierarchical framework for community-driven curation of materials knowledge, and its transference
| from fipy import * | |
| from scipy.special import erf,ellipk,ellipe | |
| from scipy.integrate import quad | |
| def thornber(E): | |
| e = 1.602e-19 | |
| kb = 1.380e-23 | |
| vs = 2e5 | |
| Eg = 3.3*e | |
| EI = 1e13 |