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1 Start time: 18:52:58 06/21/15 | |
2 | |
3 Revision: 1323 | |
4 | |
5 Model Identifier: MacBookPro10,2 | |
6 System Version: OS X 10.10.3 (14D136) | |
7 Kernel Version: Darwin 14.3.0 | |
8 Time since boot: 6 minutes | |
9 | |
10 FileVault 2 |
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""" | |
Test an installation of PyStan using a simple normal mean estimation problem. | |
The script does a Stan fit to simulated data from a normal distribution, | |
estimating the mean with a normal prior/normal sampling dist'n model. It prints | |
summaries of the posterior to the terminal, and plots two figures showing | |
traceplots (of the posterior mean and the log density) and an estimated | |
posterior PDF (blue curve) along with the analytical PDF (green dashed curve). | |
Three statistical tests are run, with results printed to the terminal. They |
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# This won't run as a standalone Python script; put it in a cell at | |
# the bottom of your BVNDemo IPy notebook and run it there. | |
# Get BVN samples to plot. | |
bvn = BivariateNormal([0,0], [1,1], .7) | |
xyvals = bvn.sample(500) | |
# We'll put 3 different, related axes in a single new figure. | |
fig = figure(figsize=(8,6)) |
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""" | |
Scrape a user's Netflix movie ratings by automating a Safari browsing | |
session (with the user already logged in). The ratings are written | |
as tab-delimited UTF-8 encoded text in a plain text file. | |
This Python script is for terminal-savvy Mac users. | |
To use | |
====== |