Mercurial > hg > plosone_underreview
comparison notebooks/sensitivity_experiment.ipynb @ 60:402f43d5b7ad branch-tests
sensitivity notebook added correlation
author | mpanteli <m.x.panteli@gmail.com> |
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date | Thu, 21 Sep 2017 15:25:07 +0100 |
parents | 444041185ba9 |
children | b0e194bfb71d |
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59:444041185ba9 | 60:402f43d5b7ad |
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1 { | 1 { |
2 "cells": [ | 2 "cells": [ |
3 { | 3 { |
4 "cell_type": "code", | 4 "cell_type": "code", |
5 "execution_count": 20, | 5 "execution_count": 1, |
6 "metadata": {}, | 6 "metadata": {}, |
7 "outputs": [ | 7 "outputs": [ |
8 { | 8 { |
9 "name": "stdout", | 9 "name": "stderr", |
10 "output_type": "stream", | 10 "output_type": "stream", |
11 "text": [ | 11 "text": [ |
12 "The autoreload extension is already loaded. To reload it, use:\n", | 12 "/homes/mp305/anaconda/lib/python2.7/site-packages/librosa/core/audio.py:33: UserWarning: Could not import scikits.samplerate. Falling back to scipy.signal\n", |
13 " %reload_ext autoreload\n" | 13 " warnings.warn('Could not import scikits.samplerate. '\n" |
14 ] | 14 ] |
15 } | 15 } |
16 ], | 16 ], |
17 "source": [ | 17 "source": [ |
18 "import numpy as np\n", | 18 "import numpy as np\n", |
4937 ] | 4937 ] |
4938 }, | 4938 }, |
4939 { | 4939 { |
4940 "cell_type": "code", | 4940 "cell_type": "code", |
4941 "execution_count": 45, | 4941 "execution_count": 45, |
4942 "metadata": {}, | 4942 "metadata": { |
4943 "collapsed": true | |
4944 }, | |
4943 "outputs": [], | 4945 "outputs": [], |
4944 "source": [ | 4946 "source": [ |
4945 "ranked_countries = pd.DataFrame()\n", | 4947 "ranked_countries = pd.DataFrame()\n", |
4946 "ranked_outliers = pd.DataFrame()\n", | 4948 "ranked_outliers = pd.DataFrame()\n", |
4947 "for n in range(n_iters):\n", | 4949 "for n in range(n_iters):\n", |
5118 ] | 5120 ] |
5119 }, | 5121 }, |
5120 { | 5122 { |
5121 "cell_type": "code", | 5123 "cell_type": "code", |
5122 "execution_count": 56, | 5124 "execution_count": 56, |
5123 "metadata": {}, | 5125 "metadata": { |
5126 "collapsed": true | |
5127 }, | |
5124 "outputs": [], | 5128 "outputs": [], |
5125 "source": [ | 5129 "source": [ |
5126 "from scipy.stats import spearmanr\n", | 5130 "from scipy.stats import spearmanr\n", |
5127 "r, p = spearmanr(ranked_countries)" | 5131 "r, p = spearmanr(ranked_countries)" |
5128 ] | 5132 ] |