{ "cells": [ { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import statsmodels.api" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import pathlib\n", "import json\n", "import geojson\n", "import datashader\n", "import pandas\n", "import toolz\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "f = pathlib.Path('/Users/baart_f/data/BOX061_transects_rates.json')" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [], "source": [ "data = geojson.load(f.open())" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "feature = data['features'][0]\n", "records = []\n", "for feature in data['features']:\n", " # fold\n", " record = toolz.merge(*toolz.get(['properties', 'geometry'], feature))\n", " records.append(record)\n", "df = pandas.DataFrame(records)" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "RMSE 17.453\n", "b_unc 7.6\n", "change_rate -0.4\n", "change_rate_unc 0.4\n", "coordinates [[115.67817480305608, -34.47973884802565], [11...\n", "country_id AUS\n", "country_name Australia\n", "distances [869.3256292927762, 865.4742744561033, 880.876...\n", "dt [29.002648925, 4.00008213721, 17.0024025134, 2...\n", "flag_ok True\n", "flag_sandy False\n", "intercept 878.5\n", "intersection_10.0015742965 [[115.67302099535196, -34.484506327567665]]\n", "intersection_11.0009103541 [[115.67286891816565, -34.484647000946886]]\n", "intersection_12.0002464116 [[115.67291832013386, -34.48460130350849]]\n", "intersection_13.0023203762 [[115.67314150751872, -34.48439485207438]]\n", "intersection_14.0016564337 [[115.6730535495047, -34.484476214521294]]\n", "intersection_15.0009924913 [[115.67286232397255, -34.484653100656104]]\n", "intersection_16.0003285488 [[115.67297683735318, -34.48454717431647]]\n", "intersection_17.0024025134 [[115.67291036582714, -34.484608661343394]]\n", "intersection_18.0017385709 [[115.67281976310385, -34.484692469968934]]\n", "intersection_19.0010746285 [[115.67290015516656, -34.48461810633333]]\n", "intersection_2.00141002211 NaN\n", "intersection_20.0004106861 [[115.67316239150423, -34.48437553407125]]\n", "intersection_21.0024846506 [[115.67313141390031, -34.48440418882279]]\n", "intersection_22.0018207082 [[115.67300110017784, -34.4845247308765]]\n", "intersection_23.0011567657 [[115.67284495784891, -34.48466916453051]]\n", "intersection_24.0004928233 [[115.67317414059615, -34.484364665981225]]\n", "intersection_25.0025667878 [[115.67284361564742, -34.48467040608298]]\n", "intersection_26.0019028454 [[115.67286570068137, -34.48464997715922]]\n", "intersection_27.0012389029 [[115.67298280586644, -34.48454165336177]]\n", "intersection_28.0005749605 [[115.67294482689645, -34.48457678441132]]\n", "intersection_29.002648925 [[115.67297940068961, -34.48454480319595]]\n", "intersection_3.00074607966 [[115.67274683314729, -34.484759931008256]]\n", "intersection_30.0019849826 [[115.67307941828575, -34.48445228552945]]\n", "intersection_31.0013210401 [[115.672689459175, -34.48481300254685]]\n", "intersection_32.0006570977 [[115.6729366173543, -34.48458437834444]]\n", "intersection_4.00008213721 [[115.67300241777018, -34.48452351208563]]\n", "intersection_5.00215610177 [[115.6728835125379, -34.48463350097267]]\n", "intersection_6.00149215932 [[115.67302772425089, -34.484500103242965]]\n", "intersection_7.00082821687 [[115.67292615651316, -34.48459405475734]]\n", "intersection_8.00016427442 [[115.67289189808466, -34.48462574423757]]\n", "intersection_9.00223823898 [[115.67299916263718, -34.48452652312794]]\n", "outliers [16]\n", "transect_id BOX_061_011_1\n", "transect_origin [115.67817480305608, -34.47973884802565]\n", "type LineString\n", "Name: 1, dtype: object" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "record = df.iloc[1]\n", "_ = plt.plot(record['dt'], record['distances'], 'k.')\n", "_ = plt.plot(np.array(record['dt'])[record['outliers']], np.array(record['distances'])[record['outliers']], 'r.')\n", "record" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
OLS Regression Results
Dep. Variable: y R-squared: 0.030
Model: OLS Adj. R-squared: -0.006
Method: Least Squares F-statistic: 0.8434
Date: Thu, 20 Apr 2017 Prob (F-statistic): 0.367
Time: 09:55:10 Log-Likelihood: -124.08
No. Observations: 29 AIC: 252.2
Df Residuals: 27 BIC: 254.9
Df Model: 1
Covariance Type: nonrobust
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
coef std err t P>|t| [95.0% Conf. Int.]
const 878.4805 7.576 115.956 0.000 862.936 894.025
x1 -0.3661 0.399 -0.918 0.367 -1.184 0.452
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
Omnibus: 1.455 Durbin-Watson: 2.021
Prob(Omnibus): 0.483 Jarque-Bera (JB): 1.247
Skew: -0.340 Prob(JB): 0.536
Kurtosis: 2.245 Cond. No. 43.0
" ], "text/plain": [ "\n", "\"\"\"\n", " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: y R-squared: 0.030\n", "Model: OLS Adj. R-squared: -0.006\n", "Method: Least Squares F-statistic: 0.8434\n", "Date: Thu, 20 Apr 2017 Prob (F-statistic): 0.367\n", "Time: 09:55:10 Log-Likelihood: -124.08\n", "No. Observations: 29 AIC: 252.2\n", "Df Residuals: 27 BIC: 254.9\n", "Df Model: 1 \n", "Covariance Type: nonrobust \n", "==============================================================================\n", " coef std err t P>|t| [95.0% Conf. Int.]\n", "------------------------------------------------------------------------------\n", "const 878.4805 7.576 115.956 0.000 862.936 894.025\n", "x1 -0.3661 0.399 -0.918 0.367 -1.184 0.452\n", "==============================================================================\n", "Omnibus: 1.455 Durbin-Watson: 2.021\n", "Prob(Omnibus): 0.483 Jarque-Bera (JB): 1.247\n", "Skew: -0.340 Prob(JB): 0.536\n", "Kurtosis: 2.245 Cond. No. 43.0\n", "==============================================================================\n", "\n", "Warnings:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", "\"\"\"" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y = np.array(record['distances'])\n", "y[record['outliers']] = None\n", "model = statsmodels.api.OLS(y, statsmodels.api.add_constant(record['dt']), missing='drop')\n", "fit = model.fit()\n", "fit.summary()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.3" } }, "nbformat": 4, "nbformat_minor": 1 }