How to use keyNames method in fMBT
Best Python code snippet using fMBT_python
paper_ploter.py
Source:paper_ploter.py 
1# Jing-Kai Lou (kaeaura@gamil.com)2import os3import sys4sys.path.append('analyzer')5import matplotlib.pylab as plt6from db import LiteDB7def load_data(path, file_dict):8 all_dbs = os.listdir(path)9 assert(set(all_filenames.values()).issubset(set(all_dbs)))10 db = LiteDB()11 all_keynames = {}12 read_keynames = set()13 for read_tracename, read_filename in all_filenames.iteritems():14 db.load(os.path.join(path, read_filename))15 read_keyname = set(db.keys()).difference(read_keynames).pop()16 all_keynames.__setitem__(read_tracename, read_keyname)17 read_keynames.add(read_keyname)18 return(db, all_keynames)19def plot_frac(db, keynames, save_path):20 inFrac_name = 'inFrac_dict'21 outFrac_name = 'outFrac_dict'22 plt.clf()23 plt.figure(figsize = (8, 5))24 x_upperbound = .225 plt.subplot(2, 2, 1)26 plt.plot(map(lambda x: x / 1000.0, db[keynames['mog']][inFrac_name].keys()), db[keynames['mog']][inFrac_name].values(), 'b-', lw = 5, label = 'fairyland')27 plt.plot(map(lambda x: x / 1000.0, db[keynames['mblg']][inFrac_name].keys()), db[keynames['mblg']][inFrac_name].values(), 'r:', lw = 5, label = 'twitter')28 plt.plot(map(lambda x: x / 1000.0, db[keynames['im']][inFrac_name].keys()), db[keynames['im']][inFrac_name].values(), 'k--', lw = 5, label = 'yahoo')29 plt.xlim(xmax = x_upperbound)30 plt.ylabel('wcc fraction (id)')31 plt.title('interaction')32 plt.grid(True)33 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best', prop = {'size':10})34 plt.subplot(2, 2, 2)35 plt.plot(map(lambda x: x / 1000.0, db[keynames['mogF']][inFrac_name].keys()), db[keynames['mogF']][inFrac_name].values(), 'b-', lw = 5, label = 'fairyland')36 plt.plot(map(lambda x: x / 1000.0, db[keynames['mblgF']][inFrac_name].keys()), db[keynames['mblgF']][inFrac_name].values(), 'r:', lw = 5, label = 'twitter')37 plt.plot(map(lambda x: x / 1000.0, db[keynames['imF']][inFrac_name].keys()), db[keynames['imF']][inFrac_name].values(), 'k--', lw = 5, label = 'yahoo')38 plt.xlim(xmax = x_upperbound)39 plt.title('ally')40 plt.grid(True)41 #plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best')42 plt.subplot(2, 2, 3)43 plt.plot(map(lambda x: x / 1000.0, db[keynames['mog']][outFrac_name].keys()), db[keynames['mog']][outFrac_name].values(), 'b-', lw = 5, label = 'fairyland')44 plt.plot(map(lambda x: x / 1000.0, db[keynames['mblg']][outFrac_name].keys()), db[keynames['mblg']][outFrac_name].values(), 'r:', lw = 5, label = 'twitter')45 plt.plot(map(lambda x: x / 1000.0, db[keynames['im']][outFrac_name].keys()), db[keynames['im']][outFrac_name].values(), 'k--', lw = 5, label = 'yahoo')46 plt.xlim(xmax = x_upperbound)47 plt.xlabel('removed fraction by od (%)')48 plt.ylabel('wc fraction (od)')49 plt.grid(True)50 plt.subplot(2, 2, 4)51 plt.plot(map(lambda x: x / 1000.0, db[keynames['mogF']][outFrac_name].keys()), db[keynames['mogF']][outFrac_name].values(), 'b-', lw = 5, label = 'fairyland')52 plt.plot(map(lambda x: x / 1000.0, db[keynames['mblgF']][outFrac_name].keys()), db[keynames['mblgF']][outFrac_name].values(), 'r:', lw = 5, label = 'twitter')53 plt.plot(map(lambda x: x / 1000.0, db[keynames['imF']][outFrac_name].keys()), db[keynames['imF']][outFrac_name].values(), 'k--', lw = 5, label = 'yahoo')54 plt.xlim(xmax = x_upperbound)55 plt.xlabel('removed fraction (%)')56 plt.grid(True)57 plt.savefig(os.path.join(save_dir, save_path))58def plot_degreeRate(db, keynames, save_path):59 degRate_x_name = 'degRateDistr_x'60 degRate_y_name = 'degRateDistr_y'61 plt.clf()62 plt.figure(figsize = (8, 5))63 plt.subplot(1, 2, 1)64 plt.plot(db[keynames['mog']][degRate_x_name], db[keynames['mog']][degRate_y_name], 'b-', lw=5, label = 'fairyland')65 plt.plot(db[keynames['mblg']][degRate_x_name], db[keynames['mblg']][degRate_y_name], 'r:', lw=5, label = 'twitter')66 plt.plot(db[keynames['im']][degRate_x_name], db[keynames['im']][degRate_y_name], 'k--', lw=5, label = 'yahoo')67 plt.xscale('log')68 plt.grid(True)69 plt.title('interaction')70 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 4, prop = {'size': 10})71 plt.xlabel('In-degree to Out-degree Ratio')72 plt.ylabel('CDF')73 plt.subplot(1, 2, 2)74 plt.plot(db[keynames['mogF']][degRate_x_name], db[keynames['mogF']][degRate_y_name], 'b-', lw=5, label = 'fairyland')75 plt.plot(db[keynames['mblgF']][degRate_x_name], db[keynames['mblgF']][degRate_y_name], 'r:', lw=5, label = 'twitter')76 #plt.plot(db[keynames['imF']][degRate_x_name], db[keynames['imF']][degRate_y_name], 'k--', lw=5, label = 'yahoo')77 plt.xscale('log')78 plt.grid(True)79 plt.title('ally')80 plt.xlabel('In-degree to Out-degree Ratio')81 plt.ylabel('CDF')82 plt.savefig(os.path.join(save_dir, save_path))83def plot_degreeOverlap(db, keynames, save_path, attr_name = 'degOverlapRatio'):84 plt.clf()85 plt.figure(figsize = (8, 5))86 x = sorted(db[keynames['mog']][attr_name].keys())87 y = [db[keynames['mog']][attr_name][xx] for xx in x]88 plt.plot(x, y, 'b-', lw = 5, label = 'fairyland interaction')89 x = sorted(db[keynames['mblg']][attr_name].keys())90 y = [db[keynames['mblg']][attr_name][xx] for xx in x]91 plt.plot(x, y, 'r:', lw = 5, label = 'twitter interaction')92 x = sorted(db[keynames['im']][attr_name].keys())93 y = [db[keynames['im']][attr_name][xx] for xx in x]94 plt.plot(x, y, 'k--', lw = 5, label = 'yahoo interaction')95 x = sorted(db[keynames['mogF']][attr_name].keys())96 y = [db[keynames['mogF']][attr_name][xx] for xx in x]97 plt.plot(x, y, 'b.', label = 'fairyland ally')98 x = sorted(db[keynames['mblgF']][attr_name].keys())99 y = [db[keynames['mblgF']][attr_name][xx] for xx in x]100 plt.plot(x, y, 'k*', label = 'twitter ally')101 plt.grid(True)102 plt.title('Overlap')103 plt.xlabel('Fraction of Users ordered by degree (%)')104 plt.ylabel('Overlap (%)')105 plt.legend(('fairyland interaction', 'twitter interaction', 'yahoo interaction', 'fairyland ally', 'twitter ally'), loc = 'best')106 plt.savefig(os.path.join(save_dir, save_path))107def plot_degreeDistr(db, keynames, save_path):108 indeg_x_name = 'inDegDistr_x'109 indeg_y_name = 'inDegDistr_y'110 outdeg_x_name = 'outDegDistr_x'111 outdeg_y_name = 'outDegDistr_y'112 deg_x_name = 'degDistr_x'113 deg_y_name = 'degDistr_y'114 x_upperbound = 10 ** 5115 y_lowerbound = 10 ** -6116 plt.clf()117 plt.figure(figsize = (8, 5))118 plt.subplot(2, 3, 1)119 plt.loglog(db[keynames['mog']][indeg_x_name], db[keynames['mog']][indeg_y_name], 'b-', linewidth=5, label='id')120 plt.loglog(db[keynames['mog']][outdeg_x_name], db[keynames['mog']][outdeg_y_name], 'r--', linewidth=5, label='od')121 #plt.loglog(db[keynames['mogF']][indeg_x_name], db[keynames['mogF']][indeg_y_name], 'r--', linewidth=5, label='ally')122 plt.ylabel('interaction CCDF')123 plt.grid(True)124 plt.xlim(xmax = x_upperbound)125 plt.ylim(ymin = y_lowerbound)126 plt.title('Fairyland Online')127 plt.legend(('id', 'od'), loc = 3, prop = {'size': 7})128 plt.subplot(2, 3, 2)129 plt.loglog(db[keynames['mblg']][indeg_x_name], db[keynames['mblg']][indeg_y_name], 'b-', linewidth=5, label='id')130 plt.loglog(db[keynames['mblg']][outdeg_x_name], db[keynames['mblg']][outdeg_y_name], 'r--', linewidth=5, label='od')131 #plt.loglog(db[keynames['mblgF']][indeg_x_name], db[keynames['mblgF']][indeg_y_name], 'r--', linewidth=5, label='ally')132 plt.grid(True)133 plt.xlim(xmax = x_upperbound)134 plt.ylim(ymin = y_lowerbound)135 plt.title('Twitter')136 plt.subplot(2, 3, 3)137 plt.loglog(db[keynames['im']][indeg_x_name], db[keynames['im']][indeg_y_name], 'b-', linewidth=5, label='id')138 plt.loglog(db[keynames['im']][outdeg_x_name], db[keynames['im']][outdeg_y_name], 'r--', linewidth=5, label='od')139 #plt.loglog(db[keynames['imF']][indeg_x_name], db[keynames['imF']][indeg_y_name], 'r--', linewidth=5, label='ally')140 plt.xlabel('k')141 plt.grid(True)142 plt.xlim(xmax = x_upperbound)143 plt.ylim(ymin = y_lowerbound)144 plt.title('Yahoo! Messenger')145 plt.subplot(2, 3, 4)146 plt.loglog(db[keynames['mogF']][indeg_x_name], db[keynames['mogF']][indeg_y_name], 'b-', linewidth=5, label='id')147 plt.loglog(db[keynames['mogF']][outdeg_x_name], db[keynames['mogF']][outdeg_y_name], 'r--', linewidth=5, label='od')148 #plt.loglog(db[keynames['mogF']][outdeg_x_name], db[keynames['mogF']][outdeg_y_name], 'r--', linewidth=5, label='ally')149 plt.xlabel('k')150 plt.ylabel('ally CCDF')151 plt.grid(True)152 plt.xlim(xmax = x_upperbound)153 plt.ylim(ymin = y_lowerbound)154 plt.subplot(2, 3, 5)155 plt.loglog(db[keynames['mblgF']][indeg_x_name], db[keynames['mblgF']][indeg_y_name], 'b-', linewidth=5, label='id')156 plt.loglog(db[keynames['mblgF']][outdeg_x_name], db[keynames['mblgF']][outdeg_y_name], 'r--', linewidth=5, label='od')157 #plt.loglog(db[keynames['mblgF']][outdeg_x_name], db[keynames['mblgF']][outdeg_y_name], 'r--', linewidth=5, label='ally')158 plt.xlabel('k')159 plt.grid(True)160 plt.xlim(xmax = x_upperbound)161 plt.ylim(ymin = y_lowerbound)162 plt.subplot(2, 3, 6)163 plt.loglog(db[keynames['imF']][deg_x_name], db[keynames['imF']][deg_y_name], 'k-', linewidth=5, label='d')164 #plt.loglog(db[keynames['imF']][indeg_x_name], db[keynames['imF']][indeg_y_name], 'b-', linewidth=5, label='id')165 #plt.loglog(db[keynames['imF']][outdeg_x_name], db[keynames['imF']][outdeg_y_name], 'r--', linewidth=5, label='od')166 #plt.loglog(db[keynames['imF']][outdeg_x_name], db[keynames['imF']][outdeg_y_name], 'r--', linewidth=5, label='ally')167 plt.xlabel('k')168 plt.grid(True)169 plt.xlim(xmax = x_upperbound)170 plt.ylim(ymin = y_lowerbound)171 plt.legend(('d'), loc = 'best', prop = {'size':7})172 plt.savefig(os.path.join(save_dir, save_path))173def plot_reusage(db, keynames, save_path, attr_name = [ 'linkWeightDistr_x', 'linkWeightDistr_y' ]):174 plt.clf()175 plt.figure(figsize = (8, 5))176 plt.loglog(db[keynames['mog']][attr_name[0]], db[keynames['mog']][attr_name[1]], 'b-', lw = 5, label = 'fariyland')177 plt.loglog(db[keynames['mblg']][attr_name[0]], db[keynames['mblg']][attr_name[1]], 'r:', lw = 5, label = 'twitter')178 plt.loglog(db[keynames['im']][attr_name[0]], db[keynames['im']][attr_name[1]], 'k--', lw = 5, label = 'yahoo')179 plt.xlabel('Usage (days)')180 plt.ylabel('CCDF')181 plt.title('Usage of Links')182 plt.grid(True)183 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best')184 plt.savefig(os.path.join(save_dir, save_path))185# knn via degree bin ####186def plot_KnnDistr(db, keynames, save_path):187 knnMean_x_name = 'knnDistr_avg_x'188 knnMean_y_name = 'knnDistr_avg_y'189 knnMedian_x_name = 'knnDistr_median_x'190 knnMedian_y_name = 'knnDistr_median_y'191 inKnnMean_x_name = 'inKnnDistr_avg_x'192 inKnnMean_y_name = 'inKnnDistr_avg_y'193 inKnnMedian_x_name = 'inKnnDistr_median_x'194 inKnnMedian_y_name = 'inKnnDistr_median_y'195 outKnnMean_x_name = 'outKnnDistr_avg_x'196 outKnnMean_y_name = 'outKnnDistr_avg_y'197 outKnnMedian_x_name = 'outKnnDistr_median_x'198 outKnnMedian_y_name = 'outKnnDistr_median_y'199 x_upperbound = 10 ** 5200 x_lowerbound = 10 ** 0201 y_upperbound = 10 ** 4202 y_lowerbound = 10 ** -1203 plt.clf()204 plt.figure(figsize = (8, 8))205 plt.subplot(2, 2, 1)206 plt.loglog(db[keynames['mog']][inKnnMean_x_name], db[keynames['mog']][inKnnMean_y_name], 'b.', mec='b', ms=5, label='fairyland')207 plt.loglog(db[keynames['mblg']][inKnnMean_x_name], db[keynames['mblg']][inKnnMean_y_name], 'r+', mec='r', mfc='None', ms=5, label='twitter')208 plt.loglog(db[keynames['im']][inKnnMean_x_name], db[keynames['im']][inKnnMean_y_name], 'k>', mec='k', mfc='None', ms=5, label='yahoo')209 plt.xlim((x_lowerbound, x_upperbound))210 plt.ylim((y_lowerbound, y_upperbound))211 plt.title('interaction')212 plt.ylabel('$<k_{nn}>^{in}$')213 plt.grid(True)214 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best', prop = {'size': 10})215 plt.subplot(2, 2, 2)216 plt.loglog(db[keynames['mogF']][inKnnMean_x_name], db[keynames['mogF']][inKnnMean_y_name], 'b.', mec='b', ms=5, label='fairyland')217 plt.loglog(db[keynames['mblgF']][inKnnMean_x_name], db[keynames['mblgF']][inKnnMean_y_name], 'r+', mec='r', mfc='None', ms=5, label='twitter')218 plt.loglog(db[keynames['imF']][knnMean_x_name], db[keynames['imF']][knnMean_y_name], 'k>', mec='k', mfc='None', ms=5, label='yahoo')219 plt.xlim((x_lowerbound, x_upperbound))220 plt.ylim((y_lowerbound, y_upperbound))221 plt.title('ally')222 plt.grid(True)223 plt.subplot(2, 2, 3)224 plt.loglog(db[keynames['mog']][outKnnMean_x_name], db[keynames['mog']][outKnnMean_y_name], 'b.', mec='b', ms=5, label='fairyland')225 plt.loglog(db[keynames['mblg']][outKnnMean_x_name], db[keynames['mblg']][outKnnMean_y_name], 'r+', mec='r', mfc='None', ms=5, label='twitter')226 plt.loglog(db[keynames['im']][outKnnMean_x_name], db[keynames['im']][outKnnMean_y_name], 'k>', mec='k', mfc='None', ms=5, label='yahoo')227 plt.xlim((x_lowerbound, x_upperbound))228 plt.ylim((y_lowerbound, y_upperbound))229 plt.title('interaction')230 plt.xlabel('$k$')231 plt.ylabel('$<k_{nn}>^{out}$')232 plt.grid(True)233 plt.subplot(2, 2, 4)234 plt.loglog(db[keynames['mogF']][outKnnMean_x_name], db[keynames['mogF']][outKnnMean_y_name], 'b.', mec='b', ms=5, label='fairyland')235 #plt.loglog(db[keynames['mogF']][outKnnMedian_x_name], db[keynames['mogF']][outKnnMedian_y_name], 'g--', label='fairyland-median')236 plt.loglog(db[keynames['mblgF']][outKnnMean_x_name], db[keynames['mblgF']][outKnnMean_y_name], 'r+', mec='r', mfc='None', ms=5, label='twitter')237 #plt.loglog(db[keynames['mblgF']][outKnnMedian_x_name], db[keynames['mblgF']][outKnnMedian_y_name], 'y--', label='twitter-median')238 plt.loglog(db[keynames['imF']][knnMean_x_name], db[keynames['imF']][knnMean_y_name], 'k>', mec='k', mfc='None', ms=5, label='yahoo')239 #plt.loglog(db[keynames['imF']][knnMedian_x_name], db[keynames['imF']][knnMedian_y_name], 'c--', ms=5, label='yahoo')240 plt.xlim((x_lowerbound, x_upperbound))241 plt.ylim((y_lowerbound, y_upperbound))242 plt.title('ally')243 plt.xlabel('$k$')244 plt.grid(True)245 plt.savefig(os.path.join(save_dir, save_path))246# clustering ####247def plot_clustDistr(db, keynames, save_path):248 cluMean_x_name = 'ccDistr_avg_x'249 cluMean_y_name = 'ccDistr_avg_y'250 cluMedian_x_name = 'ccDistr_median_x'251 cluMedian_y_name = 'ccDistr_median_y'252 x_upperbound = 10 ** 4253 y_upperbound = .4254 y_lowerbound = 10 ** -5255 plt.clf()256 plt.figure(figsize = (8, 5))257 plt.subplot(1, 2, 1)258 plt.loglog(db[keynames['mog']][cluMean_x_name], db[keynames['mog']][cluMean_y_name], 'b.', mec='b', ms=5, label='fairyland')259 plt.loglog(db[keynames['mblg']][cluMean_x_name], db[keynames['mblg']][cluMean_y_name], 'r+', mec='r', mfc='None', ms=5, label='twitter')260 plt.loglog(db[keynames['im']][cluMean_x_name], db[keynames['im']][cluMean_y_name], 'k>', mec='k', mfc='None', ms=5, label='yahoo')261 plt.title('interaction')262 plt.xlabel('$k$')263 plt.ylabel('cc')264 plt.grid(True)265 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best', prop = {'size': 10})266 plt.xlim(xmax = x_upperbound)267 plt.ylim(ymax = y_upperbound, ymin = y_lowerbound)268 plt.subplot(1, 2, 2)269 plt.loglog(db[keynames['mogF']][cluMean_x_name], db[keynames['mogF']][cluMean_y_name], 'b.', mec='b', ms=5, label='fairyland')270 plt.loglog(db[keynames['mblgF']][cluMean_x_name], db[keynames['mblgF']][cluMean_y_name], 'r+', mec='r', mfc='None', ms=5, label='twitter')271 plt.loglog(db[keynames['imF']][cluMean_x_name], db[keynames['imF']][cluMean_y_name], 'k>', mec='k', mfc='None', ms=5, label='yahoo')272 plt.title('ally')273 plt.xlabel('$k$')274 plt.grid(True)275 plt.xlim(xmax = x_upperbound)276 plt.ylim(ymax = y_upperbound, ymin = y_lowerbound)277 plt.savefig(os.path.join(save_dir, save_path))278def plot_dist(db, keynames, save_path):279 """plot the sample path distance (in number of hops)"""280 diam_name = 'diameter'281 dist_name = 'hop_counts'282 plt.clf()283 plt.figure(figsize = (8, 5))284 plt.subplot(1, 2, 1)285 x = db[keynames['mog']][dist_name].keys()286 y = db[keynames['mog']][dist_name].values()287 ySum = float(sum(y))288 y = map(lambda z: z / ySum, y)289 plt.plot(x, y, 'b-', lw = 3, label = 'fairyland')290 x = db[keynames['mblg']][dist_name].keys()291 y = db[keynames['mblg']][dist_name].values()292 ySum = float(sum(y))293 y = map(lambda z: z / ySum, y)294 plt.plot(x, y, 'r:', lw = 3, label = 'twitter')295 x = db[keynames['im']][dist_name].keys()296 y = db[keynames['im']][dist_name].values()297 ySum = float(sum(y))298 y = map(lambda z: z / ySum, y)299 plt.plot(x, y, 'k--', lw = 3, label = 'yahoo')300 plt.title('interaction')301 plt.grid(True)302 plt.xlabel('hop number')303 plt.ylabel('probability')304 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best')305 plt.xlim((0, 15))306 plt.ylim((0, .7))307 plt.subplot(1, 2, 2)308 x = db[keynames['mogF']][dist_name].keys()309 y = db[keynames['mogF']][dist_name].values()310 ySum = float(sum(y))311 y = map(lambda z: z / ySum, y)312 plt.plot(x, y, 'b-', lw = 3, label = 'fairyland')313 plt.title('ally')314 plt.grid(True)315 plt.xlabel('hop number')316 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best')317 plt.xlim((0, 15))318 plt.ylim((0, .7))319 plt.savefig(os.path.join(save_dir, save_path))320def plot_prefAttach(db, keynames, save_path):321 """docstring for plot_pref"""322 pa_name = 'pref_attach'323 import numpy as np324 from scipy.optimize import leastsq325 degree = 2326 observation_length = 200327 fit_length = 200328 plt.clf()329 plt.figure(figsize = (9, 7))330 y_upperbound = 4 * 10 ** 6331 y_lowerbound = 0332 x_upperbound = observation_length333 mSize = 5334 335 x = sorted(db[keynames['mog']][pa_name].keys())336 y = []337 for k in x:338 y.append(db[keynames['mog']][pa_name][k])339 if len(x) >= observation_length:340 x = x[:observation_length]341 y = y[:observation_length]342 A = np.vander(x[:fit_length], degree + 1)343 coef, residual, rank, sing_vals = np.linalg.lstsq(A, y[:fit_length])344 f = np.poly1d(coef)345 y_est = f(x)346 plt.plot(x, y, 'b.', label = 'fairyland', ms = mSize)347 plt.plot(x, y_est, 'b-', lw = 2, label = 'fairyland-fitness')348 x = sorted(db[keynames['mblg']][pa_name].keys())349 y = []350 for k in x:351 y.append(db[keynames['mblg']][pa_name][k])352 if len(x) >= observation_length:353 x = x[:observation_length]354 y = y[:observation_length]355 A = np.vander(x[:fit_length], degree + 1)356 coef, residual, rank, sing_vals = np.linalg.lstsq(A, y[:fit_length])357 f = np.poly1d(coef)358 y_est = f(x)359 plt.plot(x, y, 'r+', label = 'twitter', ms = mSize)360 plt.plot(x, y_est, 'r-', lw = 2, label = 'twitter-fitness')361 x = sorted(db[keynames['im']][pa_name].keys())362 y = []363 for k in x:364 y.append(db[keynames['im']][pa_name][k])365 if len(x) >= observation_length:366 x = x[:observation_length]367 y = y[:observation_length]368 A = np.vander(x[:fit_length], degree + 1)369 coef, residual, rank, sing_vals = np.linalg.lstsq(A, y[:fit_length])370 f = np.poly1d(coef)371 y_est = f(x)372 plt.plot(x, y, 'k>', mfc='None', mec='k', label = 'yahoo', ms = mSize)373 plt.plot(x, y_est, 'k--', lw = 2, label = 'yahoo-fitness')374 plt.xlim(xmax = x_upperbound)375 plt.ylim(ymax = y_upperbound, ymin = y_lowerbound)376 #plt.grid(True)377 plt.xlabel('k')378 plt.ylabel('$R_k$')379 plt.legend(('fairyland', 'fairyland-fitness', 'twitter', 'twitter-fitness', 'yahoo', 'yahoo-fitness'), loc = 2, ncol = 2, prop = {'size': 12})380 plt.savefig(os.path.join(save_dir, save_path))381def plot_clustProb(db, keynames, save_path, attr_name = 'cluster_prob'):382 """docstring for plot_pref"""383 import numpy as np384 degree = 2385 observation_length = 200386 fit_length = 200387 plt.clf()388 plt.figure(figsize = (9, 7))389 y_upperbound = 4 * 10 ** 8390 y_lowerbound = 0391 x_upperbound = observation_length392 mSize = 5393 394 x = sorted(db[keynames['mog']][attr_name].keys())395 y = []396 for k in x:397 y.append(db[keynames['mog']][attr_name][k])398 if len(x) >= observation_length:399 x = x[:observation_length]400 y = y[:observation_length]401 A = np.vander(x[:fit_length], degree + 1)402 coef, residual, rank, sing_vals = np.linalg.lstsq(A, y[:fit_length])403 f = np.poly1d(coef)404 y_est = f(x)405 plt.plot(x, y, 'b.', label = 'fairyland', ms = mSize)406 plt.plot(x, y_est, 'b-', lw = 2, label = 'fairyland-fitness')407 x = sorted(db[keynames['mblg']][attr_name].keys())408 y = []409 for k in x:410 y.append(db[keynames['mblg']][attr_name][k])411 if len(x) >= observation_length:412 x = x[:observation_length]413 y = y[:observation_length]414 A = np.vander(x[:fit_length], degree + 1)415 coef, residual, rank, sing_vals = np.linalg.lstsq(A, y[:fit_length])416 f = np.poly1d(coef)417 y_est = f(x)418 plt.plot(x, y, 'r+', label = 'twitter', ms = mSize)419 plt.plot(x, y_est, 'r-', lw = 2, label = 'twitter-fitness')420 x = sorted(db[keynames['im']][attr_name].keys())421 y = []422 for k in x:423 y.append(db[keynames['im']][attr_name][k])424 if len(x) >= observation_length:425 x = x[:observation_length]426 y = y[:observation_length]427 A = np.vander(x[:fit_length], degree + 1)428 coef, residual, rank, sing_vals = np.linalg.lstsq(A, y[:fit_length])429 f = np.poly1d(coef)430 y_est = f(x)431 plt.plot(x, y, 'k>', mfc='None', mec='k', label = 'yahoo', ms = mSize)432 plt.plot(x, y_est, 'k--', lw = 2, label = 'yahoo-fitness')433 plt.xlim(xmax = x_upperbound)434 plt.ylim(ymax = y_upperbound, ymin = y_lowerbound)435 #plt.grid(True)436 plt.xlabel('k')437 plt.ylabel('$R_k$')438 plt.legend(('fairyland', 'fairyland-fitness', 'twitter', 'twitter-fitness', 'yahoo', 'yahoo-fitness'), loc = 1, ncol = 2, prop = {'size': 12})439 plt.savefig(os.path.join(save_dir, save_path))440def plot_Knn(db, keynames, save_path, attr_names = ('knn', 'weighted_knn')):441 plt.clf()442 plt.figure(figsize = (8, 5))443 mSize = 7444 x_upperbound = 10 ** 4445 y_upperbound = 10 ** 4446 y_lowerbound = 10 ** 0447 plt.subplot(1, 2, 1)448 x = sorted(db[keynames['mog']][attr_names[0]].keys())449 y = [db[keynames['mog']][attr_names[0]][k] for k in x]450 plt.loglog(x, y, 'b.', mec = 'b', label = 'fairyland', ms = mSize)451 x = sorted(db[keynames['mblg']][attr_names[0]].keys())452 y = [db[keynames['mblg']][attr_names[0]][k] for k in x]453 plt.loglog(x, y, 'r+', label = 'twitter', ms = mSize)454 x = sorted(db[keynames['im']][attr_names[0]].keys())455 y = [db[keynames['im']][attr_names[0]][k] for k in x]456 plt.loglog(x, y, 'k>', mfc='None', label = 'yahoo', ms = mSize)457 #plt.yscale('log')458 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 'best')459 plt.title('interaction')460 plt.xlabel('$k$')461 plt.ylabel('$K_{nn}$')462 plt.xlim(xmax = x_upperbound)463 plt.ylim(ymax = y_upperbound, ymin = y_lowerbound)464 plt.grid(True)465 plt.subplot(1, 2, 2)466 x = sorted(db[keynames['mogF']][attr_names[0]].keys())467 y = [db[keynames['mogF']][attr_names[0]][k] for k in x]468 plt.loglog(x, y, 'b.', mec = 'b', label = 'fairyland', ms = mSize)469 x = sorted(db[keynames['mblgF']][attr_names[0]].keys())470 y = [db[keynames['mblgF']][attr_names[0]][k] for k in x]471 plt.loglog(x, y, 'r+', label = 'twitter', ms = mSize)472 x = sorted(db[keynames['imF']][attr_names[0]].keys())473 y = [db[keynames['imF']][attr_names[0]][k] for k in x]474 plt.loglog(x, y, 'k>', mfc='None', label = 'yahoo', ms = mSize)475 plt.title('ally')476 #plt.yscale('log')477 plt.xlabel('$k$')478 plt.xlim(xmax = x_upperbound)479 plt.ylim(ymax = y_upperbound, ymin = y_lowerbound)480 plt.grid(True)481 plt.savefig(os.path.join(save_dir, save_path))482def plot_closureProb(db, keynames, save_path, attr_name):483 plt.clf()484 plt.figure(figsize = (9, 7))485 mSize = 7486 487 x = sorted(db[keynames['mog']][attr_name].keys())488 y = []489 for k in x:490 y.append(db[keynames['mog']][attr_name][k])491 ySum = float(sum(y))492 y = map(lambda z: z / ySum, y)493 plt.plot(x, y, 'bo-', label = 'fairyland', ms = mSize)494 x = sorted(db[keynames['mblg']][attr_name].keys())495 y = []496 for k in x:497 y.append(db[keynames['mblg']][attr_name][k])498 ySum = float(sum(y))499 y = map(lambda z: z / ySum, y)500 plt.plot(x, y, 'r+:', label = 'twitter', ms = mSize)501 x = sorted(db[keynames['im']][attr_name].keys())502 y = []503 for k in x:504 y.append(db[keynames['im']][attr_name][k])505 ySum = float(sum(y))506 y = map(lambda z: z / ySum, y)507 plt.plot(x, y, 'k>--', mfc='None', mec='k', label = 'yahoo', ms = mSize)508 plt.grid(True)509 plt.xlim(xmax = 15)510 plt.xlabel('hop count $d$')511 plt.ylabel('$P(d)$')512 plt.legend(('fairyland', 'twitter', 'yahoo'), loc = 1)513 plt.savefig(os.path.join(save_dir, save_path))514# loading and plot ##########515flag = [1]516save_dir = 'doc/interactions_over_platforms/figures'517print (flag)518if 1 in flag:519 db_path = '../exp/db/degree'520 all_filenames = {'mog':'anderson_chat_degree.db', 'mogF': 'anderson_friend_degree.db', 'mblg':'twitter_cut_degree.db', 'mblgF':'twitter_follower_degree.db', 'im': 'yahoo_chat_degree.db', 'imF':'yahoo_friend_degree.db'}521 db, all_keynames = load_data(db_path, all_filenames)522 plot_degreeRate(db, all_keynames, 'degree_rate_distribution.pdf')523 plot_degreeOverlap(db, all_keynames, 'degree_overlap.pdf')524 plot_reusage(db, all_keynames, save_path = 'link_reusage.pdf')525 plot_degreeDistr(db, all_keynames, 'degree_distribution.pdf')526if 2 in flag:527 db_path = '../exp/db/focus'528 all_filenames = {'mog':'anderson_chat.db', 'mogF': 'anderson_friend.db', 'mblg':'twitter_cut.db', 'mblgF':'twitter_follower.db', 'im': 'yahoo_chat.db', 'imF':'yahoo_friend.db'}529 db, all_keynames = load_data(db_path, all_filenames)530 #plot_degreeDistr(db, all_keynames, 'degree_distribution.pdf')531 #plot_KnnDistr(db, all_keynames, 'knn_distribution.pdf')532 plot_clustDistr(db, all_keynames, 'clust_distribution.pdf')533if 3 in flag:534 db_path = '../exp/db/knn'535 all_filenames = {'mog':'anderson_chat_knn.db', 'mogF': 'anderson_friend_knn.db', 'mblg':'twitter_cut_knn.db', 'mblgF':'twitter_follower_knn.db', 'im': 'yahoo_chat_knn.db', 'imF':'yahoo_friend_knn.db'}536 db, all_keynames = load_data(db_path, all_filenames)537 plot_Knn(db, all_keynames, save_path = 'knn_distribution.pdf')538if 4 in flag:539 db_path = '../exp/db/frac'540 all_filenames = {'mog':'anderson_chat_frac.db', 'mogF': 'anderson_friend_frac.db', 'mblg':'twitter_cut_frac.db', 'mblgF':'twitter_follower_frac.db', 'im': 'yahoo_chat_frac.db', 'imF': 'yahoo_friend_frac.db'}541 db, all_keynames = load_data(db_path, all_filenames)542 plot_frac(db, all_keynames, 'frac.pdf')543if 5 in flag:544 db_path = '../exp/db/dist'545 all_filenames = {'mog':'anderson_chat_dist.db', 'mogF': 'anderson_friend_dist.db', 'mblg':'twitter_cut_dist.db', 'im': 'yahoo_chat_dist.db'}546 db, all_keynames = load_data(db_path, all_filenames)547 plot_dist(db, all_keynames, 'dist.pdf')548if 6 in flag:549 db_path = '../exp/db/pa'550 all_filenames = {'mog': 'anderson_chat_pa.db', 'mblg':'twitter_chat_pa.db', 'im': 'yahoo_chat_pa.db'}551 db, all_keynames = load_data(db_path, all_filenames)552 plot_prefAttach(db, all_keynames, 'pref_attachment_rp.pdf')553 db_path = '../exp/db/cr'554 all_filenames = {'mog': 'anderson_chat_cr.db', 'mblg':'twitter_chat_cr.db', 'im': 'yahoo_chat_cr.db'}555 db, all_keynames = load_data(db_path, all_filenames)556 plot_clustProb(db, all_keynames, 'clust_rp.pdf') 557 db_path = '../exp/db/cd'558 all_filenames = {'mog': 'anderson_chat_cd.db', 'mblg':'twitter_chat_cd.db', 'im': 'yahoo_chat_cd.db'}559 db, all_keynames = load_data(db_path, all_filenames)...
keynames.py
Source:keynames.py
1# Orca2#3# Copyright 2006-2008 Sun Microsystems Inc.4#5# This library is free software; you can redistribute it and/or6# modify it under the terms of the GNU Lesser General Public7# License as published by the Free Software Foundation; either8# version 2.1 of the License, or (at your option) any later version.9#10# This library is distributed in the hope that it will be useful,11# but WITHOUT ANY WARRANTY; without even the implied warranty of12# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU13# Lesser General Public License for more details.14#15# You should have received a copy of the GNU Lesser General Public16# License along with this library; if not, write to the17# Free Software Foundation, Inc., Franklin Street, Fifth Floor,18# Boston MA 02110-1301 USA.19"""Exposes a dictionary, keynames, that maps key events20into localized words."""21__id__ = "$Id$"22__version__ = "$Revision$"23__date__ = "$Date$"24__copyright__ = "Copyright (c) 2006-2008 Sun Microsystems Inc."25__license__ = "LGPL"26from . import chnames27from .orca_i18n import _28from .orca_i18n import C_29# __keynames is a dictionary where the keys represent a UTF-830# string for a keyboard key and the values represent the common31# phrase used to describe the key.32#33__keynames = {}34# Translators: this is how someone would speak the name of the shift key35#36__keynames["Shift"] = C_("keyboard", "Shift")37# Translators: this is how someone would speak the name of the alt key38#39__keynames["Alt"] = C_("keyboard", "Alt")40# Translators: this is how someone would speak the name of the control key41#42__keynames["Control"] = C_("keyboard", "Control")43# Translators: this is how someone would speak the name of the left shift key44#45__keynames["Shift_L"] = _("left shift")46# Translators: this is how someone would speak the name of the left alt key47#48__keynames["Alt_L"] = _("left alt")49# Translators: this is how someone would speak the name of the left ctrl key50#51__keynames["Control_L"] = _("left control")52# Translators: this is how someone would speak the name of the right shift key53#54__keynames["Shift_R"] = _("right shift")55# Translators: this is how someone would speak the name of the right alt key56#57__keynames["Alt_R"] = _("right alt")58# Translators: this is how someone would speak the name of the right ctrl key59#60__keynames["Control_R"] = _("right control")61# Translators: this is how someone would speak the name of the left meta key62#63__keynames["Meta_L"] = _("left meta")64# Translators: this is how someone would speak the name of the right meta key65#66__keynames["Meta_R"] = _("right meta")67# Translators: this is how someone would speak the name of the num lock key68#69__keynames["Num_Lock"] = _("num lock")70# Translators: this is how someone would speak the name of the caps lock key71#72__keynames["Caps_Lock"] = _("caps lock")73# Translators: this is how someone would speak the name of the scroll lock key74#75__keynames["Scroll_Lock"] = _("scroll lock")76# Translators: this is how someone would speak the name of the page up key77#78__keynames["Page_Up"] = _("page up")79# Translators: this is how someone would speak the name of the page up key80#81__keynames["KP_Page_Up"] = _("page up")82# Translators: this is how someone would speak the name of the page up key83#84__keynames["Prior"] = _("page up")85# Translators: this is how someone would speak the name of the page up key86#87__keynames["KP_Prior"] = _("page up")88# Translators: this is how someone would speak the name of the page down key89#90__keynames["Page_Down"] = _("page down")91# Translators: this is how someone would speak the name of the page down key92#93__keynames["KP_Page_Down"] = _("page down")94# Translators: this is how someone would speak the name of the page down key95#96__keynames["Next"] = _("page down")97# Translators: this is how someone would speak the name of the page down key98#99__keynames["KP_Next"] = _("page down")100# Translators: this is how someone would speak the name of the tab key101#102__keynames["Tab"] = _("tab")103# Translators: this is how someone would speak the name of the left tab key104#105__keynames["ISO_Left_Tab"] = _("left tab")106# Translators: this is how someone would speak the name of the F11 key107#108__keynames["SunF36"] = _("F 11")109# Translators: this is how someone would speak the name of the F12 key110#111__keynames["SunF37"] = _("F 12")112# Translators: this is the spoken word for the space character113#114__keynames["space"] = _("space")115# Translators: this is how someone would speak the name of the backspace key116#117__keynames["BackSpace"] = _("backspace")118# Translators: this is how someone would speak the name of the return key119#120__keynames["Return"] = _("return")121# Translators: this is how someone would speak the name of the enter key122#123__keynames["KP_Enter"] = _("enter")124# Translators: this is how someone would speak the name of the up arrow key125#126__keynames["Up"] = _("up")127# Translators: this is how someone would speak the name of the up arrow key128#129__keynames["KP_Up"] = _("up")130# Translators: this is how someone would speak the name of the down arrow key131#132__keynames["Down"] = _("down")133# Translators: this is how someone would speak the name of the down arrow key134#135__keynames["KP_Down"] = _("down")136# Translators: this is how someone would speak the name of the left arrow key137#138__keynames["Left"] = _("left")139# Translators: this is how someone would speak the name of the left arrow key140#141__keynames["KP_Left"] = _("left")142# Translators: this is how someone would speak the name of the right arrow key143#144__keynames["Right"] = _("right")145# Translators: this is how someone would speak the name of the right arrow key146#147__keynames["KP_Right"] = _("right")148# Translators: this is how someone would speak the name of the left super key149#150__keynames["Super_L"] = _("left super")151# Translators: this is how someone would speak the name of the right super key152#153__keynames["Super_R"] = _("right super")154# Translators: this is how someone would speak the name of the menu key155#156__keynames["Menu"] = _("menu")157# Translators: this is how someone would speak the name of the ISO shift key158#159__keynames["ISO_Level3_Shift"] = _("ISO level 3 shift")160# Translators: this is how someone would speak the name of the help key161#162__keynames["Help"] = _("help")163# Translators: this is how someone would speak the name of the multi key164#165__keynames["Multi_key"] = _("multi")166# Translators: this is how someone would speak the name of the mode switch key167#168__keynames["Mode_switch"] = _("mode switch")169# Translators: this is how someone would speak the name of the escape key170#171__keynames["Escape"] = _("escape")172# Translators: this is how someone would speak the name of the insert key173#174__keynames["Insert"] = _("insert")175# Translators: this is how someone would speak the name of the insert key176#177__keynames["KP_Insert"] = _("insert")178# Translators: this is how someone would speak the name of the delete key179#180__keynames["Delete"] = _("delete")181# Translators: this is how someone would speak the name of the delete key182#183__keynames["KP_Delete"] = _("delete")184# Translators: this is how someone would speak the name of the home key185#186__keynames["Home"] = _("home")187# Translators: this is how someone would speak the name of the home key188#189__keynames["KP_Home"] = _("home")190# Translators: this is how someone would speak the name of the end key191#192__keynames["End"] = _("end")193# Translators: this is how someone would speak the name of the end key194#195__keynames["KP_End"] = _("end")196# Translators: this is how someone would speak the name of the begin key197#198__keynames["KP_Begin"] = _("begin")199# Translators: this is how someone would speak the name of the200# non-spacing diacritical key for the grave glyph201#202__keynames["dead_grave"] = _("grave")203# Translators: this is how someone would speak the name of the204# non-spacing diacritical key for the acute glyph205#206__keynames["dead_acute"] = _("acute")207# Translators: this is how someone would speak the name of the208# non-spacing diacritical key for the circumflex glyph209#210__keynames["dead_circumflex"] = _("circumflex")211# Translators: this is how someone would speak the name of the212# non-spacing diacritical key for the tilde glyph213#214__keynames["dead_tilde"] = _("tilde")215# Translators: this is how someone would speak the name of the216# non-spacing diacritical key for the diaeresis glyph217#218__keynames["dead_diaeresis"] = _("diaeresis")219# Translators: this is how someone would speak the name of the220# non-spacing diacritical key for the ring glyph221#222__keynames["dead_abovering"] = _("ring")223# Translators: this is how someone would speak the name of the224# non-spacing diacritical key for the cedilla glyph225#226__keynames["dead_cedilla"] = _("cedilla")227# Translators: this is how someone would speak the name of the228# non-spacing diacritical key for the stroke glyph229#230__keynames["dead_stroke"] = _("stroke")231# Translators: this is how someone would speak the name of the minus key232#233__keynames["minus"] = _("minus")234# Translators: this is how someone would speak the name of the plus key235#236__keynames["plus"] = _("plus")237def getKeyName(key):238 """Given a keyboard key, return its name as people might refer to it239 in ordinary conversation.240 Arguments:241 - key: the key to get the name for242 Returns a string representing the name for the key243 """244 if isinstance(key, unicode):245 key = key.encode("UTF-8")246 try:247 return __keynames[key]248 except:249 return chnames.getCharacterName(key)250def localizeKeySequence(keys):251 """Given a sequence of keys, such as 'Shift Control A', localize the252 full sequence.253 Arguments:254 - keys: the key sequence to localize255 Returns a string representing the localized version to present to the256 user257 """258 keyList = keys.split()259 for key in keyList:260 keyName = getKeyName(key)261 try:262 key = key.encode("UTF-8")263 except UnicodeDecodeError:264 pass265 try:266 keyName = keyName.encode("UTF-8")267 except UnicodeDecodeError:268 pass269 try:270 keys = keys.replace(key, keyName)271 except UnicodeDecodeError:272 pass...
gen_keys.py
Source:gen_keys.py
1import sys, os2# genereate keys.h file3f = file("src/engine/keys.h", "w")4keynames = []5for i in range(0, 512):6 keynames += ["&%d"%i]7print >>f, "#ifndef ENGINE_KEYS_H"8print >>f, "#define ENGINE_KEYS_H"9print >>f, '/* AUTO GENERATED! DO NOT EDIT MANUALLY! */'10print >>f, "enum"11print >>f, "{"12highestid = 013for line in open("scripts/SDL_keysym.h"):14 l = line.strip().split("=")15 if len(l) == 2 and "SDLK_" in line:16 key = l[0].strip().replace("SDLK_", "KEY_")17 value = int(l[1].split(",")[0].strip())18 print >>f, "\t%s = %d,"%(key, value)19 20 keynames[value] = key.replace("KEY_", "").lower()21 22 if value > highestid:23 highestid =value24print >>f, "\tKEY_MOUSE_1 = %d,"%(highestid+1); keynames[highestid+1] = "mouse1"25print >>f, "\tKEY_MOUSE_2 = %d,"%(highestid+2); keynames[highestid+2] = "mouse2"26print >>f, "\tKEY_MOUSE_3 = %d,"%(highestid+3); keynames[highestid+3] = "mouse3"27print >>f, "\tKEY_MOUSE_4 = %d,"%(highestid+4); keynames[highestid+4] = "mouse4"28print >>f, "\tKEY_MOUSE_5 = %d,"%(highestid+5); keynames[highestid+5] = "mouse5"29print >>f, "\tKEY_MOUSE_6 = %d,"%(highestid+6); keynames[highestid+6] = "mouse6"30print >>f, "\tKEY_MOUSE_7 = %d,"%(highestid+7); keynames[highestid+7] = "mouse7"31print >>f, "\tKEY_MOUSE_8 = %d,"%(highestid+8); keynames[highestid+8] = "mouse8"32print >>f, "\tKEY_MOUSE_WHEEL_UP = %d,"%(highestid+9); keynames[highestid+9] = "mousewheelup"33print >>f, "\tKEY_MOUSE_WHEEL_DOWN = %d,"%(highestid+10); keynames[highestid+10] = "mousewheeldown"34print >>f, "\tKEY_LAST,"35print >>f, "};"36print >>f, ""37print >>f, "#endif"38# generate keynames.c file39f = file("src/engine/client/keynames.h", "w")40print >>f, '/* AUTO GENERATED! DO NOT EDIT MANUALLY! */'41print >>f, ''42print >>f, '#ifndef KEYS_INCLUDE'43print >>f, '#error do not include this header!'44print >>f, '#endif'45print >>f, ''46print >>f, "#include <string.h>"47print >>f, ""48print >>f, "const char g_aaKeyStrings[512][16] ="49print >>f, "{"50for n in keynames:51 print >>f, '\t"%s",'%n52print >>f, "};"53print >>f, ""...
Automation Testing Tutorials
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