How to use getTtestPvalue method in autotest

Best Python code snippet using autotest_python

regression.py

Source:regression.py Github

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...143 def getSD(self):144 return self._process_files(self.files_dict, self._get_list_sd)145 def getSDRate(self, sds_dict):146 return self._process_files(sds_dict, self._get_rate)147 def getTtestPvalue(self, fs_dict1, fs_dict2, paired=None):148 """149 scipy lib is used to compute p-value of Ttest150 scipy: http://www.scipy.org/151 t-test: http://en.wikipedia.org/wiki/Student's_t-test152 """153 try:154 from scipy import stats155 import numpy as np156 except ImportError:157 print "No python scipy/numpy library installed!"158 return None159 ret = []160 s1 = self._process_files(fs_dict1, self._get_list_self, merge=False)161 s2 = self._process_files(fs_dict2, self._get_list_self, merge=False)162 # s*[line][col] contians items (line*col) of all sample files163 for line in range(len(s1)):164 tmp = []165 if type(s1[line]) != list:166 tmp = s1[line]167 else:168 if len(s1[line][0]) < 2:169 continue170 for col in range(len(s1[line])):171 avg1 = self._get_list_avg(s1[line][col])172 avg2 = self._get_list_avg(s2[line][col])173 sample1 = np.array(s1[line][col])174 sample2 = np.array(s2[line][col])175 warnings.simplefilter("ignore", RuntimeWarning)176 if (paired):177 (t, p) = stats.ttest_rel(sample1, sample2)178 else:179 (t, p) = stats.ttest_ind(sample1, sample2)180 flag = "+"181 if float(avg1) > float(avg2):182 flag = "-"183 tmp.append(flag + "%.3f" % (1 - p))184 tmp = "|".join(tmp)185 ret.append(tmp)186 return ret187 def _get_rate(self, data):188 """ num2 / num1 * 100 """189 result = "0.0"190 if len(data) == 2 and float(data[0]) != 0:191 result = float(data[1]) / float(data[0]) * 100192 if result < 1:193 result = "%.2f%%" % result194 else:195 result = "%.0f%%" % result196 return result197 def _get_augment_rate(self, data):198 """ (num2 - num1) / num1 * 100 """199 result = "+0.0"200 if len(data) == 2 and float(data[0]) != 0:201 result = "%+.3f%%" % ((float(data[1]) - float(data[0])) /202 float(data[0]) * 100)203 return result204 def _get_list_sd(self, data):205 """206 sumX = x1 + x2 + ... + xn207 avgX = sumX / n208 sumSquareX = x1^2 + ... + xn^2209 SD = sqrt([sumSquareX - (n * (avgX ^ 2))] / (n - 1))210 """211 sum = sqsum = 0212 n = len(data)213 for i in data:214 sum += float(i)215 sqsum += float(i) ** 2216 avg = sum / n217 if avg == 0 or n == 1 or sqsum - (n * avg ** 2) <= 0:218 return "0.0"219 return "%.3f" % (((sqsum - (n * avg ** 2)) / (n - 1)) ** 0.5)220 def _get_list_avg(self, data):221 """ Compute the average of list entries """222 sum = 0223 for i in data:224 sum += float(i)225 if is_int(str(data[0])):226 return "%d" % (sum / len(data))227 return "%.2f" % (sum / len(data))228 def _get_list_self(self, data):229 """ Use this to convert sample dicts """230 return data231 def _process_lines(self, files_dict, row, func, avg_update, merge):232 """ Use unified function to process same lines of different samples """233 lines = []234 ret = []235 for i in range(len(files_dict)):236 lines.append(files_dict[i][row].split("|"))237 for col in range(len(lines[0])):238 data_list = []239 for i in range(len(lines)):240 tmp = lines[i][col].strip()241 if is_int(tmp):242 data_list.append(int(tmp))243 else:244 data_list.append(float(tmp))245 ret.append(func(data_list))246 if avg_update:247 for i in avg_update.split('|'):248 line = i.split(',')249 ret[int(line[0])] = "%.2f" % (float(ret[int(line[1])]) /250 float(ret[int(line[2])]))251 if merge:252 return "|".join(ret)253 return ret254 def _process_files(self, files_dict, func, avg_update=None, merge=True):255 """256 Process dicts of sample files with assigned function,257 func has one list augment.258 """259 ret_lines = []260 for i in range(len(files_dict[0])):261 if re.findall("[a-zA-Z]", files_dict[0][i]):262 ret_lines.append(files_dict[0][i].strip())263 else:264 line = self._process_lines(files_dict, i, func, avg_update,265 merge)266 ret_lines.append(line)267 return ret_lines268def display(lists, rates, allpvalues, f, ignore_col, sum="Augment Rate",269 prefix0=None, prefix1=None, prefix2=None, prefix3=None):270 """271 Display lists data to standard format272 param lists: row data lists273 param rates: augment rates lists274 param f: result output file275 param ignore_col: do not display some columns276 param sum: compare result summary277 param prefix0: output prefix in head lines278 param prefix1: output prefix in Avg/SD lines279 param prefix2: output prefix in Diff Avg/P-value lines280 param prefix3: output prefix in total Sign line281 """282 def str_ignore(str, split=False):283 str = str.split("|")284 for i in range(ignore_col):285 str[i] = " "286 if split:287 return "|".join(str[ignore_col:])288 return "|".join(str)289 def tee_line(content, file, n=None):290 fd = open(file, "a")291 print content292 str = ""293 str += "<TR ALIGN=CENTER>"294 content = content.split("|")295 for i in range(len(content)):296 if n and i >= 2 and i < ignore_col + 2:297 str += "<TD ROWSPAN=%d WIDTH=1%% >%s</TD>" % (n, content[i])298 else:299 str += "<TD WIDTH=1%% >%s</TD>" % content[i]300 str += "</TR>"301 fd.write(str + "\n")302 fd.close()303 for l in range(len(lists[0])):304 if not re.findall("[a-zA-Z]", lists[0][l]):305 break306 tee("<TABLE BORDER=1 CELLSPACING=1 CELLPADDING=1 width=10%><TBODY>",307 f)308 tee("<h3>== %s " % sum + "==</h3>", f)309 category = 0310 for i in range(len(lists[0])):311 for n in range(len(lists)):312 is_diff = False313 for j in range(len(lists)):314 if lists[0][i] != lists[j][i]:315 is_diff = True316 if len(lists) == 1 and not re.findall("[a-zA-Z]", lists[j][i]):317 is_diff = True318 pfix = prefix1[0]319 if len(prefix1) != 1:320 pfix = prefix1[n]321 if is_diff:322 if n == 0:323 tee_line(pfix + lists[n][i], f, n=len(lists) + len(rates))324 else:325 tee_line(pfix + str_ignore(lists[n][i], True), f)326 if not is_diff and n == 0:327 if '|' in lists[n][i]:328 tee_line(prefix0 + lists[n][i], f)329 elif "Category:" in lists[n][i]:330 if category != 0 and prefix3:331 if len(allpvalues[category - 1]) > 0:332 tee_line(prefix3 + str_ignore(333 allpvalues[category - 1][0]), f)334 tee("</TBODY></TABLE>", f)335 tee("<br>", f)336 tee("<TABLE BORDER=1 CELLSPACING=1 CELLPADDING=1 "337 "width=10%><TBODY>", f)338 category += 1339 tee("<TH colspan=3 >%s</TH>" % lists[n][i], f)340 else:341 tee("<TH colspan=3 >%s</TH>" % lists[n][i], f)342 for n in range(len(rates)):343 if lists[0][i] != rates[n][i] and not re.findall("[a-zA-Z]",344 rates[n][i]):345 tee_line(prefix2[n] + str_ignore(rates[n][i], True), f)346 if prefix3 and len(allpvalues[-1]) > 0:347 tee_line(prefix3 + str_ignore(allpvalues[category - 1][0]), f)348 tee("</TBODY></TABLE>", f)349def analyze(test, type, arg1, arg2, configfile):350 """ Compute averages/p-vales of two samples, print results nicely """351 config = ConfigParser.ConfigParser()352 config.read(configfile)353 ignore_col = int(config.get(test, "ignore_col"))354 avg_update = config.get(test, "avg_update")355 desc = config.get(test, "desc")356 def get_list(dir):357 result_file_pattern = config.get(test, "result_file_pattern")358 cmd = 'find %s|grep "%s.*/%s"' % (dir, test, result_file_pattern)359 print cmd360 return commands.getoutput(cmd)361 if type == 'file':362 arg1 = get_list(arg1)363 arg2 = get_list(arg2)364 commands.getoutput("rm -f %s.*html" % test)365 s1 = Sample(type, arg1)366 avg1 = s1.getAvg(avg_update=avg_update)367 sd1 = s1.getSD()368 s2 = Sample(type, arg2)369 avg2 = s2.getAvg(avg_update=avg_update)370 sd2 = s2.getSD()371 sd1 = s1.getSDRate([avg1, sd1])372 sd2 = s1.getSDRate([avg2, sd2])373 avgs_rate = s1.getAvgPercent([avg1, avg2])374 navg1 = []375 navg2 = []376 allpvalues = []377 tmp1 = []378 tmp2 = []379 for i in range(len(avg1)):380 if not re.findall("[a-zA-Z]", avg1[i]):381 tmp1.append([avg1[i]])382 tmp2.append([avg2[i]])383 elif 'Category' in avg1[i] and i != 0:384 navg1.append(tmp1)385 navg2.append(tmp2)386 tmp1 = []387 tmp2 = []388 navg1.append(tmp1)389 navg2.append(tmp2)390 for i in range(len(navg1)):391 allpvalues.append(s1.getTtestPvalue(navg1[i], navg2[i], True))392 pvalues = s1.getTtestPvalue(s1.files_dict, s2.files_dict, False)393 rlist = [avgs_rate]394 if pvalues:395 # p-value list isn't null396 rlist.append(pvalues)397 desc = desc % s1.len398 tee("<pre>####1. Description of setup#1\n" + s1.version + "</pre>",399 test + ".html")400 tee("<pre>####2. Description of setup#2\n" + s2.version + "</pre>",401 test + ".html")402 tee("<pre>" + '\n'.join(desc.split('\\n')) + "</pre>", test + ".html")403 tee("<pre>" + s1.desc + "</pre>", test + ".html")404 display([avg1, sd1, avg2, sd2], rlist, allpvalues, test + ".html",405 ignore_col, sum="Regression Testing: %s" % test, prefix0="#|Tile|",406 prefix1=["1|Avg|", " |%SD|", "2|Avg|", " |%SD|"],...

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