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How to use getSDRate method in autotest

Best Python code snippet using autotest_python

regression.py

Source:regression.py

...141    def getAvgPercent(self, avgs_dict):142        return self._process_files(avgs_dict, self._get_augment_rate)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 = []...

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