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How to use fun method in responses

Best Python code snippet using responses

lib_acquisition_function.py

Source:lib_acquisition_function.py

...36                (res.fun < best_acquisition_value):37            res.x = numpy.ndarray.tolist(res.x)38            res.x = lib_data.match_val_type(res.x, x_bounds, x_types)39            if (minimize_constraints_fun is None) or \40                    (minimize_constraints_fun(res.x) is True):41                best_acquisition_value = res.fun42                best_x = res.x43    outputs = None44    if best_x is not None:45        mu, sigma = fun_prediction(best_x, *fun_prediction_args)46        outputs = {'hyperparameter': best_x, 'expected_mu': mu,47                   'expected_sigma': sigma, 'acquisition_func': "ei"}48    return outputs49def _expected_improvement(x, fun_prediction, fun_prediction_args,50                          x_bounds, x_types, samples_y_aggregation,51                          minimize_constraints_fun):52    # This is only for step-wise optimization53    x = lib_data.match_val_type(x, x_bounds, x_types)54    expected_improvement = sys.maxsize55    if (minimize_constraints_fun is None) or (56            minimize_constraints_fun(x) is True):57        mu, sigma = fun_prediction(x, *fun_prediction_args)58        loss_optimum = min(samples_y_aggregation)59        scaling_factor = -160        # In case sigma equals zero61        with numpy.errstate(divide="ignore"):62            Z = scaling_factor * (mu - loss_optimum) / sigma63            expected_improvement = scaling_factor * (mu - loss_optimum) * \64                norm.cdf(Z) + sigma * norm.pdf(Z)65            expected_improvement = 0.0 if sigma == 0.0 else expected_improvement66        # We want expected_improvement to be as large as possible67        # (i.e., as small as possible for minimize(...))68        expected_improvement = -1 * expected_improvement69    return expected_improvement70def next_hyperparameter_lowest_confidence(fun_prediction,71                                          fun_prediction_args,72                                          x_bounds, x_types,73                                          minimize_starting_points,74                                          minimize_constraints_fun=None):75    """76    "Lowest Confidence" acquisition function77    """78    best_x = None79    best_acquisition_value = None80    x_bounds_minmax = [[i[0], i[-1]] for i in x_bounds]81    x_bounds_minmax = numpy.array(x_bounds_minmax)82    for starting_point in numpy.array(minimize_starting_points):83        res = minimize(fun=_lowest_confidence,84                       x0=starting_point.reshape(1, -1),85                       bounds=x_bounds_minmax,86                       method="L-BFGS-B",87                       args=(fun_prediction,88                             fun_prediction_args,89                             x_bounds,90                             x_types,91                             minimize_constraints_fun))92        if (best_acquisition_value) is None or (93                res.fun < best_acquisition_value):94            res.x = numpy.ndarray.tolist(res.x)95            res.x = lib_data.match_val_type(res.x, x_bounds, x_types)96            if (minimize_constraints_fun is None) or (97                    minimize_constraints_fun(res.x) is True):98                best_acquisition_value = res.fun99                best_x = res.x100    outputs = None101    if best_x is not None:102        mu, sigma = fun_prediction(best_x, *fun_prediction_args)103        outputs = {'hyperparameter': best_x, 'expected_mu': mu,104                   'expected_sigma': sigma, 'acquisition_func': "lc"}105    return outputs106def _lowest_confidence(x, fun_prediction, fun_prediction_args,107                       x_bounds, x_types, minimize_constraints_fun):108    # This is only for step-wise optimization109    x = lib_data.match_val_type(x, x_bounds, x_types)110    ci = sys.maxsize111    if (minimize_constraints_fun is None) or (112            minimize_constraints_fun(x) is True):113        mu, sigma = fun_prediction(x, *fun_prediction_args)114        ci = (sigma * 1.96 * 2) / mu115        # We want ci to be as large as possible116        # (i.e., as small as possible for minimize(...),117        # because this would mean lowest confidence118        ci = -1 * ci119    return ci120def next_hyperparameter_lowest_mu(fun_prediction,121                                  fun_prediction_args,122                                  x_bounds, x_types,123                                  minimize_starting_points,124                                  minimize_constraints_fun=None):125    """126    "Lowest Mu" acquisition function127    """128    best_x = None129    best_acquisition_value = None130    x_bounds_minmax = [[i[0], i[-1]] for i in x_bounds]131    x_bounds_minmax = numpy.array(x_bounds_minmax)132    for starting_point in numpy.array(minimize_starting_points):133        res = minimize(fun=_lowest_mu,134                       x0=starting_point.reshape(1, -1),135                       bounds=x_bounds_minmax,136                       method="L-BFGS-B",137                       args=(fun_prediction, fun_prediction_args,138                             x_bounds, x_types, minimize_constraints_fun))139        if (best_acquisition_value is None) or (140                res.fun < best_acquisition_value):141            res.x = numpy.ndarray.tolist(res.x)142            res.x = lib_data.match_val_type(res.x, x_bounds, x_types)143            if (minimize_constraints_fun is None) or (144                    minimize_constraints_fun(res.x) is True):145                best_acquisition_value = res.fun146                best_x = res.x147    outputs = None148    if best_x is not None:149        mu, sigma = fun_prediction(best_x, *fun_prediction_args)150        outputs = {'hyperparameter': best_x, 'expected_mu': mu,151                   'expected_sigma': sigma, 'acquisition_func': "lm"}152    return outputs153def _lowest_mu(x, fun_prediction, fun_prediction_args,154               x_bounds, x_types, minimize_constraints_fun):155    """156    Calculate the lowest mu157    """158    # This is only for step-wise optimization159    x = lib_data.match_val_type(x, x_bounds, x_types)160    mu = sys.maxsize161    if (minimize_constraints_fun is None) or (162            minimize_constraints_fun(x) is True):163        mu, _ = fun_prediction(x, *fun_prediction_args)...

checkCreatMultiAndInitRecusion.py

Source:checkCreatMultiAndInitRecusion.py

...51    def setVarSource(self):52        self.VarSource = "pstru" + self.struNameHld53    def setVarCheck(self):54        self.VarCheck = self.VarSource + "Check"55    def setfun(self):56        self.fun = "void " + getFunName(self.struNameHld) + "(" + self.struName + " *" + self.VarSource + ", " + self.struName + " *" + self.VarCheck + ")\n{\n"57        if self.VarLoopFlag:58            self.fun = self.fun + "    u32    u32i;\n\n"59        for linenum, VarName in enumerate(self.VarNameList):60            VarryObject = re.search(r'([\w|_]+)\[([\w|_]+)\]', VarName)61            if VarryObject:62                VarName = VarryObject.group(1)63                VarSourceName = self.VarSource + "->" + VarName + "[u32i]"64                VarCheckName = self.VarCheck + "->" + VarName + "[u32i]"65                self.fun = self.fun + "\n    for(u32i = 0; u32i < " + VarryObject.group(2) + "; u32i++)\n    {\n"66                if IsStruct(VarName):67                    self.fun = self.fun + "        " + getFunName(self.VarStructNameList[linenum]) + "(&" + VarSourceName + ", &" + VarCheckName + ");\n"68                elif IsStrucPoint(VarName):69                    self.fun = self.fun + "        " + getFunName(self.VarStructNameList[linenum]) + "(" + VarSourceName + ", " + VarCheckName + ");\n"70                else:71                    self.fun = self.fun + "        CHECK_EQUAL_TEXT(" + VarCheckName + ",  " + VarSourceName + ",  " + "\"" + VarSourceName + "\");\n"72                self.fun = self.fun + "    }\n\n"73            else:74                VarSourceName = self.VarSource + "->" + VarName75                VarCheckName = self.VarCheck + "->" + VarName76                if IsStruct(VarName):77                    self.fun = self.fun + "    " + getFunName(self.VarStructNameList[linenum]) + "(&" + VarSourceName + ", &" + VarCheckName + ");\n"78                elif IsStrucPoint(VarName):79                    self.fun = self.fun + "    " + getFunName(self.VarStructNameList[linenum]) + "(" + VarSourceName + ", " + VarCheckName + ");\n"80                else:81                    self.fun = self.fun + "    CHECK_EQUAL_TEXT(" + VarCheckName + ",  " + VarSourceName + ",  " + "\"" + VarSourceName + "\");\n"82        self.fun = self.fun + funEnd83    def getStruInitCode(self, struVarName,structInsList):84        subVarNameList = []85        for instance in structInsList:86            if struVarName == instance.struName:87                subVarNameList = instance.VarNameList88                break89        return subVarNameList90    def setInitFun(self):91        self.initFun = "void " + getInitFunName(self.struNameHld) + "( )\n{\n"92        self.initFun = self.initFun + "    " + self.struName + "  *" + self.VarSource + ";\n"93        for linenum, VarName in enumerate(self.VarNameList):94            VarryObject = re.search(r'([\w|_]+)\[([\w|_]+)\]', VarName)95            if VarryObject:96                VarName = VarryObject.group(1)97                VarSourceName = self.VarSource + "->" + VarName + "[u32i]"98                self.initFun = self.initFun + "\n    for(u32i = 0; u32i < " + VarryObject.group(2) + "; u32i++)\n    {\n"99                if IsStruct(VarName):100                    self.initFun = self.initFun + "        " + VarSourceName + " = ;\n"101                else:102                    self.initFun = self.initFun + "        " + VarSourceName + " = ;\n"103                self.initFun = self.initFun + "    }\n\n"104            else:105                VarSourceName = self.VarSource + "->" + VarName106                if re.search(r'^stru', VarName):107                    self.initFun = self.initFun + "    " + VarSourceName + " = ;\n"108                else:109                    self.initFun = self.initFun + "    " + VarSourceName + " = ;\n"110        self.initFun = self.initFun + funEnd111    def subStruct(self):112        funInitTemp = ""113        codeLine = re.split(r'\n', code)114        for line in codeLine:115            if 116    def checkfunInit(self):117        codeLine = 118    def creatfun(self, code):119        self.setStruName(code)120        self.setVarNameList(code)121        self.setVarSource()122        self.setVarCheck()123        self.setfun()124        self.setInitFun()125fileDef = open('def.txt','r')126fileFun = open('fun.txt','w')127fileFunInit = open('funInit.txt','w')128fileDefStr = fileDef.read()129codeList = splitStructCode(fileDefStr)130for code in codeList:131    structInstance = StructClass()132    structInstance.creatfun(code)133    fileFun.write(structInstance.fun)134    fileFunInit.write(structInstance.initFun)135fileFun.close()136fileDef.close()...

fun_linecount.py

Source:fun_linecount.py

1import os, codecs2import re3import xlwt4from os.path import join, getsize5#filedir = r'D:\ViewRoot\chengengyu_Merge\EMB5216_L2'6filedir = r'D:\ViewRoot\RRM\EMB5216_HL'7#filedir = r'D:\learn\HL DBAå½æ°è§£æ\now'8class Funline(object):9    def __init__(self):10        self.FunName = False;11        self.FunLineCount = 0;12        self.FunStart = 0;13        self.FunEnd = 0;14        self.FunFileName = False;15    16def findfiles(filedir):17    filelist = []18    filename_file = open('filename.txt','w')19    for root, dirs, files in os.walk(filedir):20        if files:21            for name in files:22                if re.search('.c$', name):23                    filelist.append(join(root, name))               24                    filename_file.write(name+'\n')25    filename_file.close26    return filelist27#è·åæä»¶åè¡¨28filelist = findfiles(filedir)29fun_check_result = open('fun_check_result.txt','w')30fun_check_errLine = open('fun_check_errLine.txt','w')31FunLineList = []32for file in filelist:33    filename = ''34    filename = re.findall(r'\\([^\\]+\.c)$', file)35    try:36        fp = codecs.open(file,'rb')37        #fp = open(file,'r')38        #print(file)39        FirstFunFlag = True40        LastFunFlag = False41        FunLineNum = 042        for num,eachline in enumerate(fp):         43            try:44                #å°è¯ç¨ gbkè§£ç 45                eachline = eachline.decode('GBK')46                linetemp = eachline.strip()47                if re.search(r'^(?:void|s32|OSP_STATUS|u32|u8|u16|s8|s16) +\S+(?:$|\s*\(.*(,|\)))', linetemp):48                    if not re.search(r';|extern', linetemp):49                        if FirstFunFlag == False:      #ä¸æ¯ç¬¬ä¸ä¸ªå½æ°åéè¦è®°å½å¶è¡æ°50                            #print(num, FunlineNum)51                            if fun.FunLineCount != 0:52                                fun_check_result.write("å¼å¸¸åå®¹fun:" + fun.FunName + eachline + '\n')53                            else:54                                fun.FunLineCount = num - FunLineNum55                                fun.FunStart = FunLineNum56                                fun.FunEnd = num57                        fun = Funline()58                        FunLineList.append(fun)59                        FirstFunFlag = False60                        FunLineNum = num  #è®°å½å½æ°å¼å§çè¡æ°61                        LastFunFlag = True #åå®è¿æ¯æåä¸ä¸ªå½æ°62                        if fun.FunName != False:63                           fun_check_result.write("å¼å¸¸åå®¹fun:" + eachline + '\n')64                        else:65                            fun.FunName = linetemp66                            fun.FunFileName = filename67            except Exception as e:68                #è§£æå¤±è´¥ï¼éå¸¸æ¯å ä¸ºä¸äºæ±åçåè§å¨è§æé®é¢        69                print(e)70                fun_check_errLine.write(str(e))71                err = "æ æ³è§£æçè¡: æä»¶ä¸º" + file + "è¡å·ä¸º:" + str(num+1) + '\n'72                fun_check_errLine.write(err)73        fp.close74        if LastFunFlag:75            if fun.FunLineCount != 0:76               fun_check_result.write("å¼å¸¸åå®¹fun:" + fun.FunName + eachline + '\n')77            else:78                fun.FunLineCount = num - FunLineNum79                fun.FunStart = FunLineNum80                fun.FunEnd = num81    except Exception as e:82        print(e)83        fun_check_errLine.write(str(e))84        err = 'æ æ³æå¼æä»¶' + file +'\n'85        fun_check_result.write(err)86fun_check_result.close()87fun_check_errLine.close()88#print(FunLineList)89styles = {'datetime': xlwt.easyxf(num_format_str='yyyy-mm-dd hh:mm:ss'),90          'date': xlwt.easyxf(num_format_str='yyyy-mm-dd'),91          'time': xlwt.easyxf(num_format_str='hh:mm:ss'),92          'header': xlwt.easyxf('font: name Times New Roman, color-index black, bold on', num_format_str='#,##0.00'),93          'default': xlwt.Style.default_style}94wb = xlwt.Workbook(encoding = 'utf-8')95sheet = wb.add_sheet(u'å½æ°')96row = 097sheet.write(row,0, 'æä»¶å')98sheet.write(row,1, 'å½æ°å')99sheet.write(row,2, 'è¡æ°')100sheet.write(row,3, 'å¼å§è¡æ°')101sheet.write(row,4, 'ç»æè¡æ°')102for num,eachitem in enumerate(FunLineList):     103    row = num + 1104    sheet.write(row,0, eachitem.FunFileName)105    sheet.write(row,1, eachitem.FunName)106    sheet.write(row,2, eachitem.FunLineCount)107    sheet.write(row,3, eachitem.FunStart)108    sheet.write(row,4, eachitem.FunEnd)...

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