How to use mark_as_failure method in Slash

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spectral_recorder.py

Source:spectral_recorder.py

1#!/usr/bin/env python2#3#4# This program is free software: you can redistribute it and/or modify5# it under the terms of the GNU General Public License as published by6# the Free Software Foundation, either version 3 of the License, or7# (at your option) any later version.8# 9# This program is distributed in the hope that it will be useful,10# but WITHOUT ANY WARRANTY; without even the implied warranty of11# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the12# GNU General Public License for more details.13# 14# You should have received a copy of the GNU General Public License15# along with this program. If not, see <http://www.gnu.org/licenses/>.16import array17import struct18import sys19import time20import os21import json22from subprocess import call23from operator import itemgetter24from sklearn import preprocessing25import numpy as np26import matplotlib27matplotlib.use('TkAgg')28import matplotlib.pyplot as plt29import numpy as np30class SpectralRecorder:31	phy = "phy0"32	dev = "wlan0"33	drv= "ath9k"34	mode="manual"		#works35	fft_period=1536	spectral_count=10037	spectral_period=138	short_repeat=139	f0=2437e640	def __init__(self, phy="self.phy0", dev="wlan0", drv="ath9k",41			mode="manual", fft_period=15, spectral_count=100, 	spectral_period=1,short_repeat=1,42		load=False,offline=True,freq=2437e6):43		self.phy 		= self.phy44		self.dev 		= self.dev45		self.drv		= drv46		self.mode		= mode47		self.fft_period		= fft_period48		self.spectral_count	= spectral_count49		self.spectral_period	= spectral_period50		self.short_repeat	= short_repeat51		self.f0			= freq #optional useful only if load is True52		#set spectral parameters53		if offline==False:54			self.set_spectral_params()55		if load:56			self.load_monitor()57	def get_spectral_params(self):58		return self.fft_period,self.spectral_count,self.spectral_period,self.short_repeat59	def load_monitor(self):60		#call("bash build.sh --load-module",shell=True)61		call("ifconfig "+self.dev+" down",shell=True)62		call("iwconfig "+self.dev+" mode monitor",shell=True)63		call("ifconfig "+self.dev+" up",shell=True)64		call("iwconfig "+self.dev+" freq "+str(self.f0),shell=True)65	def set_spectral_params(self):66		call("echo "+ self.mode		  		+ " > /sys/kernel/debug/ieee80211/" +self.phy+ "/"+ self.drv +"/spectral_scan_ctl", shell=True)67		call("echo "+ str(self.short_repeat)	  	+ " > /sys/kernel/debug/ieee80211/" +self.phy+ "/"+ self.drv +"/spectral_short_repeat",shell=True)68		call("echo "+ str(self.fft_period)	  	+ " > /sys/kernel/debug/ieee80211/" +self.phy+ "/"+ self.drv +"/spectral_fft_period",shell=True)69		call("echo "+ str(self.spectral_count-1) 	+ " > /sys/kernel/debug/ieee80211/" +self.phy+ "/"+ self.drv +"/spectral_count",shell=True)70		call("echo "+ str(self.spectral_period)		+ " > /sys/kernel/debug/ieee80211/" +self.phy+ "/"+ self.drv +"/spectral_period",shell=True)71	def acquire(self,filename="data",T_acquire=1,T=0.1):72		73		call("cat /sys/kernel/debug/ieee80211/" + self.phy + "/"+ self.drv +"/spectral_scan0 > {}".format(filename), shell=True)74		time.sleep(T)75		t0=time.time()76		t0_a=t077		now=t078		now_a=t079		while now_a-t0_a < T_acquire:80			now_a=time.time()81			while now-t0 < T:82				now=time.time()83				call("echo trigger > /sys/kernel/debug/ieee80211/" + self.phy + "/"+ self.drv +"/spectral_scan_ctl", shell=True)84			now=time.time()85			t0=now86			call("cat /sys/kernel/debug/ieee80211/" + self.phy + "/"+ self.drv +"/spectral_scan0 >> {}".format(filename), shell=True)87			#print(now_a-t0_a)88	def fix_timestamp_dict(self,samp_dict,T=50e3):89		ret=samp_dict90		timestamp=[v['tsf'] for v in samp_dict]91		timestamp=np.array(timestamp)-timestamp[0]92		decr=093		if len(timestamp)!=0:94			tsf_diff=[]95			for i_t in range(0,len(timestamp)-1):96				t_=timestamp[i_t]97				t=timestamp[i_t+1]98				dt=t-t_99				print("t[{}]={}".format(i_t,t))100				print("t[{}]_={}".format(i_t,t_))101				if abs(dt) > T:102					#EMERGE ERROR, TSF chagnes103					print("[E] t[{}]={}".format(i_t,t))104					print("[E] t_[{}]={}".format(i_t,t_))105					ret.pop(i_t+1)106					decr=decr+1107				else:108					tsf_diff.append(dt)109					tsf_new=sum(tsf_diff)110					ret[i_t-decr]['tsf']=tsf_new111		else:112			print("timestamp is empty")113		ret.pop(len(ret)-1)114		return ret115	def fix_timestamp(self,timestamp,busy,x,T=50e3):116		if len(timestamp)!=0:117			timestamp=np.array(timestamp)-timestamp[0]118			tsf_diff=[]119			for i_t in range(0,len(timestamp)-1):120				t_=timestamp[i_t]121				t=timestamp[i_t+1]122				dt=t-t_123				#print("t={}".format(t))124				#print("t_={}".format(t_))125				if abs(dt) > T:126					#EMERGE ERROR, TSF chagnes127					print("t={}".format(t))128					print("t_={}".format(t_))129					busy.pop(i_t)130					x.pop(i_t)131				else:132					tsf_diff.append(dt)133			timestamp=np.cumsum(tsf_diff)134			busy=busy[0:len(timestamp)]135		else:136			print ("timestamp is empty")137		return timestamp,busy,x138	def extract_samples(self,filename="data",out_file="out_samp.json",T=-1):139		y = []140		p_fft=[]141		freq_fft=[]142		busy = []143		timestamp = []144		out_samp=[]145		take_all_samples=False;146		if T == -1:147			take_all_samples=True;148		with open(filename, "rb") as file:149			data = file.read(76)150			i_pos_tmp=0151#			while data != "":152			while data:153				i_pos_tmp=i_pos_tmp+1154				y_t = []155				x = []156				t, length = struct.unpack(">BH", data[0:3])157				if t != 1 or length != 73:158				    print("only 20MHz supported atm")159				    sys.exit(1)160				### metadata161				max_exp, freq, rssi, noise, max_magnitude, max_index, bitmap_weight, tsf = struct.unpack('>BHbbHBBQ', data[3:20])162				### measurements163				measurements = array.array("B")164				measurements.fromstring(data[20:])165				squaresum = sum([(m << max_exp)**2 for m in measurements])166				if squaresum == 0:167				    data = file.read(76)168				    continue169				fft_sub=[]170				for i, m in enumerate(measurements):171					if m == 0 and max_exp == 0:172						m = 1173					v = 10.0**((noise + rssi + 20.0 * np.log10(m << max_exp) - 10.0 * np.log10(squaresum))/10.0)174					fft_sub.append(v)175				entry={}176				entry['tsf']=tsf177				timestamp.append(int(tsf))178				entry['freq']=freq179				entry['rssi']=rssi180				entry['noise']=noise181				entry['fft_sub']=fft_sub182				out_samp.append(entry)183				data = file.read(76)184				if not(take_all_samples):185					if int(timestamp[len(timestamp)-1])-int(timestamp[0]) < T:186						data = file.read(76)187						continue;188					else:189					    	break190		#with open(out_file, 'w') as file:191		#	out_json=json.dumps(out_samp)192		#	file.write(out_json)193		return out_samp194	def get_feature(self,busy,timestamp):195		W = 1e3; #usec196		ts = timestamp-timestamp[0]197		t_= ts[0];198		t = ts[1];199		b_curr=[];200		b_mean=[];201		b_var =[];202		for b in range(0,len(busy)):203			if t-t_ < W:204				t = ts[b]205			else:206				t_= ts[b]207				b_mean.append(np.mean(b_curr))208				b_var.append(np.var(b_curr))209				b_curr=[]210			b_curr.append(busy[b])211		return b_mean, b_var212	def rrc_f(self, T=1, beta=0.8):213		out = []214		for f in np.linspace(-1 / (2.0 * T), 1 / (2.0 * T), num=5):215			if abs(f) <= (1 - beta) / float(2.0 * T):216				out.append(1.0)217			else:218				if (1 - beta) / float(2.0 * T) < abs(f) and abs(f) <= (1 + beta) / float(2.0 * T):219					v = 0.5 * (1 + np.cos(np.pi * T / float(beta) * (abs(f) - (1 - beta) / float(2.0 * T))))220					out.append(v)221				else:222					out.append(0)223		return out224	def get_freq_list(self,freq, N=1):225		ff = []226		for i in range(0, 56):227			# if m == 0 and max_exp == 0:228			#    m = 1229			if i < 28:230				fr = freq - (20.0 / 64) * (28 - i)231			else:232				fr = freq + (20.0 / 64) * (i - 27)233			ff.append(fr)234		fff = []235		#Overasmpling: unused if N=1236		for f in ff:237			for o in range(0, N):238				fff.append(f + o * (20.0 / 64 / N))239		return fff240	def get_spectrum_scan_features(self,filename="demo.tlv",T=100e3):241		skip = False242		thr_bw = 0.05243		thr_corr = 1e-10244		thr_corr_mean = 1245		P_thr_db = -75246		P_thr = 10 ** (P_thr_db / 10.0)247		dt_thr = 2600248		# OUTPUT FEATURES249		spectrum_features = []250		duration_features = []251		duration_energy_det_features = []252		measurements = self.extract_samples(filename, out_file="not-in-use.json",T=T)253		power_features=[]254		mark_as_failure = False255		csi_data = list(map(itemgetter('fft_sub'), measurements))256		csi_data = np.array(csi_data)257		freq = list(map(itemgetter('freq'), measurements))258		tsf = list(map(itemgetter('tsf'), measurements))259		freq = list(set(freq))260		freq = freq[0]261		ff = self.get_freq_list(freq)262		y = np.array(csi_data[0])263		y_ = y264		y_nofilt_ = y265		tt = tsf[0]266		tt_ = tt;267		PLOT = False268		if PLOT:269			fig = plt.figure();270			plt.ion()271			plt.show()272		start_corr = True273		corr_duration = 0;274		energy_det_duration = 0;275		t_corr_start = 0;276		t_energy_det_start = 0;277		y_cont=[]278		P_av_w=[]279		P_av_=0280		print("====================================");281		p_av_list = np.convolve(np.mean(csi_data, axis=1), np.array([1, 1, 1, 1])[::-1], 'same')282		for ii, cc in enumerate(csi_data):283			if ii==0:284				start_energy_det = True285				finish_energy_det = False286			skip = False287			yy = []288			start_f = []289			stop_f = []290			START_BW = True291			y_pow = []292			bw_meas = []293			freq_meas = []294			y = np.array(cc)295			tt = tsf[ii]296			dt = tt - tt_297			y_nofilt = y298			weights = self.rrc_f()299			#weights = [1, 1, 1]300			y = np.convolve(y, np.array(weights)[::-1], 'same')301			min_max_scaler = preprocessing.MinMaxScaler()302			y_det = min_max_scaler.fit_transform(y.reshape(-1, 1))303			y_det_ = min_max_scaler.fit_transform(y_.reshape(-1, 1))304			y_det_nofilt = min_max_scaler.fit_transform(y_nofilt.reshape(-1, 1))305			y_det_nofilt_ = min_max_scaler.fit_transform(y_nofilt_.reshape(-1, 1))306			y_det = y_det[:, 0]307			y_det_ = y_det_[:, 0]308			y_det_nofilt = y_det_nofilt[:, 0]309			y_det_nofilt_ = y_det_nofilt_[:, 0]310			P_av = np.mean(y)311			P_av_w = p_av_list[ii]312			power_features.append(313			{"tsf_p": tt, "p_av": P_av,"p_av_w": P_av_w})314			P_av=P_av_w315			# if len(P_av_w) >N_av: #window size = 5316			# 	P_av_w.pop(0) #window step=1317			# ENERGY DETECTION318			# if P_av_ < P_thr and P_av > P_thr and dt < dt_thr:319			# 	start_energy_det=True;320			# 	t_energy_det_start = tt321			# else:322			# 	if P_av_ > P_thr and P_av < P_thr and dt < dt_thr:323			# 		start_energy_det = False;324			# 		energy_det_duration = tt - t_energy_det_start325			# 		duration_energy_det_features.append(326			# 		 	{"tsf": t_energy_det_start, "duration": energy_det_duration})327			# 	else:328			if P_av >= P_thr and start_energy_det:329						t_energy_det_start = tt;330						print("start:{}",t_energy_det_start);331						start_energy_det = False332						mark_as_failure = False;333			if P_av <= P_thr and not start_energy_det:334						t_energy_det_stop = tt_;335						print("stop:{}", t_energy_det_stop);336						finish_energy_det = True337			if P_av >= P_thr and not start_energy_det:338				if ii < len(tsf)-1:339					if tsf[ii+1]-tsf[ii] > dt_thr:340						mark_as_failure=True341						print("[ii={}] failure dt={}".format(ii,tsf[ii+1]-tsf[ii]))342			if P_av <= P_thr and finish_energy_det:343				if not mark_as_failure:344					print(" [ OK ] finish:{}", t_energy_det_stop-t_energy_det_start);345				else:346					print(" [FAIL] finish:{}", t_energy_det_stop - t_energy_det_start);347				finish_energy_det=False348				start_energy_det=True349				if not mark_as_failure:350						# duration_energy_det_features.append(351						# {"tsf": t_energy_det_start, "duration": t_energy_det_stop-t_energy_det_start})352					duration_energy_det_features.append(353						{"tsf": t_energy_det_start, "tsf_stop": t_energy_det_stop, "duration": t_energy_det_stop - t_energy_det_start})354			print(dt)355			# else:356			# 	if start_energy_det == False:357			# 		energy_det_duration = tt - t_energy_det_start358			# 		start_energy_det = True359			# 		if energy_det_duration != 0:360			# 			if not mark_as_failure:361			# 				duration_energy_det_features.append(362			# 					{"tsf": t_energy_det_start, "duration": energy_det_duration})363			# 			else:364			# 				print("FAILED")365			# 				print({"tsf": t_energy_det_start, "duration": energy_det_duration})366			# 				mark_as_failure=False;367			# 		energy_det_duration = 0368			P_av_ = P_av369			#print(duration_energy_det_features)370			yy = y_det371			N_av = 10372			if len(y_cont) >= N_av:373				y_cont.pop(0)  # window step=1374			if P_av >= P_thr:375				# collect some consecutive samples and average it!376				y_cont.append(yy)377				yy = np.mean(y_cont, axis=0)378				if len(y_cont) == N_av:379					for i in range(0, len(yy)):380						#print(yy[i])381						if yy[i] > thr_bw and i < len(yy) - 1:382							y_pow.append(yy[i])383							if START_BW:384								# print "START"385								start_f.append(ff[i])386								START_BW = False387						else:388							if not START_BW:389								stop_f.append(ff[i - 1])390								START_BW = True391				for i in range(0, min(len(start_f), len(stop_f))):392					bw_meas.append(stop_f[i] - start_f[i] - 20/64.0)393					freq_meas.append((stop_f[i] + start_f[i]) / 2.0)394				# CORRELATION395				y_corr = np.correlate(y_det, y_det_, "same")396				# y_corr = np.correlate(y_det_nofilt, y_det_nofilt_, "same")397				if dt >= dt_thr:398					start_corr = True399					corr_duration = 0400				else:401					# if np.median(y_corr) <= thr_corr_mean and P_av >= P_thr:402					if np.median(y_corr) <= thr_corr_mean:403						if start_corr:404							t_corr_start = tt;405							start_corr = False406						else:407							corr_duration = tt - t_corr_start408					else:409						if start_corr == False:410							start_corr = True411							if corr_duration != 0:412								duration_features.append({"tsf": t_corr_start, "duration": corr_duration})413							corr_duration = 0414				spectrum_features.append({"tsf": tsf[ii], "bw": bw_meas, "freq": freq_meas})415			else:416				y_cont = []417			# update state variables, ready for next round418			tt_ = tt419			y_ = y420			y_nofilt_ = y_nofilt421			#if P_av <= P_thr:422			#	skip = True423			#else:424		return measurements, spectrum_features, duration_energy_det_features, duration_features,freq,power_features425	def plot_waterfall(self,ax,measurements,exp_name):426		csi_data = list(map(itemgetter('fft_sub'), measurements))427		timestamp = list(map(itemgetter('tsf'), measurements))428		freq = list(map(itemgetter('freq'), measurements))429		freq=list(set(freq))430		freq=freq[0]431		timestamp=np.array(timestamp)-timestamp[0]432		T=np.max(timestamp)433		N=len(timestamp)434		y=self.get_freq_list(freq)435		x=timestamp[0:N]436		Z=10.0 * np.log10(csi_data[0:N])437		X,Y = np.meshgrid(y,x)438		cc=ax.pcolormesh(X,Y,Z,vmin=-140, vmax=-20)439		fmin=min(y)440		fmax=max(y)441		ax.set_xlim([fmin,fmax])442		ax.set_ylim([0,T])443		ax.set_ylabel('Time [us]')444		ax.set_xlabel('freq [MHz]')445		ax.set_title(exp_name)446		return ax447	def get_freq_list(self,freq, N=1):448		ff = []449		for i in range(0, 56):450			# if m == 0 and max_exp == 0:451			#    m = 1452			if i < 28:453				fr = freq - (20.0 / 64) * (28 - i)454			else:455				fr = freq + (20.0 / 64) * (i - 27)456			ff.append(fr)457		fff = []458		for f in ff:459			for o in range(0, N):460				fff.append(f + o * (20.0 / 64 / N))461		return fff...

test_database.py

Source:test_database.py

...30        tid3 = uuid()31        try:32            raise KeyError('foo')33        except KeyError as exception:34            self.b.mark_as_failure(tid3, exception)35        assert self.b.get_status(tid3) == states.FAILURE36        assert isinstance(self.b.get_result(tid3), KeyError)37    def xxx_backend(self):38        tid = uuid()39        assert self.b.get_status(tid) == states.PENDING40        assert self.b.get_result(tid) is None41        self.b.mark_as_done(tid, 42)42        assert self.b.get_status(tid) == states.SUCCESS43        assert self.b.get_result(tid) == 4244        tid2 = uuid()45        try:46            raise KeyError('foo')47        except KeyError as exception:48            self.b.mark_as_failure(tid2, exception)49        assert self.b.get_status(tid2) == states.FAILURE50        assert isinstance(self.b.get_result(tid2), KeyError)51    def test_forget(self):52        tid = uuid()53        self.b.mark_as_done(tid, {'foo': 'bar'})54        x = self.app.AsyncResult(tid)55        assert x.result.get('foo') == 'bar'56        x.forget()57        if celery.VERSION[0:3] == (3, 1, 10):58            # bug in 3.1.10 means result did not clear cache after forget.59            x._cache = None...

Automation Testing Tutorials

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