def draw_Q(self, a, b, da):
t = Task1(a, b)
x1 = []
y1 = []
x2 = []
y2 = []
while a < b:
x1.append(a)
x2.append(a)
y1.append(t.calculate_q())
y2.append(t.calculate_qx())
a += da
t.reload(a, b)
gp.s([x1, y1], filename='tmp1.dat')
gp.s([x2, y2], filename='tmp2.dat')
gp.c('set xlabel "Значение а"')
gp.c('set ylabel "Значение функции"')
gp.c(
'set title "Графики зависимостей показателей Q и Q* от значений a"'
)
gp.c('set yrange [0:5]')
gp.c(
'plot "tmp1.dat" u 1:2 w i title "VarN(a)", "tmp2.dat" u 1:2 w i title "VarN*(a)"'
)
gp.pdf("Q.pdf")
def draw_D(self, a, b, da):
t = Task1(a, b)
x1 = []
y1 = []
x2 = []
y2 = []
while a < b:
x1.append(a)
x2.append(a)
y1.append(t.calculate_Dw())
y2.append(t.calculate_Dv())
a += da
t.reload(a, b)
gp.s([x1, y1], filename='tmp1.dat')
gp.s([x2, y2], filename='tmp2.dat')
gp.c('set xlabel "Значение а"')
gp.c('set ylabel "Значение функции"')
gp.c(
'set title "Графики зависимостей показателей Dw и Dv от значений a"'
)
gp.c('set yrange [0:5]')
gp.c(
'plot "tmp1.dat" u 1:2 w l title "Dw(a)", "tmp2.dat" u 1:2 w l title "Dv(a)"'
)
gp.pdf("D.pdf")
# g = Graphics()
# g.draw_D(0.1, 0.7, 0.001)
# t = Task1(0.3,0.4)
# print(t.calculate_VarN())
def plot_graphs_modes_markers(agreg_step):
'''Funkce vykreslí grafy podle dat ve vstupních souborech a uloží je ve formátu PDF do složky output/graphs'''
agreguj_data_rezie_modes_markers(agreg_step)
#priprav_data_pro_sloupcovy_graf_rezie_nizky_bitrate_modes_markers()
#priprav_data_pro_sloupcovy_graf_rezie_vysoky_bitrate_modes_markers()
'''# histogram rezie pro nizky bitrate
pg.c('set xlabel "ZABEZPEČENÍ"; set ylabel "REŽIE ZABEZPEČENÍ [ % ]"')
pg.c('unset key; set style data histogram; set style fill solid border; set style histogram clustered')
pg.c("plot for [COL=2:3] 'output/graphs_data/agreg/histogram_nizky_bitrate_rezie_modes_markers.dat' using COL:xticlabels(1) title columnheader")
pg.pdf('output/graphs/histogram_rezie_nizky_bitrate_modes_markers.pdf')
# histogram rezie pro vysoky bitrate
pg.c('set xlabel "ZABEZPEČENÍ"; set ylabel "REŽIE ZABEZPEČENÍ [ % ]"')
pg.c('unset key; set style data histogram; set style fill solid border; set style histogram clustered')
pg.c("plot for [COL=2:3] 'output/graphs_data/agreg/histogram_vysoky_bitrate_rezie_modes_markers.dat' using COL:xticlabels(1) title columnheader")
pg.pdf('output/graphs/histogram_rezie_vysoky_bitrate_modes_markers.pdf')'''
# Kolik % velikosti souboru zabírají markery v závislosti na bitrate
pg.c('set xlabel "BITRATE"; set ylabel "REŽIE ZABEZPEČENÍ [ % ]"')
pg.c('set yrange [0:65]; set xrange [0:2.5]; set key right top')
pg.c("plot '" + str(graphs_data_bitrate_rezie_sop_eph_agreg_filename) +
"' title 'SOP + EPH' with lines lw 3")
pg.c(
"replot '" +
str(graphs_data_bitrate_rezie_vsechny_mody_sop_eph_agreg_filename) +
"' title 'Líné paralelní zpracování + SEGMARK + SOP + EPH' with lines lw 3"
)
pg.pdf('output/graphs/bitrate_rezie_zabezpeceni_modes_markers.pdf')
agreguj_data_nedekomprimovatelnych_souboru(
graphs_data_failed_na_poskozeni_bez_ochrany_filename,
graphs_data_failed_na_poskozeni_bez_ochrany_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(
graphs_data_failed_na_poskozeni_vsechny_mody_sop_eph_filename,
graphs_data_failed_na_poskozeni_vsechny_mody_sop_eph_agreg_filename)
# Kolik % velikosti souboru zabírají markery v závislosti na bitrate a měnících se PRECINCTS a sop+eph pro layers=12
pg.c(
'set key right bottom; set xlabel "POŠKOZENÍ [ % ]"; set ylabel "POČET NEDEKOMPRIMOVATELNÝCH SOUBORŮ [ % ]"'
)
#pg.c('set yrange [0.5:1]; set xrange [0:0.1]; set key right')
pg.c('set yrange [0:100]; set xrange [-0.00005:0.0205]; set key right')
pg.c("plot '" + str(graphs_data_fails_mode_none_agreg_filename) +
"' title 'Bez ochrany' with lines lw 3")
pg.c("replot '" +
str(graphs_data_failed_na_poskozeni_sop_eph_agreg_filename) +
"' title 'SOP + EPH' with lines lw 3")
#pg.c("replot '" + str(graphs_data_failed_na_poskozeni_sop_eph_segmark_agreg_filename) + "' title 'SOP, EPH, SEGMARK' with lines linestyle 5")
pg.c("replot '" +
str(graphs_data_fails_mode_lazyparallelsegmark_agreg_filename) +
"' title 'Líné paralelní zpracování + SEGMARK' with lines lw 3")
pg.c(
"replot '" +
str(graphs_data_failed_na_poskozeni_vsechny_mody_sop_eph_agreg_filename
) +
"' title 'Líné paralelní zpracování + SEGMARK + SOP + EPH' with lines lw 3"
)
pg.pdf('output/graphs/poskozeni_neuspesne_soubory_modes_markers.pdf')
def plotSNfit(result, vc, pidx, digi='D1'):
''' result : fitting results
vc, variable carrier
pidx power index
digi = 'D1' or 'D2'
'''
vc.Tz = result.params['Tz'].value
if digi == 'D1':
f = vc.f1
T = result.params['T1'].value
G = result.params['G1'].value
Tn = result.params['Tn1'].value
data = np.array(vc.cPD1[pidx]) * 1.0
if digi == 'D2':
f = vc.f2
T = result.params['T2'].value
G = result.params['G2'].value
Tn = result.params['Tn2'].value
data = np.array(vc.cPD2[pidx]) * 1.0
if digi == 'D12':
f = vc.f1
T = result.params['T12'].value
G = result.params['G12'].value
Tn = result.params['Tn12'].value
data = np.array(vc.cPD3[pidx]) * 1.0
if digi == 'D12c':
f = vc.f1
T = result.params['T12c'].value
G = result.params['G12c'].value
Tn = result.params['Tn12c'].value
data = np.array(vc.cPD4[pidx]) * 1.0
factor = f*h*vc.B*G # factor to photon #
SNf = fitfunc(G, Tn, T, f, vc)
Amp = G*vc.B*kB*Tn
title2 = (digi + ', RF-Drive ' + str(vc.d2.lin[pidx]) + ' G ' + str(np.round(G/1e7, 2)) +
'e7 = ' + str(np.round(np.log10(G)*10.0, 2)) + 'dB T ' + str(np.round(Tn, 2)) + 'K')
dataname = digi + '_' + str(vc.d2.lin[pidx]) + '.dat'
gp.c('')
gp.figure()
# gp.c('clear')
gp.s([vc.I*1e6, (data)/factor, (SNf)/factor, np.ones_like(data)*Amp/factor],
filename=vc.resultfolder+dataname)
gp.c('set title "' + title2 + '"')
gp.c('set xrange[-19:19]')
gp.c('set key center top')
gp.c('plot "' + dataname + '" u 1:2 w l t "Data" ')
gp.c('replot "' + dataname + '" u 1:3 w l t "Fit" ')
gp.c('replot "' + dataname + '" u 1:4 w l t "Amplifier Noise" ')
gp.c('save "' + dataname[:-3] + 'gn"')
gp.pdf(dataname[:-3]+'pdf')
print dataname[:-3]+'pdf'
def plotData(self, xmin=0, xmax=0, filename=''):
if not xmin == xmax == 0:
gp.c("set xrange [%f:%f]" % (xmin, xmax))
gp.s(self.dataArray, "plot.dat")
gp.c("plot 'plot.dat' u 1:2 w lp t 'Data'")
if len(filename) > 0:
gp.pdf(filename)
def plot_graphs_modes(agreg_step):
'''Funkce vykreslí grafy podle dat ve vstupních souborech a uloží je ve formátu PDF do složky output/graphs'''
#agreguj_data_rezie_modu(agreg_step)
#priprav_data_pro_sloupcovy_graf_rezie_nizky_bitrate_modes()
#priprav_data_pro_sloupcovy_graf_rezie_vysoky_bitrate_modes()
'''# histogram rezie pro nizky bitrate
pg.c('set xlabel "ZABEZPEČENÍ"; set ylabel "REŽIE ZABEZPEČENÍ [ % ]"')
pg.c('unset key; set style data histogram; set style fill solid border; set style histogram clustered')
pg.c("plot for [COL=2:3] 'output/graphs_data/agreg/histogram_nizky_bitrate_rezie_modes.dat' using COL:xticlabels(1) title columnheader")
pg.pdf('output/graphs/histogram_rezie_nizky_bitrate_modes.pdf')
# histogram rezie pro vysoky bitrate
pg.c('set xlabel "ZABEZPEČENÍ"; set ylabel "REŽIE ZABEZPEČENÍ [ % ]"')
pg.c('unset key; set style data histogram; set style fill solid border; set style histogram clustered')
pg.c("plot for [COL=2:3] 'output/graphs_data/agreg/histogram_vysoky_bitrate_rezie_modes.dat' using COL:xticlabels(1) title columnheader")
pg.pdf('output/graphs/histogram_rezie_vysoky_bitrate_modes.pdf')'''
'''agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_all_filename, graphs_data_fails_mode_all_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_none_filename, graphs_data_fails_mode_none_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_bypass_filename, graphs_data_fails_mode_bypass_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_parallel_filename, graphs_data_fails_mode_parallel_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_lazyparallel_filename, graphs_data_fails_mode_lazyparallel_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_ertermsegmark_filename, graphs_data_fails_mode_ertermsegmark_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_segmark_filename, graphs_data_fails_mode_segmark_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_bypasssegmark_filename, graphs_data_fails_mode_bypasssegmark_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_parallelsegmark_filename, graphs_data_fails_mode_parallelsegmark_agreg_filename)
agreguj_data_nedekomprimovatelnych_souboru(graphs_data_fails_mode_lazyparallelsegmark_filename, graphs_data_fails_mode_lazyparallelsegmark_agreg_filename)'''
pg.c(
'set key right bottom; set xlabel "POŠKOZENÍ [ % ]"; set ylabel "POČET NEDEKOMPRIMOVATELNÝCH SOUBORŮ [ % ]"'
)
# pg.c('set yrange [0.5:1]; set xrange [0:0.1]; set key right')
pg.c('set yrange [0:100]; set xrange [-0.00005:0.0205]; set key right')
pg.c("plot '" + str(graphs_data_fails_mode_none_agreg_filename) +
"' title 'Žádný mód' with lines lw 3")
pg.c("replot '" + str(graphs_data_fails_mode_bypass_agreg_filename) +
"' title 'Liné zpracování' with lines lw 3")
pg.c("replot '" + str(graphs_data_fails_mode_parallel_agreg_filename) +
"' title 'Paralelní zpracování' with lines lw 3")
#pg.c("replot '" + str(graphs_data_fails_mode_lazyparallel_agreg_filename) + "' title 'Líné paralelní zpracování' with lines linestyle 4")
pg.c("replot '" +
str(graphs_data_fails_mode_ertermsegmark_agreg_filename) +
"' title 'ERTERM + SEGMARK' with lines lw 3")
#pg.c("replot '" + str(graphs_data_fails_mode_segmark_agreg_filename) + "' title 'SEGMARK' with lines linestyle 6")
#pg.c("replot '" + str(graphs_data_fails_mode_bypasssegmark_agreg_filename) + "' title 'BYPASS, SEGMARK' with lines linestyle 7")
#pg.c("replot '" + str(graphs_data_fails_mode_parallelsegmark_agreg_filename) + "' title 'Paralelní zpracování + SEGMARK' with lines linestyle 8")
pg.c("replot '" +
str(graphs_data_fails_mode_lazyparallelsegmark_agreg_filename) +
"' title 'Líné paralelní zpracování + SEGMARK' with lines lw 3")
#pg.c("replot '" + str(graphs_data_fails_mode_all_agreg_filename) + "' title 'Všechny módy' with lines linestyle 12")
pg.pdf('output/graphs/poskozeni_neuspesne_soubory_modes.pdf')
import numpy as np
import PyGnuplot as pg
x = np.arange(1000) / 20.0
y1 = x - 25
y2 = y1 * np.sin(x - 25)
pg.s([x, y1, y2], filename='example.out') # save data into a file t.out
pg.c('set title "example.pdf"; set xlabel "x-axis"; set ylabel "y-axis"')
pg.c('set yrange [-25:25]; set key center top')
pg.c("plot 'example.out' u 1:2 w l t 'y=x-25") # plot fist part
pg.c("replot 'example.out' u 1:3 w l t 'y=(x-25)*sin(x-25)'")
pg.c("replot 'example.out' u 1:(-$2) w l t 'y=25-x'")
pg.pdf('example.pdf') # export figure into a pdf file
def fitData(self, xmin: float, xmax: float, filename=""):
# fun right here
fitlog_del = open("fit.log", "w")
fitlog_del.close()
arrX = []
arrY = []
arrErrY = []
for i in range(len(self.dataArray[0])):
if xmin <= self.dataArray[0][i] <= xmax:
arrX.append(self.dataArray[0][i])
arrY.append(self.dataArray[1][i])
arrErrY.append(self.dataArray[2][i])
gp.s([arrX, arrY, arrErrY], "tmp.dat")
gp.c("m=%f" % self.mpar)
gp.c("b=%f" % self.bpar)
gp.c("f_reta(x)=m*x+b")
viaStr = "m, b, "
gaussStr = ""
paramNumber = 2
for i in range(len(self.Apars)):
gp.c("A%d=%f" % (i, self.Apars[i]))
gp.c("mu%d=%f" % (i, self.mupars[i]))
gp.c("sig%d=%f" % (i, self.sigpars[i]))
if i != 0:
gaussStr += "+"
viaStr += ", "
gaussStr += "A%d/(sqrt(2*pi)*sig%d) * exp( -0.5*((x-mu%d)/sig%d)**2)" % (
i, i, i, i)
viaStr += "A%d, mu%d, sig%d" % (i, i, i)
paramNumber += 3
gp.c("ftot(x)=" + gaussStr + "+m*x+b")
gp.c("fit ftot(x) 'tmp.dat' u 1:2:3 yerrors via " + viaStr)
gp.c(
"plot 'tmp.dat' u 1:2:3 w yerrorbars t 'Data', ftot(x) t 'f({/Symbol b})'"
)
if len(filename) != 0:
gp.pdf(filename)
time.sleep(0.1) # needed to create the fit.log file in time
# then view file fit.log to get parameters
fitlog = open("fit.log", "r")
fileLines = fitlog.readlines()
fitlog.close()
if len(fileLines) == 0:
time.sleep(0.3)
fitlog = open("fit.log", "r")
fileLines = fitlog.readlines()
fitlog.close()
chi2 = 0
paramspos = 0
paramStr = []
paramVal = []
paramErr = []
for i in range(len(fileLines)):
if "(reduced chisquare) = WSSR/ndf" in fileLines[i]:
chi2 = float(fileLines[i].split(" : ")[1])
if "Final set of parameters" in fileLines[i]:
paramspos = i
if paramspos != 0 and paramspos + 1 < i < paramspos + 2 + paramNumber:
paramStr.append(fileLines[i].split(" ")[0])
pars = fileLines[i].split(" = ")[1]
paramVal.append(float(pars.split()[0]))
paramErr.append(float(pars.split(" +/- ")[1].split()[0]))
# print("chi2: ", chi2)
# for i in range(len(paramStr)):
# print(paramStr[i], paramVal[i], paramErr[i])
return [chi2, paramStr, paramVal, paramErr]