def plot_data_with_matplotlib(spec):
start_time = time.time()
hitnum = int(s6fits.get_hits_over_file(spec.filename))
end_time = time.time()
print("get hit num time was %g seconds" % (end_time - start_time))
snr = spec.s6hits[0].detected_power / spec.s6hits[0].mean_power
x = np.array([snr])
start_time = time.time()
for i in range(1, hitnum - 1):
snr = spec.s6hits[i].detected_power / spec.s6hits[i].mean_power
x = np.append(x, snr)
#print("SNR %f" % (snr))
#print("det %s" % (spec.s6hits[i].detected_power))
end_time = time.time()
print("make snr array was %g seconds" % (end_time - start_time))
#plt.plot(y,x,marker='.',)
start_time = time.time()
plt.hist(x, bins=1000)
end_time = time.time()
print("make plot was %g seconds" % (end_time - start_time))
plt.xticks(np.arange(min(x), max(x) + 1, 10, dtype=int))
start_time = time.time()
plt.show()
end_time = time.time()
print("show plot was %g seconds" % (end_time - start_time))
def load_file(filename):
spec = s6fits.s6dataspec_t()
spec.filename = filename
spec.sortby_rfreq = 0
spec.sortby_time = 0
spec.sortby_bors = 0
#spec.sortby_ifreq = 0
# Setting up this mode will remove all those hits which shows change of RF due to
# smart frequency switching experiment. It only reads those hits which occur maximum number of time.
spec.filterby_rf_center_mode = 1
#Get hits from file
s6fits.get_s6data(spec)
hitnum = int(s6fits.get_hits_over_file(spec.filename))
m_rfreq = []
m_unix_time = []
m_meanpower = []
base_filename = ntpath.basename(spec.filename)
start_time = spec.s6hits[0].unix_time
#MARK for i in range(0,hitnum-1):
for i in range(hitnum):
if spec.s6hits[i].unix_time == start_time:
m_rfreq.append(spec.s6hits[i].rfreq)
m_unix_time.append(spec.s6hits[i].unix_time)
m_meanpower.append(spec.s6hits[i].mean_power)
else:
break
sort_rfreq_index = np.argsort(m_rfreq)
sort_rfreq = np.array(m_rfreq)[sort_rfreq_index]
sort_meanpower = np.array(m_meanpower)[sort_rfreq_index]
return sort_meanpower, sort_rfreq, base_filename
def plot_data_with_matplotlib(spec):
start_time = time.time()
hitnum = int(s6fits.get_hits_over_file(spec.filename))
end_time = time.time()
print("get hit num time was %g seconds" % (end_time - start_time))
m_ifreq = [] # new
m_unix_time = [] # new
m_meanpower = [] # new
start_time = time.time()
starttime = spec.s6hits[0].unix_time
for i in range(0, hitnum - 1):
if spec.s6hits[i].unix_time == starttime:
m_ifreq.append(spec.s6hits[i].ifreq)
m_meanpower.append(spec.s6hits[i].mean_power)
m_unix_time.append(spec.s6hits[i].unix_time)
else:
break
sort_ifreq_index = np.argsort(m_ifreq)
sort_ifreq = np.array(m_ifreq)[sort_ifreq_index]
sort_meanpower = np.array(m_meanpower)[sort_ifreq_index]
#unique_unix_time, unique_index = np.unique(m_unix_time, return_index=True)
#unique_ifreq = np.array(m_ifreq)[unique_index]
#unique_meanpower = np.array(m_meanpower)[unique_index]
#unique_ifreq_index = np.argsort(unique_ifreq)
#sort_unique_ifreq = np.array(unique_ifreq)[unique_ifreq_index]
#sort_unique_meanpower = np.array(unique_meanpower)[unique_ifreq_index]
end_time = time.time()
print("make snr array was %g seconds" % (end_time - start_time))
#plt.plot(unix_time, ifreq,marker='.-',)
start_time = time.time()
#df.plot(kind='line',x="unix_time", y="ifreq")
#plt.plot(unique_unix_time, unique_ifreq, '.-')
plt.plot(sort_ifreq, sort_meanpower, '.-')
plt.xlabel('ifreq')
plt.ylabel('mean power')
end_time = time.time()
print("make plot was %g seconds" % (end_time - start_time))
# plt.xticks(np.arange(min(x), max(x)+1, 10, dtype=int))
start_time = time.time()
plt.show()
end_time = time.time()
print("show plot was %g seconds" % (end_time - start_time))
def plot_data_with_gnuplot(spec):
#flen = float(s6fits.get_time_over_file(spec.filename))
hitnum = int(s6fits.get_hits_over_file(spec.filename))
base_filename = ntpath.basename(spec.filename)
data_filename = base_filename + ".mp_data"
plot_filename = base_filename + ".mp.png"
m_unix_time = []
m_meanpower = []
time_value = []
j = 0
meanpower = 0
start_time = long(spec.s6hits[0].unix_time)
start_time = int(spec.s6hits[0].unix_time)
for i in range(0, hitnum - 1):
if spec.s6hits[i].unix_time != start_time:
m_unix_time.append(start_time)
m_meanpower.append(math.log(meanpower / j))
start_time = spec.s6hits[i].unix_time
j = 0
meanpower = 0
meanpower += spec.s6hits[i].mean_power
j += 1
m_unix_time = np.array(m_unix_time)
plot_time = np.arange(len(m_unix_time))
sort_meanpower = np.array(m_meanpower)
data_f = open(data_filename, 'w')
for x in range(0, len(m_unix_time) - 1):
#print >> data_f, sort_meanpower[x], m_unix_time[x]
print >> data_f, sort_meanpower[x], plot_time[x]
data_f.close()
cmd = 'set term png; set out "%s"; \
set title "%s"; unset key; \
set xl "time/s"; set yl "Mean Power/log"; \
plot "%s" using 2:1 with line;' \
% (plot_filename, base_filename, data_filename)
cmd_f = open("baseband_gnuplot_cmds", 'w')
print >> cmd_f, cmd
cmd_f.close()
os.system('gnuplot baseband_gnuplot_cmds')
os.remove("baseband_gnuplot_cmds")
os.remove(data_filename)
def plot_data_with_gnuplot(spec):
##hitrec = spec.s6hits
##s6fits.print_hits_table(spec.s6hits)
#spechdr = spec.s6hitsheaders
#print spec.total_missedpk
#print spec.rf_center_mode,spec.filter_rf_center_mode,spec.cfitsio_error
os.system('gnuplot pow_gnuplot_cmds')
flen = float(s6fits.get_time_over_file(spec.filename))
hitnum = int(s6fits.get_hits_over_file(spec.filename))
base_filename = ntpath.basename(spec.filename)
data_filename = base_filename + ".pow_data"
plot_filename = base_filename + ".pow.png"
histo = [0] * 100
data_f = open(data_filename, 'w')
for i in range(1, hitnum - 1):
snr = spec.s6hits[i].detected_power / spec.s6hits[i].mean_power
print >> data_f, snr
# see http://psy.swansea.ac.uk/staff/carter/gnuplot/gnuplot_frequency.htm
cmd = 'set term png; set out "%s"; \
set boxwidth 0.05 absolute ; set style fill solid 1.0 noborder; \
set title "%s"; unset key; set logscale x; \
set xl "SNR"; set yl "number of hits"; \
\
bin_width = 0.1; bin_number(x) = floor(x/bin_width); \
rounded(x) = bin_width * ( bin_number(x) + 0.5 ); \
\
plot "%s" using (rounded($1)):(1) smooth frequency with boxes;' \
% (plot_filename, base_filename, data_filename)
cmd_f = open("pow_gnuplot_cmds", 'w')
print >> cmd_f, cmd
cmd_f.close()
os.system('gnuplot pow_gnuplot_cmds')
os.remove("pow_gnuplot_cmds")
os.remove(data_filename)
print flen, hitnum
def plot_data_with_gnuplot(spec):
#flen = float(s6fits.get_time_over_file(spec.filename))
hitnum = int(s6fits.get_hits_over_file(spec.filename))
base_filename = ntpath.basename(spec.filename)
data_filename = base_filename + ".bb_data"
plot_filename = base_filename + ".bb.png"
m_ifreq = []
m_unix_time = []
m_meanpower = []
start_time = spec.s6hits[0].unix_time
for i in range(0, hitnum - 1):
if spec.s6hits[i].unix_time == start_time:
m_ifreq.append(spec.s6hits[i].ifreq)
m_unix_time.append(spec.s6hits[i].unix_time)
m_meanpower.append(spec.s6hits[i].mean_power)
else:
break
sort_ifreq_index = np.argsort(m_ifreq)
sort_ifreq = np.array(m_ifreq)[sort_ifreq_index]
sort_meanpower = np.array(m_meanpower)[sort_ifreq_index]
data_f = open(data_filename, 'w')
for x in range(0, len(m_ifreq) - 1):
print >> data_f, sort_meanpower[x], sort_ifreq[x]
data_f.close()
cmd = 'set term png; set out "%s"; \
set title "%s"; unset key; \
set xl "ifreq"; set yl "Mean Power"; \
plot "%s" using 2:1 with line;' \
% (plot_filename, base_filename, data_filename)
cmd_f = open("baseband_gnuplot_cmds", 'w')
print >> cmd_f, cmd
cmd_f.close()
os.system('gnuplot baseband_gnuplot_cmds')
os.remove("baseband_gnuplot_cmds")
os.remove(data_filename)
def plot_data_with_matplotlib(spec):
start_time = time.time()
hitnum = int(s6fits.get_hits_over_file(spec.filename))
end_time = time.time()
print("get hit num time was %g seconds" % (end_time - start_time))
start_time = time.time()
z = np.dtype(spec.s6hits[0])
z.names
end_time = time.time()
print("make freq array one line was %g seconds" % (end_time - start_time))
hit_start_time = spec.s6hits[0].unix_time
#print("start time %s" % (hit_start_time))
x = np.array([spec.s6hits[0].unix_time - hit_start_time])
start_time = time.time()
for i in range(1, hitnum - 1):
x = np.append(x, [spec.s6hits[i].unix_time - hit_start_time])
#print("time %s x %s" % (spec.s6hits[i].unix_time, x))
end_time = time.time()
print("make time array was %g seconds" % (end_time - start_time))
start_time = time.time()
y = np.array([spec.s6hits[0].ifreq])
for i in range(1, hitnum - 1):
y = np.append(y, [spec.s6hits[i].ifreq])
#print("ifreq %s" % (spec.s6hits[i].ifreq))
end_time = time.time()
print("make freq array was %g seconds" % (end_time - start_time))
#plt.plot(y,x,marker='.',)
start_time = time.time()
plt.scatter(y, x, s=.1)
end_time = time.time()
print("make plot was %g seconds" % (end_time - start_time))
start_time = time.time()
plt.show()
end_time = time.time()
print("show plot was %g seconds" % (end_time - start_time))
print flen, hitnum
def plot_data_with_gnuplot(spec):
##hitrec = spec.s6hits
##s6fits.print_hits_table(spec.s6hits)
#spechdr = spec.s6hitsheaders
#print spec.total_missedpk
#print spec.rf_center_mode,spec.filter_rf_center_mode,spec.cfitsio_error
#print spec.s6hits[0].unix_time, spec.s6hits[1].unix_time
flen = float(s6fits.get_time_over_file(spec.filename))
hitnum = int(s6fits.get_hits_over_file(spec.filename))
base_filename = ntpath.basename(spec.filename)
data_filename = base_filename + ".wf_data"
plot_filename = base_filename + ".wf.png"
data_f = open(data_filename, 'w')
start_time = spec.s6hits[0].unix_time
start_jtime = spec.s6hits[0].julian_date
for x in range(0, hitnum - 1):
#print >> data_f, spec.s6hits[x].unix_time - start_time, spec.s6hits[x].ifreq
print >> data_f, int((spec.s6hits[x].julian_date - start_jtime) *
86400), spec.s6hits[x].rfreq
data_f.close()
cmd = 'set term png; set out "%s"; \
set title "%s"; unset key; \
set xl "Freq (MHz)"; set yl "Time (Sec)"; \
plot "%s" using 2:1 with dots;' \
% (plot_filename, base_filename, data_filename)
cmd_f = open("wf_gnuplot_cmds", 'w')
print >> cmd_f, cmd
cmd_f.close()
os.system('gnuplot wf_gnuplot_cmds')
os.remove("wf_gnuplot_cmds")
os.remove(data_filename)
print flen, hitnum