def main():
# Input asp-style ascii profile will be first argument.
# (command-line options to come later)
prof_file = argv[1]
# First, read in profile data file, and assign each column to a separate
# numpy array
prof_data = read_asc_prof(prof_file, ionly=True)
# print res_data['mjd']
# meaningThe following means that the 2nd argument is the
# desired output plot file name
if (len(argv) > 2):
plot_file = argv[2]
else:
plot_file = 'profile.png'
plot_prof(prof_data) #, hgrid=True, vgrid=True)
# plt.show()
plt.savefig(plot_file)
def main():
# Input asp-style ascii profile will be first argument.
# (command-line options to come later)
prog_name = argv[0].strip(".py")
# Scale factor for plotting difference plots
scale = 2.0
# ref_file = argv[len(argv)-1]
ref_file = argv[1]
# arg = get_opt(prog_name)
print "n_args = ", len(argv) - 1
# prof_file = argv[1]
input_files = []
for file in argv[1:]:
# For some reason this works and ".appen()" doesn't:
input_files[len(input_files) :] = glob.glob(file)
# input_files.append(glob.glob(file))
input_files.reverse()
if input_files.count(ref_file) > 0:
input_files.remove(ref_file)
# First, read in profile data file, and assign each column to a separate
# numpy array
# prof_file = input_files[0]
# prof_header = read_asc_header(prof_file)
# prof_data[0] = read_asc_prof(prof_file)
ref_header = read_asc_header(ref_file)
ref_data = read_asc_prof(ref_file)
# ref_data['i'] = norm(ref_data['i'], duty)
# if(len(input_files) > 1):
# for prof_file in input_files:
prof_data = []
date_text = []
nobs = []
for i_prof in np.arange(len(input_files)):
prof_header = read_asc_header(input_files[i_prof])
duty = get_duty(prof_header["psrname"])
nobs.append(prof_header["obscode"])
print "NOBS = ", nobs
prof_data_temp = read_asc_prof(input_files[i_prof])
# prof_data_temp['i'] = norm(prof_data_temp['i'], duty)
# prof_data_temp['i'] = prof_data_temp['i'] + i_prof
diff_prof = remove_base((prof_data_temp["i"] - ref_data["i"]), duty)
prof_data_temp["i"] = scale * (diff_prof) + i_prof + 1.2
print "Index = ", i_prof, ", Min = ", np.min(prof_data_temp["i"]), ", Max = ", np.max(prof_data_temp["i"])
prof_data.append(prof_data_temp)
# Set up labelling for each profile:
prof_date = mjd.mjdtodate(prof_header["imjd"], dateformat="%Y %b %d")
date_text.append((0.8, i_prof + 0.25, prof_date))
print "Date = ", date_text
# Make first prof in list for plot to be the ref profile
prof_data.append(ref_data)
ref_date = mjd.mjdtodate(ref_header["imjd"], dateformat="%Y %b %d")
date_text.append((0.5, 0.20, ref_date))
nobs.append(ref_header["obscode"])
nobs_unique = list(set(nobs))
clr = []
for i_nobs in range(len(nobs)):
if nobs_unique <= 1:
clr.append("black")
else:
clr.append(cm.gist_heat(float(nobs_unique.index(nobs[i_nobs])) / float(len(nobs_unique))))
# Do this just to make the ordering such that the first alphanumerically
# is at the top...
# prof_data.reverse()
# date_text.reverse()
print "LENGTH of PROF DATA = ", len(prof_data)
print "LENGTH of colour = ", len(clr)
plot_prof(
prof_data,
yticks=False,
canvassize=(8, 10),
hgrid=False,
vgrid=False,
ylim=(np.min(prof_data[0]["i"]) - 0.1, len(input_files) + 0.1 + 1.0),
figtext=date_text,
linecolour=clr,
)
# meaningThe following means that the 2nd argument is the
# desired output plot file name
# plot_file = 'multi_profile.png'
plot_file = "diff_profile.pdf"
# plt.show()
plt.savefig(plot_file)
def main():
# Input asp-style ascii profile will be first argument.
# (command-line options to come later)
prog_name = argv[0].strip('.py')
# arg = get_opt(prog_name)
# prof_file = argv[1]
input_files = []
for file in argv[1:]:
# For some reason this works and ".appen()" doesn't:
input_files[len(input_files):] = glob.glob(file)
# input_files.append(glob.glob(file))
input_files.reverse()
prof_data = []
# prof_date = []
date_text = []
# First, read in profile data file, and assign each column to a separate
# numpy array
# prof_file = input_files[0]
# prof_header = read_asc_header(prof_file)
# prof_data[0] = read_asc_prof(prof_file)
duty = get_duty('0737-3039A')
# if(len(input_files) > 1):
# for prof_file in input_files:
for i_prof in np.arange(len(input_files)):
prof_header = read_asc_header(input_files[i_prof])
prof_data_temp = read_asc_prof(input_files[i_prof])
prof_data_temp['i'] = norm(prof_data_temp['i'], duty)
prof_data_temp['i'] = prof_data_temp['i'] + i_prof
print "Index = ", i_prof, \
", Min = ", np.min(prof_data_temp['i']), \
", Max = ", np.max(prof_data_temp['i'])
prof_data.append(prof_data_temp)
# Set up labelling for each profile:
prof_date = mjd.mjdtodate(prof_header['imjd'], \
dateformat='%Y %b %d')
date_text.append((0.5, i_prof+0.16, prof_date))
print "Date = ", date_text
# Do this just to make the ordering such that the first alphanumerically
# is at the top...
# prof_data.reverse()
# date_text.reverse()
plot_prof(prof_data, yticks=False, canvassize=(8,10), \
hgrid=False, vgrid=False, \
ylim=(np.min(prof_data[0]['i'])-0.1, len(input_files)+0.1), \
figtext=date_text)
# meaningThe following means that the 2nd argument is the
# desired output plot file name
# plot_file = 'multi_profile.png'
plot_file = 'multi_profile.eps'
plt.savefig(plot_file)
def main():
# Input asp-style ascii profile will be first argument.
# (command-line options to come later)
prog_name = argv[0].strip('.py')
# Scale factor for plotting difference plots
scale = 2.0
# arg = get_opt(prog_name)
# prof_file = argv[1]
# ref_file = argv[1]
ref_file = argv[len(argv)-1]
input_files = []
for file in argv[1:]:
# For some reason this works and ".append()" doesn't:
input_files[len(input_files):] = glob.glob(file)
# input_files.append(glob.glob(file))
input_files.reverse()
# Remove reference file from list if it is in the plotting list
if(input_files.count(ref_file) > 0):
input_files.remove(ref_file)
duty = get_duty('0737-3039A')
# Read in reference profile
ref_header = read_asc_header(ref_file)
ref_data = read_asc_prof(ref_file)
# ref_data['i'] = norm(ref_data['i'], duty)
# Make first prof in list for plot to be the ref profile
prof_data = [ref_data]
ref_date = mjd.mjdtodate(ref_header['imjd'], \
dateformat='%Y %b %d')
date_text = [(0.5, 0.20, ref_date)]
nobs = []
# Now calculate difference profiles and append to plotting list
for i_prof in np.arange(len(input_files)):
prof_header = read_asc_header(input_files[i_prof])
nobs.append(prof_header['obscode'])
print 'NOBS = ', nobs
prof_data_temp = read_asc_prof(input_files[i_prof])
# prof_data_temp['i'] = norm(prof_data_temp['i'], duty)
diff_prof = remove_base((prof_data_temp['i'] - ref_data['i']), duty)
prof_data_temp['i'] = scale*(diff_prof) + i_prof + 1.2
print "Index = ", i_prof
prof_data.append(prof_data_temp)
# Set up labelling for each profile:
prof_date = mjd.mjdtodate(prof_header['imjd'], \
dateformat='%Y %b %d')
date_text.append((0.5, i_prof+1.4+scale*0.02, prof_date))
print "Date = ", date_text
nobs_unique = list(set(nobs))
clr=[]
for i_nobs in range(len(nobs)):
if(nobs_unique <= 1):
clr.append('black')
else:
clr.append(cm.gist_heat(float(nobs_unique.index(nobs[i_nobs]))/float(len(nobs_unique))))
# Do this just to make the ordering such that the first alphanumerically
# is at the top...
# prof_data.reverse()
# date_text.reverse()
plot_prof(prof_data, yticks=False, canvassize=(8,10), vgrid=False, \
ylim=(np.min(prof_data[0]['i'])-0.1, len(input_files)+1 +0.1), \
figtext=date_text, linecolour=clr)
# meaningThe following means that the 2nd argument is the
# desired output plot file name
# plot_file = 'diff_profile.png'
plot_file = 'diff_profile.pdf'
plt.savefig(plot_file)
def main():
# Input asp-style ascii profile will be first argument.
# (command-line options to come later)
prog_name = argv[0].strip('.py')
# arg = get_opt(prog_name)
print 'n_args = ', len(argv) - 1
# prof_file = argv[1]
input_files = []
for file in argv[1:]:
# For some reason this works and ".appen()" doesn't:
input_files[len(input_files):] = glob.glob(file)
# input_files.append(glob.glob(file))
input_files.reverse()
prof_data = []
# prof_date = []
date_text = []
# First, read in profile data file, and assign each column to a separate
# numpy array
# prof_file = input_files[0]
# prof_header = read_asc_header(prof_file)
# prof_data[0] = read_asc_prof(prof_file)
# if(len(input_files) > 1):
# for prof_file in input_files:
nobs = []
for i_prof in np.arange(len(input_files)):
prof_header = read_asc_header(input_files[i_prof])
duty = get_duty(prof_header['psrname'])
nobs.append(prof_header['obscode'])
print 'NOBS = ', nobs
prof_data_temp = read_asc_prof(input_files[i_prof], ionly=True)
prof_data_temp['i'] = norm(prof_data_temp['i'], duty)
prof_data_temp['i'] = prof_data_temp['i'] + i_prof
print "Index = ", i_prof, \
", Min = ", np.min(prof_data_temp['i']), \
", Max = ", np.max(prof_data_temp['i'])
prof_data.append(prof_data_temp)
# Set up labelling for each profile:
prof_date = mjd.mjdtodate(prof_header['imjd'], \
dateformat='%Y %b %d')
date_text.append((0.8, i_prof+0.25, prof_date))
print "Date = ", date_text
nobs_unique = list(set(nobs))
clr=[]
for i_nobs in range(len(nobs)):
if(nobs_unique <= 1):
clr.append('black')
else:
clr.append(cm.gist_heat(float(nobs_unique.index(nobs[i_nobs]))/float(len(nobs_unique))))
# Do this just to make the ordering such that the first alphanumerically
# is at the top...
# prof_data.reverse()
# date_text.reverse()
plot_prof(prof_data, yticks=False, canvassize=(8,10), \
hgrid=False, vgrid=False, \
ylim=(np.min(prof_data[0]['i'])-0.1, len(input_files)+0.1),
figtext=date_text, linecolour=clr)
# meaningThe following means that the 2nd argument is the
# desired output plot file name
# plot_file = 'multi_profile.png'
plot_file = 'multi_profile.png'
# plt.show()
plt.savefig(plot_file)
