n_scan, n_mz = im.get_size()
for ii in range(n_mz):
ic = im.get_ic_at_index(ii)
ic_smooth = savitzky_golay(ic)
ic_base = tophat(ic_smooth, struct="1.5m")
im.set_ic_at_index(ii, ic_base)
# Load the experiment
exper = load_expr(expr_file)
# Load the peak list
peak_list = exper.get_peak_list()
# Pass Ion Chromatograms into a list of ICs
n_mz = len(im.get_mass_list())
ic = []
for m in range(n_mz):
ic.append(im.get_ic_at_index(m))
# Create a new display object, this time plot four ICs
# and the TIC, as well as the peak list
display = Display()
display.plot_ics(ic)
display.plot_peaks(peak_list, 'Peaks')
display.do_plotting('ICs, and PyMS Detected Peaks')
area = peak_sum_area(real_im, peak)
peak.set_area(area)
# real_peak_list is PyMS' best guess at the true peak list
################## Run Simulator ######################
# Simulator takes a peak list, time_list and mass_list
# and returns an IntensityMatrix object.
# The mass_list and time_list are the same for the real
# data and the simulated data.
time_list = real_im.get_time_list()
mass_list = real_im.get_mass_list()
sim_im = gcms_sim(time_list, mass_list, real_peak_list)
# sim_im is an IntensityMatrix object
# Now add noise to the simulated intensity matrix object
scale = 1000
add_gaussc_noise(sim_im, scale)
### Now display the ics from the simulated data
ics = []
for i in range(n_mz):
ics.append(sim_im.get_ic_at_index(i))
display = Display()
display.plot_ics(ics)
display.do_plotting(
'ICs of Simulated Data with gaussian noise (constant scale)')
peak.set_area(area)
# real_peak_list is PyMS' best guess at the true peak list
################## Run Simulator ######################
# Simulator takes a peak list, time_list and mass_list
# and returns an IntensityMatrix object.
# The mass_list and time_list are the same for the real
# data and the simulated data.
time_list = real_im.get_time_list()
mass_list = real_im.get_mass_list()
sim_im = gcms_sim(time_list, mass_list, real_peak_list)
# sim_im is an IntensityMatrix object
# select one ic to add noise to from this simulated intensity matrix
ic = sim_im.get_ic_at_mass(73)
ic_add_noise = copy.deepcopy(ic)
# Now add noise to the simulated intensity matrix object
scale = 1000
add_gaussc_noise_ic(ic_add_noise, scale)
display = Display()
display.plot_ics([ic, ic_add_noise], ['Without noise', 'With noise added'])
display.do_plotting('Simulated IC for m/z = 73, with and without noise')
area = peak_sum_area(real_im, peak)
peak.set_area(area)
# real_peak_list is PyMS' best guess at the true peak list
################## Run Simulator ######################
# Simulator takes a peak list, time_list and mass_list
# and returns an IntensityMatrix object.
# The mass_list and time_list are the same for the real
# data and the simulated data.
time_list = real_im.get_time_list()
mass_list = real_im.get_mass_list()
sim_im = gcms_sim(time_list, mass_list, real_peak_list)
# sim_im is an IntensityMatrix object
# select one ic to add noise to from this simulated intensity matrix
ic = sim_im.get_ic_at_mass(73)
ic_add_noise = copy.deepcopy(ic)
# Now add noise to the simulated intensity matrix object
scale = 1000
add_gaussc_noise_ic(ic_add_noise, scale)
display = Display()
display.plot_ics([ic, ic_add_noise], ['Without noise', 'With noise added'])
display.do_plotting('Simulated IC for m/z = 73, with and without noise')
#
# IonChromatogram
#
# TIC from raw data
tic = data.get_tic()
# save TIC to a file
# Get Ion Chromatograms for 4 separate m/z channels
ic = im.get_ic_at_mass(191)
ic1 = im.get_ic_at_mass(73)
ic2 = im.get_ic_at_mass(57)
ic3 = im.get_ic_at_mass(55)
# create a list of ICs for passing to plot_ics()
ics = [ic, ic1, ic2, ic3]
# load list of peaks
# NB NB NB NB You must first run proc_save_peaks.py from
# this directory to generate the peak list
peak_list = load_peaks("output/peaks.bin")
# Create a new display object, this time plot four ICs
# and the TIC, as well as the peak list
display = Display()
display.plot_tic(tic, 'TIC')
display.plot_ics(ics, ['191', '73', '57', '55'])
display.plot_peaks(peak_list, 'Peaks')
display.do_plotting('TIC, ICs, and PyMS Detected Peaks')
# IonChromatogram
#
# TIC from raw data
tic = data.get_tic()
# save TIC to a file
# Get Ion Chromatograms for 4 separate m/z channels
ic = im.get_ic_at_mass(191)
ic1 = im.get_ic_at_mass(73)
ic2 = im.get_ic_at_mass(57)
ic3 = im.get_ic_at_mass(55)
# create a list of ICs for passing to plot_ics()
ics = [ic, ic1, ic2, ic3]
# load list of peaks
# NB NB NB NB You must first run proc_save_peaks.py from
# this directory to generate the peak list
peak_list = load_peaks("output/peaks.bin")
# Create a new display object, this time plot four ICs
# and the TIC, as well as the peak list
display = Display()
display.plot_tic(tic, 'TIC')
display.plot_ics(ics, ['191','73','57','55'])
display.plot_peaks(peak_list, 'Peaks')
display.do_plotting('TIC, ICs, and PyMS Detected Peaks')
