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')
# trim by relative intensity
pl = rel_threshold(peak_list, r)
# trim by threshold
new_peak_list = num_ions_threshold(pl, n, t)
print "Number of filtered peaks: ", len(new_peak_list)
# TIC from raw data
tic = data.get_tic()
# save TIC to a file
# Get Ion Chromatograms for all m/z channels
n_mz = len(im.get_mass_list())
ic = []
# All plotting from here on
for m in range(n_mz):
ic.append(im.get_ic_at_index(m))
# Create a new display object, this time plot the ICs
# and the TIC, as well as the peak list
display = Display()
display.plot_tic(tic, 'TIC')
display.plot_ics(ic)
display.plot_peaks(new_peak_list, 'PyMS peaks')
display.do_plotting()
# trim by threshold
new_peak_list = num_ions_threshold(pl, n, t)
print "Number of filtered peaks: ", len(new_peak_list)
# TIC from raw data
tic = data.get_tic()
# save TIC to a file
# Get Ion Chromatograms for all m/z channels
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 the ICs
# and the TIC, as well as the peak list
display = Display()
display.plot_tic(tic, 'TIC')
display.plot_ics(ic)
display.plot_peaks(new_peak_list, 'Peaks')
display.do_plotting('TIC, and PyMS Detected Peaks')
ic_smooth2 = savitzky_golay(ic_smooth1)
ic_bc = tophat(ic_smooth1, struct="1.5m")
sim_im.set_ic_at_index(ii, ic_bc)
### Now detect peaks in the noisy simulated IntensityMatrix
pre_peak_list = BillerBiemann(sim_im, points=3, scans=2)
print "Number of peaks found in simulated data", len(pre_peak_list)
### Filter this peak list as for real_im
r = 1
# minimum number of ions, n
n = 3
# greater than or equal to threshold, t
t = 10000
# trim by relative intensity
spl = rel_threshold(pre_peak_list, r)
# trim by threshold
sim_peak_list = num_ions_threshold(spl, n, t)
print "Number of filtered peaks in simulated data", len(sim_peak_list)
### Now display the ics and the filtered peak list 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.plot_peaks(sim_peak_list, 'Peaks')
display.do_plotting('ICs, and PyMS Detected Peaks of Simulated Data')
