print("Number of filtered peaks: ", len(new_peak_list))
# Creating the plot proceeds much as before, except that
# `ClickEventHandler(peak_list=new_peak_list)` must be called before `plt.show()`.
#
# You should also assign this to a variable to prevent it being garbage collected.
# In[6]:
# 3rd party
from pyms.Display import ClickEventHandler
fig, ax = plt.subplots(1, 1, figsize=(8, 5))
# Plot the TIC
plot_ic(ax, tic, label="TIC")
# Plot the peaks
plot_peaks(ax, new_peak_list)
# Set the title
ax.set_title("TIC for gc01_0812_066 with Detected Peaks")
# Set up the ClickEventHandler
handler = ClickEventHandler(new_peak_list)
# Add the legend
plt.legend()
plt.show()
# Extract the desired IonChromatograms from the `IntensityMatrix`.
# In[2]:
ic73 = im.get_ic_at_mass(73)
ic147 = im.get_ic_at_mass(147)
# Import matplotlib and the `plot_ic()` function, create a subplot, and plot the ICs on the chart:
# In[3]:
# 3rd party
import matplotlib.pyplot as plt
from pyms.Display import plot_ic
fig, ax = plt.subplots(1, 1, figsize=(8, 5))
# Plot the ICs
plot_ic(ax, tic, label="TIC")
plot_ic(ax, ic73, label="m/z 73")
plot_ic(ax, ic147, label="m/z 147")
# Set the title
ax.set_title("TIC and ICs for m/z = 73 & 147")
# Add the legend
plt.legend()
plt.show()
pl = rel_threshold(peak_list, percent=2)
new_peak_list = num_ions_threshold(pl, n=3, cutoff=10000)
print("Number of filtered peaks: ", len(new_peak_list))
# Get Ion Chromatograms for 4 separate m/z channels.
ic191 = im.get_ic_at_mass(191)
ic73 = im.get_ic_at_mass(73)
ic57 = im.get_ic_at_mass(57)
ic55 = im.get_ic_at_mass(55)
# Create a subplot and plot the TIC and peaks
fig, ax = plt.subplots(1, 1)
# Plot the ICs
plot_ic(ax, tic, label="TIC")
plot_ic(ax, ic191, label="m/z 191")
plot_ic(ax, ic73, label="m/z 73")
plot_ic(ax, ic57, label="m/z 57")
plot_ic(ax, ic55, label="m/z 55")
# Plot the peaks
plot_peaks(ax, new_peak_list)
# Set the title
ax.set_title('TIC, ICs, and PyMS Detected Peaks')
# Add the legend
plt.legend()
# Show the plot
