def plot_peaks(ax: Axes, peak_list: List[Peak.Peak], label: str = "Peaks", style: str = 'o') -> List[Line2D]:
"""
Plots the locations of peaks as found by PyMassSpec.
:param ax: The axes to plot the peaks on
:param peak_list: List of peaks to plot
:param label: label for plot legend.
:param style: The marker style. See `https://matplotlib.org/3.1.1/api/markers_api.html` for a complete list
:return: A list of Line2D objects representing the plotted data.
"""
if not is_peak_list(peak_list):
raise TypeError("'peak_list' must be a list of Peak objects")
time_list = []
height_list = []
if "line" in style.lower():
lines = []
for peak in peak_list:
lines.append(ax.axvline(x=peak.rt, color="lightgrey", alpha=0.8, linewidth=0.3))
return lines
else:
for peak in peak_list:
time_list.append(peak.rt)
height_list.append(sum(peak.mass_spectrum.intensity_list))
# height_list.append(peak.height)
# print(peak.height - sum(peak.mass_spectrum.intensity_list))
# print(sum(peak.mass_spectrum.intensity_list))
return ax.plot(time_list, height_list, style, label=label)
def store_peaks(peak_list: Peak,
file_name: Union[str, pathlib.Path],
protocol=1):
"""
Store the list of peak objects
:param peak_list: A list of peak objects
:type peak_list: list of :class:`pyms.Peaks.Class.Peak`
:param file_name: File name to store peak list
:type file_name: str or os.PathLike
:param protocol:
:type protocol:
:author: Andrew Isaac
:author: Dominic Davis-Foster (type assertions and pathlib support)
"""
if not is_peak_list(peak_list):
raise TypeError("'peak_list' must be a list of Peak objects")
if not is_path(file_name):
raise TypeError("'file_name' must be a string or a PathLike object")
file_name = prepare_filepath(file_name)
fp = file_name.open('wb')
pickle.dump(peak_list, fp, protocol)
fp.close()
def __init__(self, expr_code: str, peak_list: Sequence[Peak]):
if not isinstance(expr_code, str):
raise TypeError("'expr_code' must be a string")
if not is_peak_list(peak_list):
raise TypeError("'peak_list' must be a list of Peak objects")
self._expr_code = expr_code
self._peak_list = list(peak_list)
def __init__(self, expr_code, peak_list):
"""
Models an experiment
"""
if not isinstance(expr_code, str):
raise TypeError("'expr_code' must be a string")
if not is_peak_list(peak_list):
raise TypeError("'peak_list' must be a list of Peak objects")
self._expr_code = expr_code
self._peak_list = peak_list
def rel_threshold(pl: Sequence[Peak],
percent: float = 2,
copy_peaks: bool = True) -> List[Peak]:
"""
Remove ions with relative intensities less than the given relative
percentage of the maximum intensity.
:param pl:
:param percent: Threshold for relative percentage of intensity.
:default percent: ``2%``
:param copy_peaks: Whether the returned peak list should contain copies of the peaks.
:return: A new list of Peak objects with threshold ions.
:author: Andrew Isaac, Dominic Davis-Foster (type assertions)
""" # noqa: D400
peak_list = pl
if not is_peak_list(peak_list):
raise TypeError("'pl' must be a list of Peak objects")
if not is_number(percent):
raise TypeError("'percent' must be a number > 0")
if percent <= 0:
raise ValueError("'percent' must be a number > 0")
if copy_peaks:
peak_list = copy.deepcopy(peak_list)
new_peak_list = []
for peak in peak_list:
ms = peak.mass_spectrum
# if ms is None:
# raise ValueError("The peak has no mass spectrum.")
ia = ms.mass_spec
# assume max(ia) big so /100 1st
cutoff = (max(ia) / 100.0) * float(percent)
for i in range(len(ia)):
if ia[i] < cutoff:
ia[i] = 0
ms.mass_spec = ia
peak.mass_spectrum = ms
new_peak_list.append(peak)
return new_peak_list
def num_ions_threshold(pl: List,
n: int,
cutoff: float,
copy_peaks: bool = True) -> List:
"""
Remove Peaks where there are less than a given number of ion intensities above the given threshold
:param pl: A list of Peak objects
:type pl: list
:param n: Minimum number of ions that must have intensities above the cutoff
:type n: int
:param cutoff: The minimum intensity threshold
:type cutoff: int or float
:param copy_peaks: Whether a the returned peak list should contain copies of the peaks. Default ``False``
:type copy_peaks: bool, optional
:return: A new list of Peak objects
:rtype: list
:author: Andrew Isaac, Dominic Davis-Foster (type assertions)
"""
if not is_peak_list(pl):
raise TypeError("'pl' must be a list of Peak objects")
if not isinstance(n, int):
raise TypeError("'n' must be an integer")
if not isinstance(cutoff, Number):
raise TypeError("'cutoff' must be a Number")
if copy_peaks:
pl = copy.deepcopy(pl)
new_pl = []
for p in pl:
ms = p.mass_spectrum
ia = ms.mass_spec
ions = 0
for i in range(len(ia)):
if ia[i] >= cutoff:
ions += 1
if ions >= n:
new_pl.append(p)
return new_pl
def rel_threshold(pl: List,
percent: float = 2,
copy_peaks: bool = True) -> List:
"""
Remove ions with relative intensities less than the given relative percentage of the maximum intensity.
:param pl: A list of Peak objects
:type pl: list
:param percent: Threshold for relative percentage of intensity. Default ``2%``
:type percent: float, optional
:param copy_peaks: Whether a the returned peak list should contain copies of the peaks. Default ``False``
:type copy_peaks: bool, optional
:return: A new list of Peak objects with threshold ions
:rtype: list
:author: Andrew Isaac, Dominic Davis-Foster (type assertions)
"""
if not is_peak_list(pl):
raise TypeError("'pl' must be a list of Peak objects")
if not isinstance(percent, (int, float)):
raise TypeError("'percent' must be a number > 0")
if percent <= 0:
raise ValueError("'percent' must be a number > 0")
if copy_peaks:
pl = copy.deepcopy(pl)
new_pl = []
for p in pl:
ms = p.mass_spectrum
ia = ms.mass_spec
# assume max(ia) big so /100 1st
cutoff = (max(ia) / 100.0) * float(percent)
for i in range(len(ia)):
if ia[i] < cutoff:
ia[i] = 0
ms.mass_spec = ia
p.mass_spectrum = ms
new_pl.append(p)
return new_pl
def num_ions_threshold(
pl: Sequence[Peak],
n: int,
cutoff: float,
copy_peaks: bool = True,
) -> List[Peak]:
"""
Remove Peaks where there are fewer than ``n`` ions with intensities above the given threshold.
:param pl:
:param n: Minimum number of ions that must have intensities above the cutoff.
:param cutoff: The minimum intensity threshold.
:param copy_peaks: Whether the returned peak list should contain copies of the peaks.
:return: A new list of Peak objects.
:author: Andrew Isaac, Dominic Davis-Foster (type assertions)
"""
if not is_peak_list(pl):
raise TypeError("'pl' must be a list of Peak objects")
if not isinstance(n, int):
raise TypeError("'n' must be an integer")
if not is_number(cutoff):
raise TypeError("'cutoff' must be a number")
if copy_peaks:
pl = copy.deepcopy(pl)
new_pl = []
for p in pl:
ms = p.mass_spectrum
ia = ms.mass_spec
ions = 0
for i in range(len(ia)):
if ia[i] >= cutoff:
ions += 1
if ions >= n:
new_pl.append(p)
return new_pl
def plot_peaks(ax, peak_list, label="Peaks", style="o"):
"""
Plots the locations of peaks as found by PyMassSpec.
:param ax: The axes to plot the peaks on
:type ax: matplotlib.axes.Axes
:param peak_list: List of peaks to plot
:type peak_list: :class:`list` of :class:`pyms.Peak.Class.Peak` objects
:param label: label for plot legend. Default ``Peaks``
:type label: str, optional
:param style: The marker style. See `https://matplotlib.org/3.1.1/api/markers_api.html` for a complete list
:type style: str
:return: A list of Line2D objects representing the plotted data.
:rtype: list of :class:`matplotlib.lines.Line2D`
"""
if not is_peak_list(peak_list):
raise TypeError("'peak_list' must be a list of Peak objects")
time_list = []
height_list = []
if "line" in style.lower():
lines = []
for peak in peak_list:
lines.append(
ax.axvline(x=peak.rt,
color="lightgrey",
alpha=0.8,
linewidth=0.3))
return lines
else:
for peak in peak_list:
time_list.append(peak.rt)
height_list.append(sum(peak.get_mass_spectrum().intensity_list))
# height_list.append(peak.height)
# print(peak.height - sum(peak.get_mass_spectrum().intensity_list))
# print(sum(peak.mass_spectrum.intensity_list))
return ax.plot(time_list, height_list, style, label=label)