def test_main(self, peak, im_i):
ion_area_val = ion_area(list(range(100)), 20)
assert isinstance(ion_area_val, tuple)
assert len(ion_area_val) == 5
assert ion_area_val[0] == 231
assert ion_area_val[1] == 19
assert ion_area_val[2] == 1
assert ion_area_val[3] is False
assert ion_area_val[4] is True
def missing_peak_finder(
sample: Sample,
file_name: str,
points: int = 3,
null_ions: Optional[List] = None,
crop_ions: Optional[List] = None,
threshold: int = 1000,
rt_window: float = 1,
filetype: MissingPeakFiletype = MZML,
):
r"""
Integrates raw data around missing peak locations to fill ``NA``\s in the data matrix.
:param sample: The sample object containing missing peaks
:param file_name: Name of the raw data file
:param points: Peak finding - Peak if maxima over 'points' number of scans.
:param null_ions: Ions to be deleted in the matrix.
:default null_ions: ``[73, 147]``
:param crop_ions: Range of Ions to be considered.
:default crop_ions: ``[50, 540]``
:param threshold: Minimum intensity of IonChromatogram allowable to fill.
:param rt_window: Window in seconds around average RT to look for.
:param filetype:
:author: Sean O'Callaghan
"""
if not null_ions:
null_ions = [73, 147]
if not crop_ions:
crop_ions = [50, 540]
# TODO: some error checks on null and crop ions
# TODO: a for root,files,dirs in os.path.walk(): loop
print("Sample:", sample.name, "File:", file_name)
if filetype == NETCDF:
# this package
from pyms.GCMS.IO.ANDI import ANDI_reader
data = ANDI_reader(file_name)
elif filetype == MZML:
# this package
from pyms.GCMS.IO.MZML import mzML_reader
data = mzML_reader(file_name)
else:
print("file type not valid")
# build integer intensity matrix
im = build_intensity_matrix_i(data)
for null_ion in null_ions:
im.null_mass(null_ion)
im.crop_mass(crop_ions[0], crop_ions[1])
# get the size of the intensity matrix
n_scan, n_mz = im.size
# smooth data
for ii in range(n_mz):
ic = im.get_ic_at_index(ii)
ic1 = savitzky_golay(ic, points)
ic_smooth = savitzky_golay(ic1, points)
ic_base = tophat(ic_smooth, struct="1.5m")
im.set_ic_at_index(ii, ic_base)
for mp in sample.missing_peaks:
mp_rt = mp.rt
common_ion = mp.common_ion
qual_ion_1 = float(mp.qual_ion1)
qual_ion_2 = float(mp.qual_ion2)
ci_ion_chrom = im.get_ic_at_mass(common_ion)
print("ci = ", common_ion)
qi1_ion_chrom = im.get_ic_at_mass(qual_ion_1)
print("qi1 = ", qual_ion_1)
qi2_ion_chrom = im.get_ic_at_mass(qual_ion_2)
print("qi2 = ", qual_ion_2)
######
# Integrate the CI around that particular RT
#######
# Convert time to points
# How long between scans?
points_1 = ci_ion_chrom.get_index_at_time(float(mp_rt))
points_2 = ci_ion_chrom.get_index_at_time(float(mp_rt) - rt_window)
print("rt_window = ", points_1 - points_2)
rt_window_points = points_1 - points_2
maxima_list = get_maxima_list_reduced(ci_ion_chrom, mp_rt,
rt_window_points)
large_peaks = []
for rt, intens in maxima_list:
if intens > threshold:
q1_index = qi1_ion_chrom.get_index_at_time(rt)
q2_index = qi2_ion_chrom.get_index_at_time(rt)
q1_intensity = qi1_ion_chrom.get_intensity_at_index(q1_index)
q2_intensity = qi2_ion_chrom.get_intensity_at_index(q2_index)
if q1_intensity > threshold / 2 and q2_intensity > threshold / 2:
large_peaks.append([rt, intens])
print(f"found {len(large_peaks):d} peaks above threshold")
areas = []
for peak in large_peaks:
apex = ci_ion_chrom.get_index_at_time(peak[0])
ia = ci_ion_chrom.intensity_array.tolist()
area, left, right, l_share, r_share = ion_area(ia, apex, 0)
areas.append(area)
########################
areas.sort()
if len(areas) > 0:
biggest_area = areas[-1]
mp.common_ion_area = biggest_area
# mp.exact_rt = f"{float(mp_rt) / 60.0:.3f}"
mp.exact_rt = float(mp_rt) / 60.0
print("found area:", biggest_area, "at rt:", mp_rt)
else:
print("Missing peak at rt = ", mp_rt)
mp.common_ion_area = None
def missing_peak_finder(sample, andi_file, points=7, null_ions=[73, 207],\
crop_ions=[45,300], threshold=100000, rt_window=10):
"""
@summary: Integrates raw data around missing peak locations
to fill in NAs in the data matrix
@param sample: The sample object containing missing peaks
@type sample: pyms.MissingPeak.Class.Sample
@param andi_file: Name of the raw data file
@type andi_file: stringType
@param points: Peak finding - Peak if maxima over 'points' \
number of scans (Default 3)
@type points: intType
@param null_ions: Ions to be deleted in the matrix
@type null_ions: listType
@param crop_ions: Range of Ions to be considered
@type crop_ions: listType
@param threshold: Minimum intensity of IonChromatogram allowable to fill\
missing peak
@type threshold: intType
@param rt_window: Window in seconds around average RT to look for \
missing peak
@type rt_window: floatType
@author: Sean O'Callaghan
"""
### some error checks on null and crop ions
### a for root,files,dirs in os.path.walk(): loop
print "Sample:", sample.get_name(), "andi_file:", andi_file
data = ANDI_reader(andi_file)
# build integer intensity matrix
im = build_intensity_matrix_i(data)
for null_ion in null_ions:
im.null_mass(null_ion)
im.crop_mass(crop_ions[0], crop_ions[1])
# get the size of the intensity matrix
n_scan, n_mz = im.get_size()
# smooth data
for ii in range(n_mz):
ic = im.get_ic_at_index(ii)
ic1 = savitzky_golay(ic, points)
ic_smooth = savitzky_golay(ic1, points)
ic_base = tophat(ic_smooth, struct="1.5m")
im.set_ic_at_index(ii, ic_base)
for mp in sample.get_missing_peaks():
#JT: Debug peak attributes
#attrs = vars(mp)
#print ', '.join("%s: %s" % item for item in attrs.items())
mp_rt = mp.get_rt()
#print(repr(mp_rt))
common_ion = mp.get_ci()
qual_ion_1 = float(mp.get_qual_ion1())
qual_ion_2 = float(mp.get_qual_ion2())
ci_ion_chrom = im.get_ic_at_mass(common_ion)
#print "ci = ",common_ion
qi1_ion_chrom = im.get_ic_at_mass(qual_ion_1)
#print "qi1 = ", qual_ion_1
qi2_ion_chrom = im.get_ic_at_mass(qual_ion_2)
#print "qi2 = ", qual_ion_2
######
# Integrate the CI around that particular RT
#######
#Convert time to points
# How long between scans?
points_1 = ci_ion_chrom.get_index_at_time(float(mp_rt))
points_2 = ci_ion_chrom.get_index_at_time(float(mp_rt) - rt_window)
#print "rt_window = ", points_1 - points_2
rt_window_points = points_1 - points_2
maxima_list = get_maxima_list_reduced(ci_ion_chrom, mp_rt, \
rt_window_points)
large_peaks = []
for rt, intens in maxima_list:
if intens > threshold:
q1_index = qi1_ion_chrom.get_index_at_time(rt)
q2_index = qi2_ion_chrom.get_index_at_time(rt)
q1_intensity = qi1_ion_chrom.get_intensity_at_index(q1_index)
q2_intensity = qi2_ion_chrom.get_intensity_at_index(q2_index)
if q1_intensity > threshold / 2 and q2_intensity > threshold / 2:
large_peaks.append([rt, intens])
#print('found %d peaks above threshold'%len(large_peaks))
areas = []
for peak in large_peaks:
apex = ci_ion_chrom.get_index_at_time(peak[0])
ia = ci_ion_chrom.get_intensity_array().tolist()
area, left, fight, l_share, r_share = ion_area(ia, apex, 0)
areas.append(area)
########################
areas.sort()
if len(areas) > 0:
biggest_area = areas[-1]
mp.set_ci_area(biggest_area)
#print "found area:", biggest_area, "at rt:", mp_rt
else:
#print "Missing peak at rt = ", mp_rt
mp.set_ci_area('NA')
def test_tol_errors(self, obj):
with pytest.raises(TypeError):
ion_area(list(range(100)), 20, tol=obj)
def test_max_bound_errors(self, obj):
with pytest.raises(TypeError):
ion_area(list(range(100)), 20, max_bound=obj)
def test_apex_errors(self, obj):
with pytest.raises(TypeError):
ion_area(list(range(100)), obj)
def test_ia_errors(self, obj):
with pytest.raises(TypeError):
ion_area(obj, 20)
def missing_peak_finder(sample, filename, points=13, null_ions=[73, 147],\
crop_ions=[50,540], threshold=1000, rt_window=1, filetype='cdf'):
"""
@summary: Integrates raw data around missing peak locations
to fill in NAs in the data matrix
@param sample: The sample object containing missing peaks
@type sample: pyms.MissingPeak.Class.Sample
@param andi_file: Name of the raw data file
@type andi_file: stringType
@param points: Peak finding - Peak if maxima over 'points' \
number of scans (Default 3)
@type points: intType
@param null_ions: Ions to be deleted in the matrix
@type null_ions: listType
@param crop_ions: Range of Ions to be considered
@type crop_ions: listType
@param threshold: Minimum intensity of IonChromatogram allowable to fill\
missing peak
@type threshold: intType
@param rt_window: Window in seconds around average RT to look for \
missing peak
@type rt_window: floatType
@author: Sean O'Callaghan
"""
### some error checks on null and crop ions
### a for root,files,dirs in os.path.walk(): loop
print "Sample:", sample.get_name(), "File:", filename
if filetype == 'cdf':
data = ANDI_reader(filename)
elif filetype == 'mzml':
data = mzML_reader(filename)
else:
print "file type not valid"
# build integer intensity matrix
im = build_intensity_matrix_i(data)
for null_ion in null_ions:
im.null_mass(null_ion)
im.crop_mass(crop_ions[0], crop_ions[1])
# get the size of the intensity matrix
n_scan, n_mz = im.get_size()
# smooth data
for ii in range(n_mz):
ic = im.get_ic_at_index(ii)
ic1 = savitzky_golay(ic, points)
ic_smooth = savitzky_golay(ic1, points)
ic_base = tophat(ic_smooth, struct="1.5m")
im.set_ic_at_index(ii, ic_base)
for mp in sample.get_missing_peaks():
mp_rt = mp.get_rt()
common_ion = mp.get_ci()
qual_ion_1 = float(mp.get_qual_ion1())
qual_ion_2 = float(mp.get_qual_ion2())
ci_ion_chrom = im.get_ic_at_mass(common_ion)
print "ci = ",common_ion
qi1_ion_chrom = im.get_ic_at_mass(qual_ion_1)
print "qi1 = ", qual_ion_1
qi2_ion_chrom = im.get_ic_at_mass(qual_ion_2)
print "qi2 = ", qual_ion_2
######
# Integrate the CI around that particular RT
#######
#Convert time to points
# How long between scans?
points_1 = ci_ion_chrom.get_index_at_time(float(mp_rt))
points_2 = ci_ion_chrom.get_index_at_time(float(mp_rt)-rt_window)
print "rt_window = ", points_1 - points_2
rt_window_points = points_1 - points_2
maxima_list = get_maxima_list_reduced(ci_ion_chrom, mp_rt, \
rt_window_points)
large_peaks = []
for rt, intens in maxima_list:
if intens > threshold:
q1_index = qi1_ion_chrom.get_index_at_time(rt)
q2_index = qi2_ion_chrom.get_index_at_time(rt)
q1_intensity = qi1_ion_chrom.get_intensity_at_index(q1_index)
q2_intensity = qi2_ion_chrom.get_intensity_at_index(q2_index)
if q1_intensity > threshold/2 and q2_intensity > threshold/2:
large_peaks.append([rt, intens])
print('found %d peaks above threshold'%len(large_peaks))
areas = []
for peak in large_peaks:
apex = ci_ion_chrom.get_index_at_time(peak[0])
ia = ci_ion_chrom.get_intensity_array().tolist()
area, left, fight, l_share, r_share = ion_area(ia, apex, 0)
areas.append(area)
########################
areas.sort()
if len(areas)>0:
biggest_area = areas[-1]
mp.set_ci_area(biggest_area)
print "found area:", biggest_area, "at rt:", mp_rt
else:
print "Missing peak at rt = ", mp_rt
mp.set_ci_area('na')
