def window_analyzer(ic, window=_DEFAULT_WINDOW, n_windows=_DEFAULT_N_WINDOWS, rand_seed=None ):
"""
@summary: A simple estimator of the signal noise based on randomly
placed windows and median absolute deviation
The noise value is estimated by repeatedly and picking random
windows (of a specified width) and calculating median absolute
deviation (MAD). The noise estimate is given by the minimum MAD.
@param ic: An IonChromatogram object
@type ic: pyms.IO.Class.IonCromatogram
@param window: Window width selection
@type window: IntType or StringType
@param n_windows: The number of windows to calculate
@type n_windows: IntType
@param rand_seed: Random seed generator
@type rand_seed: IntType
@return: The noise estimate
@rtype: FloatType
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("argument must be an IonChromatogram object")
ia = ic.get_intensity_array() # fetch the intensities
# create an instance of the Random class
if rand_seed != None:
generator = random.Random(rand_seed)
else:
generator = random.Random()
window_pts = window_sele_points(ic, window)
maxi = ia.size - window_pts
noise_level = math.fabs(ia.max()-ia.min())
best_window_pos = None
seen_positions = []
cntr = 0
while cntr < n_windows:
# generator.randrange(): last point not included in range
try_pos = generator.randrange(0, maxi+1)
# only process the window if not analyzed previously
if try_pos not in seen_positions:
end_slice = try_pos + window_pts
slice = ia[try_pos:end_slice]
crnt_mad = MAD(slice)
if crnt_mad < noise_level:
noise_level = crnt_mad
best_window_pos = try_pos
cntr = cntr + 1
seen_positions.append(try_pos)
return noise_level
def savitzky_golay(ic, window=__DEFAULT_WINDOW, \
degree=__DEFAULT_POLYNOMIAL_DEGREE):
"""
@summary: Applies Savitzky-Golay filter on ion chromatogram
@param ic: The input ion chromatogram
@type ic: pyms.GCMS.Class.IonChromatogram
@param window: The window selection parameter. This can be an integer
or time string. If integer, taken as the number of points. If a
string, must of the form "<NUMBER>s" or "<NUMBER>m", specifying
a time in seconds or minutes, respectively
@type window: IntType or StringType
@param degree: degree of the fitting polynomial for the Savitzky-Golay
filter
@type degree: IntType
@return: Smoothed ion chromatogram
@rtype: pyms.GCMS.Class.IonChromatogram
@author: Uwe Schmitt
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("'ic' not an IonChromatogram object")
if not is_int(degree):
error("'degree' not an integer")
ia = ic.get_intensity_array()
wing_length = ic_window_points(ic, window, half_window=True)
#print " -> Applying Savitzky-Golay filter"
#print " Window width (points): %d" % ( 2*wing_length+1 )
#print " Polynomial degree: %d" % ( degree )
coeff = __calc_coeff(wing_length, degree)
ia_denoise = __smooth(ia, coeff)
ic_denoise = copy.deepcopy(ic)
ic_denoise.set_intensity_array(ia_denoise)
return ic_denoise
def window_smooth(ic, window=__DEFAULT_WINDOW, median=False):
"""
@summary: Applies window smoothing on ion chromatogram
@param ic: The input ion chromatogram
@type ic: pyms.GCMS.Class.IonChromatogram
@param window: The window selection parameter. This can be an integer
or time string. If integer, taken as the number of points. If a
string, must of the form "<NUMBER>s" or "<NUMBER>m", specifying
a time in seconds or minutes, respectively
@type window: IntType or StringType
@param median: An indicator whether the mean or median window smoothing
to be used
@type median: Booleantype
@return: Smoothed ion chromatogram
@rtype: pyms.GCMS.Class.IonChromatogram
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("'ic' not an IonChromatogram object")
ia = ic.get_intensity_array()
wing_length = ic_window_points(ic, window, half_window=True)
if median:
ia_denoise = __median_window(ia, wing_length)
else:
ia_denoise = __mean_window(ia, wing_length)
ic_denoise = copy.deepcopy(ic)
ic_denoise.set_intensity_array(ia_denoise)
return ic_denoise
def window_smooth(ic, window=__DEFAULT_WINDOW, median=False):
"""
@summary: Applies window smoothing on ion chromatogram
@param ic: The input ion chromatogram
@type ic: pyms.GCMS.Class.IonChromatogram
@param window: The window selection parameter. This can be an integer
or time string. If integer, taken as the number of points. If a
string, must of the form "<NUMBER>s" or "<NUMBER>m", specifying
a time in seconds or minutes, respectively
@type window: IntType or StringType
@param median: An indicator whether the mean or median window smoothing
to be used
@type median: Booleantype
@return: Smoothed ion chromatogram
@rtype: pyms.GCMS.Class.IonChromatogram
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("'ic' not an IonChromatogram object")
ia = ic.get_intensity_array()
wing_length = ic_window_points(ic, window, half_window=True)
if median:
ia_denoise = __median_window(ia, wing_length)
else:
ia_denoise = __mean_window(ia, wing_length)
ic_denoise = copy.deepcopy(ic)
ic_denoise.set_intensity_array(ia_denoise)
return ic_denoise
def tophat(ic, struct=None):
"""
@summary: Top-hat baseline correction on Ion Chromatogram
@param ic: The input ion chromatogram
@type ic: pyms.GCMS.Class.IonChromatogram
@param struct: Top-hat structural element as time string
@type struct: StringType
@return: Top-hat corrected ion chromatogram
@rtype: pyms.IO.Class.IonChromatogram
@author: Woon Wai Keen
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("'ic' not an IonChromatogram object")
else:
ia = copy.deepcopy(ic.get_intensity_array())
if struct == None:
struct_pts = int(round(ia.size * _STRUCT_ELM_FRAC))
else:
struct_pts = ic_window_points(ic, struct)
# print " -> Top-hat: structural element is %d point(s)" % ( struct_pts )
str_el = numpy.repeat([1], struct_pts)
ia = ndimage.white_tophat(ia, None, str_el)
ic_bc = copy.deepcopy(ic)
ic_bc.set_intensity_array(ia)
return ic_bc
def tophat(ic, struct=None):
"""
@summary: Top-hat baseline correction on Ion Chromatogram
@param ic: The input ion chromatogram
@type ic: pyms.GCMS.Class.IonChromatogram
@param struct: Top-hat structural element as time string
@type struct: StringType
@return: Top-hat corrected ion chromatogram
@rtype: pyms.IO.Class.IonChromatogram
@author: Woon Wai Keen
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("'ic' not an IonChromatogram object")
else:
ia = copy.deepcopy(ic.get_intensity_array())
if struct == None:
struct_pts = int(round(ia.size * _STRUCT_ELM_FRAC))
else:
struct_pts = ic_window_points(ic,struct)
# print " -> Top-hat: structural element is %d point(s)" % ( struct_pts )
str_el = numpy.repeat([1], struct_pts)
ia = ndimage.white_tophat(ia, None, str_el)
ic_bc = copy.deepcopy(ic)
ic_bc.set_intensity_array(ia)
return ic_bc
def window_analyzer(ic,
window=_DEFAULT_WINDOW,
n_windows=_DEFAULT_N_WINDOWS,
rand_seed=None):
"""
@summary: A simple estimator of the signal noise based on randomly
placed windows and median absolute deviation
The noise value is estimated by repeatedly and picking random
windows (of a specified width) and calculating median absolute
deviation (MAD). The noise estimate is given by the minimum MAD.
@param ic: An IonChromatogram object
@type ic: pyms.IO.Class.IonCromatogram
@param window: Window width selection
@type window: IntType or StringType
@param n_windows: The number of windows to calculate
@type n_windows: IntType
@param rand_seed: Random seed generator
@type rand_seed: IntType
@return: The noise estimate
@rtype: FloatType
@author: Vladimir Likic
"""
if not is_ionchromatogram(ic):
error("argument must be an IonChromatogram object")
ia = ic.get_intensity_array() # fetch the intensities
# create an instance of the Random class
if rand_seed != None:
generator = random.Random(rand_seed)
else:
generator = random.Random()
window_pts = window_sele_points(ic, window)
maxi = ia.size - window_pts
noise_level = math.fabs(ia.max() - ia.min())
best_window_pos = None
seen_positions = []
cntr = 0
while cntr < n_windows:
# generator.randrange(): last point not included in range
try_pos = generator.randrange(0, maxi + 1)
# only process the window if not analyzed previously
if try_pos not in seen_positions:
end_slice = try_pos + window_pts
slice = ia[try_pos:end_slice]
crnt_mad = MAD(slice)
if crnt_mad < noise_level:
noise_level = crnt_mad
best_window_pos = try_pos
cntr = cntr + 1
seen_positions.append(try_pos)
return noise_level
