def extract_peaks(file,time_range):
peak_data = {}
run = pymzml.run.Reader(file+'.mzML')
peak_data[file] = {}
print(file)
for spec in run:
if spec.get('filter string')!= None and spec.get('total ion current') != None and spec.get('scan time') >= time_range[0] and spec.get('scan time') <= time_range[1]:
if spec.get('filter string') in peak_data[file]:
peak_data[file][spec.get('filter string')]['scan_count'] += 1
peak_data[file][spec.get('filter string')]['scan'] = mod_signal.combine(peak_data[file][spec.get('filter string')]['scan'], np.array(spec.peaks))
calculations.signal_filter(peak_data[file][spec.get('filter string')]['scan'],0.005)
else:
peak_data[file][spec.get('filter string')] = {}
peak_data[file][spec.get('filter string')]['scan_count'] = 1
peak_data[file][spec.get('filter string')]['scan'] = np.array(spec.peaks)
for scan in peak_data[file].keys():
peak_data[file][scan]['scan'] = mod_signal.multiply(peak_data[file][scan]['scan'],y=1.0/peak_data[file][scan]['scan_count'])
with open(file+scan+'.np', 'wb') as f:
np.save(f,peak_data[file][scan]['scan'])
def filter(signal,width=0.005):
if not isinstance(signal, numpy.ndarray):
raise TypeError, "Signals must be NumPy arrays!"
if signal.dtype.name != 'float64':
raise TypeError, "Signals data must be float64!"
return calculations.signal_filter(signal, width)