TADuncombe

clear;
%File Directory (SET)
base_folder='D:\Herr Lab\Data\Data analysis\20150915-BT474-HER2 isoform study\slide 4\';

%USER DEFINED SETTINGS (SET)
fileNumber=1; %first file to analyze
loop='y';%'y' to loop through all files
curveFit='y';%'y' to perform curve fitting
overlayArray='y';%'y' to overlay array

TADuncombe

import numpy as np
from math import pi, log
import pylab
from scipy import fft, ifft
from scipy.optimize import curve_fit

i = 10000
x = np.linspace(0, 3.5 * pi, i)
y = (0.3*np.sin(x) + np.sin(1.3 * x) + 0.9 * np.sin(4.2 * x) + 0.06 *
    np.random.randn(i))

TADuncombe

import numpy as np
from scipy.linalg import solveh_banded


def als_baseline(intensities, asymmetry_param=0.05, smoothness_param=1e6,
                 max_iters=10, conv_thresh=1e-5, verbose=False):
  '''Computes the asymmetric least squares baseline.
  * http://www.science.uva.nl/~hboelens/publications/draftpub/Eilers_2005.pdf

  smoothness_param: Relative importance of smoothness of the predicted response.

TADuncombe

from als import als_baseline
from peakdetect import peakdetect

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

def msProcess(mz, raw_intensity, 
                 asymmetry_param=0.05, smoothness_param=1e6, #background subract params
                 max_iters=10, conv_thresh=1e-5, verbose=False, #background subract params