def rawMassLynx_MZDT_extract(path=None, mz_start=0, mz_end=50000, mz_nPoints=5000, dt_start=1, dt_end=200,
silent_extract=True, driftscope_path='C:\DriftScope\lib', **kwargs):
# check if data should be extracted to data folder OR temporary folder
if kwargs.get("use_temp_folder", True) and os.path.exists(temp_data_folder):
out_path = temp_data_folder
else:
out_path = path
# Create input file
range_file = os.path.join(out_path, '__.2dDTMZ.inp')
try:
fileID = open(range_file, 'w')
except IOError as err:
dlgBox(exceptionTitle="Error", exceptionMsg=str(err), type="Error")
return
fileID.write("{} {} {}\n0.0 9999.0 1\n{} {} 200".format(mz_start, mz_end, mz_nPoints, dt_start, dt_end))
fileID.close()
# Create command for execution
cmd = ''.join([driftscope_path, '\imextract.exe -d "', path, '" -f 1 -o "',
out_path, '\output.2dDTMZ" -t mobilicube -p "', range_file, '"'])
extractIMS = Popen(cmd, shell=kwargs.get("verbose", True),
creationflags=CREATE_NEW_CONSOLE)
extractIMS.wait()
# return data
if kwargs.get("return_data", False):
if kwargs.get("normalize", False):
dt, dtnorm = rawMassLynx_MZDT_load(out_path, normalize=True)
return dt, dtnorm
else:
dt = rawMassLynx_MZDT_load(out_path)
return dt
else:
return None
def remove_noise_1D(inputData=None, threshold=0):
# Check whether threshold values meet the criteria.
# First check if value is not above the maximum or below 0
if (threshold > np.max(inputData)) or (threshold < 0):
dlgBox(
exceptionTitle='Warning',
exceptionMsg=
"Threshold value was too high - the maximum value is %s. Value was reset to 0. Consider reducing your threshold value."
% np.max(inputData),
type="Warning")
threshold = 0
elif threshold == 0.0:
pass
# Check if the value is a fraction (i.e. if working on a normalized dataset)
elif (threshold <
(np.max(inputData) /
10000)): # This is somewhat guesswork! It won't be 100 % fool proof
if (threshold > 1) or (threshold <= 0):
threshold = 0
dlgBox(
exceptionTitle='Warning',
exceptionMsg=
"Threshold value was too low - the maximum value is %s. Value was reset to 0. Consider increasing your threshold value."
% np.max(inputData),
type="Warning")
threshold = 0
# Or leave it as is if the values are correct
else:
threshold = threshold
inputData[inputData <= threshold] = 0
return inputData
def onUniDecView(self, evt):
self.config.unidec_plot_panel_view = self.unidec_view_value.GetStringSelection()
dlgBox(exceptionTitle="Warning",
exceptionMsg="Changing the panel view will not take place until you restart ORIGAMI.",
type="Warning")
def smooth_gaussian_2D(inputData=None, sigma=2): # smoothDataGaussian
# Check if input data is there
if inputData is None or len(inputData) == 0:
return None
if sigma < 0:
dlgBox(exceptionTitle='Warning',
exceptionMsg="Value of sigma is too low. Value was reset to 1",
type="Warning")
sigma = 1
else:
sigma = sigma
dataOut = gaussian_filter(inputData, sigma=sigma, order=0)
dataOut[dataOut < 0] = 0
return dataOut
def smooth_gaussian_1D(data=None, sigma=1): # smooth1D
"""
This function uses Gaussian filter to smooth 1D data
"""
if data is None or len(data) == 0:
return None
if sigma < 0:
dlgBox(exceptionTitle='Warning',
exceptionMsg="Value of sigma is too low. Value was reset to 1",
type="Warning")
sigma = 1
else:
sigma = sigma
dataOut = gaussian_filter(data, sigma=sigma, order=0)
return dataOut
def rawMassLynx_MS_extract(path, bin_size=10000, rt_start=0, rt_end=99999.0, dt_start=1, dt_end=200,
mz_start=0, mz_end=50000, driftscope_path='C:\DriftScope\lib', **kwargs):
"""
@param bin_size (int): number of points in the m/z dimension
@param rt_start (float): start retention time (minutes)
@param rt_end (float): end retention time (minutes)
@param dt_start (float): start drift time (bins)
@param dt_end (float): end drift time (bins)
@param mz_start (float): start m/z (Da)
@param mz_end (float): end m/z (Da)
@param driftscope_path (str): path to DriftScope directory
"""
# check if data should be extracted to data folder OR temporary folder
if kwargs.get("use_temp_folder", True) and os.path.exists(temp_data_folder):
out_path = temp_data_folder
else:
out_path = path
# Write range file
range_file = os.path.join(out_path, '__.1dMZ.inp')
try:
fileID = open(range_file, 'w')
except IOError as err:
dlgBox(exceptionTitle="Error", exceptionMsg=str(err), type="Error")
return
fileID.write("%s %s %s\n%s %s 1\n%s %s 1" % (mz_start, mz_end, bin_size, rt_start, rt_end, dt_start, dt_end))
fileID.close()
# Create command for execution
cmd = ''.join([driftscope_path, '\imextract.exe -d "', path, '" -f 1 -o "', out_path,
'\output.1dMZ" -t mobilicube -p "', range_file, '"'])
# Extract command
extractIMS = Popen(cmd, shell=kwargs.get("verbose", True),
creationflags=CREATE_NEW_CONSOLE)
extractIMS.wait()
# return data
if kwargs.get("return_data", False):
msX, msY = rawMassLynx_MS_load(out_path)
return msX, msY
else:
return None
def rawMassLynx_RT_extract(path=None, rt_start=0, rt_end=99999.0, dt_start=1, dt_end=200,
mz_start=0, mz_end=50000, driftscope_path='C:\DriftScope\lib',
**kwargs):
"""
Extract the retention time for specified (or not) mass range
"""
# check if data should be extracted to data folder OR temporary folder
if kwargs.get("use_temp_folder", True) and os.path.exists(temp_data_folder):
out_path = temp_data_folder
else:
out_path = path
# Create input file
range_file = os.path.join(out_path, '__.1dRT.inp')
try:
fileID = open(range_file, 'w')
except IOError as err:
dlgBox(exceptionTitle="Error", exceptionMsg=str(err), type="Error")
return
fileID.write("{} {} 1\n0.0 9999.0 5000\n{} {} 1".format(mz_start, mz_end, dt_start, dt_end))
fileID.close()
# Create command for execution
cmd = ''.join([driftscope_path, '\imextract.exe -d "', path, '" -f 1 -o "',
out_path, '\output.1dRT" -t mobilicube -p "', range_file, '"'])
extractIMS = Popen(cmd, shell=kwargs.get("verbose", True),
creationflags=CREATE_NEW_CONSOLE)
extractIMS.wait()
# return data
if kwargs.get("return_data", False):
if kwargs.get("normalize", False):
rtY, rtYnorm = rawMassLynx_RT_load(out_path, normalize=True)
rtX = np.arange(1, len(rtY) + 1)
return rtX, rtY, rtYnorm
else:
rtY = rawMassLynx_RT_load(out_path)
rtX = np.arange(1, len(rtY) + 1)
return rtX, rtY
else:
return None
def smooth_savgol_2D(inputData=None,
polyOrder=2,
windowSize=5): # smoothDataSavGol
# Check if input data is there
if inputData is None or len(inputData) == 0:
return None
# Check whether polynomial order is of correct size
if (polyOrder <= 0):
dlgBox(
exceptionTitle='Warning',
exceptionMsg="Polynomial order is too small. Value was reset to 2",
type="Warning")
polyOrder = 2
else:
polyOrder = polyOrder
# Check whether window size is of correct size
if windowSize is None:
windowSize = polyOrder + 1
elif (windowSize % 2) and (windowSize > polyOrder):
windowSize = windowSize
elif windowSize <= polyOrder:
dlgBox(
exceptionTitle='Warning',
exceptionMsg=
"Window size was smaller than the polynomial order. Value was reset to %s"
% (polyOrder + 1),
type="Warning")
windowSize = polyOrder + 1
else:
print('Window size is even. Adding 1 to make it odd.')
windowSize = windowSize + 1
dataOut = savgol_filter(inputData,
polyorder=polyOrder,
window_length=windowSize,
axis=0)
dataOut[dataOut < 0] = 0 # Remove any values that are below 0
return dataOut
def rawMassLynx_MS_bin(filename=None, startScan=0, endScan=-1, function=1,
mzStart=None, mzEnd=None, binsize=None, binData=False,
**kwargs):
"""
Extract MS data, bin it
---
@param binData: boolean, determines if data should be binned or not
"""
tstart = time.clock()
# Create pointer to the file
try:
filePointer = mlLib.newCMassLynxRawReader(filename)
except WindowsError as err:
dlgBox(exceptionTitle="Error", exceptionMsg=str(err), type="Error")
return
# Setup scan reader
dataPointer = mlLib.newCMassLynxRawScanReader(filePointer)
# Extract number of scans available from the file
nScans = mlLib.getScansInFunction(dataPointer, function)
# Initilise pointers to data
xpoint = c_float()
ypoint = c_float()
# Initilise empty lists
msX = []
msY = []
msDict = {}
if endScan == -1 or endScan > nScans:
endScan = nScans
if 'linearization_mode' in kwargs:
if kwargs['linearization_mode'] == 'Raw':
binData = False
if binsize == 0.: binData = False
if binData:
if 'auto_range' in kwargs and kwargs['auto_range'] :
mzStart = kwargs['mz_min']
mzEnd = kwargs['mz_max']
if mzStart == None or mzEnd == None or binsize == None:
print('Missing parameters')
return
elif kwargs['linearization_mode'] == "Binning":
msList = np.arange(mzStart, mzEnd + binsize, binsize)
msCentre = msList[:-1] + (binsize / 2)
else:
msCentre = get_linearization_range(mzStart, mzEnd, binsize, kwargs['linearization_mode'])
msRange = np.arange(startScan, endScan) + 1
# First extract data
for scan in msRange:
nPoints = mlLib.getScanSize(dataPointer, function, scan)
# Read XY coordinates
mlLib.getXYCoordinates(filePointer, function, scan, byref(xpoint), byref(ypoint))
# Prepare pointers
mzP = (c_float * nPoints)()
mzI = (c_float * nPoints)()
# Read spectrum
mlLib.readSpectrum(dataPointer, function, scan, byref(mzP), byref(mzI))
# Extract data from pointer and assign it to list
msX = np.ndarray((nPoints,), 'f', mzP, order='C')
msY = np.ndarray((nPoints,), 'f', mzI, order='C')
if binData:
if kwargs['linearization_mode'] == "Binning":
msYbin = bin_1D(x=msX, y=msY, bins=msList)
else:
msCentre, msYbin = linearize(data=np.transpose([msX, msY]),
binsize=binsize, mode=kwargs['linearization_mode'],
input_list=msCentre)
msDict[scan] = [msCentre, msYbin]
else:
msDict[scan] = [msX, msY]
tend = time.clock()
print("It took {:.4f} seconds to process {} scans".format((tend - tstart), len(msRange)))
# Return data
return msDict
def saveFigure2(self, path, **kwargs):
"""
Saves figures in specified location.
Transparency and DPI taken from config file
"""
# check if plot exists
if not hasattr(self, 'plotMS'):
print('Cannot save a plot that does not exist')
return
# Get resize parameter
resizeName = kwargs.get('resize', None)
resizeSize = None
if resizeName is not None:
resizeSize = self.config._plotSettings[resizeName]['resize_size']
if not hasattr(self.plotMS, "get_position"):
resizeSize = None
if resizeSize is not None and not self.lock_plot_from_updating_size:
dpi = wx.ScreenDC().GetPPI()
# Calculate new size
figsizeNarrowPix = (int(resizeSize[0] * dpi[0]), int(resizeSize[1] * dpi[1]))
# Set new canvas size and reset the view
self.canvas.SetSize(figsizeNarrowPix)
self.canvas.draw()
# Get old and new plot sizes
oldAxesSize = self.plotMS.get_position()
newAxesSize = self.config._plotSettings[resizeName]['save_size']
try:
self.plotMS.set_position(newAxesSize)
except RuntimeError:
self.plotMS.set_position(oldAxesSize)
self.repaint()
# Save figure
try:
kwargs['bbox_inches'] = "tight"
self.figure.savefig(path, **kwargs)
except IOError:
# reset axes size
if resizeSize is not None and not self.lock_plot_from_updating_size:
self.plotMS.set_position(oldAxesSize)
self.sizeHandler()
# warn user
dlgBox(exceptionTitle='Warning',
exceptionMsg="Cannot save file: %s as it appears to be currently open or the folder doesn't exist" % path,
type="Error")
# get file extension
fname, delimiter_txt = splitext(path)
try: bname = basename(fname)
except: bname = ""
fileType = "Image file (%s)|*%s" % (delimiter_txt, delimiter_txt)
dlg = wx.FileDialog(None, "Save as...",
"", "", fileType, wx.FD_SAVE | wx.FD_OVERWRITE_PROMPT)
dlg.SetFilename(bname)
if dlg.ShowModal() == wx.ID_OK:
fname, __ = splitext(dlg.GetPath())
path = join(fname + delimiter_txt)
# reset axes, again
if resizeSize is not None and not self.lock_plot_from_updating_size:
self.canvas.SetSize(figsizeNarrowPix)
self.canvas.draw()
try:
self.plotMS.set_position(newAxesSize)
except RuntimeError:
self.plotMS.set_position(oldAxesSize)
self.repaint()
try:
kwargs['bbox_inches'] = "tight"
self.figure.savefig(path, **kwargs)
except:
try:
del kwargs['bbox_inches']
self.figure.savefig(path, **kwargs)
except: pass
# Reset previous view
if resizeSize is not None and not self.lock_plot_from_updating_size:
self.plotMS.set_position(oldAxesSize)
self.sizeHandler()
