nmrglue.analysisbase

analysisbase provides general purpose analysis functions and classes used by several nmrglue.analysis modules

This modules is imported as nmrglue.analysisbase and can be called as such.

Low-Level Functions

These functions are typically not used directly by users. They are called by high level functions.

nmrglue.analysis.analysisbase.recnames(dnames, ls_classes, Ms)

Determind the names of a records array provided lineshape classes,

Parameters:

• dnames List of dimension names.
• ls_classes List of lineshape classes.
• Ms List of lineshape lengths.

Returns list of records array names (strings).

nmrglue.analysis.analysisbase.find_limits(pts)

Find the limits which outline the provided list of points

Parameters:

• pts List of points [(z0,y0,x0),(z1,y1,x1),...]

Returns (min,max):

• min array of minimum indices array([zmin,ymin,xmin]
• max array of maximum indices array([zmin,ymin,xmin]

nmrglue.analysis.analysisbase.limits2slice(limits)

Create a set of slice objects given list of min,max limits

Parameters:

• limits Tuple of minimum and maximum indices

Returns: list of slices which will return points between limits.

nmrglue.analysis.analysisbase.slice2limits(slices)

Create a tuple of min,max limits from a set of slices

Parameters:

• slices: list of slices

Returns: Tuple of minimum and maximum indices

nmrglue.analysis.analysisbase.squish(r, axis)

Squish array r along axis - sum along all but one axis

nmrglue.analysis.analysisbase.pick2linesh(centers, linewidths, amplitudes)

Convert peakpick.pick output to linesh.fit_NDregion input

Parameters:

• centers Array of estimated peak locations, shape (n_peaks,ndim).
• linewidths Array of estimated peak linewidths, shape (n_peaks,ndim).
• amplitudes Array of estimated peak amplitude, shape (n_peaks).

Return: guesses,amp_guesses

• guesses P-length list (P is the number of peaks in region) of

  N-length lists of tuples where each each tuple is the optimiztion starting parameters for a given peak and dimension lineshape.

• amp_guesses P-length list of amplitudes.

nmrglue.analysis.analysisbase.linesh2pick(guesses, amp_guesses)

Convert linesh.fit_NDregion input/output to peakpick.pick output

Parameters:

• guesses P-length list (P is the number of peaks in region) of

  N-length lists of tuples where each each tuple is the optimiztion starting parameters for a given peak and dimension lineshape.

• amp_guesses P-length list of amplitudes.

Return: (centers,linewidths,amplitudes)

• centers Array of estimated peak locations, shape (n_peaks,ndim).
• linewidths Array of estimated peak linewidths, shape (n_peaks,ndim).
• amplitudes Array of estimated peak amplitude, shape (n_peaks).

nmrglue.analysis.analysisbase.ls_str2class(l)

Convert lineshape string to lineshape class

nmrglue.analysis.analysisbase.center_fwhm(signal)

Estimate the center and full-width half max of a signal.

nmrglue.analysis.analysisbase.center_fwhm_bymoments(signal)

Estimate the center and full-width half max of a signal using moments

Low-Level Classes

class nmrglue.analysis.analysisbase.gauss1D

Gaussian (normal) lineshape class

Parameters (mu,sigma):

• mu mean (center of mean)
• sigma variance (width of distribution)

class nmrglue.analysis.analysisbase.peak1D

Peak lineshape class

This is really a gaussian lineshape which takes a center,fwhm as parameters

class nmrglue.analysis.analysisbase.lorentz1D

Lorentzian lineshape class

Parameters (x0,g):

• x0 the center of the lorentzian.
• gamma the scale parameter .

class nmrglue.analysis.analysisbase.scale1D

One dimensional scale class

Simulates a lineshape with functional form:

1.0,a0,a1,a2,....

Where a0, a1, ... are the parameters provided.

class nmrglue.analysis.analysisbase.ndwindow(shape, wsize)

An N-dimentional iterator to slice arrays into windows.

Given the shape of an array and a window size, an ‘ndwindow’ instance iterators over tuples of slices which slice an the array into wsize sub-arrays. At each iteration, the index of the center of the sub-array is incremented by one along the last dimension. Array border are ignored so the resulting sub-array can be smaller than wsize. If wsize contains even values the window is off center containing an additional point with lower index.

Parameters

• size Size of array to generate tuples of slices from.
• wsize Size of the area to select from array (sub-array maximum size).

Example:

>>> a = np.arange(12).reshape(3,4)
>>> for s in ndwindow(a.shape,(3,3))
...     print a[s]
[[0 1]
 [4 5]]
[[0 1 2]
 [4 5 6]]
[[1 2 3]
 [5 6 7]]
[[2 3]
 [6 7]]
[[0 1]
 [4 5]
 [8 9]]
[[ 0  1  2]
 [ 4  5  6]
 [ 8  9 10]]
...

class nmrglue.analysis.analysisbase.ndwindow_index(shape, wsize)

An N-dimensional interator object which returns the index of the window center and a ndwindow slice array.

Equivalent to:

for slices,index in zip(np.ndindex(shape),ndwindow(shape,wshape)):

return (index,slice)

class nmrglue.analysis.analysisbase.ndwindow_inside(shape, wsize)

An N-dimentional iterator to slice arrays into uniform size windows.

Given the shape of an array and a window size, an ‘ndwindow_inside’ instance iterators over tuples of slices which slice an the array into uniform size wsize sub-arrays. At each iteration, the index of the top left of the sub-array is incremented by one along the last dimension utill the windows would extend past the array border. All sub-arrays are equal sized (wsize).

Parameters:

• size Size of array to generate tuples of slices from.
• wsize Size of the area to select from array (widow size).

Example:

>>> a = np.arange(9).reshape(3,3)
>>> for s in ndwindow_inside(a.shape,(2,2):
...     print a[s]
[[0 1]
 [4 5]]
[[1 2]
 [5 6]]
[[2 3]
 [6 7]]
[[4 5]
 [8 9]]
[[ 5  6]
 [ 9 10]]
[[ 6  7]
 [10 11]]

class nmrglue.analysis.analysisbase.ndwindow_inside_index(shape, wsize)

An N-dimensional interator object which returns the index of the window top-left and a ndwindow_inside slice array.

Similar to ndwindow_index but reports top left index of window.