pyMSpec.pyisocalc package

Subpackages

• pyMSpec.pyisocalc.canopy package
  • Submodules
  • pyMSpec.pyisocalc.canopy.sum_formula module
  • pyMSpec.pyisocalc.canopy.sum_formula_actions module
  • Module contents

Submodules

pyMSpec.pyisocalc.periodic_table module

pyMSpec.pyisocalc.pyisocalc module

class pyMSpec.pyisocalc.pyisocalc.Element(id)

Bases: object

An element from the periodic table.

average_mass()

Return the average mass of this element, that is the dot product of its masses and ratios. :rtype: float

charge()

Return the atomic charge of this element. :rtype: int

mass_ratios()

Return the probability of each isotope, ordered by the isotope’s atomic mass. :rtype: sequence

masses()

Return the masses of all possible isotopes in ascending order.

Return type:sequence

name()

Return the element symbol as a string.

number()

Return the atomic number of this element in the periodic table. :rtype: int

class pyMSpec.pyisocalc.pyisocalc.FormulaSegment(element, amount)

Bases: object

A segment from an expanded molecular sum formula.

A segment is a single element together with its number of occurrences within a molecule. For example, the molecule ‘H20’ would consist of the segments (‘H’, 2) and (‘O’, 1).

amount()

Return the amount of the element.

average_mass()

The element’s average mass multiplied by its amount.

charge()

The element’s charge multiplied by its amount.

element()

Return the chemical element.

class pyMSpec.pyisocalc.pyisocalc.SumFormula(segments)

Bases: object

A molecular sum formula, built up from FormulaSegments. Use parseSumFormula to parse your string representation into a SumFormula object.

To get the expanded string representation of this object, use str().

average_mass()

The sum of the average masses of its segments. :rtype: float

charge()

The sum of the charges of its segments. :rtype: int

get_segments()

Return the sequence of segments of which this sum formula consists. :rtype: tuple

pyMSpec.pyisocalc.pyisocalc.apply_gaussian(ms_input, sigma, pts_per_mz=10, exact=True)

Smooth every peak into a gaussian shape using instrument-specific configuration.

Parameters:

• ms_input (MassSpectrum) – the mass spectrum
• sigma – sigma parameter for Gaussian. See fwhm_to_sigma
• pts_per_mz (int) – Number of points per one mz unit for the regular grid
• exact – if False, this function may use an approximate implementation

Returns:

a new mass spectrum containing the smoothed data in both profile and centroid mode

pyMSpec.pyisocalc.pyisocalc.cartesian(rx, mx, threshold=0.0001)

pyMSpec.pyisocalc.pyisocalc.cartesian(rx, mx, threshold)

Combine multiple isotope patterns into a single one.

Parameters:

• rx (Sequence[ndarray]) – Sequence of ratio arrays
• mx (Sequence[ndarray]) – Sequence of mass arrays
• threshold – threshold below which the resulting ratios are filtered out

Returns:

The resulting ratio array and the mass array

Return type:

Tuple[ndarray]

pyMSpec.pyisocalc.pyisocalc.complete_isodist(sf, sigma=0.001, cutoff_perc=0.1, charge=None, pts_per_mz=10000, centroid_func=<function gradient>, centroid_kwargs=None)

Wrapper function for applying perfect_pattern, then gen_gaussian and eventually centroid detection.

Parameters:

• sf – the sum formula
• sigma (float) – Full width at half maximum
• cutoff_perc (float) – min percentage of the maximum intensity to return, max value = 100
• charge (int) – charge of the molecule
• pts_per_mz – Number of points per mz for the regular grid
• centroid_func – the centroid function to apply to the isotope pattern or None if no centroid detection

should be performed. Must have the same signature as centroid_detection.gradient. :param centroid_kwargs: dict to pass to centroid_func as optional parameters :return:

pyMSpec.pyisocalc.pyisocalc.fwhm_to_sigma(min_x, max_x, fwhm)

When fitting an isotope pattern to a gaussian distribution, this function calculates the standard deviation sigma for the gaussian distribution.

Parameters:

• min_x – the lowest m/z value
• max_x – the highest m/z value
• fwhm – the full width at half maximum

Returns:

Sigma

Return type:

float

Throws ValueError:  

if min_x > max_x or if not all inputs are greater than 0

pyMSpec.pyisocalc.pyisocalc.gen_approx_gaussian(ms, sigma, pts, n=20)

Approximate and faster version of gen_gaussian

Parameters:ms – the isotope pattern as a MassSpectrum object Returns:the smoothed pattern Return type:Tuple[ndarray] Throws ValueError:  if sigma or pts are not greater than 0 Throws TypeError:  if pts is not an integer

pyMSpec.pyisocalc.pyisocalc.gen_gaussian(ms, sigma, pts)

Transform each peak in an isotope pattern into a gaussian curve.

Each of the curves is scaled up to the intensity value for the corresponding m/z. The output will be on a regular grid with pts points, starting from min_mz - 1, up to max_mz + 1, where min_mz is the lowest m/z value and max_mz is the highest m/z value. Since each curve is rendered on the same grid, overlapping curves will add up.

Parameters:ms – the isotope pattern as a MassSpectrum object Returns:the smoothed pattern Return type:Tuple[ndarray] Throws ValueError:  if sigma or pts are not greater than 0 Throws TypeError:  if pts is not an integer

pyMSpec.pyisocalc.pyisocalc.normalize(m, n, charges, cutoff)

pyMSpec.pyisocalc.pyisocalc.parseSumFormula(string)

Parses string representation of a sum formula into a list of FormulaSegments

pyMSpec.pyisocalc.pyisocalc.perfect_pattern(sf, cutoff_perc=0.1, single_pattern_func=<function single_pattern_fft>, charge=None)

Compute the isotope pattern of a molecule given by its sum formula.

First applies single_pattern_func to each segment within the sum formula, then combines these individual patterns into a single one.

Parameters:

• sf (SumFormula) – the sum formula
• cutoff_perc (float) – min percentage of the maximum intensity to return, max value = 100
• single_pattern_func – the function to compute a single isotope pattern. Must have the same signature as

single_pattern_fft :param charge: charge of the molecule :type charge: int :return: the combined isotope pattern as a mass spectrum :rtype: MassSpectrum

pyMSpec.pyisocalc.pyisocalc.single_pattern_fft(segment, threshold=1e-09)

pyMSpec.pyisocalc.pyisocalc.single_pattern_fft(segment[, threshold=1e-9])

Calculates the isotope pattern of a single FormulaSegment using multidimensional fast fourier transform.

See ‘Efficient Calculation of Exact Fine Structure Isotope Patterns via the Multidimensional Fourier Transform’ (A. Ipsen, 2014).

Parameters:threshold (float) – Only intensities above this threshold will be part of the result. Must be a non-negative number Returns:the isotopic pattern as a MassSpectrum Return type:MassSpectrum

pyMSpec.pyisocalc.pyisocalc.total_points(min_x, max_x, points_per_mz)

Calculate the number of points for the regular grid based on the full width at half maximum.

Parameters:

• min_x – the lowest m/z value
• max_x – the highest m/z value
• points_per_mz – number of points per fwhm

Returns:

total number of points

Return type:

int

pyMSpec.pyisocalc.pyisocalc.trim(y, x)

pyMSpec.pyisocalc.pyisocalc.trim(y, x)

Remove duplicate elements in the second array and sum the duplicate values in the first one. This function returns an array containing the unique values from y and an array containing the values from x where its elements at the indexes of the duplicate elements in y have been summed.

Example:

>>> trim([5, 1, 2, 5], [1, 2, 2, 3])
(array([ 5.,  3.,  5.]), array([1, 2, 3]))

Parameters:

• y (Union[ndarray, Iterable]) – the array from which the values are summed
• x (Union[ndarray, Iterable]) – the array from which the duplicates are removed

Returns:

the trimmed y array and the trimmed x array

Return type:

Tuple[ndarray]

pyMSpec.pyisocalc.tools module

pyMSpec.pyisocalc.tools.make_sf_adduct_database(sum_formulae, adducts, output_filename, sigma=0.001, resolution=10000, charge=1)

pyMSpec.pyisocalc.tools.make_sf_adduct_optimusfilter(sum_formulae, adducts, output_filename, sigma=0.001, resolution=10000, charge=1)

pyMSpec.pyisocalc.tools.normalise_sf(sf_string)

Module contents