Changelog

Changes in v2.3.0

All functions, classes and methods now have PEP 484 type hints. Contributed by Chris Davis-Foster in #4
All modules now implement __all__ to limit the objects imported when using * imports.

Removed the following deprecated functions:

Removed object	Suggested replacement
`pyms.Experiment.Experiment.get_expr_code()`	`pyms.Experiment.Experiment.expr_code()`
`pyms.Experiment.Experiment.get_peak_list()`	`pyms.Experiment.Experiment.peak_list()`
`pyms.Experiment.Experiment.store()`	`pyms.Experiment.Experiment.dump()`
`pyms.Experiment.store_expr()`	`pyms.Experiment.Experiment.dump()`
`pyms.GCMS.Class.GCMS_data.get_scan_list()`	`pyms.GCMS.Class.GCMS_data.scan_list()`
`pyms.GCMS.Class.GCMS_data.get_tic()`	`pyms.GCMS.Class.GCMS_data.tic()`
`pyms.Gapfill.Class.MissingPeak.get_common_ion()`	`pyms.Gapfill.Class.MissingPeak.common_ion()`
`pyms.Gapfill.Class.MissingPeak.get_common_ion_area()`	`pyms.Gapfill.Class.MissingPeak.common_ion_area`
`pyms.Gapfill.Class.MissingPeak.get_exact_rt()`	`pyms.Gapfill.Class.MissingPeak.exact_rt()`
`pyms.Gapfill.Class.MissingPeak.get_qual_ion1()`	`pyms.Gapfill.Class.MissingPeak.qual_ion1()`
`pyms.Gapfill.Class.MissingPeak.get_qual_ion2()`	`pyms.Gapfill.Class.MissingPeak.qual_ion2()`
`pyms.Gapfill.Class.MissingPeak.get_rt()`	`pyms.Gapfill.Class.MissingPeak.rt()`
`pyms.Gapfill.Class.MissingPeak.set_common_ion_area()`	`pyms.Gapfill.Class.MissingPeak.common_ion_area`
`pyms.Gapfill.Class.MissingPeak.set_exact_rt()`	`pyms.Gapfill.Class.MissingPeak.exact_rt`
`pyms.Gapfill.Class.Sample.get_missing_peaks()`	`pyms.Gapfill.Class.Sample.missing_peaks()`
`pyms.Gapfill.Class.Sample.get_mp_rt_area_dict()`	`pyms.Gapfill.Class.Sample.rt_areas()`
`pyms.Gapfill.Class.Sample.get_name()`	`pyms.Gapfill.Class.Sample.name()`
`pyms.Gapfill.Function.transposed()`
`pyms.IonChromatogram.IonChromatogram.get_mass()`	`pyms.IonChromatogram.IonChromatogram.mass()`
`pyms.IonChromatogram.IonChromatogram.get_time_step()`	`pyms.IonChromatogram.IonChromatogram.time_step()`
`pyms.IonChromatogram.IonChromatogram.set_intensity_array()`	`pyms.IonChromatogram.IonChromatogram.intensity_array()`
`pyms.Mixins.MaxMinMassMixin.get_max_mass()`	`pyms.Mixins.MaxMinMassMixin.max_mass()`
`pyms.Mixins.MaxMinMassMixin.get_min_mass()`	`pyms.Mixins.MaxMinMassMixin.min_mass()`
`pyms.Mixins.MassListMixin.get_mass_list()`	`pyms.Mixins.MassListMixin.mass_list()`
`pyms.Mixins.TimeListMixin.get_time_list()`	`pyms.Mixins.TimeListMixin.time_list()`
`pyms.Mixins.IntensityArrayMixin.get_intensity_array()`	`pyms.Mixins.IntensityArrayMixin.intensity_array()`
`pyms.Mixins.IntensityArrayMixin.get_matrix_list()`	`pyms.Mixins.IntensityArrayMixin.intensity_array_list()`
`pyms.Peak.Class.Peak.get_area()`	`pyms.Peak.Class.Peak.area()`
`pyms.Peak.Class.Peak.get_ic_mass()`	`pyms.Peak.Class.ICPeak.ic_mass()`
`pyms.Peak.Class.Peak.get_ion_areas()`	`pyms.Peak.Class.Peak.ion_areas()`
`pyms.Peak.Class.Peak.get_mass_spectrum()`	`pyms.Peak.Class.Peak.mass_spectrum()`
`pyms.Peak.Class.Peak.get_pt_bounds()`	`pyms.Peak.Class.Peak.bounds()`
`pyms.Peak.Class.Peak.get_rt()`	`pyms.Peak.Class.Peak.rt()`
`pyms.Peak.Class.Peak.get_UID()`	`pyms.Peak.Class.Peak.UID()`
`pyms.Peak.Class.Peak.set_area()`	`pyms.Peak.Class.Peak.area()`
`pyms.Peak.Class.Peak.set_ic_mass()`	`pyms.Peak.Class.ICPeak.ic_mass()`
`pyms.Peak.Class.Peak.set_ion_areas()`	`pyms.Peak.Class.Peak.ion_areas()`
`pyms.Peak.Class.Peak.set_mass_spectrum()`	`pyms.Peak.Class.Peak.mass_spectrum()`
`pyms.Peak.Class.Peak.set_pt_bounds()`	`pyms.Peak.Class.Peak.pt_bounds`
`pyms.Utils.Utils.is_positive_int()`
`pyms.Utils.Utils.is_list_of_dec_nums()`

Renamed pyms.Gapfill.Function.file2matrix() to pyms.Gapfill.Function.file2dataframe(). The function now returns a Pandas DataFrame.
Split pyms.IntensityMatrix.IntensityMatrix into two classes: pyms.IntensityMatrix.BaseIntensityMatrix and pyms.IntensityMatrix.IntensityMatrix. This makes subclassing easier.
Split pyms.Peak.Class.Peak into three classes: pyms.Peak.Class.AbstractPeak, pyms.Peak.Class.Peak, pyms.Peak.Class.ICPeak. ICPeak is returned when a mass is passed to the Peak constructor instead of a mass spectrum.

Added the following functions and classes:

`pyms.Gapfill.Function.MissingPeakFiletype`(value)	Flag to indicate the filetype for `pyms.Gapfill.Function.missing_peak_finder()`.
`pyms.IntensityMatrix.AsciiFiletypes`(value)	Enumeration of supported ASCII filetypes for `export_ascii()`.
`pyms.IntensityMatrix.IntensityMatrix.bpc`	Constructs a Base Peak Chromatogram from the data.
`pyms.IonChromatogram.IonChromatogram.is_eic`()	Returns whether the ion chromatogram is an extracted ion chromatogram (EIC).
`pyms.IonChromatogram.IonChromatogram.is_bpc`()	Returns whether the ion chromatogram is a base peak chromatogram (BPC).
`pyms.IonChromatogram.ExtractedIonChromatogram`(…)	Models an extracted ion chromatogram (EIC).
`pyms.IonChromatogram.BasePeakChromatogram`(…)	Models a base peak chromatogram (BPC).
`pyms.Spectrum.array_as_numeric`(array)	Convert the given numpy array to a numeric data type.
`pyms.Utils.Utils.is_path`(obj)	Returns whether the object represents a filesystem path.
`pyms.Utils.Utils.is_sequence`(obj)	Returns whether the object is a `Sequence`, and not a string.
`pyms.Utils.Utils.is_sequence_of`(obj, of)	Returns whether the object is a `Sequence`, and not a string, of the given type.
`pyms.Utils.Utils.is_number`(obj)	Returns whether `obj` is a numerical value (`int`, :class`float` etc).
`pyms.eic`	Class to model a subset of data from an Intensity Matrix.

The ia parameter of pyms.IonChromatogram.IonChromatogram` was renamed to intensity_list.

Changes in v2.2.22-beta2

pyms.Spectrum.Scan and pyms.Spectrum.MassSpectrum can now accept any values for mass and intensity that that can be converted to a float or int. This includes strings representing numbers. Previously only int and float values were permitted.
If the mass and intensity values supplied to a pyms.Spectrum.Scan or a pyms.Spectrum.MassSpectrum are float, int, or a data type derived from numpy.number, the data is stored in that type. For other data types, such as strings, decimal.Decimal etc., the data is stored as float.

If the data contains values in mixed types then, in most cases, all values will be converted to float. If you wish to control this behaviour you should construct a numpy.ndarray with the desired type. See https://numpy.org/devdocs/user/basics.types.html for a list of types.
A TypeError is no longer raised when creating a pyms.Spectrum.Scan or a pyms.Spectrum.MassSpectrum with a float, int etc. rather than a sequence. Instead, value is treated as being the sole element in a list.
Passing a non-numeric string or a list of non-numeric strings to pyms.Spectrum.Scan or pyms.Spectrum.MassSpectrum now raises a ValueError and not a TypeError as in previous versions.
pyms.Peak.Class.Peak.ion_areas() now accepts dictionary keys as float as well as int.

Changes in v2.2.22-beta1

ANDI_reader() and pyms.Spectrum.Scan were modified to allow ANDI-MS files to be read if the data either:
- had the m/z data stored from highest m/z to lowest; or
- contained 0-length scans.