GitLocker: The Coding Marketplace

Description:

pyMSHRF 0.0.2

pyMSHRF - HRF Calculator for GC/MS annotation
Theoritical Background
High-resolution filtering (HRF) approach is both feasible and highly specific toward correct identifications, which bridges the gap between unit resolution GC/MS spectra and accurate mass data dubious. (ref)
How to use this package
Installation
pyMSHRF requires Python 3+ and is unfortunately not compatible with Python 2. If you are still using Python 2, a clever workaround is to install Python 3 and use that instead.
The easiest way of installing pyISOPACh is using pip:
pip install pyMSHRF

Usage of HRF calculation function
import pyMSHRF

formula = 'C5H7N3O2'
peaks_query = np.array([[191.09071, 14670.0], [124.05742, 3543.0], [141.09334, 6191.0]], dtype = np.float32)

# Calculate HRF score
HRF_score = pyMSHRF.HRF(formula, peaks_query, delta_da = 0.02)
print(f"HRF score is {HRF_score}.")

Calculate the reverse high-resolution filtering (RHRF) score need reference spectrum:
peaks_reference = np.array([[82, 6.99], [141, 999.0], [124, 562.49]], dtype = np.float32)

# Calculate RHRF score
RHRF_score = pyMSHRF.RHRF(formula, peaks_query, peaks_reference, delta_da = 0.02)
print(f"RHRF score is {RHRF_score}.")

Useful functions
Reading Spectra from a File
For ease of use, a function named read_one_spectrum is provided in the pyMSHRF package, allowing you to easily read spectra from a file.(ref) Here is an example of how you can use it:
import pyMSHRF

# Load all spectra from file into python
spectra_list = list(pyMSHRF.read_one_spectrum('path/to/spectrum/file'))

# Get spectrum peak list
for spectrum in spectra_list:
query_spec = spectrum['peaks']

This function returns a dictionary, where each key-value pair corresponds to a specific metadata of the spectrum.
Currently, the read_one_spectrum function supports the following file formats: .mgf, .msp, .mzML, and .lbm2.
License
Code released under the MIT license.