Conversion between units used in magnetism

Related tags

Deep Learningpythonconversionunitsmagnetismmagnetic
Overview

PyPI Version Supported Python Versions

convmag

Conversion between various units used in magnetism

The conversions between base units available are:

         T  <->  G         :    1e4
         T  <->  Oe        :    1e4
       A/m  <->  T         :    MU_0
       A/m  <->  G         :    1e4 * MU_0
         G  <->  Oe        :    1
       A/m  <->  Oe        :    1e4 * MU_0
  emu/cm^3  <->  T         :    1e3 * MU_0
erg/Oecm^3  <->  A/m       :    1e3
     emu/g  <->  Am^2/kg   :    1
     J/m^3  <->  GOe       :    1e8 * MU_0
     J/m^3  <->  erg/cm^3  :    1e1
  erg/cm^3  <->  GOe       :    1e7 * MU_0
      Am^2  <->  emu       :    1e3
      Am^2  <->  erg/G     :    1e3
      Am^2  <->  erg/Oe    :    1e3
       emu  <->  erg/G     :    1
       muB  <->  Am^2      :    MU_B
       muB  <->  emu       :    1e3 * MU_B
    muB/fu  <->  T         :    requires user input of lattice parameters

(the factors given above are for the forward conversion)

  • permeability of free space, MU_0 = 4 * 3.14159 * 1e-7 H/m (== Vs/Am)

  • Bohr magneton, MU_B = 9.274015e-24 Am^2 (muB is the unit string for conversions with Bohr magnetons)

The prefactors available for any base unit are: M (1e6), k (1e3), m (1e-3), ยต (1e-6)

You can combine prefactors and base units to give e.g. MA/m or kJ/m^3


Installation:

Pip

You can install the current release (0.0.3) with pip:

    pip install convmag

Usage options:

  1. a console script is provided and should be located in the Scripts directory of your Python distribution after installation. If you have this directory in your Path (environment variable on Windows) you can start the program by typing "convmag" in the console. In this case only single values can be converted (at one time).

  2. the package can be imported into python and then you can pass numpy arrays into the function convert_unit(), making sure to keep the default verbose=False. That way many values can be converted at once. The converted values are returned as a numpy array for further processing.

    >>> import numpy as np
    >>> import convmag as cm
    
    >>> vals_in_T = np.arange(0,130,20)
    
    >>> vals_in_T
    array([  0,  20,  40,  60,  80, 100, 120])
   
    >>> vals_in_Oe = cm.convert_unit(vals_in_T, "T", "Oe", verbose=False)
    
    >>> vals_in_Oe
    array([      0.,  200000.,  400000.,  600000.,  800000., 1000000., 1200000.])

Pure python, no other dependencies.

Requires Python >= 3.6 because f-strings are used

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