wmm-calculator 1.4.4

WMM Python module

This is a Python implementation of the latest World Magnetic Model(WMM) by the Cooperative Institute For Research in Environmental Sciences (CIRES), University of Colorado. The World Magnetic Model (WMM) is the standard model for navigation, attitude, and heading referencing systems that use the geomagnetic field.

A new version of the model is updated every five years to address changes in Earth’s magnetic field. The current version (WMM2025) was released on December 17, 2024, and will remain valid until late 2029.

For more information about the WMM model, please visit WMM website.

NCEI also developed the World Magnetic Model High Resolution (WMMHR), an advanced magnetic field model with more comprehensive data on the geomagnetic fields than the original World Magnetic Model.

The Python API for WMMHR: https://pypi.org/project/wmmhr/

Table of contents

• Installation

• Outputs

• WMM Python API Quick Start

• WMM Python API Reference

  • wmm_calc(nmax=12)
  • wmm_calc.setup_time
  • wmm_calc.setup_env
  • wmm_calc.get_uncertainty
  • Get magnetic elements

• Contacts and contributing to WMM

Installation

The recommended way to install wmm-calculator is via pip

pip install wmm-calculator 

Outputs

It will output the magnetic components(X, Y, Z, H, F, I and D, dX, dY, dZ, dD, dI, dH, dF) and its uncertainty value. To get the detail of the outputs, please see Description of the WMM magnetic components

WMM Python API Quick Start

WARNING: Input arrays of length 3,000,000 require ~ 16GB of memory. However, all input vectors must have the same length.

Get magnetic components

Set up the time and latitude and longtitude and altitude for the WMM model

from wmm import wmm_calc
model = wmm_calc()
lat = [23.35, 24.5]
lon = [40, 45]
alt = [21, 21]

year = [2025, 2026]
month = [12, 1]
day = [6, 15]

# set up time
model.setup_time(year, month, day)
# set up the coordinates
model.setup_env(lat, lon, alt)

Get all of the geomagnetic elements

mag_map = model.get_all()
print(model.get_all())

It will return

{'x': array([33805.9794844 , 33492.10462007]), 'y': array([2167.06741335, 1899.8602046 ]), 'z': array([23844.95317237, 26150.62563705]), 'h': array([33875.36612457, 33545.94671013]), 'f': array([41426.10555998, 42534.52435243]), 'dec': array([3.6678175, 3.2466589]), 'inc': array([35.14180823, 37.93807267]), 'dx': array([ 9.91215814, 14.60583551]), 'dy': array([-2.63505666, -4.26437959]), 'dz': array([40.35078867, 34.39738965]), 'dh': array([ 9.72328589, 14.34088148]), 'df': array([31.17702034, 32.45814375]), 'ddec': array([-0.00552022, -0.00868461]), 'dinc': array([0.03789554, 0.02466632])}

Get uncertainty value

print(model.get_uncertainty())

{'x_uncertainty': 137, 'y_uncertainty': 89, 'z_uncertainty': 141, 'h_uncertainty': 133, 'f_uncertainty': 138, 'declination_uncertainty': array([7.67519380e-06, 7.75056379e-06]), 'inclination_uncertainty': 0.2}

WMM Python API Reference

1. Change the resolution(max degree) of the model

wmm_calc(nmax=12)

The default maximum degree for WMM is 12. Users allow to assign the max degree from 1 to 12 to WMM Python API.

from wmm import wmm_calc
model = wmm_calc(nmax=10)

2. Set up time

setup_time(self, year: Optional[np.ndarray] = None, month: Optional[np.ndarray] = None, day: Optional[np.ndarray] = None, dyear: Optional[np.ndarray] = None):

If users don't call or assign any value to setup_time(), the current time will be used to compute the model. Either by providing year, month, day or deciaml year. When passing the decimal year, please pass the decimal year as float point or array to dyear

from wmm import wmm_calc
model = wmm_calc()
model.setup_time(2024, 12, 30)

or

from wmm import wmm_calc
model = wmm_calc()
model.setup_time(dyear=2025.1)

User allow to assign the date from "2024-11-13" to "2030-01-01"

3. Set up the coordinates

setup_env(self, lat: np.ndarray, lon: np.ndarray, alt: np.ndarray, unit: str = "km", msl: bool = False)

from wmm import wmm_calc
model = wmm_calc()
lat, lon, alt = 50.3, 100.4, 0
model.setup_env(lat, lon, alt, unit="m")

The default unit and type of altitude is km and default in GPS(ellipsoid height). Assign the parameter for unit and msl, if the latitude is not in km or in mean sea level. "m" for meter and "feet" for feet. For example,

from wmm import wmm_calc
model = wmm_calc()
lat, lon, alt = 50.3, 100.4, 0
model.setup_env(lat, lon, alt, unit="m", msl=True)

4. Get the geomagnetic elements

wmm_calc.get_all()

After setting up the time and coordinates for the WMM model, you can get all the geomagnetic elements by

from wmm import wmm_calc
model = wmm_calc()
lat, lon, alt = 50.3, 100.4, 0
year, month, day = 2025, 3, 30
model.setup_env(lat, lon, alt, unit="m", msl=True)
model.setup_time(year, month, day)
mag_map = model.get_all()

which will return all magnetic elements in dict type.

Get single magnetic elements by calling

for example,

from wmm import wmm_calc
model = wmm_calc()
lat, lon, alt = 50.3, 100.4, 0
year, month, day = 2025, 3, 30
model.setup_env(lat, lon, alt, unit="m", msl=True)
model.setup_time(year, month, day)
mag_map = model.get_Bh()

5. Get uncertainty value

wmm_calc.get_uncertainty()

The WMM Python API includes an error model that providesing uncertainty estimates for every geomagnetic element (X, Y, Z, H, F, I and D) and every location at Earth's surface.

For more infromation about the error model, please visit World Magnetic Model Accuracy, Limitations, and Error Model

model = wmm_calc()
lat = [80.,  0., 80.]
lon = [  0., 120.,   0.]
alt = [0., 0., 0.]
dyear = [2025.,  2025.,  2027.5]

# set up time
model.setup_time(dyear=dyear)
# set up the coordinates
model.setup_env(lat, lon, alt)
print(model.get_uncertainty())

It will return

{'x_uncertainty': 137, 'y_uncertainty': 89, 'z_uncertainty': 141, 'h_uncertainty': 133, 'f_uncertainty': 138, 'declination_uncertainty': array([3.98575493e-05, 6.55276509e-06, 3.99539341e-05]), 'inclination_uncertainty': 0.2}

Contacts and contributing to WMM:

If you have any questions, please email geomag.models@noaa.gov, submit issue or pull request at https://github.com/CIRES-Geomagnetism/wmm.