Create a Global Map and Polar Views

Compute a map of the first time-derivative of the radial field component on the core surface in 2016 using CHAOS.

Out:

/home/docs/checkouts/readthedocs.org/user_builds/chaosmagpy/checkouts/master/chaosmagpy/chaos.py:2437: UserWarning: Missing calibration parameters: 'pp_CAL'
  warnings.warn(f'Missing calibration parameters: {err}')

import chaosmagpy as cp
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import cartopy.crs as ccrs

model = cp.CHAOS.from_mat('CHAOS-6-x9.mat')  # load the mat-file of CHAOS-6-x9

time = cp.data_utils.mjd2000(2016, 1, 1)  # convert date to mjd2000
radius = 3485.  # radius of the core surface in km
theta = np.linspace(1., 179., 181)  # colatitude in degrees
phi = np.linspace(-180., 180, 361)  # longitude in degrees

# compute radial SV up to degree 16 using CHAOS
B, _, _ = model.synth_values_tdep(time, radius, theta, phi,
                                  nmax=16, deriv=1, grid=True)

limit = 30e3  # nT colorbar limit

# create figure
fig = plt.figure(figsize=(12, 8))

fig.subplots_adjust(
    top=0.98,
    bottom=0.02,
    left=0.013,
    right=0.988,
    hspace=0.0,
    wspace=1.0
)

# make array of axes
gs = gridspec.GridSpec(2, 2, width_ratios=[0.5, 0.5], height_ratios=[0.35, 0.65])

axes = [
    plt.subplot(gs[0, 0], projection=ccrs.NearsidePerspective(central_latitude=90.)),
    plt.subplot(gs[0, 1], projection=ccrs.NearsidePerspective(central_latitude=-90.)),
    plt.subplot(gs[1, :], projection=ccrs.Mollweide())
]

for ax in axes:
    pc = ax.pcolormesh(phi, 90. - theta, B, cmap='PuOr', vmin=-limit,
                       vmax=limit, transform=ccrs.PlateCarree())
    ax.gridlines(linewidth=0.5, linestyle='dashed',
                 ylocs=np.linspace(-90, 90, num=7),  # parallels
                 xlocs=np.linspace(-180, 180, num=13))  # meridians
    ax.coastlines(linewidth=0.5)

# inset axes into global map and move upwards
cax = inset_axes(axes[-1], width="45%", height="5%", loc='upper center',
                 borderpad=-12)

# use last artist for the colorbar
clb = plt.colorbar(pc, cax=cax, extend='both', orientation='horizontal')
clb.set_label('nT/yr', fontsize=14)

plt.show()