[DEPRECATED] Magnetic data from Rio de Janeiro
Note
Click here to download the full example code
[DEPRECATED] Magnetic data from Rio de JaneiroΒΆ
Warning
All sample datasets in Verde are deprecated and will be removed in Verde v2.0.0. The tutorials/examples will transition to using Ensaio instead.
We provide sample total-field magnetic anomaly data from an airborne survey of
Rio de Janeiro, Brazil, from the 1970s. The data are made available by the
Geological Survey of Brazil (CPRM) through their GEOSGB portal. See the documentation for
verde.datasets.fetch_rio_magnetic for more details.
Out:
/usr/share/miniconda3/envs/test/lib/python3.9/site-packages/verde/datasets/sample_data.py:209: FutureWarning: The Rio magnetic anomaly dataset is deprecated and will be removed in Verde v2.0.0. Use a different dataset instead.
warnings.warn(
longitude latitude ... line_type line_number
0 -42.590424 -22.499878 ... LINE 2902
1 -42.590485 -22.498978 ... LINE 2902
2 -42.590530 -22.498077 ... LINE 2902
3 -42.590591 -22.497177 ... LINE 2902
4 -42.590652 -22.496277 ... LINE 2902
[5 rows x 6 columns]
/usr/share/miniconda3/envs/test/lib/python3.9/site-packages/verde/datasets/sample_data.py:242: FutureWarning: The Rio magnetic anomaly dataset is deprecated and will be removed in Verde v2.0.0. Use a different dataset instead.
warnings.warn(
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import verde as vd
# The data are in a pandas.DataFrame
data = vd.datasets.fetch_rio_magnetic()
print(data.head())
# Make a Mercator map of the data using Cartopy
crs = ccrs.PlateCarree()
plt.figure(figsize=(7, 5))
ax = plt.axes(projection=ccrs.Mercator())
ax.set_title("Total-field Magnetic Anomaly of Rio de Janeiro")
# Since the data is diverging (going from negative to positive) we need to
# center our colorbar on 0. To do this, we calculate the maximum absolute value
# of the data to set vmin and vmax.
maxabs = vd.maxabs(data.total_field_anomaly_nt)
# Cartopy requires setting the projection of the original data through the
# transform argument. Use PlateCarree for geographic data.
plt.scatter(
data.longitude,
data.latitude,
c=data.total_field_anomaly_nt,
s=1,
cmap="seismic",
vmin=-maxabs,
vmax=maxabs,
transform=crs,
)
plt.colorbar(pad=0.01).set_label("nT")
# Set the proper ticks for a Cartopy map
vd.datasets.setup_rio_magnetic_map(ax)
plt.show()
Total running time of the script: ( 0 minutes 0.796 seconds)