To visualize earthquake data using dask, we can use dask.array to create a scatter plot of earthquake locations, with the magnitude of each earthquake represented by the color of the point.
Here's an example of how to create a scatter plot of earthquake data using dask:
import dask.array as daimport matplotlib.pyplot as pltwith h5py.File('earthquake_data.h5', 'r') as f: latitude = da.from_array(f['latitude'], chunks='auto') longitude = da.from_array(f['longitude'], chunks='auto') magnitude = da.from_array(f['magnitude'], chunks='auto')plt.scatter(longitude.compute(), latitude.compute(), c=magnitude.compute(), cmap='magma')plt.xlabel('Longitude')plt.ylabel('Latitude')plt.colorbar(label='Magnitude')plt.show() |
In this example, we use da.from_array() to create dask arrays from the latitude, longitude, and magnitude datasets in the HDF5 file. We pass chunks='auto' to let dask determine the optimal chunk size based on the size of the data.
We then use plt.scatter() to create a scatter plot of earthquake locations, with the magnitude of each earthquake represented by the color of the point. We pass longitude.compute() and latitude.compute() to compute the NumPy arrays for longitude and latitude, and magnitude.compute() to compute the NumPy array for the magnitude. We use plt.colorbar() to add a colorbar to the plot.
This code will produce a scatter plot of earthquake locations, with the magnitude of each earthquake represented by the color of the point. The colormap used is 'magma', which is a popular choice for visualizing earthquake data.