Lazy dask plotting

[ahuang11]

Some related posts

Larger than memory plotting: how to set initial slice to plot

Okay, I think this works import h5py import numpy as np import panel as pn import xarray as xr import holoviews as hv import dask.array as da from holoviews.operation.datashader import rasterize, shade hv.extension('bokeh', logo=False) f = h5py.File('data.h5', "r") full_data = da.from_array(f['data'], chunks=(60*60, 2401), name=False) da = xr.DataArray( full_data, dims=("x", "y"), coords={"x": np.arange(full_data.shape[0]), "y": np.arange(full_data.shape[1])}, ) class BigSpectrogr…

How to plot a huge image out of memory?

It loads the entire dataset before doing anything (and crashes), so I was wondering if it could just skip every 10 at farthest zoom (e.g. is there a decimate function for datashader outside of hv)? import numpy as np import dask.array as da import xarray as xr from datashader import transfer_functions as tf def sample(range_=(0.0,2.4)): xs = da.arange(700000, dtype=np.float32) ys = da.arange(280000, dtype=np.float32) return xr.DataArray( da.random.random((len(ys), len(xs)),…

Also, perhaps converting to zarr format can help