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Using the dataset ds defined below how can I attribute one colormap and its associated range per value of channels when rendering the holomap?

import numpy as np
import holoviews as hv
from holoviews import opts
hv.extension('bokeh', 'matplotlib')

data = np.random.rand(100, 100, 3,20)
times = np.arange(0,10,.5)
channels = ['a','b','c']
ds = hv.Dataset((times,channels,
                 np.linspace(0., 1., 100),
                 np.linspace(0., 1., 100),
                 data),
                kdims=['t', 'channel', 'y', 'x'],
                vdims=hv.Dimension('T', range=(0, .9)))
opts.defaults(
    opts.GridSpace(shared_xaxis=True, shared_yaxis=True),
    opts.Image(cmap='jet', width=300, height=300,colorbar=True,),)
ds.to(hv.Image, ['y', 'x'])
paugam
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1 Answers1

1

here is a solution that uses xarray to manage the dataset. 

import numpy as np
import holoviews as hv
from holoviews import opts
import param
import panel as pn
import panel.widgets as pnw
import xarray as xr
hv.extension('bokeh', 'matplotlib')

data = np.random.rand(10, 3, 100, 100)
times = np.arange(0,10)
channels=['a','b','c']

da = xr.DataArray(
        data,
        [
            ("t", times),
            ("c", channels),
            ("y", np.linspace(0., 1., 100)),
            ("x", np.linspace(0., 1., 100)),
         ],
         )
ds = da.to_dataset(name="T")

class Parameters(param.Parameterized):

    select_channel = param.Selector(default=channels[0], objects=channels)
    select_time =    param.Integer(default=int(times[0]), bounds=(0, int(len(times)-1) ) )    

    @param.depends('select_time','select_channel')

    def plots(self):

        if self.select_channel == channels[0]:
            img = hv.Image(hv.Dataset(ds.loc[dict(c=self.select_channel,t=self.select_time)]))
            cmap = 'inferno'

        elif self.select_channel == channels[1]:
            img = hv.Image(hv.Dataset(ds.loc[dict(c=self.select_channel,t=self.select_time)]))
            cmap = 'jet'  

        else:
            img = hv.Image(hv.Dataset(ds.loc[dict(c=self.select_channel,t=self.select_time)]))
            cmap = 'gray'


        frame_width = 500 
        return img.opts( cmap=cmap, 
                         frame_width=frame_width, 
                         frame_height=np.int(np.round(frame_width * ds.dims['y']/ds.dims['x'],0)),
                         framewise=False, axiswise=False, colorbar=False, aspect='equal',
                         fontsize={'title': 16,})

obj = Parameters()

fire_dmap = hv.DynamicMap(obj.plots)
widgets_parameters = pn.panel(obj.param, parameters=['select_channel','select_time'],width=200)
app = pn.Row(widgets_parameters, fire_dmap)
app
paugam
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