Shaded Plot Image

[S-Hanly]

This would require datashader, including this isn't a "need," curious people's thoughts?

import datashader as ds
import datashader.transfer_functions as tf
import xarray as xr
from collections import OrderedDict

def datashader_large_time(df,height=300,width=900):
  """Use datashader to render an image off a large time series"""
  if isinstance(df.index, pd.DatetimeIndex):
    floats = df.index.values.astype(float)/ 1E9
    df.index = floats-floats[0]
    df.index.name = 'timestamp'

  x_range = (df.index[0], df.index[-1])
  y_range = (df.min(axis=1).min(), 1.2*df.max(axis=1).max())

  cvs = ds.Canvas(x_range=x_range, y_range=y_range, plot_height=height, plot_width=width)
  
  cols = df.columns
  aggs = OrderedDict((c, cvs.line(df.reset_index(), df.index.name, c)) for c in cols)

  imgs = [tf.shade(aggs[i]) for i in cols]
  
  renamed = [aggs[key].rename({key: 'value'}) for key in aggs]
  merged = xr.concat(renamed, 'cols')
  total = tf.shade(merged.sum(dim='cols'), how='linear')

  return imgs, total

def shaded_plot(df,height=300,width=900):
  imgs, total = datashader_large_time(df,height=height,width=width)
  fig = px.imshow(total,
                  color_continuous_scale  =[[0.0, '#6914F0'],
                                            [0.2, '#3764FF'],
                                            [0.4, '#2DB473'],
                                            [0.6, '#FAC85F'],
                                            [0.8, '#EE7F27'],
                                            [1, 'rgba(255,255,255,0)'] ], 
                  origin='lower')
  fig.update_layout(
      width=width+80*2,
      height=height+180 )
  return fig

[S-Hanly]

I'm going to close this because if we just plot a line plot with vertical lines you get the same effect and it is easier & more intuitive.

See #13

[S-Hanly]

Here is a figure from a dataframe with over 6 million rows

This is a zoomed in view to get a sense of what is happening.