Consider making `plotly` plot directly instead of converting from `ggplot` plot

[nmdefries]

There's some indication that plotly plots are faster to generate than making a ggplot2 plot and converting to plotly. Since plot creation and rendering is a slow part of the dashboard, meaning this switch could be a good way to provide overall speedups to the dashboard.

Most of the work has already been done on the ndefries/use-plotly-directly branch. Remaining tasks to match behavior of current dashboard:

• Add gray rectangle between faceted plots to display horizon info. Formatting info for rectangles and horizon labels:

# Horizon rectangles
str(finalPlot$x$layout$shapes, max.level = 2)
List of 4
$ :List of 9
..$ type     : chr "rect"
..$ fillcolor: chr "transparent"
$ line     :List of 3
  ..$ color   : chr "rgba(51,51,51,1)"
  ..$ width   : num 0.664
  ..$ linetype: chr "solid"
..$ yref     : chr "paper"
..$ xref     : chr "paper"
..$ x0       : num 0
..$ x1       : num 1
..$ y0       : num 0.514
..$ y1       : num 1
$ :List of 11
..$ type     : chr "rect"
..$ fillcolor: chr "rgba(217,217,217,1)"
..$ line     :List of 3
..$ yref     : chr "paper"
..$ xref     : chr "paper"
..$ x0       : num 0
..$ x1       : num 1
..$ y0       : num 0
..$ y1       : num 23.4
..$ yanchor  : num 1
..$ ysizemode: chr "pixel"

# Horizon labels
> str(finalPlot$x$layout$annotations, max.level = 2)
$ :List of 12
..$ text     : chr "Horizon: 2 Week(s)"
..$ x        : num 0.5
..$ y        : num 0.486
..$ showarrow: logi FALSE
..$ ax       : num 0
..$ ay       : num 0
..$ font     :List of 3
..$ xref     : chr "paper"
..$ yref     : chr "paper"
..$ textangle: num 0
..$ xanchor  : chr "center"
..$ yanchor  : chr "bottom"

• Add "drag to zoom" text as separate annotation? might scale better with page size changes
• Add horizontal reference line for coverage plots
• Setting x-axis limits depending on the as-of date selection and whether forecast values are displayed on the truth plot. plotly doesn't let an axis limit float if passed an NA, so we'd probably need to define a separate function to calculate min/max x limits based on data range.
• Make y-axis ranges match across subplots