-
Notifications
You must be signed in to change notification settings - Fork 4
Better Plotting Capabilities #2
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Comments
less fancy, but also check out the examples for the python http://nbviewer.jupyter.org/github/pierre-rouanet/dtw/blob/master/simple%20example.ipynb Seems like as long as we can plot a 2D matrix with |
I have something basic working. I think it would be cool to get some error bars around the path through the matrix to get a sense of how much slack there is in the fit. @ssfrr - do you know of any simple way to do this? |
I think it is cleaner if this package only implements computations related to dynamic time warping. I started another repo here to hold the plot recipes: https://github.com/ahwillia/TimeSeriesPlots.jl |
I changed my mind. I'm going to organize the plots like this: module TimeWarp
# ... dtw fitting code here
module WarpPlots
using Reexport
@reexport using Plots
# ... plotting recipes here
end
end So that users can do: using TimeWarp
using TimeWarp.WarpPlots
dtwplot(randn(10,1), randn(10,1)) To produce the plot above. This also allows users to change the Plots backend and not deal with plots unless they explicitly import them. |
The dtw package in R has some nice ideas for visualizing fits. Would be nice to have similar functionality here:
Toni Giorgino (2009). Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package. Journal of Statistical Software, 31(7), 1-24, doi:10.18637/jss.v031.i07.
The text was updated successfully, but these errors were encountered: