Hi,
I think there is a good reason to add the functionality to plot
pre-computed histograms to hist() or to a new function with similar API.
Sometimes histograms are heavy or we don't want to recompute them to
perform a series of plots.
In this case, I miss the ability to easily set the plot sty
Le 24/04/2015 12:58, Christian Alis responds to the problem posed by
Virgil Stokes
> I had the same problem some time ago and what I did is to use bar() to
> plot the histogram, which can be done in one line:
>
> hst, bin_edges = np.histogram(data)
> plt.bar(bin_edges[:-1], hst)
>
> Perhaps this
On 24-Apr-2015 12:58, Christian Alis wrote:
> I had the same problem some time ago and what I did is to use bar() to
> plot the histogram, which can be done in one line:
>
> hist, bin_edges = np.histogram(data)
> plt.bar(bin_edges[:-1], hist)
Very elegant Christian :-)
>
> Perhaps this trick can be
I had the same problem some time ago and what I did is to use bar() to
plot the histogram, which can be done in one line:
hist, bin_edges = np.histogram(data)
plt.bar(bin_edges[:-1], hist)
Perhaps this trick can be added in the documentation?
I am willing to code Virgil's request if many will fi
I have some Python (2.7.9) code that processes some rather large data sets to
determine the curvatures along 2D curves. One feature of these data that I like
to look at is the distribution of the curvatures. I use NumPy to to determine
histograms for each set, and save the histogram parameters r
