Matplotlib: contour plot line style with markers - matplotlib

Is there a way to make a contour plot ax.contour line style not a simply dot-dashed but with some hollow markers, like this:
In documentation I see only linestyles parameter with limited set of values, and I know also about a way to tune dash-dot style, like this linestyles=[(0, (7, 3))], but what I looking for is a way to use a marker instead of a simple point in dot-dash style.

Related

Dots repel in Pandas scatterplot

I am trying to draw a scatterplot where visualizing all the dots hue and size is important.
However, some dots are localized at the same location x,y therefore they overlap, and we cannot see them well.
I know there is the equivalent of the 'repel' function in Pandas for the dots labels with the following script.
https://github.com/Phlya/adjustText
Would anyone know if there is another software that allow to repel the dots themselves, and not just the text annotation?

Seaborn Heatmap Colorbar Location

The cbar_kws argument of seaborn.heatmap accepts the parameters that fig.colobar accepts.
Is there a way to adjust the placement of the colorbar, simply to adjust the location to the left (especially when the correlation matrix is adjusted to have only a lower triangle).
I can adjust the labels by overriding the tick labels. As of now I still have to adjust the upper-right borders in post-processing, but it would make things much easier if I didn't have to edit the color bar as well.
heatmap accepts a cbar_ax argument; if you want to specify the position of the colorbar, the best thing to do is to set up the figure how you want it and then pass the specific axes.
You can also move axes around after plotting through normal matplotlib commands.

Selecting a single color from a matplotlib colormap in Juila

I'm constructing a graph plot in Julia and need to color each edge of the graph differently, based on some weighting factor. I can't find a way to get a specific RGB (or HSV, it doesn't matter) value from a colormap. Let's say I'd like to get the RGB value on 'jet' that would correspond to a data value of n on imshow plot.
In python, I would just use jet(n), where n is the value along the colormap in which I am interested. PyPlot in Julia doesn't seem to have wrapped this functionality. I've also already tried indexing into the cmap object returned from get_cmap(). Any advice?
I'm stumped, so even an approximate solution would help. Thanks!
Maybe you can look at the Colors.jl package (https://github.com/JuliaGraphics/Colors.jl):
using Colors
palette = colormap("Oranges", 100)
Then you can access each color with palette[n]. Or are you using PyCall? A code describing what you're trying to do would help.

Set the height and width of a mpld3 plot

I want to set the width and height of a mpld3 plot to a specific value (in pixels, so it fits the div it is in). The way I tried it looks like this (javascript):
commands["width"]=plotWidth;
commands["height"]=plotHeight;
mpld3.draw_figure("plotname",commands);
plotWidth and plotHeight the values I want the height and width to be set to.
Now, this actually sets the size of the mpld3-figure object to the values I want, but the plot inside still keeps its old size, so it looks like nothing happened.
So, how do I change the size of the plot itself? So far it looks like whatever I do, the plot does not change.
You can change the shape of an mpld3 plot when creating a figure with the python code plt.figure(figsize=(width,height)) (where width and height are in inches). Here is a notebook demonstrating this.
There has been some interest in making mpld3 figures "responsive", which would be a cooler and more precise way to accomplish your goal, but so far no one has tried making the necessary code changes. Patches welcome!

How can I get and set the position of a draggable legend in matplotlib

I'm trying to get and set the position of a draggable legend in matplotlib. My application consists of an interactive GUI, which has a redraw/plot function that should perform the follow steps:
save the position of the current legend.
clear the current axes and perform various plotting operations, which may or may add labels to their plots.
build a new draggable legend (ax.legend().draggable()) and restore the old position of the legend.
In between these steps the user is free to drag the legend around, and the goal is to persist the legend position when the plots are redrawn.
My first approach was to use oldpos = legend.get_bbox_to_anchor() and legend.set_bbox_to_anchor(oldpos) in steps 1 and 3. However this causes to move the legend completely off the visible area.
Note that I have to use ax.legend() and cannot use fig.legend(lines, labels), since step 2 is completely decoupled, i.e., I don't know anything about lines and labels in step 3. According to answers to the question How to position and align a matplotlib figure legend? there seems to be a difference between these two possibilities regarding axes or figure coordinates. Obviously my problem calls for figure coordinates, but I haven't fully understood how to convert the bbox to a "bbox in figure coordinates".
The even more severe problem I just realized is that apparently legend.get_bbox_to_anchor() always seems to return the same values irrespective of the drag position. So maybe the anchor can only be (ab-)used to manipulate the position of static legends? Is there another/proper way to save and restore the position of a draggable legend?
By looking at the implementation of Legend I found out that there is an undocumented property _loc, which exactly does what I want. My solution now looks astonishingly simple:
oldLegPos = ax.get_legend()._loc
# perform all plotting operations...
legend = ax.legend().draggable()
legend._loc = oldLegPos
It looks like _loc automatically stores figure coordinates, since I do not have to convert the coordinates in any way (eg. when the plotting operations completely change the axes ranges/coordinates).