I'm using python to create boxplots seen here:
The filers are 'o' markers, but the width of the circles are too thick.
I want to know how to show hollow instead of solid dots.
Related
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?
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.
I am really pretty new to matplotlib, though I know that it can be very powerful.
I've been reading number of tutorials and examples and it's a real hassle to understand how does matplotlib's Figure and Axes work. I am illustrating, what I am trying to understand, with the attached figure.
I know how to create a figure instance of certain size in inches. However, what bothers me is how can I create subplots and then axes, within each subplot, with relative coordinates (bottom=0,left=0,top=1,right=1) as illustrated.
So, for example I want to create a "parent" plot area (say (6in,10in)). Then, I want to create two subplot areas, each with size (3in,3in), with 1in space from the top, 2in space between the two vertical subplot areas and 1in from bottom. Then, 1in space on the left and 2in space on the write. In the same time, I would like to be able to get the coordinates of the subplot areas with respect to the main plot area.
Then, inside the first subplot area, I'd like to create 2 axis instances, with Axis 1, having coordinates with respect to Subplot Area1 (0.1,0.7,0.7,0.2) and Axes 2 (0.1,0.2,0.7,0.5). And then of course I'd like to be able to plot on these axes e.g., ax1.plot()....
If you could provide a sample code to achieve that, then I can study it.
Your help will be very much appreciated!
a subplot and an Axes object are really the same thing. There is not really a "subplot" as you describe it in matplotlib. You can just create your three Axes objects using gridspec without the need to put them in your "subplots".
There are a few different ways to create Axes instances within your figure.
fig.add_axes will create an Axes instance at the position given to it (you give it [left,bottom,width,height] in figure coordinates (i.e. 0,0 is bottom left, 1,1 is top right).
fig.add_subplot will also create an Axes instance. In this case, rather than giving it a rectangle to be created in, you give it the number of rows and columns of subplots you would like, and then the plot_number, where plot_number starts at 1, increments across rows first and has a maximum of nrows * ncols.
For example, to create the top-left Axes in a grid of 2 row and 2 columns, you could do the following:
fig.add_subplot(2,2,1)
or the shorthand
fig.add_subplot(221)
There are some more customisable ways to create Axes as well, for example gridspec and subplot2grid which allow for easy creation of many subplots of different shapes and sizes.
I need to know how to get the inverse color by lesscss.
Example: I have #000, i need #FFF.
And i need the detail explanation of spin(). And necessary links where i can see a color wheel where i can understand how spin() works.
Thanks.
Why it is not working as you expect
The spin() function only deals with hue (color), not value (grey scale changes are a value change). Take a look at Figures 9 and 10 on this page from North Carolina State University's site. Those figures help show the difference. The spin() function is rotating only in the two dimensional space of the hue circle of color, not along the axis of the third dimensional space dealing with saturation; i.e. the gray scale itself, which is what differentiates white from black, both of which have no color saturation).
This is why on the LESS site we read of spin() (emphasis added):
Note that colors are passed through an RGB conversion, which doesn't
retain hue value for greys (because hue has no meaning when there is
no saturation)
And
Colors are always returned as RGB values, so applying spin to a grey
value will do nothing.
Getting what you want (Color Inversion)
See #seven-phases-max's answer.
The spin function changes the Hue property of a colour. Shades of grey (incl. white and black) are achromatic colours (i.e. they have the same "undefined" hue value).
To simply invert a colour use either difference function:
difference(white, #colour)
or the simple colour arithmetic:
(#fff - #colour)
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).