I have a plot and want a legend placed in the upper right corner without any frame around with two lines:
a = 10
b = 3*pi
Those lines are some coefficients of my plotted function.
So far, I have
ax1.plot(x, y, label='a')
ax1.legend(["a = 10", "b = 3*pi"], loc="upper right", ncol=1, frameon=False)
But that keeps lines type or color next to my two strings. How to remove them?
Put it in the title is not an option. There is a different text.
Use the text method of the axes object.
Also, remember that the default is that the first 2 arguments of ax1.text are in data coordinates, so in your example, Hello will be put at (x,y)=(.6, .06), unless you also add the parameter transform=ax1.transAxes to ax1.text, like so:
ax1.text(.60, .06, r'Hello', transform=ax1.transAxes)
That will add the text label a little over halfway from the left and a little higher than the bottom of the axes.
Related
I have a very customized subplot set up.
fig = plt.figure(figsize=(12, 10))
gs = fig.add_gridspec(nrows=2, ncols=2, width_ratios=[3, 1])
ax = fig.add_subplot(gs[:, 0])
ax3 = fig.add_subplot(gs[-1, -1])
ax4=fig.add_subplot(gs[0, 1])
This sets up 3 slots for plotting: one that takes up half the space on the left, and two smaller ones on the right. However, I only want the bottom right to actually be a plot. I want the top right to be the space where the legend for the larger plot on the left to go. I could just use the axes from ax to do this, but that shifts the whole plotting space off. Instead I thought of trying to just create ax4 and place the ax legend there.
lines = []
labels = []
for ax in fig.get_axes():
ln, la = ax.get_legend_handles_labels()
lines.extend(ln)
labels.extend(la)
legend = ax4.legend(lines, labels, labelspacing=0.1, loc=(-0.3,0.6), fontsize='xx-large')
fig.tight_layout()
This puts the legend exactly where I want it, but the blank figure shows up, which I don't want. Is it possible to accomplish what I want using this method? If not, what is my alternative? Picture below to better understand.
You can use ax4.axis('off') to make axis 4 invisible if you want to stick to your approach.
However, I don't see why you don't just skip creating axis 4 and just use fig.legend() instead of ax.legend(). Then the legend is placed outside the axis and you can then control the exact position just as you already did with the loc keyword.
I need to precisely control the position of my ylabel independently of my yticklabels with matplotlib. This is because I have a matplotlib animation that currently has the ylabel jumping around as I change yticklabels. This is undesirable.
The docs seem to only allow me to specify distance from the leftmost part of my yticklabels. (which does not solve the problem, and indeed is causing it)
One solution would be to manually put the label. But is there a simpler way?
You can emulate the behavior of a normal y-label by adding text explicitly to the axes. If the y-limits are changing quite a bit, this is best done by placing the text in axes coordinates, rather than data coordinates. This is done with the transform keyword-argument, like so:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
t = ax.text(-0.1, 0.5, 'Y label', rotation=90,
verticalalignment='center', horizontalalignment='right',
transform=ax.transAxes)
ax.set_ylim(-10, 10) # Change y-limits, label position won't change.
This places the text halfway up the axes, and slightly to the left. Changes to the data limits of the axes have no effect on the text, as it is always defined in axes coordinates. Similarly, scaling the plot or axes (resizing the window with the mouse, using fig.set_size_inches, etc) will keep the y-label in position relative to the axes box itself, exactly what you want for a label.
You may have to play with the x-position of the label, to make sure it doesn't overlap the tickmarks as they change during animation.
I'm writing a pythonic script for a coastal engineering application which should output, amongst other things, a figure with two subplots.
The problem is that I would like to shade a section of both subplots using plt.axvspan() but for some reason it only shades one of them.
Please find below an excerpt of the section of the code where I set up the plots as well as the figure that it's currently outputting (link after code).
Thanks for your help, and sorry if this is a rookie question (but it just happens that I am indeed a rookie in Python... and programming in general) but I couldn't find an answer for this anywhere else.
Feel free to add any comments to the code.
# PLOTTING
# now we generate a figure with the bathymetry vs required m50 and another figure with bathy vs Hs
#1. Generate plots
fig = plt.figure() # Generate Figure
ax = fig.add_subplot(211) # add the first plot to the figure.
depth = ax.plot(results[:,0],results[:,1]*-1,label="Depth [mDMD]") #plot the first set of data onto the first set of axis.
ax2 = ax.twinx() # generate a secondary vertical axis with the same horizontal axis as the first
m50 = ax2.plot(results[:,0],results[:,6],"r",label="M50 [kg]") # plot the second set of data onto the second vertical axis
ax3 = fig.add_subplot(212) # generate the second subplot
hs = ax3.plot(results[:,0],results[:,2],"g",label="Hs(m)")
#Now we want to find where breaking starts to occur so we shade it on the plot.
xBreakingDistance = results[numpy.argmax(breakingIndex),0]
# and now we plot a box from the origin to the depth of breaking.
plt.axvspan(0,xBreakingDistance,facecolor="b",alpha=0.1) # this box is called a span in matplotlib (also works for axhspan)
# and then we write BREAKING ZONE in the box we just created
yLimits = ax.get_ylim() # first we get the range of y being plotted
yMiddle = (float(yLimits[1])-float(yLimits[0])) / 2 + yLimits[0] # then we calculate the middle value in y (to center the text)
xMiddle = xBreakingDistance / 2 # and then the middle value in x (to center the text)
#now we write BREAKING ZONE in the center of the box.
ax.text(xMiddle,yMiddle,"BREAKING ZONE",fontweight="bold",rotation=90,verticalalignment="center",horizontalalignment="center")
#FIGURE FORMATTING
ax.set_xlabel("Distance [m]") # define x label
ax.set_ylabel("Depth [mDMD]") # define y label on the first vertical axis (ax)
ax2.set_ylabel("M50 [kg]") # define y label on the second vertical axis (ax2)
ax.grid() # show grid
ax3.set_xlabel("Distance[m]") #define x label
ax3.set_ylabel("Hs[m]") # define y label
ax3.grid()
plt.tight_layout() # minimize subplot labels overlapping
# generating a label on a plot with 2 vertical axis is not very intuitive. Normally we would just write ax.label(loc=0)
combined_plots = depth+m50 #first we need to combine the plots in a vector
combined_labels = [i.get_label() for i in combined_plots] # and then we combine the labels
ax.legend(combined_plots,combined_labels,loc=0) # and finally we plot the combined_labels of the combined_plots
plt.savefig("Required M50(kg) along the trench.png",dpi=1000)
plt.close(fig)
Output Figure:
By just calling plt.axvspan, you are telling matplotlib to create the axvspan on the currently active axes (i.e. in this case, the last one you created, ax3)
You need to plot the axvspan on both of the axes you would like for it to appear on. In this case, ax and ax3.
So, you could do:
ax.axvspan(0,xBreakingDistance,facecolor="b",alpha=0.1)
ax3.axvspan(0,xBreakingDistance,facecolor="b",alpha=0.1)
or in one line:
[this_ax.axvspan(0,xBreakingDistance,facecolor="b",alpha=0.1) for this_ax in [ax,ax3]]
It's difficult to analyze your code and not being able to reproduce it. I advise you to build a minimal example. In any case notice that you are calling "plt.axvspan(" which is general call to the library.
You need to specifically state that you want this in both "ax" and "ax2" (i think).
Also if you need more control consider using Patches (I don't know axvspan):
import matplotlib.pyplot as plt
import matplotlib.patches as patches
fig1 = plt.figure()
ax1 = fig1.add_subplot(111, aspect='equal')
ax1.add_patch(
patches.Rectangle(
(0.1, 0.1), # (x,y)
0.5, # width
0.5, # height
)
)
fig1.savefig('rect1.png', dpi=90, bbox_inches='tight')
See that call to "ax1" in the example? Just make something similar to yours. Or just add axvspan to each of your plots.
I use the matplotlib library for plotting data in python. In my figure I also have some text to distinguish the data. The problem is that the text goes over the border in the figure window. Is it possible to make the border of the plot cut off the text at the corresponding position and only when I pan inside the plot the the rest of the text gets visible (but only when inside plot area). I use the text() function to display the text
[EDIT:]
The code looks like this:
fig = plt.figure()
ax = fig.add_subplot(111)
# ...
txt = ax.text(x, y, n, fontsize=10)
txt.set_clip_on(False) # I added this due to the answer from tcaswell
I think that your text goes over the border because you didn't set the limits of your plot.
Why don't you try this?
fig=figure()
ax=fig.add_subplot(1,1,1)
text(0.1, 0.85,'dummy text',horizontalalignment='left',verticalalignment='center',transform = ax.transAxes)
This way your text will always be inside the plot and its left corner will be at point (0.1,0.85) in units of your plot.
You just need to tell the text artists to not clip:
txt = ax.text(...)
txt.set_clip_on(False) # this will turn clipping off (always visible)
# txt.set_clip_on(True) # this will turn clipping on (only visible when text in data range)
However, there is a bug matplotlib (https://github.com/matplotlib/matplotlib/pull/1885 now fixed) which makes this not work. The other way to do this (as mentioned in the comments) is
to use
txt = ax.text(..., clip_on=True)
So far i have placed my suptitles above the frame, like this:
How can i get the suptitles from above the frame into the frame?
So far i have a solution that just prints a text and sets it on the right position with computing xlim and ylim. However this is errorprone and if the text is different it just looks aweful. Is there a way to set the suplabel into the frame? Or just place text below the frame and centered?
it would be really convenient, if i did not need to know about the data that is displayed inside the frame.
Your solution using text is also my go-to solution. However, you don't need to compute the position based on xlim and ylim. If you set transform=ax.transAxes the coordinates for positioning the text are taken as being relative to the axes bounding box (0,0 being the lower left corner). Like so:
data = range(1,10);
fig = figure()
for i in range(6):
ax = fig.add_subplot(2,3,i)
ax.text(.5,.9,'centered title',
horizontalalignment='center',
transform=ax.transAxes)
ax.plot(data)
show()
Hope that helps!
Have you considered axes.set_title? You can also pass x and y coordinates as keyword arguments ax.set_title("my title", x=0.5, y=0.6).
Hope this helps.