The problem here is that ax5 is not in a subplot. fig.get_axes() [<matplotlib.axes._subplots.AxesSubplot at 0x220175c0>, <matplotlib.axes._subplots.AxesSubplot at 0x18d48240>, <matplotlib.axes._subplots.AxesSubplot at 0x1c5f3630>, <matplotlib.axes._subplots.AxesSubplot at 0x1a430710>, <matplotlib.axes._axes.Axes at 0x1c4defd0>] # There is ax5 and it is not under _subplots so when you do fig.subplots_adjust(right=0.8) you adjust the subplot and not the axe...

python,matplotlib,flatten,subplot

Rather than creating your subplots in advance using plt.subplots, just create them as you go using plt.subplot(nrows, ncols, number). The small example below shows how to do it. It's created a 3x3 array of plots and only plotted the first 6. import numpy as np import matplotlib.pyplot as plt nrows,...

python,matplotlib,font-size,subplot

Here are the changes I made to the last bit of your code: fig = plt.figure(figsize=(6,6)) # 6x6 image ax = plt.gca() #SubplotZero(fig,111,) #Plot arrows over figure #fig.add_subplot(ax) # Plot arrows over figure # Plot both nulcines on same graph plt.axis((0,1,0,1)) ax.set_title('v = 1',fontweight="bold", size=20) # Title ax.set_ylabel('Active Wee1', fontsize...

python,matplotlib,subplot,colorbar

matplotlib automatically resizes the axes and generate a second axis next to it to show the colorbar on. We can instead provide this second axis as follows: import matplotlib.pyplot as plt import numpy as np fig, (ax1, ax2) = plt.subplots(nrows=2) # Some demo data x = np.linspace(0, 18) y =...

An idea is to create three "big subplots", to give each of them a title, and make them invisible. On the top of that you can create your matrix of smaller subplots. This solution is entirely based on this post, except that more attention has been paid to actually removing...

python,matplotlib,plot,subplot

Try to do: fig = plt.figure(figsize=(4, 4)) at the beginning and your code should work. The issue seems to be the figure size which is imcompatible with its content, making it not possible to respect both wspace and hspace....

matlab,plot,division,figure,subplot

I have come this problem many times and haven't yet figured out a decent way to solve it. However what you can do is: A) Include a Label (help label) in the subplot you want. Alternatively use a "edit locked" edit text field. B) Yes in a way. Check out...

Maybe not exactly the answer of my question, but it solves my problem: After creating the figure, you connect the resize-event to an eventhandler: cid = fig.canvas.mpl_connect('resize_event', onresize) def onresize(event): plt.tight_layout() As Wicket said, I'm just calling tight_layout() again and again, but automatically....

matlab,matlab-figure,ode,differential-equations,subplot

The error is thrown when you run the function and MATLAB attempts to evaluate D_t = 3*exp(-0.05*t);. Since no value of t was given, MATLAB throws an error saying that the up-to-that-point unused t variable must be specified. The main problem with the code is in the function's design. Namely,...

I think you might be mixing things. Multiplot will generate several graphs on the same page, but you are talking about plotting more than once on one of them. The answer to your question on selecting one of the plotting areas is no, you cannot freely select one arbitrarily, unless...

python,matplotlib,pandas,plot,subplot

The problem is in your loop for i in range(2): # Iterating rows of the plot for j in range(50, 101, 10): # Iterating your file names for e in range(3): # iterating the columns of the plot The end result is that you iterate all the columns for each...

matplotlib,plot,subplot,colorbar

Sure, it's possible! What's happening is that a new axes is being created for the colorbar, and the space is being taken from the axes that pcolormesh is plotted in. If you don't want this to happen, you can specify an axes object for the colorbar to go in. Alternately,...

python,matplotlib,plot,subplot,imshow

Have you tried the tight layout functionality? plt.tight_layout() See also HERE EDIT: Alternatively, you can use gridspec: import numpy as np import matplotlib.pyplot as plt import matplotlib as mpl images = [np.random.rand(40, 40) for x in range(68)] gs = mpl.gridspec.GridSpec(17, 4) gs.update(wspace=0.1, hspace=0.1, left=0.1, right=0.4, bottom=0.1, top=0.9) for i in...

Remove the break call. The whole point of break is to exit early out of a loop. Since you don't want to exit early, don't call break.

The code you've posted seems largely correct. Other than the indexing, as @hitzg mentioned, nothing you're doing looks terribly out of the ordinary. However, it doesn't make much sense to return the figure and axes array from your plotting function. (If you need access to the figure object, you can...

matlab,for-loop,iteration,subplot

Okay, your code had several bugs. Here is one that works: % constants a=30; b=0.5; % parameters x=1:1:5 ; e1 = 0:10:10000; e2 = 0:10:10000; [e1,e2]=meshgrid(e1,e2); % plots [email protected](x)(a.^(6.*x)./factorial(6.*x))*... (exp(-b*x.*e2)); [email protected](x)((a.^(a-(6.*x)))/factorial(a-(6.*x)))*... exp(-b*(a-(6.*x)).*e1); [email protected](x)t(x)./(t(x)+u(x)); %FIGURES: figure for i=x subplot(3,2,i); mesh(e1,e2,p(i)); title(['X=',int2str(i)]); axis([1 10000 1 1000 10^-300 1]) xlabel('e1'); ylabel('e2'); zlabel('p'); end...

matlab,plot,matlab-figure,subplot

This is due to a wrong call to subplot; it looks like Matlab creates too many axes and for some reason they are placed over the tabs. A safe way to fix this is first create an axes right before entering the nested for-loop, then the subplots will be placed...

python,numpy,matplotlib,plot,subplot

After spending some some time closely looking at what I'm running, I've found that the problem might lie somewhere with the function I am using to generate data and how it interacts with the loop. Indeed, using basic test data causes no problem. That function does a lot of stuff...

python,matplotlib,axes,subplot

Setting axes position is similar in Matplotlib. You can use the get_position and set_position methods of the axes. import matplotlib.pyplot as plt ax = plt.subplot(111) pos1 = ax.get_position() # get the original position pos2 = [pos1.x0 + 0.3, pos1.y0 + 0.3, pos1.width / 2.0, pos1.height / 2.0] ax.set_position(pos2) # set...

You can use: fig, axs = plt.subplots(2,3) axs will be an array containing the subplots. Or unpack the array instantly: fig, ((ax1, ax2, ax3), (ax4, ax5, ax6)) = plt.subplots(2,3) ...

python,pandas,plot,group,subplot

Sounds like you want to iterate over the groups and the axes in parallel, so rather than having nested for loops (which iterates over all groups for each axis), you want something like this: for (i,j), ax in zip(grouped, axs.flat): j.plot(x='C1',y='C3', ax=ax) You have the right idea in your second...

python,numpy,matplotlib,graph,subplot

Get rid of the penultimate line, plt.show() Here is the result of running your code without that line ...

python,matplotlib,colorbox,subplot

Following the answer to @plonser, tick = np.linspace(min(your_variable),max(your_variable),3) plt.tight_layout(pad=0.5, w_pad=2.5, h_pad=2.0) ax1 = plt.subplot(131) # creates first axis ax1.set_xticks([0,2000,500,1000,1500]) ax1.set_yticks([0,2000,500,1000,1500]) i1 = ax1.imshow(U,cmap='hot',extent=(X.min(),2000,Y.min(),2000)) plt.colorbar(i1,ax=ax1,ticks=tick) ax1.set_title("$ \mathrm{Ux_{mes} \/ (pix)}$") ax2 = plt.subplot(132) # creates second axis ax2.set_xticks([0,2000,500,1000,1500]) ax2.set_yticks([0,2000,500,1000,1500])...

python,matplotlib,plot,subplot

I hope I do not misunderstand your question and the answer helps: You need to replace your ax1.plot(x,r1) and ax2.plot(x,m2) with ax1.bar(x,m1, t) and ax2.bar(x,m2, t) , where t is an arbitrary value and indicates width of the bar. You cannot ax1.plot(x,r1), as r1 is already a 'bar container'. In...

matlab,for-loop,plot,matlab-figure,subplot

Use something like figure(6) hold on max_i = max(piektijden_start(:,2)); for i = 1:max_i %// ... subplot(2, max_i, i) %// ... subplot(2, max_i, i+max_i) %// ... end The second argument to subplot is the number of subplot columns. The third is the addressed subplot, such that such that the first subplot...

python,datetime,matplotlib,time-series,subplot

When the plot layout has multiple rows and columns, the returned array is two-dimensional. You'll need to access the individual subplots using things like axarr[0, 0] and axarr[0, 1].

python,loops,matplotlib,subplot

I hope this helps import numpy as np import matplotlib.pyplot as plt #data data1 = [11,20,25,80] data2 = [15,35,50,90] data3 = [25,36,58,63] data4 = [30,40,68,78] element = np.arange(4) # data is used to automatize the fill_between argument data = [[data1,data2],[data3,data4]] # creating an list of the colors used cols =...

fig.savefig can adjust the padding it gives the figure. Try something like plt.savefig('test.png', bbox_inches='tight', pad_inches=0.1) ...

If I understand correctly, it suffices to write figure(1) or figure(2) before the subplot statement. If h is the handle or the Number property value of an existing figure, then figure(h) makes that existing figure the current figure, makes it visible, and moves it on top of all other figures...

python,python-2.7,matplotlib,figure,subplot

When using subplots_adjust, the values of left, right, bottom and top are to be provided as fractions of the figure width and height. In additions, all values are measured from the left and bottom edges of the figure. This is why right and top can't be lower than left and...

Since you set sharey=True, all three axes now behave as if their were one. For instance, when you invert one of them, you affect all four. The problem resides in that you are inverting the axes in a for loop which runs over an iterable of length four, you are...

python,matplotlib,pandas,subplot

This is why the pyplot interface is so bad. This is way more complicated than it needs to be. Load and prepare your data. Then: fig = plt.Figure(figsize=(20, 3)) gs = gridspec.GridSpec(2, 1, width_ratios=[20,10], height_ratios=[10,5]) ax1 = fig.add_subplot(gs[0]) ax2 = fig.add_subplots(gs[1]) ax1.plot(...) ax1.set_ylabel(...) ... ax2.plot(...) ax2.set_xlabel(...) That way, you don't...

This will remove the tick labels on the vertical axis in the middle and right plots (which I think is what you mean when you say 'remove the number "pixels"'): ax2.set_yticklabels([]) ax3.set_yticklabels([]) ...

python,matplotlib,axes,subplot

Taking a cue from this answer, you can adjust the layout of your colorbar with AxisDivider. import matplotlib.pyplot as plt import numpy as np from mpl_toolkits.axes_grid1 import make_axes_locatable fig=plt.figure(figsize=(15,5.5)) ax1=plt.subplot2grid((1,3),(0,0)) ax2=plt.subplot2grid((1,3),(0,1)) ax3=plt.subplot2grid((1,3),(0,2)) image=np.random.random_integers(1,10,size=(100,100)) im = ax1.imshow(image,interpolation="none",aspect='equal') divider = make_axes_locatable(ax1) cax = divider.append_axes("bottom",size="5%",pad=0.7)...

Here is a way to do it. The trick is based from this answer and consists in creating a uipanel in which to add an axes where you can create the scrollpanel. Adapted for your scenario, here is how it looks like: clear clc %// Read demo images and create...

python,matplotlib,plot,subplot,colorbar

I found the answer to my question, resulting in the correct colorbar vs subplot spacing. Notice that if the spacing between subplot and colorbar does not matter, the answer of Molly is correct. import numpy import layout import matplotlib.pylab as plt from mpl_toolkits.axes_grid1 import make_axes_locatable data = numpy.random.random((10, 10)) test...

matlab,plot,annotations,matlab-figure,subplot

I'm afraid annotation objects are properties of figures and NOT axes, as such its harder to customize the position of each annotation objects because no matter how many subplots you have, they are all part of the same figure and you need to specify their position relatively to the figure...

python,matplotlib,axis-labels,subplot

You can turn the x and y tick labels on and off manually based on their location in the figure. This demo has some more information. import matplotlib.pyplot as plt fig = plt.figure() # Add subplots nRows = 4 nCols = 2 nPlots = 7 ax1 = fig.add_subplot(nRows,nCols,1) ax1.set_yscale('log') ax1.set_xscale('log')...