![]() Each number in the list is the size of the marker in Scatter plot.Įxample.py import matplotlib. In the following example, we will draw a scatter plot with 6 (six) data points, and set specific size for the markers of these data points on the Scatter plot, with a list of numbers. Note: The length of the size list that we give for named parameter s, should be consistent with the lengths of x and y. (x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, *, edgecolors=None, plotnonfinite=False, data=None, **kwargs) The following is definition of scatter() function with s parameter, at third position, whose default value is None. Resmap = ax2.scatter(X,Y, c=data, cmap="YlGnBu",edgecolors='none',alpha=0.5)Ĭax1 = divider1.append_axes("right", size="5%", pad=0.05)Ĭax2 = divider2.append_axes("right", size="5%", pad=0.05)Īnd btw, fig = plt.figure(figsize=(10,5)) produces a rectangle, while fig = plt.figure(figsize=(20,20)) produces a square.To set specific size for markers in Scatter Plot in Matplotlib, pass required sizes for markers as list, to s parameter of scatter() function, where each size is applied to respective data point. import matplotlib.pyplot as pltįrom mpl_toolkits.axes_grid1 import make_axes_locatableĭata = np.sin(X/2.3)*np.cos(Y/2.7)*np.cos(X*Y/20.) Unfortunately, this does not work well for the matplotlib inline backend in Jupyter because that backend uses a different default of rcParamsfigure.dpi 72. One step at a time, until you find the piece of code that causes problems. So start from there and add the stuff you might need accordingly. The following code shows how you would do that and it acutally shows no difference in size of the two plots. from matplotlib import pyplot as plt from matplotlib import gridspec as gridspec plt.rcParams'figure.figsize' 7.00, 3.50 plt.rcParams'tolayout' True fig plt.figure() ax fig.addsubplot(111) gs gridspec.GridSpec(3, 1) ax.setposition(gs0:2.getposition(fig)) ax.setsubplotspec(gs0:2) fig.addsubplot(gs2) fig.tightl. If you apply everything to both plots simultaneously, how can they be different after all? You are looking for the difference between two things - so make them as equal as possible. What you need to do is break down the problem. You will find out that producing such a minimal working example, almost always makes you find the problem and a corresponding solution yourself.Īs we do not have the necessary knowledge of your data and the variables you are using, it is almost impossible to come up with a solution. In order to get help, you need to provide a minimal working example. Si this makes me think there is some margin around the scatter.Īlso, is there a way I could make the whole PNG file not so square? Could it be a rectangle? Actually, it's supposed to be as big as its colorbar, but that doesn't work either. Resmap = plt.scatter(xs,ys, c=data,cmap=cm,edgecolors='none',alpha=0.5,s=data)īut I find no way of making the scatter plot as big as the heatmap. Then the ax is passed over to another function to plot the little blue lines on the map: def plot_chosen(edges,endnodes,side,ax):Īx.plot(,, 'k-', lw=4, color='blue',alpha=0.5)įinally, I plot the scatter like this def plot_satter(edges,endnodes,side,xs,ys,data):Īx.set_yticks(np.arange(side) + 0.5, minor=False)Īx.set_xticks(np.arange(side) + 0.5, minor=False)Īx.set_xticklabels(range(0,side), minor=False)Īx.set_yticklabels(range(0,side), minor=False) The GridSpec from the gridspec module is used to adjust the geometry of the Subplot grid. # note I could have used lumns but made "labels" insteadĪx.set_xticklabels(range(0,matrix.shape), minor=False)Īx.set_yticklabels(range(0,matrix.shape), minor=False)Ĭax = divider.append_axes("right", size="5%", pad=0.05) Create Different Subplot Sizes in Matplotlib using Gridspec. ![]() # want a more natural, table-like display import matplotlib.pyplot as plt plt.subplot(6,1,1) plt.subplot(6,1,2) plt.subplot(6,1,3) plt.subplot(2,1,2) Which will give you something. # put the major ticks at the middle of each cellĪx.set_yticks(np.arange(matrix.shape) + 0.5, minor=False)Īx.set_xticks(np.arange(matrix.shape) + 0.5, minor=False) AxesGrid functionality provides the ability create plots of different size and place them very specifically, via the subplot2grid functionality: import matplotlib.pyplot as plt ax1 plt. The way I generate the heatmap is: def plot_map(matrix):Ĭm = make_colormap() Instead, my right one (which is a scatter plot) has some margins that make it appear slightly smaller than the left (a heatmap). I managed to make them stay next to each other, but I need them to have the exact same size: each point in the right one should be easily mapped to a location on the left one with the naked eye. I am having trouble with matplotlib in Python trying to create two plots side by side.
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