![]() ![]() It is the plotting library that I prefer but for no specific reason. # set legend only in one axis (but with all lines)Īx1.legend(lines, )īTW, I used matplotlib due to (my) convenience. # places the nex axis (ticks and description) below the other axesĪx.t_position(("outward", offest*i)) # additional offset # sets the ticks to be shown at the bottomĪx.tick_params(axis='x', direction='out',labelbottom=True) ![]() # creates another axes that shares the same y-axis There are two ways to correct the problem: the first solution would be to re-write your function to use the object-oriented API of matplotlib (this is the solution that I recommend, although it requires more work) code: def plottrace (param, axs, paramname'parameter', kwargs): '''Plot the trace and posterior of a parameter.'''. This is why we need to set all these properties (where to show the axis, in which direction should the label and the ticks being placed) and a few nice things, such as the color of the label and the ticks. The problem is that matplotlib automatically places other axes on the opposite side (so 'top' in case of the x-axis and 'right' in the case of the y-axis). There is an example of how to create multiple axes in a single plot.īasically, you create another axis with twinx() and then set everything in such a way that it ends up nicely. The question is a bit tricky but feasible. One approach is to change the position of the title itself using fig.update_layout(title=dict()): fig.update_layout(Ĭomplete code for Plot 2 from plotly.subplots import make_subplots # not critical, but just to put a little air in thereįig.update_layout(xaxis1=dict(domain=),Įdit: Tighten the space between title and range. # extra data where xaxis4 is shared with subplot 2įig.update_layout(yaxis1=dict(domain=), # extra data where xaxis3 is shared with subplot 1 ![]() Title_text="Subplots with shared x-axes") Here's the result: PlotĬomplete code: from plotly.subplots import make_subplots The reason why you'll have to take domain into account is because the position attribute in point 3 can't be negative, and you'll have to make room for the double x-axes somehow. Make some final adjustments using fig.update_layout(, yaxis2=dict(domain=)) Then, adjust subplot 1 to make room for xaxis3 using: fig.update_layout(xaxis3=dict(anchor="free", overlaying="x1", position=0.0)) Set up a "regular" subplot using fig=make_subplots(rows=1, cols=2) and include two traces as described here.Īdd a third trace with its own xaxis using fig.add_trace(go.Scatter([.[, xaxis="x3")) ![]() fig.add_subplot(235) is the same as fig.add_subplot(2,ģ, 5).You'll need a precise combination of make_subplots(rows=1, cols=2), add_traces() and fig.update_layout(xaxis=dict(domain=.): Rows, the second the number of columns, and the third the index of the Pos is a three digit integer, where the first digit is the number of Index in order, the subplot will take the index position on a grid If the three integers are nrows, ncols, and ax1 = plt.subplot(321) # 3 rows, 2 cols, index 1: col 1 on row 1Īx2 = plt.subplot(322) # 3 rows, 2 cols, index 2: col 2 on row 1Īx3 = plt.subplot(312) # 3 rows, 1 cols, index 2: col 1 on row 2Īx4 = plt.subplot(313) # 3 rows, 1 cols, index 3: col 1 on row 3Įither a 3-digit integer or three separate integers describing the So for each call to subplots we specify how the plot area should be divided (using rows and cols) and then which area to put the plot in (using index), see images below. The integer that you provide to subplot is actually 3 parts: ![]()
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