How can I split the ylabel of a matplotlib figure into rows? I want to keep the ylabel on the y-axis rotated. As an example, here's my subplot so far, for which the relevant part of the code is below:
plt.ylabel('Spacing of Zeroes of $J_{\\nu}(x)$', rotation=0)
When I try doing this:
plt.ylabel('Spacing of Zeroes of $J_{\\nu}(x)$', rotation=0, ncol=2)
I receive this error:
AttributeError: Unknown property ncol
My suggestion would be to introduce linebreaks in the string.
plt.ylabel('Spacing of\nZeroes of\n$J_{\\nu}(x)$', rotation=0, ha="right")
You can use this.
https://matplotlib.org/2.0.2/examples/pylab_examples/multiline.html
plt.xlabel('this is a xlabel\n(with newlines!)')
plt.ylabel('this is vertical\ntest', multialignment='center')
Related
I'm trying to display the exact values on one axis of the color bar and a basic scale on the other. However, some of the exact values are so close together their names overlap on the color bar. Is there a way for me to make the overlapping names appear as a list or just to the side the other values name? I've already tried rotation of the labels, setting vmin/vmax in the color bar method, and setting the ylim's of the second axis. I'm at a lose at what to try next. It feels like this is something matplotlib would allow but I can't find what method or kwargs that allow this manipulation. Many of the commented out tlines are the attempts I've made with help from many posts on StackOverflow. Thank you!!
Previous code deleted for clarity
UPDATE: Paul H here is a workable example with the same issue I'm trying to fix
# Make random data with same issue
x, y = np.linspace(-3, 1.5, 20), np.linspace(0, 0.5, 20)
# two different ranges used to simulate the same issue in my data
fake_phase = np.append(np.random.random_sample(15), np.arange(0.0, .005, 0.001))
fake_labels = np.array(['V439Oph', 'ALVir', 'YZVir', 'XXVir', 'V716Oph', 'BFSer', 'BLHer',
'RXLib', 'CEHer', 'V465Oph', 'V1180Sgr', 'CSCas', 'DQAnd', 'IXCas',
'UYEri', 'TWCap', 'AUPeg', 'MZCyg', 'SWTau', 'TXDel'], dtype=object)
# Plot data
fig, ax = plt.subplots(1,1,figsize=(15,10))
plt.tight_layout()
plt.plot(x, y, marker='.', ms=17, mew=2, linestyle='none')
# Make the same colorbar
norm = cm.colors.Normalize(vmin=0.0, vmax=1.0, clip=False)
cbar = fig.colorbar(cm.ScalarMappable(norm=norm, cmap='rainbow'), ax=ax, extend='both',
orientation='vertical', pad=0.005, use_gridspec=True)
cbar.set_ticks(fake_phase)
cbar.set_ticklabels(fake_labels)
cbar.ax.tick_params(which='major', labelsize='large', width=1.5, length=6)
cbar.set_label(label='Phase', size='xx-large', labelpad=40)
cbar.ax.set_aspect('auto')
ax2 = cbar.ax.twinx()
pos = cbar.ax.get_position()
pos.x0 += 0.1
ax2.set_position(pos)
plt.show();
The output of this code: Output of workable example
My issue is that the secondary axis on the colorbar (left axis) has values that are so close together their labels overlap. I'm hoping to find a way to space the labels so they are readable. I thought I found a way to accomplish this using axis.set_ticklabels() (set_ticklabels() documentation. In the **kargs section of the doc it references using text properties. In the text properties documentation text properties doc the property 'y' says you can set the y-position of the text. However, when I add this keyword to set_ticklabels() I get an error that the keyword is not recognized.. I've tried adding the property 'y' as a keyword and attribute but I get a keyword error or does not have that attribute error...
I'm calling the property wrong but I've never gotten this detailed in editing these parameters. I honestly don't know if this is the best way to solve this, but it's the closest I've gotten so far. I was hoping to use it to offset the labels so they were stacked vertically on top of each other in the same order but far enough apart that the label is readable.
Thanks for any input!
I am using a seaborn scatterplot and just started using different point sizes.
sns.scatterplot(x='X [um]', y='Y [um]', hue='label', size='size', data=data)
All works perfectly but I'd like to remove the 'size' from the legend seen in picture:
The upper part with CH1, etc. shall remain the same but I'd want the lower part where the sizes are listed to vanish.
I use the get_legend_handles_labels() functionality to index the labels. Using indexing, I ensure that the final printed image only contains the first 13 labels in your legend.
g = sns.scatterplot(x='X [um]', y='Y [um]', hue='label', size='size', data=data)
h,l = g.get_legend_handles_labels()
plt.legend(h[0:13],l[0:13],bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
plt.show(g)
I have dictionary as:
```{'0.0': 2.445616223564293,
'0.05': 2.445594095119315,
'0.1': 2.4455740588234223,
'0.15': 2.4455560866270947,
'0.2': 2.4455401509059596,
'0.25': 2.4455262244535803,
'1.0': 2.4455411399961293,
'1.05': 2.44555597697399,
'1.1': 2.4455724183134344,
'1.15': 2.4455904432448716,
'1.2': 2.445610031303073,
'1.25': 2.4456311623222002,
'2.0': 2.4461204322901566,
'3.0': 2.447205696789686,
'4.0': 2.4486856713473726,
'5.0': 2.4504762863004363,
'10.0': 2.4623061878090624,
'20.0': 2.4922549001247876}```
Here all the values are different by some small factor. However when I plot it using matplotlib the plot is not distinctive.
I want to plot "keys" in x-axis and "values" in y-axis and then find x which has minimum y value by looking the plot.
I tried this code:
```plt.plot(*zip(*data))```
But the plot is not clear. How can I solve this problem such that plot is clearly able to show the difference in values.
The problem is your interpretation of zip(*data). I would suggest before plotting you first print and see what you are trying to plot.
print (list(zip(*data))) would print a list of splitted strings (keys of your data). To plot the keys on the x-axis and the values of the y-axis, simply do the following. I leave the visualization of the minimum up to you. If you want to plot the difference, subtract the first value from the complete list of values and then plot it on the y-axis.
plt.plot(data.keys(), data.values(), '-bx')
plt.xticks(rotation=45)
I need to plot line plot that has different colors. I create special df column 'color' that contains for each point appropriate color.
I already found the solution here:
python/matplotlib - multicolor line
And take the approach from the above question. First, it was working when I use index but now I need to plot it vs other column and I can not appropriately handle the colors. It is all the time colores only with one color.
I use this code for setting colors, but it color line with one color that is the last in the column 'color'. And also create a legend that I don't understand how to delete from the plot.
for color2, start, end in gen_repeating(df2['color']):
print(start, end)
if start > 0: # make sure lines connect
start -= 1
idx = df2.index[start:end+1]
x2 = idx
y2 = df2.loc[idx, 'age_gps_data'].tolist()
df2.plot(x='river_km', y='age_gps_data', color=color2, ax=ax[1])
ax[1].xaxis.set_major_locator(plt.MaxNLocator(5))
plt.setp(ax[1].get_xticklabels())
I would appreciate any help.
How can I set these colors to achieve different color in one line? And don't have legend on the plot.
I have a file with 5 columns of data in it. The first column are x indexes, the second are y indexes and the following three contain some data on which I perform some calculations in my gnuplot script as follows:
module(a,b,c) = sqrt(a**2+b**2+c**2);
splot 'myfile' using 1:2:(module($3,$4,$5)) with image
This works fine. However, if I try to plot the log10 of the module like this:
module(a,b,c) = log10(sqrt(a**2+b**2+c**2));
splot 'myfile' using 1:2:(module($3,$4,$5)) with image
it returns a blank plot and the warning of the title of the question.
I think it might be due to the zeros that are in my data, but even when I set an xy range to avoid those, the error persists.