Comments (2)
Hey Steffan,
I hope you are well. Thank you for the great question! Here is a hacky workaround using the currently unsupported subplots_adjust
function (gasp):
import pandas as pd
import matplotlib.pyplot as plt
import paxplot
json_str = '{"$v_{m_{0}}$":{"0":1.05101414,"1":0.97541944,"2":1.02250952,"3":1.05724531,"4":0.91881114,"5":1.00289782,"6":1.02356087,"7":0.91879598,"8":0.91856527,"9":1.05471083,"10":1.03512956,"11":1.01495961,"12":0.99814463,"13":1.08194644,"14":1.00435071,"15":0.91008701,"16":1.02191995,"17":1.0104185,"18":1.05577619,"19":1.03793584},"$v_{m_{1}}$":{"0":1.08675354,"1":0.99289773,"2":1.0006575,"3":1.03279003,"4":1.04013416,"5":1.00186099,"6":0.94705512,"7":1.08785596,"8":0.9901675,"9":1.03153871,"10":1.00552627,"11":0.97142502,"12":1.0635523,"13":0.94439644,"14":1.04267524,"15":1.00328082,"16":0.96776328,"17":1.05307138,"18":1.06106298,"19":1.04153575},"$v_{m_{2}}$":{"0":1.06366783,"1":0.91104843,"2":1.06438557,"3":1.00671504,"4":1.05875128,"5":0.97205114,"6":1.05476759,"7":0.99542596,"8":0.95052276,"9":1.02192044,"10":0.9318766,"11":0.92399757,"12":1.01605039,"13":1.0046992,"14":1.02006368,"15":1.04490573,"16":0.95427917,"17":0.92809566,"18":1.01760408,"19":1.06606671},"$v_{m_{3}}$":{"0":1.07216311,"1":0.97654954,"2":1.03222464,"3":0.96508126,"4":0.92882952,"5":0.9553515,"6":1.02212038,"7":0.99203902,"8":1.0135808,"9":1.07826395,"10":1.0875509,"11":1.02785425,"12":1.03946075,"13":1.04979572,"14":1.04030671,"15":1.07928366,"16":0.94665728,"17":1.02104275,"18":1.04965773,"19":0.97794591},"$v_{m_{4}}$":{"0":0.96261164,"1":0.98230649,"2":0.99018279,"3":0.91334141,"4":1.0495412,"5":1.04518659,"6":1.07116521,"7":1.00761336,"8":0.95882059,"9":1.05051721,"10":0.95355408,"11":0.94120487,"12":0.91258196,"13":1.01900706,"14":0.94362856,"15":1.03923165,"16":0.99024211,"17":0.95139986,"18":1.00734866,"19":0.98286251},"results":{"0":-33488.121893849,"1":3980.888057873,"2":-11523.4361694497,"3":16582.4829596293,"4":-24886.4934994639,"5":-2551.3204885725,"6":-1097.4260832155,"7":4460.7742568187,"8":441.248979536,"9":-435.2766055767,"10":-19832.8660960374,"11":-19358.1526127029,"12":-37944.4309613923,"13":-12791.378116259,"14":-28921.1231681309,"15":3990.7823822596,"16":1037.0001667862,"17":-9150.0172480353,"18":-11273.0333321415,"19":22697.3994558519}}'
# Import data
df = pd.read_json(json_str)
cols = df.columns
# Create figure
paxfig = paxplot.pax_parallel(n_axes=len(cols))
paxfig.plot(df.to_numpy())
# Add labels
paxfig.set_labels(cols)
# Add colorbar
plt.subplots_adjust(right=0.8) # Adding whitespace
color_col = 5
paxfig.add_colorbar(
ax_idx=color_col,
cmap='viridis',
colorbar_kwargs={
'label': cols[color_col],
'fraction': 0.65, # moving colorbar
'anchor': (4.5, 1.0), # moving colorbar
}
)
paxfig.set_size_inches(8, 4)
plt.show()
Long-term, it would be great to actually address the overlapping colorbar/legend issue. Under the hood, paxplot creates an additional subplot but in the case of long tick labels on the last axis (in your example) this approach yields the overlapping you describe. Additionally, support for tight_layout
would also be great, as you mentioned.
If you or anyone reading this thread wants to take on either of these issues, I would be happy to support your efforts!
from paxplot.
Thanks @kravitsjacob for your answers and ideas! I would let the issue open to allow others to take up the ideas and contributing.
from paxplot.
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from paxplot.