A simple matplotlib wrapper to avoid writing multiple plt. statements.
pip install beautifyPlot
matplotlib code:
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0,100,1)
y = x**3
plt.plot(x,y,label='y=f(x)')
plt.title("test plot")
plt.xlim([0,10])
plt.ylim([0,1000])
plt.legend(fontsize=15)
plt.tight_layout()Using beautifyPlot
from beautifyPlot.bplt import beautifyPlot
import numpy as np
x = np.arange(0,100,1)
y = x**3
plt.plot(x,y,label='y=f(x)')
plotArgs = {
'title' : ['test plot'], ## Use list to pass a set of arguments to the function
'xlim' : [0,10],
'ylim' : [0,1000],
'legend' : {'fontsize':15, 'loc':'best'}, ## Use dictionary to specify arguments
'tight_layout' : [] ## Leave list empty if there is nothing to pass
}
beautifyPlot(plotArgs)
## Next steps: Save plotArgs as JSON or use the same plot arguments in a different subplot/plot.Using beautifyPlot (with shorthand notation)
from beautifyPlot.bplt import beautifyPlot
import numpy as np
x = np.arange(0,100,1)
y = x**3
plt.plot(x,y,label='y=f(x)')
plotArgs ={
't' : ['test plot'],
'xl' : [0,10],
'yl' : [0,1000],
'l' : {'fontsize':15, 'loc':'best'},
't_l' : []
}
beautifyPlot(plotArgs)| shorthand | command |
|---|---|
| "l" | plt.legend |
| "t_p" | plt.tick_params |
| "t_l" | plt.tight_layout |
| "t" | plt.title |
| "xl" | plt.xlim |
| "yl" | plt.ylim |
| "xt" | plt.xticks |
| "yt" | plt.yticks |
| "xlab" | plt.xlabel |
| "ylab" | plt.ylabel |
| "xs" | plt.xscale |
| "ys" | plt.yscale |