rstoolbox.plot.plot_in_context¶

rstoolbox.plot.plot_in_context(df, fig, grid, refdata, igrid=None, values='*', ref_equivalences=None, legends=False, **kwargs)¶

Plot position of decoys in a backgroud reference dataset.

Note

Personalization is possible by providing argument keys for kdeplot() with the prefix kde_ and for plot() (for the points) with the prefix point_.

Parameters:

df (DataFrame) – Data container.
fig (Figure) – Figure into which the data is going to be plotted.
grid (tuple with two int) – Shape of the grid to plot the values in the figure (rows x columns).
refdata (DataFrame) – Data content to use as reference.
igrid (tuple with two int) – Initial position of the grid. Defaults to (0, 0)
values (list() of str) – Contents from the data container that are expected to be plotted.
ref_equivalences (dict) – When names between the query data and the provided data are the same, they will be directly assigned. Here a dictionary db_name:query_name can be provided otherwise.
legends (bool) – When True, show the legends of each axis.

Returns:

list() of Axes

Raises:

ValueError:	If columns are requested that do not exist in the `DataFrame` of data and reference.
ValueError:	If the given grid does not have enought positions for all the requested values.
ValueError:	If `refdata` or `df` are not `DataFrame`.

Example:

In [1]: from rstoolbox.plot import plot_in_context
   ...: from rstoolbox.utils import load_refdata
   ...: import matplotlib.pyplot as plt
   ...: df = load_refdata('scop2')
   ...: slength = 100
   ...: refdf = load_refdata('scop2', 50)
   ...: refdf = refdf[(refdf['length'] >= slength - 5) &
   ...:               (refdf['length'] <= slength + 5)]
   ...: values = ["score", "hbond_sr_bb", "avdegree", "hbond_bb_sc",
   ...:           "cavity", "CYDentropy", "pack", "radius"]
   ...: fig = plt.figure(figsize=(25, 10))
   ...: axs = plot_in_context(df, fig, (2, 4), refdata=refdf, values=values)
   ...: plt.tight_layout()
   ...: 

In [2]: plt.show()

In [3]: plt.close()