rstoolbox.plot.
positional_structural_similarity_plot
(df, ax, alpha_color='royalblue', beta_color='tomato', identity_color='black', identity_width=3)¶Generates a bar plot for positional prevalence of secondary structure elements.
Input data can/should be generated with positional_structural_count()
.
If there is a identity_perc
column present, which can be obtained by running
positional_structural_identity()
, it will also print a line showing how
often the secondary structure matches the expected/reference one.
Both DataFrame
obtained through the two functions can be simply
merged with:
pd.concat([df1, df2], axis=1)
Parameters: |
|
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Example
In [1]: from rstoolbox.io import parse_rosetta_file
...: from rstoolbox.analysis import positional_structural_count
...: from rstoolbox.analysis import positional_structural_identity
...: from rstoolbox.plot import positional_structural_similarity_plot
...: import pandas as pd
...: pd.set_option('display.width', 1000)
...: pd.set_option('display.max_columns', 500)
...: df = parse_rosetta_file("../rstoolbox/tests/data/input_ssebig.minisilent.gz",
...: {'scores': ['score'], 'structure': 'C'})
...: df.add_reference_structure('C', df.get_structure('C').values[0])
...: df1 = positional_structural_identity(df.iloc[1:], 'C')
...: df2 = positional_structural_count(df.iloc[1:], 'C')
...: fig = plt.figure(figsize=(35, 10))
...: ax00 = plt.subplot2grid((1, 1), (0, 0))
...: positional_structural_similarity_plot(pd.concat([df1, df2], axis=1), ax00)
...: plt.tight_layout()
...:
In [2]: plt.show()
In [3]: plt.close()