mandos.analysis.io_defns

Complexity

Total Complexity

2

Size/Duplication

Total Lines	69
Duplicated Lines	0 %

Importance

Changes

0

1 Function

Rating	Name	Duplication	Size	Complexity
A	_to_long_form()	0	8	2

"""
Definitions of input types for analysis.
"""

import math

The import math seems to be unused.

from collections import defaultdict

Unused defaultdict imported from collections

from itertools import cycle

Unused cycle imported from itertools

from typing import Collection, Dict, Sequence, Set, Tuple, Union, Optional

Unused Dict imported from typing

Unused Union imported from typing

Unused Tuple imported from typing

Unused Set imported from typing

Unused Sequence imported from typing

Unused Collection imported from typing

Unused Optional imported from typing

import numpy as np

Unable to import 'numpy'

Unused numpy imported as np

import pandas as pd

Unable to import 'pandas'

Unused pandas imported as pd

from typeddfs import TypedDfs

Unable to import 'typeddfs'

def _to_long_form(self, kind: str, key: str):
    if kind not in ["phi", "psi"]:
        raise ValueError(f"'type' should be 'phi' or 'psi', not {kind}")
    df = self.long_form()

Variable name "df" doesn't conform to snake_case naming style ('([^\\W\\dA-Z][^\\WA-Z]2,|_[^\\WA-Z]*|__[^\\WA-Z\\d_][^\\WA-Z]+__)$' pattern)

    df = df.rename(columns=dict(row="inchikey_1", column="inchikey_2"))

Variable name "df" doesn't conform to snake_case naming style ('([^\\W\\dA-Z][^\\WA-Z]2,|_[^\\WA-Z]*|__[^\\WA-Z\\d_][^\\WA-Z]+__)$' pattern)

    df["type"] = kind
    df["key"] = key
    return SimilarityDfLongForm.convert(df)


SimilarityDfLongForm = (
    TypedDfs.typed("SimilarityDfLongForm")
    .require("inchikey_1", "inchikey_2", dtype=str)
    .require("type", "key", dtype=str)
    .require("value", dtype=float)
    .reserve("sample", dtype=int)
    .strict()
).build()

SimilarityDfShortForm = (
    TypedDfs.affinity_matrix("SimilarityDfShortForm").add_methods(to_long_form=_to_long_form)
).build()

ScoreDf = (
    TypedDfs.typed("InputScoreFrame")
    .require("inchikey", "score_name", dtype=str)
    .require("score_value", dtype=float)
).build()


EnrichmentDf = (
    TypedDfs.typed("EnrichmentFrame")
    .require("predicate", "object", "key", "source", dtype=str)
    .require("score_name", dtype=str)
    .require("value", "inverse", dtype=float)
    .reserve("sample", dtype=int)
).build()


ConcordanceDf = (
    TypedDfs.typed("ConcordanceDf")
    .require("phi", "psi", dtype=str)
    .require("tau", dtype=float)
    .reserve("sample", dtype=int)
).build()


PsiProjectedDf = (
    TypedDfs.typed("PsiProjectedDf")
    .require("psi", dtype=str)
    .require("inchikey", dtype=str)
    .require("x", "y", dtype=float)
    .reserve("color", "marker", dtype=str)
).build()