tombolo.plots.forest_plot

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 1import re
 2import jsonschema
 3import matplotlib.pyplot as plt
 4
 5from .primitives.forest import _forest
 6
 7_matrix = {
 8    "type": "object",
 9    "additionalProperties": {
10        "type": "object",
11        "additionalProperties": {"type": ["number", "null"]},
12    },
13}
14
15_schema = {
16    "type": "object",
17    "required": ["league"],
18    "properties": {
19        "league": {
20            "type": "object",
21            "required": ["md", "lower", "upper"],
22            "properties": {
23                "md": _matrix,
24                "lower": _matrix,
25                "upper": _matrix,
26                "pval": _matrix,
27            },
28        }
29    },
30}
31
32
33def forest_plot(data: dict, reference: str) -> plt.Figure:
34    """Forest plot of all treatments relative to a reference.
35
36    Args:
37        data: Result dict from `tombolo.nma` or `tombolo.bnma`. Only `league` is used.
38        reference: Name of the reference treatment. All other treatments are plotted
39            relative to it, sorted by effect size. Non-alphanumeric characters are
40            normalized to underscores.
41
42    Returns:
43        Mean differences and confidence (or credible) intervals for each treatment
44        versus the reference. P-values are included for NMA results.
45
46    Raises:
47        RuntimeError: If `reference` is not found in the data.
48    """
49    jsonschema.validate(instance=data, schema=_schema)
50    ref = re.sub(r"[^A-Za-z0-9_]", "_", reference)
51    if ref not in data["league"]["md"]:
52        raise RuntimeError("Missing reference")
53    label = "[95% CI]" if "pval" in data["league"] else "[95% CrI]"
54    return _forest(data["league"], ref, interval_label=label)

def forest_plot(data: dict, reference: str) -> matplotlib.figure.Figure: View Source

34def forest_plot(data: dict, reference: str) -> plt.Figure:
35    """Forest plot of all treatments relative to a reference.
36
37    Args:
38        data: Result dict from `tombolo.nma` or `tombolo.bnma`. Only `league` is used.
39        reference: Name of the reference treatment. All other treatments are plotted
40            relative to it, sorted by effect size. Non-alphanumeric characters are
41            normalized to underscores.
42
43    Returns:
44        Mean differences and confidence (or credible) intervals for each treatment
45        versus the reference. P-values are included for NMA results.
46
47    Raises:
48        RuntimeError: If `reference` is not found in the data.
49    """
50    jsonschema.validate(instance=data, schema=_schema)
51    ref = re.sub(r"[^A-Za-z0-9_]", "_", reference)
52    if ref not in data["league"]["md"]:
53        raise RuntimeError("Missing reference")
54    label = "[95% CI]" if "pval" in data["league"] else "[95% CrI]"
55    return _forest(data["league"], ref, interval_label=label)

Forest plot of all treatments relative to a reference.

Args: data: Result dict from tombolo.nma or tombolo.bnma. Only league is used. reference: Name of the reference treatment. All other treatments are plotted relative to it, sorted by effect size. Non-alphanumeric characters are normalized to underscores.

Returns: Mean differences and confidence (or credible) intervals for each treatment versus the reference. P-values are included for NMA results.

Raises: RuntimeError: If reference is not found in the data.