18209569030

Committed 03 Oct 2025 12:42AM UTC coverage: 80.878% (+1.6%) from 79.246%

Build # 18209569030

Build Type

push

github

Committed by

avivajpeyi

Commit Message

fix logger

Coverage Stats

549 of 654 branches covered (83.94%)

Branch coverage included in aggregate %.

2 of 2 new or added lines in 1 file covered. (100.0%)

469 existing lines in 17 files now uncovered.

3799 of 4722 relevant lines covered (80.45%)

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Source File
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93.22

/src/log_psplines/benchmark/plotting.py

import json
import os
from typing import List

import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
from matplotlib.patches import Patch

from ..logger import logger

MH_COLOR = "tab:blue"
NUTS_COLOR = "tab:orange"
GPU_MARKER = "o--"
CPU_MARKER = "s-"
CPU_ALPHA = 0.75
GPU_ALPHA = 1.0

CPU_KWGS = dict(alpha=0.75, filled=False)
GPU_KWGS = dict(alpha=1.0, filled=True)
MH_KWGS = dict(color=MH_COLOR)
NUTS_KWGS = dict(color=NUTS_COLOR)


def logspace_widths(xs, log_width=0.1):
    xs = np.array(xs)
    return 10 ** (np.log10(xs) + log_width / 2) - 10 ** (
        np.log10(xs) - log_width / 2
    )


def plot_box(ax, xs, ys, color="C0", alpha=0.7, filled=True):
    xscale = ax.get_xscale()

    if xscale == "log":
        widths = logspace_widths(xs, log_width=0.1)
    else:
        widths = None

    bp = ax.boxplot(
        ys,
        positions=xs,
        widths=widths,
        patch_artist=True,
        showfliers=False,
        label=None,
    )

    for box in bp["boxes"]:
        if filled:
            box.set_facecolor(color)
            box.set_alpha(alpha)
            box.set_linewidth(0)
        else:
            box.set_facecolor("none")
            box.set_edgecolor(color)
            box.set_alpha(alpha)
            box.set_linewidth(3)

    for median in bp["medians"]:
        median.set_color(color)
        median.set_alpha(alpha)

    for element in ["whiskers", "caps"]:
        for line in bp[element]:
            line.set_color(color)
            line.set_alpha(alpha)


def plot_ess(*args, **kwargs):
    plot_box(*args, **kwargs)
    args[0].set_ylabel("ESS")


def plot_runtimes(*args, **kwargs):
    plot_box(*args, **kwargs)
    args[0].set_ylabel("Runtime (seconds)")
    args[0].set_yscale("log")


def plot_data_size_results(filepaths: List[str]) -> None:
    """Plot data size analysis results."""

    fig, axes = plt.subplots(2, 1, sharex=True)
    axes[0].set_xscale("log")

    for filepath in filepaths:
        if not os.path.exists(filepath):
            logger.info(f"Data file {filepath} not found")
            continue

        with open(filepath, "r") as f:
            data = json.load(f)

        kwgs = _get_kwgs(filepath)
        plot_ess(axes[0], data["ns"], data["ess"], **kwgs)
        plot_runtimes(axes[1], data["ns"], data["runtimes"], **kwgs)

    axes[1].set_xlabel(r"$N$")

    axes[1].set_xscale("log")
    axes[1].xaxis.set_major_locator(ticker.LogLocator(base=10.0, numticks=10))
    axes[1].xaxis.set_minor_locator(
        ticker.LogLocator(base=10.0, subs="auto", numticks=10)
    )
    axes[1].xaxis.set_major_formatter(ticker.LogFormatterMathtext())
    axes[1].xaxis.set_minor_formatter(ticker.NullFormatter())

    # remove vertical space between subplots
    _add_legend(axes[0], [os.path.basename(f) for f in filepaths])
    plt.subplots_adjust(hspace=0.0)
    fdir = os.path.dirname(filepaths[0])

    plt.savefig(f"{fdir}/N_vs_runtime.png", dpi=150)
    plt.close()


def plot_knots_results(filepaths: List[str]) -> None:
    """Plot knots analysis results."""

    fig, axes = plt.subplots(2, 1, sharex=True)

    for filepath in filepaths:
        if not os.path.exists(filepath):
            logger.info(f"Data file {filepath} not found")
            continue

        with open(filepath, "r") as f:
            data = json.load(f)

        kwgs = {
            **(MH_KWGS if data["sampler"] == "mh" else NUTS_KWGS),
            **(CPU_KWGS if data["device"] == "cpu" else GPU_KWGS),
        }
        plot_ess(axes[0], data["ks"], data["ess"], **kwgs)
        plot_runtimes(axes[1], data["ks"], data["runtimes"], **kwgs)

    axes[1].set_xlabel(r"$K$")

    # use autoformatter for x ticks
    axes[1].xaxis.set_major_locator(ticker.AutoLocator())
    axes[1].xaxis.set_major_formatter(ticker.ScalarFormatter())

    _add_legend(axes[0], [os.path.basename(f) for f in filepaths])
    plt.subplots_adjust(hspace=0.0)
    fdir = os.path.dirname(filepaths[0])

    plt.savefig(f"{fdir}/K_vs_runtime.png", dpi=150)
    plt.close()


def _get_kwgs(fname: str):
    return {
        **(MH_KWGS if "_mh_" in fname else NUTS_KWGS),
        **(CPU_KWGS if "cpu" in fname else GPU_KWGS),
    }


def _add_legend(ax, fnames: List[str]) -> None:
    """Add legend to the axes."""

    patches, labels = [], []
    for fname in fnames:
        kwgs = _get_kwgs(fname)
        if kwgs["filled"]:
            p = Patch(color=kwgs["color"], alpha=kwgs["alpha"])
        else:
            p = Patch(
                edgecolor=kwgs["color"], alpha=kwgs["alpha"], facecolor="none"
            )
        patches.append(p)

        sampler = "MH" if "mh" in fname else "NUTS"
        device = "CPU" if "cpu" in fname else "GPU"
        labels.append(f"{sampler} ({device})")

    ax.legend(
        handles=patches,
        labels=labels,
        frameon=True,
        fontsize="small",
        loc="upper right",
    )

1	import json	2✔
2	import os	2✔
3	from typing import List	2✔
4
5	import matplotlib.pyplot as plt	2✔
6	import matplotlib.ticker as ticker	2✔
7	import numpy as np	2✔
8	from matplotlib.patches import Patch	2✔
9
10	from ..logger import logger	2✔
11
12	MH_COLOR = "tab:blue"	2✔
13	NUTS_COLOR = "tab:orange"	2✔
14	GPU_MARKER = "o--"	2✔
15	CPU_MARKER = "s-"	2✔
16	CPU_ALPHA = 0.75	2✔
17	GPU_ALPHA = 1.0	2✔
18
19	CPU_KWGS = dict(alpha=0.75, filled=False)	2✔
20	GPU_KWGS = dict(alpha=1.0, filled=True)	2✔
21	MH_KWGS = dict(color=MH_COLOR)	2✔
22	NUTS_KWGS = dict(color=NUTS_COLOR)	2✔
23
24
25	def logspace_widths(xs, log_width=0.1):	2✔
26	xs = np.array(xs)	2✔
27	return 10 (np.log10(xs) + log_width / 2) - 10 (	2✔
28	np.log10(xs) - log_width / 2
29	)
30
31
32	def plot_box(ax, xs, ys, color="C0", alpha=0.7, filled=True):	2✔
33	xscale = ax.get_xscale()	2✔
34
35	if xscale == "log":	2✔
36	widths = logspace_widths(xs, log_width=0.1)	2✔
37	else:
38	widths = None	2✔
39
40	bp = ax.boxplot(	2✔
41	ys,
42	positions=xs,
43	widths=widths,
44	patch_artist=True,
45	showfliers=False,
46	label=None,
47	)
48
49	for box in bp["boxes"]:	2✔
50	if filled:	2✔
51	box.set_facecolor(color)	×
UNCOV 52	box.set_alpha(alpha)	×
UNCOV 53	box.set_linewidth(0)	×
54	else:
55	box.set_facecolor("none")	2✔
56	box.set_edgecolor(color)	2✔
57	box.set_alpha(alpha)	2✔
58	box.set_linewidth(3)	2✔
59
60	for median in bp["medians"]:	2✔
61	median.set_color(color)	2✔
62	median.set_alpha(alpha)	2✔
63
64	for element in ["whiskers", "caps"]:	2✔
65	for line in bp[element]:	2✔
66	line.set_color(color)	2✔
67	line.set_alpha(alpha)	2✔
68
69
70	def plot_ess(args, *kwargs):	2✔
71	plot_box(args, *kwargs)	2✔
72	args[0].set_ylabel("ESS")	2✔
73
74
75	def plot_runtimes(args, *kwargs):	2✔
76	plot_box(args, *kwargs)	2✔
77	args[0].set_ylabel("Runtime (seconds)")	2✔
78	args[0].set_yscale("log")	2✔
79
80
81	def plot_data_size_results(filepaths: List[str]) -> None:	2✔
82	"""Plot data size analysis results."""
83
84	fig, axes = plt.subplots(2, 1, sharex=True)	2✔
85	axes[0].set_xscale("log")	2✔
86
87	for filepath in filepaths:	2✔
88	if not os.path.exists(filepath):	2✔
UNCOV 89	logger.info(f"Data file {filepath} not found")	×
UNCOV 90	continue	×
91
92	with open(filepath, "r") as f:	2✔
93	data = json.load(f)	2✔
94
95	kwgs = _get_kwgs(filepath)	2✔
96	plot_ess(axes[0], data["ns"], data["ess"], **kwgs)	2✔
97	plot_runtimes(axes[1], data["ns"], data["runtimes"], **kwgs)	2✔
98
99	axes[1].set_xlabel(r"$N$")	2✔
100
101	axes[1].set_xscale("log")	2✔
102	axes[1].xaxis.set_major_locator(ticker.LogLocator(base=10.0, numticks=10))	2✔
103	axes[1].xaxis.set_minor_locator(	2✔
104	ticker.LogLocator(base=10.0, subs="auto", numticks=10)
105	)
106	axes[1].xaxis.set_major_formatter(ticker.LogFormatterMathtext())	2✔
107	axes[1].xaxis.set_minor_formatter(ticker.NullFormatter())	2✔
108
109	# remove vertical space between subplots
110	_add_legend(axes[0], [os.path.basename(f) for f in filepaths])	2✔
111	plt.subplots_adjust(hspace=0.0)	2✔
112	fdir = os.path.dirname(filepaths[0])	2✔
113
114	plt.savefig(f"{fdir}/N_vs_runtime.png", dpi=150)	2✔
115	plt.close()	2✔
116
117
118	def plot_knots_results(filepaths: List[str]) -> None:	2✔
119	"""Plot knots analysis results."""
120
121	fig, axes = plt.subplots(2, 1, sharex=True)	2✔
122
123	for filepath in filepaths:	2✔
124	if not os.path.exists(filepath):	2✔
UNCOV 125	logger.info(f"Data file {filepath} not found")	×
UNCOV 126	continue	×
127
128	with open(filepath, "r") as f:	2✔
129	data = json.load(f)	2✔
130
131	kwgs = {	2✔
132	**(MH_KWGS if data["sampler"] == "mh" else NUTS_KWGS),
133	**(CPU_KWGS if data["device"] == "cpu" else GPU_KWGS),
134	}
135	plot_ess(axes[0], data["ks"], data["ess"], **kwgs)	2✔
136	plot_runtimes(axes[1], data["ks"], data["runtimes"], **kwgs)	2✔
137
138	axes[1].set_xlabel(r"$K$")	2✔
139
140	# use autoformatter for x ticks
141	axes[1].xaxis.set_major_locator(ticker.AutoLocator())	2✔
142	axes[1].xaxis.set_major_formatter(ticker.ScalarFormatter())	2✔
143
144	_add_legend(axes[0], [os.path.basename(f) for f in filepaths])	2✔
145	plt.subplots_adjust(hspace=0.0)	2✔
146	fdir = os.path.dirname(filepaths[0])	2✔
147
148	plt.savefig(f"{fdir}/K_vs_runtime.png", dpi=150)	2✔
149	plt.close()	2✔
150
151
152	def _get_kwgs(fname: str):	2✔
153	return {	2✔
154	**(MH_KWGS if "_mh_" in fname else NUTS_KWGS),
155	**(CPU_KWGS if "cpu" in fname else GPU_KWGS),
156	}
157
158
159	def _add_legend(ax, fnames: List[str]) -> None:	2✔
160	"""Add legend to the axes."""
161
162	patches, labels = [], []	2✔
163	for fname in fnames:	2✔
164	kwgs = _get_kwgs(fname)	2✔
165	if kwgs["filled"]:	2✔
UNCOV 166	p = Patch(color=kwgs["color"], alpha=kwgs["alpha"])	×
167	else:
168	p = Patch(	2✔
169	edgecolor=kwgs["color"], alpha=kwgs["alpha"], facecolor="none"
170	)
171	patches.append(p)	2✔
172
173	sampler = "MH" if "mh" in fname else "NUTS"	2✔
174	device = "CPU" if "cpu" in fname else "GPU"	2✔
175	labels.append(f"{sampler} ({device})")	2✔
176
177	ax.legend(	2✔
178	handles=patches,
179	labels=labels,
180	frameon=True,
181	fontsize="small",
182	loc="upper right",
183	)

nz-gravity / LogPSplinePSD / 18209569030

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