# /// script
# requires-python = ">=3.10"
# dependencies = ['matplotlib', 'numpy', 'pyperf']
# ///
"""pyperf micro-benchmarks for matplotlib axis/tick init+clear cost.

"""
import pyperf

setup = """
import matplotlib
matplotlib.use("Agg")
# matplotlib.use("QtAgg")  # snap/glibc mismatch; use offscreen:
# import os; os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")

import numpy as np
import matplotlib.pyplot as plt

GRID = 8
rng = np.random.default_rng(0)
x1000 = np.arange(1000)
y1000 = rng.standard_normal(1000)

# Pre-create reusable figure for clear_grid / reuse_axes cases.
_fig_clear = plt.figure()
_fig_grid, _axs_grid = plt.subplots(GRID, GRID)
_axs_flat = _axs_grid.ravel()

# Warmup — first call pays font-cache / backend-init costs.
plt.close(plt.subplots(GRID, GRID)[0])
"""

runner = pyperf.Runner()

# Fresh figure each iter — full Axes.__init__ cost for an 8x8 grid.
runner.timeit(
    name="init_grid 8x8",
    stmt="fig, axs = plt.subplots(GRID, GRID); plt.close(fig)",
    setup=setup,
)

# Reuse one Figure, clear + re-populate with an 8x8 grid.
runner.timeit(
    name="clear_grid 8x8",
    stmt="_fig_clear.clear(); _fig_clear.subplots(GRID, GRID)",
    setup=setup,
)

# Iterate ax.clear() across an existing 8x8 grid.
runner.timeit(
    name="reuse_axes 8x8",
    stmt="[ax.clear() for ax in _axs_flat]",
    setup=setup,
)

# Figure num=100: clear + plot 1000-point line + legend. Reuses the same
# numbered figure across iterations so only clear+plot+legend is measured.
runner.timeit(
    name="fig100 clear+plot1000+legend",
    stmt=(
        "fig = plt.figure(num=100);"
        " fig.clear();"
        " ax = fig.add_subplot();"
        " ax.plot(x1000, y1000, label='y');"
        " ax.legend()"
    ),
    setup=setup,
)