Vehicle-Anti-Theft-Face-Recognition-System/venv/Lib/site-packages/matplotlib/tests/test_backend_bases.py

import re

from matplotlib.backend_bases import (
    FigureCanvasBase, LocationEvent, MouseButton, MouseEvent,
    NavigationToolbar2, RendererBase)
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import matplotlib.path as path
import os
import numpy as np
import pytest


def test_uses_per_path():
    id = transforms.Affine2D()
    paths = [path.Path.unit_regular_polygon(i) for i in range(3, 7)]
    tforms_matrices = [id.rotate(i).get_matrix().copy() for i in range(1, 5)]
    offsets = np.arange(20).reshape((10, 2))
    facecolors = ['red', 'green']
    edgecolors = ['red', 'green']

    def check(master_transform, paths, all_transforms,
              offsets, facecolors, edgecolors):
        rb = RendererBase()
        raw_paths = list(rb._iter_collection_raw_paths(
            master_transform, paths, all_transforms))
        gc = rb.new_gc()
        ids = [path_id for xo, yo, path_id, gc0, rgbFace in
               rb._iter_collection(
                   gc, master_transform, all_transforms,
                   range(len(raw_paths)), offsets,
                   transforms.AffineDeltaTransform(master_transform),
                   facecolors, edgecolors, [], [], [False],
                   [], 'screen')]
        uses = rb._iter_collection_uses_per_path(
            paths, all_transforms, offsets, facecolors, edgecolors)
        if raw_paths:
            seen = np.bincount(ids, minlength=len(raw_paths))
            assert set(seen).issubset([uses - 1, uses])

    check(id, paths, tforms_matrices, offsets, facecolors, edgecolors)
    check(id, paths[0:1], tforms_matrices, offsets, facecolors, edgecolors)
    check(id, [], tforms_matrices, offsets, facecolors, edgecolors)
    check(id, paths, tforms_matrices[0:1], offsets, facecolors, edgecolors)
    check(id, paths, [], offsets, facecolors, edgecolors)
    for n in range(0, offsets.shape[0]):
        check(id, paths, tforms_matrices, offsets[0:n, :],
              facecolors, edgecolors)
    check(id, paths, tforms_matrices, offsets, [], edgecolors)
    check(id, paths, tforms_matrices, offsets, facecolors, [])
    check(id, paths, tforms_matrices, offsets, [], [])
    check(id, paths, tforms_matrices, offsets, facecolors[0:1], edgecolors)


def test_get_default_filename(tmpdir):
    plt.rcParams['savefig.directory'] = str(tmpdir)
    fig = plt.figure()
    canvas = FigureCanvasBase(fig)
    filename = canvas.get_default_filename()
    assert filename == 'image.png'


def test_canvas_change():
    fig = plt.figure()
    # Replaces fig.canvas
    canvas = FigureCanvasBase(fig)
    # Should still work.
    plt.close(fig)
    assert not plt.fignum_exists(fig.number)


@pytest.mark.backend('pdf')
def test_non_gui_warning(monkeypatch):
    plt.subplots()

    monkeypatch.setitem(os.environ, "DISPLAY", ":999")

    with pytest.warns(UserWarning) as rec:
        plt.show()
        assert len(rec) == 1
        assert ('Matplotlib is currently using pdf, which is a non-GUI backend'
                in str(rec[0].message))

    with pytest.warns(UserWarning) as rec:
        plt.gcf().show()
        assert len(rec) == 1
        assert ('Matplotlib is currently using pdf, which is a non-GUI backend'
                in str(rec[0].message))


@pytest.mark.parametrize(
    "x, y", [(42, 24), (None, 42), (None, None), (200, 100.01), (205.75, 2.0)])
def test_location_event_position(x, y):
    # LocationEvent should cast its x and y arguments to int unless it is None.
    fig, ax = plt.subplots()
    canvas = FigureCanvasBase(fig)
    event = LocationEvent("test_event", canvas, x, y)
    if x is None:
        assert event.x is None
    else:
        assert event.x == int(x)
        assert isinstance(event.x, int)
    if y is None:
        assert event.y is None
    else:
        assert event.y == int(y)
        assert isinstance(event.y, int)
    if x is not None and y is not None:
        assert re.match(
            "x={} +y={}".format(ax.format_xdata(x), ax.format_ydata(y)),
            ax.format_coord(x, y))
        ax.fmt_xdata = ax.fmt_ydata = lambda x: "foo"
        assert re.match("x=foo +y=foo", ax.format_coord(x, y))


def test_interactive_zoom():
    fig, ax = plt.subplots()
    ax.set(xscale="logit")
    assert ax.get_navigate_mode() is None

    tb = NavigationToolbar2(fig.canvas)
    tb.zoom()
    assert ax.get_navigate_mode() == 'ZOOM'

    xlim0 = ax.get_xlim()
    ylim0 = ax.get_ylim()

    # Zoom from x=1e-6, y=0.1 to x=1-1e-5, 0.8 (data coordinates, "d").
    d0 = (1e-6, 0.1)
    d1 = (1-1e-5, 0.8)
    # Convert to screen coordinates ("s").  Events are defined only with pixel
    # precision, so round the pixel values, and below, check against the
    # corresponding xdata/ydata, which are close but not equal to d0/d1.
    s0 = ax.transData.transform(d0).astype(int)
    s1 = ax.transData.transform(d1).astype(int)

    # Zoom in.
    start_event = MouseEvent(
        "button_press_event", fig.canvas, *s0, MouseButton.LEFT)
    fig.canvas.callbacks.process(start_event.name, start_event)
    stop_event = MouseEvent(
        "button_release_event", fig.canvas, *s1, MouseButton.LEFT)
    fig.canvas.callbacks.process(stop_event.name, stop_event)
    assert ax.get_xlim() == (start_event.xdata, stop_event.xdata)
    assert ax.get_ylim() == (start_event.ydata, stop_event.ydata)

    # Zoom out.
    start_event = MouseEvent(
        "button_press_event", fig.canvas, *s1, MouseButton.RIGHT)
    fig.canvas.callbacks.process(start_event.name, start_event)
    stop_event = MouseEvent(
        "button_release_event", fig.canvas, *s0, MouseButton.RIGHT)
    fig.canvas.callbacks.process(stop_event.name, stop_event)
    # Absolute tolerance much less than original xmin (1e-7).
    assert ax.get_xlim() == pytest.approx(xlim0, rel=0, abs=1e-10)
    assert ax.get_ylim() == pytest.approx(ylim0, rel=0, abs=1e-10)

    tb.zoom()
    assert ax.get_navigate_mode() is None