10000 Use np.hypot whereever possible. · matplotlib/matplotlib@5a00e0d · GitHub
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anntzeranntzer
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Use np.hypot whereever possible.
Except examples, where it may be too obscure? Also added -T to CI sphinx-build invocation, to help troubleshooting e.g. https://circleci.com/gh/anntzer/matplotlib/2505?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link (show traceback on sphinx failure).
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+68
-82
lines changed
  • test_streamplot.py
  • test_triangulation.py
  • tri
  • widgets.py
  • mpl_toolkits
  • unit

    • 23 files changed

    +68
    -82
    lines changed

    ‎.circleci/config.yml

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -68,7 +68,7 @@ mpl-run: &mpl-install
    6868

    6969
    doc-run: &doc-build
    7070
    name: Build documentation
    71-
    command: make html
    71+
    command: make html O=-T
    7272
    working_directory: doc
    7373

    7474
    doc-bundle-run: &doc-bundle

    ‎examples/event_handling/pick_event_demo.py

    Lines changed: 2 additions & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -122,7 +122,8 @@ def line_picker(line, mouseevent):
    122122
    xdata = line.get_xdata()
    123123
    ydata = line.get_ydata()
    124124
    maxd = 0.05
    125-
    d = np.sqrt((xdata - mouseevent.xdata)**2. + (ydata - mouseevent.ydata)**2.)
    125+
    d = np.sqrt(
    126+
    (xdata - mouseevent.xdata)**2 + (ydata - mouseevent.ydata)**2)
    126127

    127128
    ind = np.nonzero(np.less_equal(d, maxd))
    128129
    if len(ind):

    ‎examples/images_contours_and_fields/barb_demo.py

    Lines changed: 5 additions & 3 deletions
    Original file line numberDiff line numberDiff line change
    @@ -28,12 +28,14 @@
    2828

    2929
    # Arbitrary set of vectors, make them longer and change the pivot point
    3030
    # (point around which they're rotated) to be the middle
    31-
    axs1[0, 1].barbs(data['x'], data['y'], data['u'], data['v'], length=8, pivot='middle')
    31+
    axs1[0, 1].barbs(
    32+
    data['x'], data['y'], data['u'], data['v'], length=8, pivot='middle')
    3233

    3334
    # Showing colormapping with uniform grid. Fill the circle for an empty barb,
    3435
    # don't round the values, and change some of the size parameters
    35-
    axs1[1, 0].barbs(X, Y, U, V, np.sqrt(U * U + V * V), fill_empty=True, rounding=False,
    36-
    sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3))
    36+
    axs1[1, 0].barbs(
    37+
    X, Y, U, V, np.sqrt(U ** 2 + V ** 2), fill_empty=True, rounding=False,
    38+
    sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3))
    3739

    3840
    # Change colors as well as the increments for parts of the barbs
    3941
    axs1[1, 1].barbs(data['x'], data['y'], data['u'], data['v'], flagcolor='r',

    ‎examples/images_contours_and_fields/contourf_demo.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -30,7 +30,7 @@
    3030
    Z[:nr // 6, :nc // 6] = np.ma.masked
    3131

    3232
    # mask a circle in the middle:
    33-
    interior = np.sqrt((X**2) + (Y**2)) < 0.5
    33+
    interior = np.sqrt(X**2 + Y**2) < 0.5
    3434
    Z[interior] = np.ma.masked
    3535

    3636
    # We are using automatic selection of contour levels;

    ‎examples/images_contours_and_fields/plot_streamplot.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -20,7 +20,7 @@
    2020
    Y, X = np.mgrid[-w:w:100j, -w:w:100j]
    2121
    U = -1 - X**2 + Y
    2222
    V = 1 + X - Y**2
    23-
    speed = np.sqrt(U*U + V*V)
    23+
    speed = np.sqrt(U**2 + V**2)
    2424

    2525
    fig = plt.figure(figsize=(7, 9))
    2626
    gs = gridspec.GridSpec(nrows=3, ncols=2, height_ratios=[1, 1, 2])

    ‎examples/lines_bars_and_markers/scatter_masked.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -20,7 +20,7 @@
    2020
    y = 0.9 * np.random.rand(N)
    2121
    area = np.pi * (10 * np.random.rand(N))**2 # 0 to 10 point radii
    2222
    c = np.sqrt(area)
    23-
    r = np.sqrt(x * x + y * y)
    23+
    r = np.sqrt(x ** 2 + y ** 2)
    2424
    area1 = np.ma.masked_where(r < r0, area)
    2525
    area2 = np.ma.masked_where(r >= r0, area)
    2626
    plt.scatter(x, y, s=area1, marker='^', c=c)

    ‎lib/matplotlib/contour.py

    Lines changed: 3 additions & 5 deletions
    Original file line numberDiff line numberDiff line change
    @@ -232,11 +232,9 @@ def print_label(self, linecontour, labelwidth):
    232232

    233233
    def too_close(self, x, y, lw):
    234234
    "Return *True* if a label is already near this location."
    235-
    for loc in self.labelXYs:
    236-
    d = np.sqrt((x - loc[0]) ** 2 + (y - loc[1]) ** 2)
    237-
    if d < 1.2 * lw:
    238-
    return True
    239-
    return False
    235+
    thresh = (1.2 * lw) ** 2
    236+
    return any((x - loc[0]) ** 2 + (y - loc[1]) ** 2 < thresh
    237+
    for loc in self.labelXYs)
    240238

    241239
    def get_label_coords(self, distances, XX, YY, ysize, lw):
    242240
    """

    ‎lib/matplotlib/lines.py

    Lines changed: 6 additions & 7 deletions
    Original file line numberDiff line numberDiff line change
    @@ -481,17 +481,16 @@ def contains(self, mouseevent):
    481481
    else:
    482482
    pixels = self.figure.dpi / 72. * self.pickradius
    483483

    484-
    # the math involved in checking for containment (here and inside of
    485-
    # segment_hits) assumes that it is OK to overflow. In case the
    486-
    # application has set the error flags such that an exception is raised
    487-
    # on overflow, we temporarily set the appropriate error flags here and
    488-
    # set them back when we are finished.
    484+
    # The math involved in checking for containment (here and inside of
    485+
    # segment_hits) assumes that it is OK to overflow, so temporarily set
    486+
    # the error flags accordingly.
    489487
    with np.errstate(all='ignore'):
    490488
    # Check for collision
    491489
    if self._linestyle in ['None', None]:
    492490
    # If no line, return the nearby point(s)
    493-
    d = (xt - mouseevent.x) ** 2 + (yt - mouseevent.y) ** 2
    494-
    ind, = np.nonzero(np.less_equal(d, pixels ** 2))
    491+
    ind, = np.nonzero(
    492+
    (xt - mouseevent.x) ** 2 + (yt - mouseevent.y) ** 2
    493+
    <= pixels ** 2)
    495494
    else:
    496495
    # If line, return the nearby segment(s)
    497496
    ind = segment_hits(mouseevent.x, mouseevent.y, xt, yt, pixels)

    ‎lib/matplotlib/patches.py

    Lines changed: 5 additions & 7 deletions
    Original file line numberDiff line numberDiff line change
    @@ -1338,10 +1338,8 @@ def get_path(self):
    13381338
    xb1, yb1, xb2, yb2 = self.getpoints(x1, y1, x2, y2, k1)
    13391339

    13401340
    # a point on the segment 20% of the distance from the tip to the base
    1341-
    theta = math.atan2(y2 - y1, x2 - x1)
    1342-
    r = math.sqrt((y2 - y1) ** 2. + (x2 - x1) ** 2.)
    1343-
    xm = x1 + self.frac * r * math.cos(theta)
    1344-
    ym = y1 + self.frac * r * math.sin(theta)
    1341+
    xm = x1 + self.frac * (x2 - x1)
    1342+
    ym = y1 + self.frac * (y2 - y1)
    13451343
    xc1, yc1, xc2, yc2 = self.getpoints(x1, y1, xm, ym, k1)
    13461344
    xd1, yd1, xd2, yd2 = self.getpoints(x1, y1, xm, ym, k2)
    13471345

    @@ -2899,10 +2897,10 @@ def connect(self, posA, posB):
    28992897
    codes.append(Path.LINETO)
    29002898
    else:
    29012899
    dx1, dy1 = x1 - cx, y1 - cy
    2902-
    d1 = (dx1 ** 2 + dy1 ** 2) ** .5
    2900+
    d1 = np.hypot(dx1, dy1)
    29032901
    f1 = self.rad / d1
    29042902
    dx2, dy2 = x2 - cx, y2 - cy
    2905-
    d2 = (dx2 ** 2 + dy2 ** 2) ** .5
    2903+
    d2 = np.hypot(dx2, dy2)
    29062904
    f2 = self.rad / d2
    29072905
    vertices.extend([(cx + dx1 * f1, cy + dy1 * f1),
    29082906
    (cx, cy),
    @@ -3295,7 +3293,7 @@ def transmute(self, path, mutation_size, linewidth):
    32953293

    32963294
    head_length = self.head_length * mutation_size
    32973295
    head_width = self.head_width * mutation_size
    3298-
    head_dist = math.sqrt(head_length ** 2 + head_width ** 2)
    3296+
    head_dist = np.hypot(head_length, head_width)
    32993297
    cos_t, sin_t = head_length / head_dist, head_width / head_dist
    33003298

    33013299
    # begin arrow

    ‎lib/matplotlib/projections/geo.py

    Lines changed: 7 additions & 11 deletions
    Original file line numberDiff line numberDiff line change
    @@ -465,15 +465,12 @@ def transform_non_affine(self, ll):
    465465
    diff_long = longitude - clong
    466466
    cos_diff_long = np.cos(diff_long)
    467467

    468-
    inner_k = (1.0 +
    469-
    np.sin(clat)*sin_lat +
    470-
    np.cos(clat)*cos_lat*cos_diff_long)
    471-
    # Prevent divide-by-zero problems
    472-
    inner_k = np.where(inner_k == 0.0, 1e-15, inner_k)
    473-
    k = np.sqrt(2.0 / inner_k)
    474-
    x = k*cos_lat*np.sin(diff_long)
    475-
    y = k*(np.cos(clat)*sin_lat -
    476-
    np.sin(clat)*cos_lat*cos_diff_long)
    468+
    inner_k = np.max( # Prevent divide-by-zero problems
    469+
    1 + np.sin(clat)*sin_lat + np.cos(clat)*cos_lat*cos_diff_long,
    470+
    1e-15)
    471+
    k = np.sqrt(2 / inner_k)
    472+
    x = k * cos_lat*np.sin(diff_long)
    473+
    y = k * (np.cos(clat)*sin_lat - np.sin(clat)*cos_lat*cos_diff_long)
    477474

    478475
    return np.concatenate((x, y), 1)
    479476
    transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
    @@ -497,8 +494,7 @@ def transform_non_affine(self, xy):
    497494
    y = xy[:, 1:2]
    498495
    clong = self._center_longitude
    499496
    clat = self._center_latitude
    500-
    p = np.sqrt(x*x + y*y)
    501-
    p = np.where(p == 0.0, 1e-9, p)
    497+
    p = np.max(np.hypot(x, y), 1e-9)
    502498
    c = 2.0 * np.arcsin(0.5 * p)
    503499
    sin_c = np.sin(c)
    504500
    cos_c = np.cos(c)

    ‎lib/matplotlib/projections/polar.py

    Lines changed: 2 additions & 9 deletions
    Original file line numberDiff line numberDiff line change
    @@ -151,15 +151,8 @@ def __str__(self):
    151151
    def transform_non_affine(self, xy):
    152152
    x = xy[:, 0:1]
    153153
    y = xy[:, 1:]
    154-
    r = np.sqrt(x*x + y*y)
    155-
    with np.errstate(invalid='ignore'):
    156-
    # At x=y=r=0 this will raise an
    157-
    # invalid value warning when doing 0/0
    158-
    # Divide by zero warnings are only raised when
    159-
    # the numerator is different from 0. That
    160-
    # should not happen here.
    161-
    theta = np.arccos(x / r)
    162-
    theta = np.where(y < 0, 2 * np.pi - theta, theta)
    154+
    r = np.hypot(x, y)
    155+
    theta = (np.arctan2(y, x) + 2 * np.pi) % (2 * np.pi)
    163156

    164157
    # PolarAxes does not use the theta transforms here, but apply them for
    165158
    # backwards-compatibility if not being used by it.

    ‎lib/matplotlib/streamplot.py

    Lines changed: 3 additions & 3 deletions
    Original file line numberDiff line numberDiff line change
    @@ -190,7 +190,7 @@ def streamplot(axes, x, y, u, v, density=1, linewidth=None, color=None,
    190190
    streamlines.extend(np.hstack([points[:-1], points[1:]]))
    191191

    192192
    # Add arrows half way along each trajectory.
    193-
    s = np.cumsum(np.sqrt(np.diff(tx) ** 2 + np.diff(ty) ** 2))
    193+
    s = np.cumsum(np.hypot(np.diff(tx), np.diff(ty)))
    194194
    n = np.searchsorted(s, s[-1] / 2.)
    195195
    arrow_tail = (tx[n], ty[n])
    196196
    arrow_head = (np.mean(tx[n:n + 2]), np.mean(ty[n:n + 2]))
    @@ -416,7 +416,7 @@ def get_integrator(u, v, dmap, minlength, maxlength, integration_direction):
    416416
    # speed (path length) will be in axes-coordinates
    417417
    u_ax = u / dmap.grid.nx
    418418
    v_ax = v / dmap.grid.ny
    419-
    speed = np.ma.sqrt(u_ax ** 2 + v_ax ** 2)
    419+
    speed = np.ma.hypot(u_ax, v_ax)
    420420

    421421
    def forward_time(xi, yi):
    422422
    ds_dt = interpgrid(speed, xi, yi)
    @@ -539,7 +539,7 @@ def _integrate_rk12(x0, y0, dmap, f, maxlength):
    539539

    540540
    nx, ny = dmap.grid.shape
    541541
    # Error is normalized to the axes coordinates
    542-
    error = np.sqrt(((dx2 - dx1) / nx) ** 2 + ((dy2 - dy1) / ny) ** 2)
    542+
    error = np.hypot((dx2 - dx1) / nx, (dy2 - dy1) / ny)
    543543

    544544
    # Only save step if within error tolerance
    545545
    if error < maxerror:

    ‎lib/matplotlib/tests/test_axes.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -1183,7 +1183,7 @@ def test_pcolorargs():
    11831183
    x = np.linspace(-1.5, 1.5, n)
    11841184
    y = np.linspace(-1.5, 1.5, n*2)
    11851185
    X, Y = np.meshgrid(x, y)
    1186-
    Z = np.sqrt(X**2 + Y**2)/5
    1186+
    Z = np.hypot(X, Y) / 5
    11871187

    11881188
    _, ax = plt.subplots()
    11891189
    with pytest.raises(TypeError):

    ‎lib/matplotlib/tests/test_contour.py

    Lines changed: 2 additions & 2 deletions
    Original file line numberDiff line numberDiff line change
    @@ -291,7 +291,7 @@ def test_corner_mask():
    291291
    np.random.seed([1])
    292292
    x, y = np.meshgrid(np.linspace(0, 2.0, n), np.linspace(0, 2.0, n))
    293293
    z = np.cos(7*x)*np.sin(8*y) + noise_amp*np.random.rand(n, n)
    294-
    mask = np.where(np.random.rand(n, n) >= mask_level, True, False)
    294+
    mask = np.random.rand(n, n) >= mask_level
    295295
    z = np.ma.array(z, mask=mask)
    296296

    297297
    for corner_mask in [False, True]:
    @@ -362,7 +362,7 @@ def test_circular_contour_warning():
    362362
    # Check that almost circular contours don't throw a warning
    363363
    with pytest.warns(None) as record:
    364364
    x, y = np.meshgrid(np.linspace(-2, 2, 4), np.linspace(-2, 2, 4))
    365-
    r = np.sqrt(x ** 2 + y ** 2)
    365+
    r = np.hypot(x, y)
    366366

    367367
    plt.figure()
    368368
    cs = plt.contour(x, y, r)

    ‎lib/matplotlib/tests/test_image.py

    Lines changed: 2 additions & 3 deletions
    Original file line numberDiff line numberDiff line change
    @@ -769,12 +769,11 @@ def test_mask_image():
    769769
    def test_imshow_endianess():
    770770
    x = np.arange(10)
    771771
    X, Y = np.meshgrid(x, x)
    772-
    Z = ((X-5)**2 + (Y-5)**2)**0.5
    772+
    Z = np.hypot(X - 5, Y - 5)
    773773

    774774
    fig, (ax1, ax2) = plt.subplots(1, 2)
    775775

    776-
    kwargs = dict(origin="lower", interpolation='nearest',
    777-
    cmap='viridis')
    776+
    kwargs = dict(origin="lower", interpolation='nearest', cmap='viridis')
    778777

    779778
    ax1.imshow(Z.astype('<f8'), **kwargs)
    780779
    ax2.imshow(Z.astype('>f8'), **kwargs)

    ‎lib/matplotlib/tests/test_quiver.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -137,7 +137,7 @@ def test_barbs():
    137137
    X, Y = np.meshgrid(x, x)
    138138
    U, V = 12*X, 12*Y
    139139
    fig, ax = plt.subplots()
    140-
    ax.barbs(X, Y, U, V, np.sqrt(U*U + V*V), fill_empty=True, rounding=False,
    140+
    ax.barbs(X, Y, U, V, np.hypot(U, V), fill_empty=True, rounding=False,
    141141
    sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3),
    142142
    cmap='viridis')
    143143

    ‎lib/matplotlib/tests/test_streamplot.py

    Lines changed: 3 additions & 3 deletions
    Original file line numberDiff line numberDiff line change
    @@ -51,9 +51,9 @@ def test_colormap():
    5151
    @image_comparison(baseline_images=['streamplot_linewidth'])
    5252
    def test_linewidth():
    5353
    X, Y, U, V = velocity_field()
    54-
    speed = np.sqrt(U*U + V*V)
    55-
    lw = 5*speed/speed.max()
    56-
    df = 25. / 30. # Compatibility factor for old test image
    54+
    speed = np.hypot(U, V)
    55+
    lw = 5 * speed / speed.max()
    56+
    df = 25 / 30 # Compatibility factor for old test image
    5757
    plt.streamplot(X, Y, U, V, density=[0.5 * df, 1. * df], color='k',
    5858
    linewidth=lw)
    5959

    ‎lib/matplotlib/tests/test_triangulation.py

    Lines changed: 11 additions & 11 deletions
    Original file line numberDiff line numberDiff line change
    @@ -664,10 +664,10 @@ def test_triinterp_transformations():
    664664
    min_radius = 0.15
    665665

    666666
    def z(x, y):
    667-
    r1 = np.sqrt((0.5-x)**2 + (0.5-y)**2)
    668-
    theta1 = np.arctan2(0.5-x, 0.5-y)
    669-
    r2 = np.sqrt((-x-0.2)**2 + (-y-0.2)**2)
    670-
    theta2 = np.arctan2(-x-0.2, -y-0.2)
    667+
    r1 = np.hypot(0.5 - x, 0.5 - y)
    668+
    theta1 = np.arctan2(0.5 - x, 0.5 - y)
    669+
    r2 = np.hypot(-x - 0.2, -y - 0.2)
    670+
    theta2 = np.arctan2(-x - 0.2, -y - 0.2)
    671671
    z = -(2*(np.exp((r1/10)**2)-1)*30. * np.cos(7.*theta1) +
    672672
    (np.exp((r2/10)**2)-1)*30. * np.cos(11.*theta2) +
    673673
    0.7*(x**2 + y**2))
    @@ -752,10 +752,10 @@ def test_tri_smooth_contouring():
    752752
    min_radius = 0.15
    753753

    754754
    def z(x, y):
    755-
    r1 = np.sqrt((0.5-x)**2 + (0.5-y)**2)
    756-
    theta1 = np.arctan2(0.5-x, 0.5-y)
    757-
    r2 = np.sqrt((-x-0.2)**2 + (-y-0.2)**2)
    758-
    theta2 = np.arctan2(-x-0.2, -y-0.2)
    755+
    r1 = np.hypot(0.5 - x, 0.5 - y)
    756+
    theta1 = np.arctan2(0.5 - x, 0.5 - y)
    757+
    r2 = np.hypot(-x - 0.2, -y - 0.2)
    758+
    theta2 = np.arctan2(-x - 0.2, -y - 0.2)
    759759
    z = -(2*(np.exp((r1/10)**2)-1)*30. * np.cos(7.*theta1) +
    760760
    (np.exp((r2/10)**2)-1)*30. * np.cos(11.*theta2) +
    761761
    0.7*(x**2 + y**2))
    @@ -817,8 +817,8 @@ def dipole_potential(x, y):
    817817

    818818
    # Computes the electrical field (Ex, Ey) as gradient of -V
    819819
    tci = mtri.CubicTriInterpolator(triang, -V)
    820-
    (Ex, Ey) = tci.gradient(triang.x, triang.y)
    821-
    E_norm = np.sqrt(Ex**2 + Ey**2)
    820+
    Ex, Ey = tci.gradient(triang.x, triang.y)
    821+
    E_norm = np.hypot(Ex, Ey)
    822822

    823823
    # Plot the triangulation, the potential iso-contours and the vector field
    824824
    plt.figure()
    @@ -938,7 +938,7 @@ def test_trirefine():
    938938
    y = np.asarray([0.0, 0.0, 1.0, 1.0])
    939939
    triang = [mtri.Triangulation(x, y, [[0, 1, 3], [3, 2, 0]]),
    940940
    mtri.Triangulation(x, y, [[0, 1, 3], [2, 0, 3]])]
    941-
    z = np.sqrt((x-0.3)*(x-0.3) + (y-0.4)*(y-0.4))
    941+
    z = np.hypot(x - 0.3, y - 0.4)
    942942
    # Refining the 2 triangulations and reordering the points
    943943
    xyz_data = []
    944944
    for i in range(2):

    ‎lib/matplotlib/tri/tritools.py

    Lines changed: 3 additions & 3 deletions
    Original file line numberDiff line numberDiff line change
    @@ -92,9 +92,9 @@ def circle_ratios(self, rescale=True):
    9292
    a = tri_pts[:, 1, :] - tri_pts[:, 0, :]
    9393
    b = tri_pts[:, 2, :] - tri_pts[:, 1, :]
    9494
    c = tri_pts[:, 0, :] - tri_pts[:, 2, :]
    95-
    a = np.sqrt(a[:, 0]**2 + a[:, 1]**2)
    96-
    b = np.sqrt(b[:, 0]**2 + b[:, 1]**2)
    97-
    c = np.sqrt(c[:, 0]**2 + c[:, 1]**2)
    95+
    a = np.hypot(a[:, 0], a[:, 1])
    96+
    b = np.hypot(b[:, 0], b[:, 1])
    97+
    c = np.hypot(c[:, 0], c[:, 1])
    9898
    # circumcircle and incircle radii
    9999
    s = (a+b+c)*0.5
    100100
    prod = s*(a+b-s)*(a+c-s)*(b+c-s)

    ‎lib/matplotlib/widgets.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -2676,7 +2676,7 @@ def _onmove(self, event):
    26762676
    # Calculate distance to the start vertex.
    26772677
    x0, y0 = self.line.get_transform().transform((self._xs[0],
    26782678
    self._ys[0]))
    2679-
    v0_dist = np.sqrt((x0 - event.x) ** 2 + (y0 - event.y) ** 2)
    2679+
    v0_dist = np.hypot(x0 - event.x, y0 - event.y)
    26802680
    # Lock on to the start vertex if near it and ready to complete.
    26812681
    if len(self._xs) > 3 and v0_dist < self.vertex_select_radius:
    26822682
    self._xs[-1], self._ys[-1] = self._xs[0], self._ys[0]

    ‎lib/mpl_toolkits/mplot3d/proj3d.py

    Lines changed: 2 additions & 2 deletions
    Original file line numberDiff line numberDiff line change
    @@ -43,7 +43,7 @@ def line2d_dist(l, p):
    4343
    """
    4444
    a, b, c = l
    4545
    x0, y0 = p
    46-
    return abs((a*x0 + b*y0 + c)/np.sqrt(a**2+b**2))
    46+
    return abs((a*x0 + b*y0 + c) / np.hypot(a, b))
    4747

    4848

    4949
    def line2d_seg_dist(p1, p2, p0):
    @@ -63,7 +63,7 @@ def line2d_seg_dist(p1, p2, p0):
    6363

    6464
    u = (x01*x21 + y01*y21) / (x21**2 + y21**2)
    6565
    u = np.clip(u, 0, 1)
    66-
    d = np.sqrt((x01 - u*x21)**2 + (y01 - u*y21)**2)
    66+
    d = np.hypot(x01 - u*x21, y01 - u*y21)
    6767

    6868
    return d
    6969

    ‎lib/mpl_toolkits/tests/test_mplot3d.py

    Lines changed: 2 additions & 2 deletions
    Original file line numberDiff line numberDiff line change
    @@ -145,7 +145,7 @@ def f(t):
    145145

    146146
    ax = fig.add_subplot(2, 1, 2, projection='3d')
    147147
    X, Y = np.meshgrid(np.arange(-5, 5, 0.25), np.arange(-5, 5, 0.25))
    148-
    R = np.sqrt(X ** 2 + Y ** 2)
    148+
    R = np.hypot(X, Y)
    149149
    Z = np.sin(R)
    150150

    151151
    surf = ax.plot_surface(X, Y, Z, rcount=40, ccount=40,
    @@ -193,7 +193,7 @@ def test_surface3d():
    193193
    X = np.arange(-5, 5, 0.25)
    194194
    Y = np.arange(-5, 5, 0.25)
    195195
    X, Y = np.meshgrid(X, Y)
    196-
    R = np.sqrt(X ** 2 + Y ** 2)
    196+
    R = np.hypot(X, Y)
    197197
    Z = np.sin(R)
    198198
    surf = ax.plot_surface(X, Y, Z, rcount=40, ccount=40, cmap=cm.coolwarm,
    199199
    lw=0, antialiased=False)

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