def test_issue_20113():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
# verify the capability to use custom backends
with raises(TypeError):
plot(sin(x), backend=Plot, show=False)
p2 = plot(sin(x), backend=MatplotlibBackend, show=False)
assert p2.backend == MatplotlibBackend
assert len(p2[0].get_data()[0]) >= 30
p3 = plot(sin(x), backend=DummyBackendOk, show=False)
assert p3.backend == DummyBackendOk
assert len(p3[0].get_data()[0]) >= 30
# test for an improper coded backend
p4 = plot(sin(x), backend=DummyBackendNotOk, show=False)
assert p4.backend == DummyBackendNotOk
assert len(p4[0].get_data()[0]) >= 30
with raises(NotImplementedError):
p4.show()
with raises(NotImplementedError):
p4.save("test/path")
with raises(NotImplementedError):
p4._backend.close()
def test_plot_and_save_6():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
with TemporaryDirectory(prefix='sympy_') as tmpdir:
filename = 'test.png'
###
# Test expressions that can not be translated to np and generate complex
# results.
###
p = plot(sin(x) + I*cos(x))
p.save(os.path.join(tmpdir, filename))
p = plot(sqrt(sqrt(-x)))
p.save(os.path.join(tmpdir, filename))
p = plot(LambertW(x))
p.save(os.path.join(tmpdir, filename))
p = plot(sqrt(LambertW(x)))
p.save(os.path.join(tmpdir, filename))
#Characteristic function of a StudentT distribution with nu=10
x1 = 5 * x**2 * exp_polar(-I*pi)/2
m1 = meijerg(((1 / 2,), ()), ((5, 0, 1 / 2), ()), x1)
x2 = 5*x**2 * exp_polar(I*pi)/2
m2 = meijerg(((1/2,), ()), ((5, 0, 1/2), ()), x2)
expr = (m1 + m2) / (48 * pi)
p = plot(expr, (x, 1e-6, 1e-2))
p.save(os.path.join(tmpdir, filename))
def test_empty_Plot():
if not matplotlib:
skip("Matplotlib not the default backend")
# No exception showing an empty plot
plot()
p = Plot()
p.show()
def plot_polynomial(expr):
"""Plots the polynomial using the functions written in
plotting module which in turn uses matplotlib backend.
Parameter
=========
expr: Denotes a polynomial(SymPy expression)
"""
from sympy.plotting.plot import plot3d, plot
gens = expr.free_symbols
if len(gens) == 2:
plot3d(expr)
else:
plot(expr)
def plot_polynomial(expr):
"""Plots the polynomial using the functions written in
plotting module which in turn uses matplotlib backend.
Parameter
=========
expr: Denotes a polynomial(SymPy expression)
"""
from sympy.plotting.plot import plot3d, plot
gens = expr.free_symbols
if len(gens) == 2:
plot3d(expr)
else:
plot(expr)
def test_issue_15265():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
eqn = sin(x)
p = plot(eqn, xlim=(-S.Pi, S.Pi), ylim=(-1, 1))
p._backend.close()
p = plot(eqn, xlim=(-1, 1), ylim=(-S.Pi, S.Pi))
p._backend.close()
p = plot(eqn, xlim=(-1, 1), ylim=(sympify('-3.14'), sympify('3.14')))
p._backend.close()
p = plot(eqn, xlim=(sympify('-3.14'), sympify('3.14')), ylim=(-1, 1))
p._backend.close()
raises(ValueError,
lambda: plot(eqn, xlim=(-S.ImaginaryUnit, 1), ylim=(-1, 1)))
raises(ValueError,
lambda: plot(eqn, xlim=(-1, 1), ylim=(-1, S.ImaginaryUnit)))
raises(ValueError,
lambda: plot(eqn, xlim=(S.NegativeInfinity, 1), ylim=(-1, 1)))
raises(ValueError,
lambda: plot(eqn, xlim=(-1, 1), ylim=(-1, S.Infinity)))
def test_plot_and_save_4():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
y = Symbol('y')
###
# Examples from the 'advanced' notebook
###
# XXX: This raises the warning "The evaluation of the expression is
# problematic. We are trying a failback method that may still work. Please
# report this as a bug." It has to use the fallback because using evalf()
# is the only way to evaluate the integral. We should perhaps just remove
# that warning.
with TemporaryDirectory(prefix='sympy_') as tmpdir:
with warns(
UserWarning,
match="The evaluation of the expression is problematic",
test_stacklevel=False,
):
i = Integral(log((sin(x)**2 + 1)*sqrt(x**2 + 1)), (x, 0, y))
p = plot(i, (y, 1, 5))
filename = 'test_advanced_integral.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
def plot_absolute_error(self,
title: str = None,
nb_of_points: int = 400,
show: bool = True) -> Plot:
"""
Plots the absolute error between the function and the approximation polynomial using sympy's plot
on the given interval.
:param title: title for the plot
:param nb_of_points: number of points
:param show: whether to show the plot
:return: plot of the absolute error
:rtype: Plot
"""
if title is None:
title = f'y = |f(x) - {self.function}|'
return plot(abs(self.function - self.approximation),
(x, self.interval[0], self.interval[1]),
title=title,
adaptive=False,
nb_of_points=nb_of_points,
ylabel='',
show=show)
def test_append_issue_7140():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
p1 = plot(x)
p2 = plot(x**2)
plot(x + 2)
# append a series
p2.append(p1[0])
assert len(p2._series) == 2
with raises(TypeError):
p1.append(p2)
with raises(TypeError):
p1.append(p2._series)
def test_issue_16572():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
p = plot(LambertW(x), show=False)
# Random number of segments, probably more than 50, but we want to see
# that there are segments generated, as opposed to when the bug was present
assert len(p[0].get_data()[0]) >= 30
def test_plot_size():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
p1 = plot(sin(x), backend="matplotlib", size=(8, 4))
s1 = p1._backend.fig.get_size_inches()
assert (s1[0] == 8) and (s1[1] == 4)
p2 = plot(sin(x), backend="matplotlib", size=(5, 10))
s2 = p2._backend.fig.get_size_inches()
assert (s2[0] == 5) and (s2[1] == 10)
p3 = PlotGrid(2, 1, p1, p2, size=(6, 2))
s3 = p3._backend.fig.get_size_inches()
assert (s3[0] == 6) and (s3[1] == 2)
with raises(ValueError):
plot(sin(x), backend="matplotlib", size=(-1, 3))
def test_deprecated_get_segments():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
f = sin(x)
p = plot(f, (x, -10, 10), show=False)
with warns_deprecated_sympy():
p[0].get_segments()
def test_issue_17405():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
f = x**0.3 - 10*x**3 + x**2
p = plot(f, (x, -10, 10), show=False)
# Random number of segments, probably more than 100, but we want to see
# that there are segments generated, as opposed to when the bug was present
assert len(p[0].get_data()[0]) >= 30
def test_issue_11461():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
p = plot(real_root((log(x/(x-2))), 3), show=False)
# Random number of segments, probably more than 100, but we want to see
# that there are segments generated, as opposed to when the bug was present
# and that there are no exceptions.
assert len(p[0].get_data()[0]) >= 30
def test_issue_11865():
if not matplotlib:
skip("Matplotlib not the default backend")
k = Symbol('k', integer=True)
f = Piecewise((-I*exp(I*pi*k)/k + I*exp(-I*pi*k)/k, Ne(k, 0)), (2*pi, True))
p = plot(f, show=False)
# Random number of segments, probably more than 100, but we want to see
# that there are segments generated, as opposed to when the bug was present
# and that there are no exceptions.
assert len(p[0].get_data()[0]) >= 30
def test_plot_and_save_5():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
y = Symbol('y')
with TemporaryDirectory(prefix='sympy_') as tmpdir:
s = Sum(1/x**y, (x, 1, oo))
p = plot(s, (y, 2, 10))
filename = 'test_advanced_inf_sum.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot(Sum(1/x, (x, 1, y)), (y, 2, 10), show=False)
p[0].only_integers = True
p[0].steps = True
filename = 'test_advanced_fin_sum.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
def test_logplot_PR_16796():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
p = plot(x, (x, .001, 100), xscale='log', show=False)
# Random number of segments, probably more than 100, but we want to see
# that there are segments generated, as opposed to when the bug was present
assert len(p[0].get_data()[0]) >= 30
assert p[0].end == 100.0
assert p[0].start == .001
def test_issue_13516():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
pm = plot(sin(x), backend="matplotlib", show=False)
assert pm.backend == MatplotlibBackend
assert len(pm[0].get_data()[0]) >= 30
pt = plot(sin(x), backend="text", show=False)
assert pt.backend == TextBackend
assert len(pt[0].get_data()[0]) >= 30
pd = plot(sin(x), backend="default", show=False)
assert pd.backend == DefaultBackend
assert len(pd[0].get_data()[0]) >= 30
p = plot(sin(x), show=False)
assert p.backend == DefaultBackend
assert len(p[0].get_data()[0]) >= 30
def test_custom_coloring():
x = Symbol('x')
y = Symbol('y')
plot(cos(x), line_color=lambda a: a)
plot(cos(x), line_color=1)
plot(cos(x), line_color="r")
plot_parametric(cos(x), sin(x), line_color=lambda a: a)
plot_parametric(cos(x), sin(x), line_color=1)
plot_parametric(cos(x), sin(x), line_color="r")
plot3d_parametric_line(cos(x), sin(x), x, line_color=lambda a: a)
plot3d_parametric_line(cos(x), sin(x), x, line_color=1)
plot3d_parametric_line(cos(x), sin(x), x, line_color="r")
plot3d_parametric_surface(cos(x + y), sin(x - y), x - y,
(x, -5, 5), (y, -5, 5),
surface_color=lambda a, b: a**2 + b**2)
plot3d_parametric_surface(cos(x + y), sin(x - y), x - y,
(x, -5, 5), (y, -5, 5),
surface_color=1)
plot3d_parametric_surface(cos(x + y), sin(x - y), x - y,
(x, -5, 5), (y, -5, 5),
surface_color="r")
plot3d(x*y, (x, -5, 5), (y, -5, 5),
surface_color=lambda a, b: a**2 + b**2)
plot3d(x*y, (x, -5, 5), (y, -5, 5), surface_color=1)
plot3d(x*y, (x, -5, 5), (y, -5, 5), surface_color="r")
def test_plotgrid_and_save():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
y = Symbol('y')
with TemporaryDirectory(prefix='sympy_') as tmpdir:
p1 = plot(x)
p2 = plot_parametric((sin(x), cos(x)), (x, sin(x)), show=False)
p3 = plot_parametric(cos(x),
sin(x),
adaptive=False,
nb_of_points=500,
show=False)
p4 = plot3d_parametric_line(sin(x), cos(x), x, show=False)
# symmetric grid
p = PlotGrid(2, 2, p1, p2, p3, p4)
filename = 'test_grid1.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
# grid size greater than the number of subplots
p = PlotGrid(3, 4, p1, p2, p3, p4)
filename = 'test_grid2.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p5 = plot(cos(x), (x, -pi, pi), show=False)
p5[0].line_color = lambda a: a
p6 = plot(Piecewise((1, x > 0), (0, True)), (x, -1, 1), show=False)
p7 = plot_contour((x**2 + y**2, (x, -5, 5), (y, -5, 5)),
(x**3 + y**3, (x, -3, 3), (y, -3, 3)),
show=False)
# unsymmetric grid (subplots in one line)
p = PlotGrid(1, 3, p5, p6, p7)
filename = 'test_grid3.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
def test_plot_limits():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
p = plot(x, x**2, (x, -10, 10))
backend = p._backend
xmin, xmax = backend.ax[0].get_xlim()
assert abs(xmin + 10) < 2
assert abs(xmax - 10) < 2
ymin, ymax = backend.ax[0].get_ylim()
assert abs(ymin + 10) < 10
assert abs(ymax - 100) < 10
def plot_approximation(self,
title: str = None,
nb_of_points: int = 400,
show: bool = True) -> Plot:
"""
Plots the approximation polynomial using sympy's plot function on the given interval.
:param title: title for the plot
:param nb_of_points: number of points
:param show: whether to show the plot
:return: plot of the approximation
:rtype: Plot
"""
if title is None:
title = f'f(x) $\\approx$ {self.function}'
return plot(self.approximation.as_expr(),
(x, self.interval[0], self.interval[1]),
title=title,
adaptive=False,
nb_of_points=nb_of_points,
show=show,
ylabel='')
def test_plot_and_save_3():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
y = Symbol('y')
z = Symbol('z')
with TemporaryDirectory(prefix='sympy_') as tmpdir:
###
# Examples from the 'colors' notebook
###
p = plot(sin(x))
p[0].line_color = lambda a: a
filename = 'test_colors_line_arity1.png'
p.save(os.path.join(tmpdir, filename))
p[0].line_color = lambda a, b: b
filename = 'test_colors_line_arity2.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot(x*sin(x), x*cos(x), (x, 0, 10))
p[0].line_color = lambda a: a
filename = 'test_colors_param_line_arity1.png'
p.save(os.path.join(tmpdir, filename))
p[0].line_color = lambda a, b: a
filename = 'test_colors_param_line_arity1.png'
p.save(os.path.join(tmpdir, filename))
p[0].line_color = lambda a, b: b
filename = 'test_colors_param_line_arity2b.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot3d_parametric_line(sin(x) + 0.1*sin(x)*cos(7*x),
cos(x) + 0.1*cos(x)*cos(7*x),
0.1*sin(7*x),
(x, 0, 2*pi))
p[0].line_color = lambdify_(x, sin(4*x))
filename = 'test_colors_3d_line_arity1.png'
p.save(os.path.join(tmpdir, filename))
p[0].line_color = lambda a, b: b
filename = 'test_colors_3d_line_arity2.png'
p.save(os.path.join(tmpdir, filename))
p[0].line_color = lambda a, b, c: c
filename = 'test_colors_3d_line_arity3.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot3d(sin(x)*y, (x, 0, 6*pi), (y, -5, 5))
p[0].surface_color = lambda a: a
filename = 'test_colors_surface_arity1.png'
p.save(os.path.join(tmpdir, filename))
p[0].surface_color = lambda a, b: b
filename = 'test_colors_surface_arity2.png'
p.save(os.path.join(tmpdir, filename))
p[0].surface_color = lambda a, b, c: c
filename = 'test_colors_surface_arity3a.png'
p.save(os.path.join(tmpdir, filename))
p[0].surface_color = lambdify_((x, y, z), sqrt((x - 3*pi)**2 + y**2))
filename = 'test_colors_surface_arity3b.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot3d_parametric_surface(x * cos(4 * y), x * sin(4 * y), y,
(x, -1, 1), (y, -1, 1))
p[0].surface_color = lambda a: a
filename = 'test_colors_param_surf_arity1.png'
p.save(os.path.join(tmpdir, filename))
p[0].surface_color = lambda a, b: a*b
filename = 'test_colors_param_surf_arity2.png'
p.save(os.path.join(tmpdir, filename))
p[0].surface_color = lambdify_((x, y, z), sqrt(x**2 + y**2 + z**2))
filename = 'test_colors_param_surf_arity3.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
def test_plot_and_save_1():
if not matplotlib:
skip("Matplotlib not the default backend")
x = Symbol('x')
y = Symbol('y')
with TemporaryDirectory(prefix='sympy_') as tmpdir:
###
# Examples from the 'introduction' notebook
###
p = plot(x, legend=True, label='f1')
p = plot(x*sin(x), x*cos(x), label='f2')
p.extend(p)
p[0].line_color = lambda a: a
p[1].line_color = 'b'
p.title = 'Big title'
p.xlabel = 'the x axis'
p[1].label = 'straight line'
p.legend = True
p.aspect_ratio = (1, 1)
p.xlim = (-15, 20)
filename = 'test_basic_options_and_colors.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p.extend(plot(x + 1))
p.append(plot(x + 3, x**2)[1])
filename = 'test_plot_extend_append.png'
p.save(os.path.join(tmpdir, filename))
p[2] = plot(x**2, (x, -2, 3))
filename = 'test_plot_setitem.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot(sin(x), (x, -2*pi, 4*pi))
filename = 'test_line_explicit.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot(sin(x))
filename = 'test_line_default_range.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot((x**2, (x, -5, 5)), (x**3, (x, -3, 3)))
filename = 'test_line_multiple_range.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
raises(ValueError, lambda: plot(x, y))
#Piecewise plots
p = plot(Piecewise((1, x > 0), (0, True)), (x, -1, 1))
filename = 'test_plot_piecewise.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
p = plot(Piecewise((x, x < 1), (x**2, True)), (x, -3, 3))
filename = 'test_plot_piecewise_2.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
# test issue 7471
p1 = plot(x)
p2 = plot(3)
p1.extend(p2)
filename = 'test_horizontal_line.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
# test issue 10925
f = Piecewise((-1, x < -1), (x, And(-1 <= x, x < 0)), \
(x**2, And(0 <= x, x < 1)), (x**3, x >= 1))
p = plot(f, (x, -3, 3))
filename = 'test_plot_piecewise_3.png'
p.save(os.path.join(tmpdir, filename))
p._backend.close()
