本文整理汇总了Python中sympy.stats.skewness函数的典型用法代码示例。如果您正苦于以下问题:Python skewness函数的具体用法?Python skewness怎么用?Python skewness使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了skewness函数的13个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: test_exponential
def test_exponential():
rate = Symbol('lambda', positive=True, real=True, finite=True)
X = Exponential('x', rate)
assert E(X) == 1/rate
assert variance(X) == 1/rate**2
assert skewness(X) == 2
assert skewness(X) == smoment(X, 3)
assert smoment(2*X, 4) == smoment(X, 4)
assert moment(X, 3) == 3*2*1/rate**3
assert P(X > 0) == S(1)
assert P(X > 1) == exp(-rate)
assert P(X > 10) == exp(-10*rate)
assert where(X <= 1).set == Interval(0, 1)
开发者ID:vprusso,项目名称:sympy,代码行数:15,代码来源:test_continuous_rv.py
示例2: test_multiple_normal
def test_multiple_normal():
X, Y = Normal('x', 0, 1), Normal('y', 0, 1)
assert E(X + Y) == 0
assert variance(X + Y) == 2
assert variance(X + X) == 4
assert covariance(X, Y) == 0
assert covariance(2*X + Y, -X) == -2*variance(X)
assert skewness(X) == 0
assert skewness(X + Y) == 0
assert correlation(X, Y) == 0
assert correlation(X, X + Y) == correlation(X, X - Y)
assert moment(X, 2) == 1
assert cmoment(X, 3) == 0
assert moment(X + Y, 4) == 12
assert cmoment(X, 2) == variance(X)
assert smoment(X*X, 2) == 1
assert smoment(X + Y, 3) == skewness(X + Y)
assert E(X, Eq(X + Y, 0)) == 0
assert variance(X, Eq(X + Y, 0)) == S.Half
开发者ID:vprusso,项目名称:sympy,代码行数:20,代码来源:test_continuous_rv.py
示例3: test_exponential
def test_exponential():
rate = Symbol('lambda', positive=True, real=True, bounded=True)
X = Exponential('x', rate)
assert E(X) == 1/rate
assert variance(X) == 1/rate**2
assert skewness(X) == 2
assert P(X > 0) == S(1)
assert P(X > 1) == exp(-rate)
assert P(X > 10) == exp(-10*rate)
assert where(X <= 1).set == Interval(0, 1)
开发者ID:archipleago-creature,项目名称:sympy,代码行数:12,代码来源:test_continuous_rv.py
示例4: test_binomial_symbolic
def test_binomial_symbolic():
n = 10 # Because we're using for loops, can't do symbolic n
p = symbols('p', positive=True)
X = Binomial('X', n, p)
assert simplify(E(X)) == n*p == simplify(moment(X, 1))
assert simplify(variance(X)) == n*p*(1 - p) == simplify(cmoment(X, 2))
assert cancel((skewness(X) - (1-2*p)/sqrt(n*p*(1-p)))) == 0
# Test ability to change success/failure winnings
H, T = symbols('H T')
Y = Binomial('Y', n, p, succ=H, fail=T)
assert simplify(E(Y) - (n*(H*p + T*(1 - p)))) == 0
开发者ID:MCGallaspy,项目名称:sympy,代码行数:12,代码来源:test_finite_rv.py
示例5: test_binomial_symbolic
def test_binomial_symbolic():
n = 10 # Because we're using for loops, can't do symbolic n
p = symbols("p", positive=True)
X = Binomial("X", n, p)
assert simplify(E(X)) == n * p == simplify(moment(X, 1))
assert simplify(variance(X)) == n * p * (1 - p) == simplify(cmoment(X, 2))
assert factor(simplify(skewness(X))) == factor((1 - 2 * p) / sqrt(n * p * (1 - p)))
# Test ability to change success/failure winnings
H, T = symbols("H T")
Y = Binomial("Y", n, p, succ=H, fail=T)
assert simplify(E(Y)) == simplify(n * (H * p + T * (1 - p)))
开发者ID:rpmuller,项目名称:sympy,代码行数:12,代码来源:test_finite_rv.py
示例6: test_binomial_numeric
def test_binomial_numeric():
nvals = range(5)
pvals = [0, S(1)/4, S.Half, S(3)/4, 1]
for n in nvals:
for p in pvals:
X = Binomial('X', n, p)
assert E(X) == n*p
assert variance(X) == n*p*(1 - p)
if n > 0 and 0 < p < 1:
assert skewness(X) == (1 - 2*p)/sqrt(n*p*(1 - p))
for k in range(n + 1):
assert P(Eq(X, k)) == binomial(n, k)*p**k*(1 - p)**(n - k)
开发者ID:MCGallaspy,项目名称:sympy,代码行数:13,代码来源:test_finite_rv.py
示例7: test_binomial_numeric
def test_binomial_numeric():
nvals = range(5)
pvals = [0, S(1) / 4, S.Half, S(3) / 4, 1]
for n in nvals:
for p in pvals:
X = Binomial("X", n, p)
assert Eq(E(X), n * p)
assert Eq(variance(X), n * p * (1 - p))
if n > 0 and 0 < p < 1:
assert Eq(skewness(X), (1 - 2 * p) / sqrt(n * p * (1 - p)))
for k in range(n + 1):
assert Eq(P(Eq(X, k)), binomial(n, k) * p ** k * (1 - p) ** (n - k))
开发者ID:rpmuller,项目名称:sympy,代码行数:13,代码来源:test_finite_rv.py
示例8: test_hypergeometric_numeric
def test_hypergeometric_numeric():
for N in range(1, 5):
for m in range(0, N + 1):
for n in range(1, N + 1):
X = Hypergeometric('X', N, m, n)
N, m, n = map(sympify, (N, m, n))
assert sum(density(X).values()) == 1
assert E(X) == n * m / N
if N > 1:
assert variance(X) == n*(m/N)*(N - m)/N*(N - n)/(N - 1)
# Only test for skewness when defined
if N > 2 and 0 < m < N and n < N:
assert skewness(X) == simplify((N - 2*m)*sqrt(N - 1)*(N - 2*n)
/ (sqrt(n*m*(N - m)*(N - n))*(N - 2)))
开发者ID:MCGallaspy,项目名称:sympy,代码行数:14,代码来源:test_finite_rv.py
示例9: test_binomial_symbolic
def test_binomial_symbolic():
n = 2 # Because we're using for loops, can't do symbolic n
p = symbols('p', positive=True)
X = Binomial('X', n, p)
t = Symbol('t')
assert simplify(E(X)) == n*p == simplify(moment(X, 1))
assert simplify(variance(X)) == n*p*(1 - p) == simplify(cmoment(X, 2))
assert cancel((skewness(X) - (1 - 2*p)/sqrt(n*p*(1 - p)))) == 0
assert characteristic_function(X)(t) == p ** 2 * exp(2 * I * t) + 2 * p * (-p + 1) * exp(I * t) + (-p + 1) ** 2
assert moment_generating_function(X)(t) == p ** 2 * exp(2 * t) + 2 * p * (-p + 1) * exp(t) + (-p + 1) ** 2
# Test ability to change success/failure winnings
H, T = symbols('H T')
Y = Binomial('Y', n, p, succ=H, fail=T)
assert simplify(E(Y) - (n*(H*p + T*(1 - p)))) == 0
开发者ID:Lenqth,项目名称:sympy,代码行数:16,代码来源:test_finite_rv.py
示例10: test_dice
def test_dice():
# TODO: Make iid method!
X, Y, Z = Die('X', 6), Die('Y', 6), Die('Z', 6)
a, b = symbols('a b')
assert E(X) == 3 + S.Half
assert variance(X) == S(35)/12
assert E(X + Y) == 7
assert E(X + X) == 7
assert E(a*X + b) == a*E(X) + b
assert variance(X + Y) == variance(X) + variance(Y) == cmoment(X + Y, 2)
assert variance(X + X) == 4 * variance(X) == cmoment(X + X, 2)
assert cmoment(X, 0) == 1
assert cmoment(4*X, 3) == 64*cmoment(X, 3)
assert covariance(X, Y) == S.Zero
assert covariance(X, X + Y) == variance(X)
assert density(Eq(cos(X*S.Pi), 1))[True] == S.Half
assert correlation(X, Y) == 0
assert correlation(X, Y) == correlation(Y, X)
assert smoment(X + Y, 3) == skewness(X + Y)
assert smoment(X, 0) == 1
assert P(X > 3) == S.Half
assert P(2*X > 6) == S.Half
assert P(X > Y) == S(5)/12
assert P(Eq(X, Y)) == P(Eq(X, 1))
assert E(X, X > 3) == 5 == moment(X, 1, 0, X > 3)
assert E(X, Y > 3) == E(X) == moment(X, 1, 0, Y > 3)
assert E(X + Y, Eq(X, Y)) == E(2*X)
assert moment(X, 0) == 1
assert moment(5*X, 2) == 25*moment(X, 2)
assert P(X > 3, X > 3) == S.One
assert P(X > Y, Eq(Y, 6)) == S.Zero
assert P(Eq(X + Y, 12)) == S.One/36
assert P(Eq(X + Y, 12), Eq(X, 6)) == S.One/6
assert density(X + Y) == density(Y + Z) != density(X + X)
d = density(2*X + Y**Z)
assert d[S(22)] == S.One/108 and d[S(4100)] == S.One/216 and S(3130) not in d
assert pspace(X).domain.as_boolean() == Or(
*[Eq(X.symbol, i) for i in [1, 2, 3, 4, 5, 6]])
assert where(X > 3).set == FiniteSet(4, 5, 6)
开发者ID:MCGallaspy,项目名称:sympy,代码行数:45,代码来源:test_finite_rv.py
示例11: __init__
def __init__(self):
mu1 = Symbol('mu1', positive=True, real=True, bounded=True)
s1 = Symbol('s1', positive=True, real=True, bounded=True)
mu2 = Symbol('mu2', positive=True, real=True, bounded=True)
s2 = Symbol('s2', positive=True, real=True, bounded=True)
N1 = Normal('N1', mu1, s1)
N2 = Normal('N2', mu2, s2)
NN = N1 * N2
self.MeanNN = E(NN)
self.VarNN = variance(NN)
self.StdevNN = SQRT(self.VarNN)
self.SkewNN = skewness(NN)
self.meanNN = lambdify([mu1, s1, mu2, s2], self.MeanNN)
self.varNN = lambdify([mu1, s1, mu2, s2], self.VarNN)
self.stdevNN = lambdify([mu1, s1, mu2, s2], self.StdevNN)
self.skewNN = lambdify([mu1, s1, mu2, s2], self.SkewNN)
开发者ID:gwli,项目名称:StudyNote,代码行数:19,代码来源:sympy_stats.py
示例12: test_discreteuniform
def test_discreteuniform():
# Symbolic
a, b, c = symbols("a b c")
X = DiscreteUniform([a, b, c])
assert E(X) == (a + b + c) / 3
assert variance(X) == (a ** 2 + b ** 2 + c ** 2) / 3 - (a / 3 + b / 3 + c / 3) ** 2
assert P(Eq(X, a)) == P(Eq(X, b)) == P(Eq(X, c)) == S("1/3")
Y = DiscreteUniform(range(-5, 5))
# Numeric
assert E(Y) == S("-1/2")
assert variance(Y) == S("33/4")
assert skewness(Y) == 0
for x in range(-5, 5):
assert P(Eq(Y, x)) == S("1/10")
assert P(Y <= x) == S(x + 6) / 10
assert P(Y >= x) == S(5 - x) / 10
assert density(Die(6)) == density(DiscreteUniform(range(1, 7)))
开发者ID:BDGLunde,项目名称:sympy,代码行数:21,代码来源:test_finite_rv.py
示例13: test_discreteuniform
def test_discreteuniform():
# Symbolic
a, b, c = symbols('a b c')
X = DiscreteUniform('X', [a,b,c])
assert E(X) == (a+b+c)/3
assert variance(X) == (a**2+b**2+c**2)/3 - (a/3+b/3+c/3)**2
assert P(Eq(X, a)) == P(Eq(X, b)) == P(Eq(X, c)) == S('1/3')
Y = DiscreteUniform('Y', range(-5, 5))
# Numeric
assert E(Y) == S('-1/2')
assert variance(Y) == S('33/4')
assert skewness(Y) == 0
for x in range(-5, 5):
assert P(Eq(Y, x)) == S('1/10')
assert P(Y <= x) == S(x+6)/10
assert P(Y >= x) == S(5-x)/10
assert density(Die('D', 6)) == density(DiscreteUniform('U', range(1,7)))
开发者ID:aeberspaecher,项目名称:sympy,代码行数:21,代码来源:test_finite_rv.py
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