def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,
keepdims=keepdims)
if isinstance(ret, mu.ndarray):
ret = um.sqrt(ret, out=ret)
else:
ret = um.sqrt(ret)
return ret
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
ret = _var(a,
axis=axis,
dtype=dtype,
out=out,
ddof=ddof,
keepdims=keepdims)
if isinstance(ret, mu.ndarray):
ret = um.sqrt(ret, out=ret)
else:
ret = um.sqrt(ret)
return ret
print '*' * 80
print 'Example of a three part assembly'
x1 = N(24, 1)
x2 = N(37, 4)
x3 = Exp(2) # Exp(mu=0.5) is the same
Z = (x1 * x2**2) / (15 * (1.5 + x3))
Z.describe()
print '*' * 80
print 'Example of volumetric gas flow through orifice meter'
H = N(64, 0.5)
M = N(16, 0.1)
P = N(361, 2)
t = N(165, 0.5)
C = 38.4
Q = C * umath.sqrt((520 * H * P) / (M * (t + 460)))
Q.describe()
print '*' * 80
print 'Example of manufacturing tolerance stackup'
# for a gamma distribution we need the following conversions:
# shape = mean**2/var
# scale = var/mean
mn = 1.5
vr = 0.25
k = mn**2 / vr
theta = vr / mn
x = Gamma(k, theta)
y = Gamma(k, theta)
z = Gamma(k, theta)
w = x + y + z
# Temperature units # internal unit: K K = 1 # Kelvin # Pressure units # internal unit: kJ/mol/nm**3 Pa = J/m**3 # Pascal bar = 1.e5*Pa # bar atm = 101325*Pa # atmosphere # Constants h = 6.626176e-34*J*s hbar = h/(2.*pi) k_B = 1.3806513e-23*J/K eps0 = 1./(4.e-7*pi)*A**2*m/J/c**2 me = 0.51099906*mega*eV/c**2 electrostatic_energy = 1/(4.*pi*eps0) # CHARMM time unit akma_time = umath.sqrt(Ang**2/(kcal/mol)) # "Atomic" units Bohr = 4.*pi*eps0*hbar**2/(me*e**2) Hartree = hbar**2/(me*Bohr**2)
def point_distances(vec1, vec2):
return umath.sqrt((vec2.real-vec1.real)**2.0 +
(vec2.imag-vec1.imag)**2.0)
print '*'*80
print 'Example of a three part assembly'
x1 = N(24, 1)
x2 = N(37, 4)
x3 = Exp(2) # Exp(mu=0.5) is the same
Z = (x1*x2**2)/(15*(1.5 + x3))
Z.describe()
print '*'*80
print 'Example of volumetric gas flow through orifice meter'
H = N(64, 0.5)
M = N(16, 0.1)
P = N(361, 2)
t = N(165, 0.5)
C = 38.4
Q = C*umath.sqrt((520*H*P)/(M*(t + 460)))
Q.describe()
print '*'*80
print 'Example of manufacturing tolerance stackup'
# for a gamma distribution we need the following conversions:
# shape = mean**2/var
# scale = var/mean
mn = 1.5
vr = 0.25
k = mn**2/vr
theta = vr/mn
x = Gamma(k, theta)
y = Gamma(k, theta)
z = Gamma(k, theta)
w = x + y + z
def point_distances(vec1, vec2):
return umath.sqrt((vec2.real - vec1.real)**2.0 +
(vec2.imag - vec1.imag)**2.0)
