def test_properties_Fluid():
props = Fluid.ALL_PROPERTIES
fluid_names = ['water', 'methane', 'R134a']
Ts = [
25, 0, -1, -100, np.nan, [25, 30], [np.nan, 25], [np.nan, np.nan],
[np.inf, np.nan],
np.linspace(0, 10, 10),
np.linspace(-10, 10, 10)
]
Ps = [
1, 0, -1, -100, np.nan, [3, 4], [np.nan, 3], [np.nan, np.nan],
[np.inf, np.nan],
np.linspace(0, 10, 10),
np.linspace(-10, 10, 10)
]
for fluid_name in fluid_names:
for T, P in zip(Ts, Ps):
fluid = Fluid(fluid_name, T=Q(T, 'C'), P=Q(P, 'bar'))
repr(fluid)
for p in props:
getattr(fluid, p)
def test_properties_HumidAir():
props = HumidAir.ALL_PROPERTIES
Ts = [
25, 0, -1, -100, np.nan, [25, 30], [np.nan, 25], [np.nan, np.nan],
[np.inf, np.nan],
np.linspace(0, 10, 10),
np.linspace(-10, 10, 10)
]
Ps = [
1, 0, -1, -100, np.nan, [3, 4], [np.nan, 3], [np.nan, np.nan],
[np.inf, np.nan],
np.linspace(0, 10, 10),
np.linspace(-10, 10, 10)
]
Rs = [
0.5, 0.1, -1, -100, np.nan, -0.5, 0.00001, -0.0001, 0.99999, 1,
1.00001, [0.3, 0.4], [np.nan, 0.3], [np.nan, np.nan], [np.inf, np.nan],
np.linspace(0, 1, 10),
np.linspace(-0.5, 0.5, 10)
]
for T, P, R in zip(Ts, Ps, Rs):
ha = HumidAir(T=Q(T, 'C'), P=Q(P, 'bar'), R=Q(R))
repr(ha)
for p in props:
getattr(ha, p)
def test_Quantity_integration():
x, y, z = sp.symbols('x, y, z')
expr = x * y / z
result = expr.subs({
x: Q(235, 'yard'),
y: Q(98, 'K/m²'),
z: Q(0.4, 'minutes')
})
Q.from_expr(result).dimensionality
def test_check():
assert not Q(1, 'kg').check('[energy]')
assert Q(1, 'kg').check(Mass)
assert not Q(1, 'kg').check(Energy)
@check('[length]', '[mass]')
def func(a, b):
return a * b
func(Q(1, 'yd'), Q(20, 'lbs'))
def test_context():
with silence_stdout():
print('silenced')
with quantity_format('~Lx'):
s = str(Q(1, 'kPa'))
assert s == '\\SI[]{1}{\\kilo\\pascal}'
s = str(Q(1, 'kPa'))
assert s == '1 kPa'
def test_get_function():
x, y, z = sp.symbols('x, y, z')
expr = 25 * x * y / z
fcn = get_function(expr, units=True)
result_arr = fcn({
x: Q(np.array([235, 335]), 'yard'),
y: Q(np.array([2, 5]), 'm²'),
z: Q(0.4, 'm³/kg')
})
def test_wraps():
# @wraps(ret, args, strict=True|False) is a convenience
# decorator for making the input/output of a function into Quantity
# however, it does not enforce the return value
@wraps('kg', ('m', 'kg'), strict=True)
def func(a, b):
# this is incorrect, cannot add 1 to a dimensional Quantity
return a * b**2 + 1
assert isinstance(func(Q(1, 'yd'), Q(20, 'lbs')), Q['Mass'])
assert Q(1, 'bar').check(Pressure)
def test_heat_balance():
assert isinstance(heat_balance(Q(2, 'kg/s'), Q(2, 'kJ/s')),
Q['Temperature'])
assert isinstance(heat_balance(Q(2, 'K'), Q(2, 'kJ/s')), Q['MassFlow'])
assert isinstance(heat_balance(Q(2, 'kg'), Q(2, 'delta_degF')),
Q['Energy'])
assert isinstance(heat_balance(Q(2, 'kg/s'), Q(2, 'delta_degF')),
Q['Power'])
def test_typechecked():
@typechecked
def func_a(a: Quantity['Temperature']) -> Quantity['Pressure']:
return Q(2, 'bar')
assert func_a(Q(2, 'degC')) == Q(2, 'bar')
with pytest.raises(TypeError):
func_a(Q(2, 'meter'))
@typechecked
def func_b(a: Quantity) -> Quantity['Pressure']:
return a
assert func_b(Q(2, 'bar')) == Q(2, 'bar')
assert func_b(Q(2, 'psi')) == Q(2, 'psi')
assert func_b(Q(2, 'mmHg')) == Q(2, 'mmHg')
with pytest.raises(TypeError):
func_a(Q(2, 'meter'))
def test_shapes():
N = 16
T = Q(np.linspace(50, 60, N).reshape(4, 4), 'C')
P = Q(np.linspace(2, 4, N).reshape(4, 4), 'bar')
water = Fluid('water', T=T, P=P)
assert water.D.m.shape == P.m.shape
assert water.D.m.shape == T.m.shape
N = 27
T = Q(np.linspace(50, 60, N).reshape(3, 3, 3), 'C')
P = Q(np.linspace(2, 4, N).reshape(3, 3, 3), 'bar')
water = Fluid('water', T=T, P=P)
assert water.D.m.shape == P.m.shape
assert water.D.m.shape == T.m.shape
def test_invalid_areas():
N = 10
T = Q(np.linspace(-100, -50, N), 'K')
P = Q(np.linspace(-1, -2, N), 'bar')
water = Fluid('water', T=T, P=P)
assert water.D.check(Density)
assert isinstance(water.D.m, np.ndarray)
T = Q(np.linspace(-100, 300, N), 'K')
P = Q(np.linspace(-1, 2, N), 'bar')
water = Fluid('water', T=T, P=P)
assert water.D.check(Density)
assert isinstance(water.D.m, np.ndarray)
assert np.isnan(water.D.m[0])
assert not np.isnan(water.D.m[-1])
arr1 = np.linspace(-100, 400, N)
arr2 = np.linspace(-1, 2, N)
arr1[-2] = np.nan
arr2[-1] = np.nan
arr2[-3] = np.nan
T = Q(arr1, 'K')
P = Q(arr2, 'bar')
water = Fluid('water', T=T, P=P)
assert water.D.m.size == N
def test_intermediate_temperatures():
T1, T2 = intermediate_temperatures(Q(25, 'degC'), Q(10, 'degC'),
Q(0.05, 'W/m/K'), Q(10, 'cm'),
Q(1, 'W/m²/K'), Q(2, 'W/m²/K'), 0.7)
assert isinstance(T1, Q['Temperature'])
assert isinstance(T2, Q[Temperature])
assert T2.check(Temperature)
assert T2.check('K')
class Constants:
"""
Collection of constants.
Use a single instance of this class to refer to these constants.
"""
R = Q(8.3144598, 'kg*m²/K/mol/s²')
SIGMA = Q(5.670374419e-8, 'W/m**2/K**4')
default_density: Quantity[Density] = Q(997, 'kg/m³')
normal_conditions_pressure: Quantity[Pressure] = Q(1, 'atm')
normal_conditions_temperature: Quantity[Temperature] = Q(0, '°C').to('K')
standard_conditions_pressure: Quantity[Pressure] = Q(1, 'atm')
standard_conditions_temperature: Quantity[Temperature] = Q(15,
'degC').to('K')
def test_Water():
water_single = Water(T=Q(25, '°C'), P=Q(5, 'bar'))
repr(water_single)
water_multi = Water(T=Q(np.linspace(25, 50), '°C'), P=Q(5, 'bar'))
repr(water_multi)
water_mixed_phase = Water(T=Q(np.linspace(25, 500, 10), '°C'),
P=Q(np.linspace(0.5, 10, 10), 'bar'))
repr(water_mixed_phase)
with pytest.raises(Exception):
# mismatching sizes
# must access an attribute before it's actually evaluated
Water(T=Q(np.linspace(25, 500, 10), '°C'),
P=Q(np.linspace(0.5, 10, 50), 'bar')).P
def test_custom_units():
# "ton" should always default to metric ton
assert (Q(1, 'ton') == Q(1, 'Ton') == Q(1, 'TON') == Q(
1, 'tonne') == Q(1, 'metric_ton') == Q(1000, 'kg'))
assert Q(1, 'US_ton') == Q(907.1847400000001, 'kg')
assert (Q(1, 'ton/hour') == Q(1, 'Ton/hour') == Q(1, 'TON/hour') ==
Q(1, 'tonne/hour') == Q(1, 'metric_ton/hour') == Q(1000, 'kg/hour'))
v1 = (Q(1000, 'liter') * Q(1, 'normal')).to_base_units().m
v2 = Q(1000, 'normal liter').to_base_units().m
v3 = Q(1, 'nm3').m
v4 = Q(1, 'Nm3').m
# floating point accuracy
assert round(v1, 10) == round(v2, 10) == round(v3, 10) == round(v4, 10)
factor = Q(12, 'Nm3 water/ (normal liter air)')
(Q(1, 'kg water') / factor).to('pound air')
Q['NormalVolume'](2, 'nm**3')
with pytest.raises(DimensionalityError):
Q['NormalVolumeFlow'](2, 'm**3/hour')
Q['NormalVolumeFlow'](2, 'Nm**3/hour').to('normal liter/sec')
Q[Normal * VolumeFlow](2, 'Nm**3/hour').to('normal liter/sec')
Q(2, 'normal liter air / day')
Q(2, '1/Nm3').to('1 / (liter normal)')
def test_HumidAir():
T = Q(20, 'C')
P = Q(20, 'bar')
R = Q(20, '%')
ha = HumidAir(T=T, P=P, R=R)
ha.V
T = Q([25, 34], 'C')
P = Q(20, 'bar')
R = Q(20, '%')
ha = HumidAir(T=T, P=P, R=R)
ha.V
T = Q([25, 34], 'C')
P = Q([20, 30], 'bar')
R = Q([20, 40], '%')
ha = HumidAir(T=T, P=P, R=R)
ha.V
T = Q([25, 34], 'C')
P = Q([20, 30], 'bar')
R = Q([20, np.nan], '%')
ha = HumidAir(T=T, P=P, R=R)
ha.V
T = Q([np.nan, 34], 'C')
P = Q([np.nan, 30], 'bar')
R = Q([20, np.nan], '%')
ha = HumidAir(T=T, P=P, R=R)
ha.V
T = Q([20, 40], 'C')
P = Q([20, 1], 'bar')
R = Q([20, 101], '%')
ha = HumidAir(T=T, P=P, R=R)
val = ha.V.m
assert not np.isnan(val[0])
assert np.isnan(val[1])
def test_Fluid():
fld = Fluid('R123', P=Q(2, 'bar'), T=Q(25, '°C'))
assert fld.get('S') == Q(1087.7758824621442, 'J/(K kg)')
assert fld.D == fld.get('D')
water = Fluid('water', P=Q(2, 'bar'), T=Q(25, '°C'))
assert water.T.u == Q.get_unit('degC')
assert water.T.m == 25
HumidAir(T=Q(25, 'degC'), P=Q(125, 'kPa'), R=Q(0.2, 'dimensionless'))
Water(P=Q(1, 'bar'), Q=Q(0.9, ''))
Water(P=Q(1, 'bar'), T=Q(0.9, 'degC'))
Water(T=Q(1, 'bar'), Q=Q(0.9, ''))
with pytest.raises(Exception):
# cannot fix all of P, T, Q
Water(P=Q(1, 'bar'), T=Q(150, 'degC'), Q=(0.4, ''))
# incorrect argument name
Water(T=Q(1, 'bar'), P=Q(9, 'degC'))
Fluid('water', T=Q([25, 95], 'C'), P=Q([1, 2], 'bar')).H
Fluid('water', T=Q([25, np.nan], 'C'), P=Q([1, 2], 'bar')).H
Fluid('water', T=Q([np.nan, np.nan], 'C'), P=Q([1, 2], 'bar')).H
Fluid('water', T=Q([np.nan, np.nan], 'C'), P=Q([np.nan, np.nan], 'bar')).H
Fluid('water', T=Q(23, 'C'), P=Q([1, 2], 'bar')).H
Fluid('water', T=Q(23, 'C'), P=Q([1], 'bar')).H
Fluid('water', T=Q([23, 25], 'C'), P=Q([1], 'bar')).H
Fluid('water', T=Q([23, 25], 'C'), P=Q(np.nan, 'bar')).H
Fluid('water', T=Q([23, 25], 'C'), P=Q([1, np.nan], 'bar')).H
Water(T=Q([25, 25, 63], 'C'), Q=Q([np.nan, np.nan, 0.4], '')).H
Water(T=Q([25, np.nan, 63], 'C'), Q=Q([np.nan, 0.2, 0.5], '')).H
Water(T=Q([25, np.nan, np.nan], 'C'), Q=Q([np.nan, 0.2, np.nan], '')).H
# returns empty array (not nan)
ret = Fluid('water', T=Q([], 'C'), P=Q([], 'bar')).H.m
assert isinstance(ret, np.ndarray) and ret.size == 0
ret = Fluid('water', T=Q([], 'C'), P=Q((), 'bar')).H.m
assert isinstance(ret, np.ndarray) and ret.size == 0
ret = Fluid('water', T=Q([], 'C'), P=Q(np.array([]), 'bar')).H.m
assert isinstance(ret, np.ndarray) and ret.size == 0
# 1-element list or array works in the same way as scalar,
# except that the output is also a 1-element list or array
ret = Water(P=Q([2, 3], 'bar'), Q=Q([0.5])).D.m
assert isinstance(ret, np.ndarray) and ret.size == 2
ret = Water(P=Q([2, 3], 'bar'), Q=Q(0.5)).D.m
assert isinstance(ret, np.ndarray) and ret.size == 2
ret = Water(P=Q([2], 'bar'), Q=Q([0.5])).D.m
assert isinstance(ret, np.ndarray) and ret.size == 1
ret = Water(P=Q([2], 'bar'), Q=Q(0.5)).D.m
assert isinstance(ret, np.ndarray) and ret.size == 1
ret = Water(P=Q(2, 'bar'), Q=Q([0.5])).D.m
assert isinstance(ret, np.ndarray) and ret.size == 1
ret = Water(P=Q(2, 'bar'), Q=Q(0.5)).D.m
assert isinstance(ret, float)
ret = Water(P=Q([], 'bar'), Q=Q([0.5])).D.m
assert isinstance(ret, np.ndarray) and ret.size == 0
ret = Water(P=Q([], 'bar'), Q=Q([])).D.m
assert isinstance(ret, np.ndarray) and ret.size == 0
ret = Water(P=Q(np.array([]), 'bar'), Q=Q(np.array([]))).D.m
assert isinstance(ret, np.ndarray) and ret.size == 0
# returns 1-element list
assert isinstance(
Fluid('water', T=Q([23], 'C'), P=Q([1], 'bar')).H.m, np.ndarray)
assert isinstance(
Fluid('water', T=Q(23, 'C'), P=Q([1], 'bar')).H.m, np.ndarray)
assert isinstance(
Fluid('water', T=Q([23], 'C'), P=Q(1, 'bar')).H.m, np.ndarray)
# returns float
assert isinstance(Fluid('water', T=Q(23, 'C'), P=Q(1, 'bar')).H.m, float)
with pytest.raises(ValueError):
Fluid('water',
T=Q([np.nan, np.nan], 'C'),
P=Q([np.nan, np.nan, np.nan], 'bar')).H
Fluid('water', T=Q([np.nan, np.nan], 'C'), P=Q([], 'bar')).H
def test_convert_gas_volume():
ret = convert_gas_volume(Q(1, 'm3'), 'N', (Q(2, 'bar'), Q(25, 'degC')))
assert ret.check(Q(0, 'liter'))
def test_Q():
# test that Quantity objects can be constructed
Q(1, 'dimensionless')
Q(1, 'kg')
Q(1, 'bar')
Q(1, 'h')
Q(1, 'newton')
Q(1, 'cSt')
# make sure that the alias Q behaves identically to Quantity
assert Q(1) == Quantity(1)
assert type(Q(1)) is type(Quantity(1))
assert type(Q) is type(Quantity)
# ensure that the inputs can be nested
Q(Q(1, 'kg'))
mass = Q(12, 'kg')
Q(Q(Q(Q(mass))))
Q(Q(Q(Q(mass), 'lbs')))
Q(Q(Q(Q(mass), 'lbs')), 'stone')
# no unit input defaults to dimensionless
assert Q(12).check('')
assert Q(1) == Q(100, '%')
Q['Dimensionless'](21)
assert isinstance(Q(21), Q['Dimensionless'])
assert Q(1) == Q('1')
assert Q(1) == Q('\n1\n')
assert Q(1) == Q('1 dimensionless')
# check type of "m"
assert isinstance(Q(1, 'meter').m, int)
assert isinstance(Q(2.3, 'meter').m, float)
assert isinstance(Q([2, 3.4], 'meter').m, np.ndarray)
assert isinstance(Q(np.array([2, 3.4]), 'meter').m, np.ndarray)
# input Quantity as unit
Q(1, Q(2, 'bar'))
# input Quantity as val
Q(Q(2, 'bar'), 'kPa')
# input Quantity as both val and unit
Q(Q(2, 'bar'), Q(3, 'kPa'))
Q(Q(2, 'bar'), Q(3, 'mmHg'))
# check that the dimensionality constraints work
Q[Length](1, 'm')
Q[Pressure](1, 'kPa')
Q[Temperature](1, '°C')
# the dimensionalities can also be specified as strings
Q['Temperature'](1, '°C')
P = Q(1, 'bar')
# this Quantity must have the same dimensionality as P
Q[P](2, 'kPa')
with pytest.raises(DimensionalityError):
Q[Temperature](1, 'kg')
Q[Pressure](1, 'meter')
Q[Mass](1, P)
# in-place conversion
# NOTE: don't use this for objects that are passed in by the user
P3 = Q(1, 'bar')
P3.ito('kPa')
P3.ito(Q(123123, 'kPa'))
assert P3.m == approx(100, rel=1e-12)
# test conversions to np.ndarray with int/float dtypes
a = Q([1, 2, 3], 'bar')
a.ito('kPa')
a = Q(np.array([1, 2, 3.0]), 'bar')
a.ito('kPa')
a = Q(np.array([1.0, 2.0, 3.0]), 'bar')
a.ito('kPa')
# conversion to new object
P4 = Q(1, 'bar')
P4_b = P4.to('kPa')
P4_b = P4.to(Q(123123, 'kPa'))
assert P4_b.m == approx(100, rel=1e-12)
assert Q(1, 'bar') == Q(100, 'kPa') == Q('0.1 MPa') == Q('1e5', 'Pa')
# check that nested Quantity objects can be used as input
# only the first value is used as magnitude, the other Quantity
# objects are only used to determine unit
P2 = Q(Q(2, 'feet_water'), Q(321321, 'kPa')).to(Q(123123, 'feet_water'))
# floating point math might make this off at the N:th decimal
assert P2.m == approx(2, rel=1e-12)
assert isinstance(P2, Q['Pressure'])
with pytest.raises(Exception):
# incorrect dimensionalities should raise Exception
Q(Q(2, 'feet_water'), Q(321321, 'kg')).to(Q(123123, 'feet_water'))
# the UnitsContainer objects can be used to construct new dimensionalities
Q[Length * Length * Length / Temperature](1, 'm³/K')
with pytest.raises(Exception):
Q[Pressure / Area](1, 'bar/m')
# percent or %
Q(1.124124e-3, '').to('%').to('percent')
Q(1.124124e-3).to('%').to('percent')
# pd.Series is converted to np.ndarray
vals = [2, 3, 4]
s = pd.Series(vals, name='Pressure')
arr = Q(s, 'bar').to('kPa').m
assert isinstance(arr, np.ndarray)
assert arr[0] == 200
# np.ndarray magnitudes equality check
assert (Q(s, 'bar') == Q(vals, 'bar').to('kPa')).all()
# support a single string as input if the
# magnitude and units are separated by one or more spaces
assert Q('1 meter').check(Length)
assert Q('1 meter per second').check(Velocity)
assert (Q('1 m') ** 3).check(Volume)
def test_dataframe_assign():
df_multiple_rows = pd.DataFrame(
{
'A': [1, 2, 3],
'B': [1, 2, 3],
}
)
df_single_row = pd.DataFrame(
{
'A': [1],
'B': [1],
}
)
df_empty = pd.DataFrame(
{
'A': [],
'B': [],
}
)
for df in [df_multiple_rows, df_single_row, df_empty]:
df['C'] = Q(df.A, 'bar') * Q(25, 'meter')
df['Temp'] = Q(df.A, 'degC')
with pytest.raises(AttributeError):
density = Water(
# this is pd.Series[float]
T=df.Temp,
Q=Q(0.5)
).D
density = Water(
# wrap in Quantity() to use the Water class
T=Q(df.Temp, 'degC'),
Q=Q(0.5)
).D
# implicitly strips magnitude in whatever unit the Quantity happens to have
df['density'] = density
# assigns a column with specific unit
df['density_with_unit'] = density.to('kg/m3')
# the .m accessor is not necessary for vectors
df['density_with_unit_magnitude'] = density.to('kg/m3').m
# this does not work -- pandas function is_list_like(Q(4, 'bar')) -> True
# which means that this fails internally in pandas
# ValueError: Length of values (1) does not match length of index (3)
# df['D'] = Q(4, 'bar')
# i.e. the .m accessor must be used for scalar Quantity assignment
df['E'] = Q(df.A, 'bar').m
df['F'] = Q(4, 'bar').m
def func_a(a: Quantity['Temperature']) -> Quantity['Pressure']:
return Q(2, 'bar')
