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363 lines (293 loc) · 10.8 KB
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# Copyright (c) 2017 Dassault Systemes. All rights reserved.
import runpy
import unittest
from unittest import skipIf
import numpy as np
import math
import sdf
import os
import platform
class Test(unittest.TestCase):
@classmethod
def setUpClass(cls):
if platform.system() == "Windows":
# plot tests currently only work on Windows anyways
import matplotlib.pyplot as plt
def no_show():
pass
# suppress matplotlib.pyplot.show()
plt.show = no_show
def assertDatasetsEqual(self, ds1, ds2):
# compare string attributes
for attr in [
"name",
"comment",
"display_name",
"relative_quantity",
"unit",
"display_unit",
]:
a = getattr(ds1, attr)
b = getattr(ds2, attr)
self.assertEqual(a, b)
# compare data
self.assertTrue(np.all(ds1.data == ds2.data))
def test_data_types(self):
ds_f = sdf.Dataset(name="f", data=np.asarray([1, 2, 3], dtype=np.float32))
ds_d = sdf.Dataset(name="d", data=np.asarray([1, 2, 3], dtype=np.float64))
ds_i = sdf.Dataset(name="i", data=np.asarray([1, 2, 3], dtype=np.int32))
g = sdf.Group(name="/", datasets=[ds_f, ds_d, ds_i])
sdf.save("data_types.sdf", g)
g = sdf.load("data_types.sdf")
self.assertEqual(g["f"].data.dtype, np.float32)
self.assertEqual(g["d"].data.dtype, np.float64)
self.assertEqual(g["i"].data.dtype, np.int32)
def test_roundtrip(self):
# create a scale
ds1 = sdf.Dataset(
"DS1",
comment="dataset 1",
data=np.array([0.1, 0.2, 0.3]),
display_name="Scale 1",
unit="U1",
display_unit="DU1",
is_scale=True,
)
# create a 1D dataset
ds2 = sdf.Dataset(
"DS2",
comment="dataset 2",
data=np.array([1, 2, 3]),
display_name="Dataset 2",
relative_quantity=True,
unit="U2",
display_unit="DU2",
scales=[ds1],
)
# create a group
g = sdf.Group(
name="/",
comment="my comment",
attributes={"A1": "my string"},
datasets=[ds1, ds2],
)
g2 = sdf.Group(name="G2")
g.groups.append(g2)
# save the group
sdf.save("test.sdf", g)
# load DS2 from the file
ds2r = sdf.load("test.sdf", "/DS2")
# make sure the content is still the same
self.assertDatasetsEqual(ds2, ds2r)
self.assertDatasetsEqual(ds2.scales[0], ds2r.scales[0])
def test_hierarchy(self):
# create a scale
ds_time = sdf.Dataset(
"Time",
comment="A scale",
data=np.linspace(0, 10, 101),
unit="s",
is_scale=True,
)
ds_sine = sdf.Dataset(
"sine",
comment="A 1-d dataset /w attached scale",
data=np.sin(ds_time.data),
scales=[ds_time],
)
# create the root group
g = sdf.Group(
name="/",
comment="A test file",
attributes={"A1": "my string"},
datasets=[ds_time, ds_sine],
)
# create a scalar dataset
ds_alpha = sdf.Dataset(
"alpha",
comment="A scalar /w unit, display unit and display name",
data=np.pi,
display_name="Angle",
unit="rad",
display_unit="deg",
)
# create a sub group
g1 = sdf.Group(
name="g1",
comment="A sub-group",
attributes={"A2": "Attribute in sub group"},
datasets=[ds_alpha],
)
g.groups.append(g1)
# save the group
sdf.save("roundtrip.sdf", g)
# load the group from the file
sdf.load("roundtrip.sdf", "/")
# TODO: compare the objects
# self.assertEqual(pickle.dumps(g), pickle.dumps(g2))
def test_3D_example(self):
RPM2RADS = 2 * math.pi / 60
kfric = 1 # [Ws/rad] angular damping coefficient [0;100]
kfric3 = 1.5e-6 # [Ws3/rad3] angular damping coefficient (3rd order) [0;10-3]
psi = 0.2 # [Vs] flux linkage [0.001;10]
res = 5e-3 # [Ohm] resistance [0;100]
v_ref = 200 # [V] reference DC voltage [0;1000]
k_u = 5 # linear voltage coefficient [-100;100]
tau = np.arange(0.0, 230.0 + 10.0, 10)
w = (
np.concatenate(
(np.arange(0.0, 500.0, 100), np.arange(500.0, 12e3 + 500, 500))
)
* RPM2RADS
)
u = np.asarray([200.0, 300.0, 400.0])
# calculate the power losses
TAU, W, U = np.meshgrid(tau, w, u, indexing="ij")
P_loss = (
kfric * W + kfric3 * W**3 + (res * (TAU / psi) ** 2) + k_u * (U - v_ref)
)
# create the scales
ds_tau = sdf.Dataset(
"tau",
comment="Torque",
data=tau,
display_name="Torque",
unit="N.m",
is_scale=True,
)
ds_w = sdf.Dataset(
"w",
comment="Speed",
data=w,
display_name="Speed",
unit="rad/s",
display_unit="rpm",
is_scale=True,
)
ds_v = sdf.Dataset(
"v",
comment="DC voltage",
data=u,
display_name="DC voltage",
unit="V",
is_scale=True,
)
# create the dataset
ds_P_loss = sdf.Dataset(
"P_loss",
comment="Power losses",
display_name="Power Losses",
data=P_loss,
unit="W",
scales=[ds_tau, ds_w, ds_v],
)
# create a group
g = sdf.Group(
name="/",
comment="Example loss characteristics of an e-machine w.r.t. torque, speed and DC voltage",
datasets=[ds_tau, ds_w, ds_v, ds_P_loss],
)
errors = sdf.validate(g)
self.assertEqual([], errors)
sdf.save("emachine.sdf", g)
def test_validate_group(self):
g = sdf.Group("8")
errors = sdf._validate_group(g, is_root=False)
self.assertEqual(
[
'Object names must only contain letters, digits, and underscores ("_") and must start with a letter.'
],
errors,
)
g.name = "G1"
errors = sdf._validate_group(g, is_root=False)
self.assertEqual([], errors)
def test_validate_dataset(self):
ds1 = sdf.Dataset("DS1")
ds1.data = 1
errors = sdf._validate_dataset(ds1)
self.assertEqual(["Dataset.data must be a numpy.ndarray"], errors)
ds1.data = np.array([])
errors = sdf._validate_dataset(ds1)
self.assertEqual(["Dataset.data must not be empty"], errors)
ds1.data = np.array(1).astype(np.float32)
errors = sdf._validate_dataset(ds1)
self.assertEqual(["Dataset.data.dtype must be numpy.float64"], errors)
ds1.data = np.array([1.0, 2.0])
errors = sdf._validate_dataset(ds1)
self.assertEqual(
["The number of scales does not match the number of dimensions"], errors
)
ds2 = sdf.Dataset("DS2", data=np.array([0.0, 1.0, 2.0]), is_scale=True)
ds1.scales = [ds2]
errors = sdf._validate_dataset(ds1)
self.assertEqual([], errors)
ds2.data = np.array([[1.0, 2.0], [3.0, 4.0]])
errors = sdf._validate_dataset(ds2)
self.assertEqual(["Scales must be one-dimensional"], errors)
ds2.data = np.array([0, 1.0, 1.0])
errors = sdf._validate_dataset(ds2)
self.assertEqual(["Scales must be strictly monotonic increasing"], errors)
def test_dsres_load_all(self):
path, _ = os.path.split(sdf.__file__)
filename = os.path.join(path, "examples", "IntegerNetwork1.mat")
g = sdf.load(filename)
s = g["Time"]
self.assertEqual(s.data.size, 552)
# self.assertEqual(s.data.dtype, np.dtype(np.float32))
self.assertTrue(s.is_scale)
self.assertEqual(s.unit, "s")
self.assertEqual(s.comment, "Simulation time")
ds = g["booleanPulse2"]["period"]
self.assertEqual(ds.data, 2.0)
self.assertEqual(ds.unit, "s")
self.assertEqual(ds.comment, "Time for one period")
ds = g["booleanPulse2"]["y"]
self.assertEqual(ds.data.dtype, np.int32)
self.assertEqual(ds.data.size, 552)
self.assertEqual(ds.data[0], True)
self.assertEqual(ds.data[93], False)
self.assertEqual(ds.scales[0], s)
ds = g["integerConstant"]["k"]
self.assertEqual(ds.data.dtype, np.int32)
self.assertEqual(ds.data, 1)
# sdf.save(filename=os.path.join(path, 'examples', 'IntegerNetwork1.sdf'), group=g)
def test_dsres_load_dataset(self):
path, _ = os.path.split(sdf.__file__)
filename = os.path.join(path, "examples", "IntegerNetwork1.mat")
ds = sdf.load(filename, objectname="/booleanPulse2/period")
self.assertEqual(ds.data, 2.0)
self.assertEqual(ds.unit, "s")
self.assertEqual(ds.comment, "Time for one period")
ds = sdf.load(filename, objectname="/booleanPulse2/y")
self.assertEqual(ds.data.dtype, np.dtype(np.int32))
self.assertEqual(ds.data.size, 552)
self.assertEqual(ds.data[0], True)
self.assertEqual(ds.data[93], False)
s = ds.scales[0]
self.assertEqual(s.data.size, 552)
# self.assertEqual(s.data.dtype, np.dtype(np.float32))
self.assertEqual(s.unit, "s")
self.assertEqual(s.comment, "Simulation time")
ds = sdf.load(filename, objectname="/integerConstant/k")
self.assertEqual(ds.data.dtype, np.dtype(np.int32))
self.assertEqual(ds.data, 1)
def test_dsres_inverted_signals(self):
path = os.path.dirname(__file__)
filename = os.path.join(path, "DoublePendulum.mat")
rvisobj = sdf.load(filename, "/world/y_label/cylinders[2]/rvisobj[1]")
self.assertTrue(rvisobj.data < 0)
@skipIf(platform.system() != "Windows", "Test requires display")
def test_interp_1d_example(self):
runpy.run_module("sdf.examples.interp_1d")
@skipIf(platform.system() != "Windows", "Test requires display")
def test_interp_2d_example(self):
runpy.run_module("sdf.examples.interp_2d")
@skipIf(platform.system() != "Windows", "Test requires display")
def test_sine_example(self):
runpy.run_module("sdf.examples.sine")
@skipIf(platform.system() != "Windows", "Test requires display")
def test_spline_1d_example(self):
runpy.run_module("sdf.examples.spline_1d")
if __name__ == "__main__":
unittest.main()