forked from M-Labs/artiq
829fca6112
This also fixes (non-numpy) lists containing NaNs. Previously, accidentally storing a NaN in a dataset would bring down large parts of the system.
57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
import unittest
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import json
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from fractions import Fraction
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import numpy as np
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from artiq.protocols import pyon
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_pyon_test_object = {
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(1, 2): [(3, 4.2), (2, )],
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"slice": slice(3),
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Fraction(3, 4): np.linspace(5, 10, 1),
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"set": {"testing", "sets"},
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"a": np.int8(9), "b": np.int16(-98), "c": np.int32(42), "d": np.int64(-5),
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"e": np.uint8(8), "f": np.uint16(5), "g": np.uint32(4), "h": np.uint64(9),
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"x": np.float16(9.0), "y": np.float32(9.0), "z": np.float64(9.0),
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1j: 1-9j,
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"q": np.complex128(1j),
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}
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class PYON(unittest.TestCase):
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def test_encdec(self):
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for enc in pyon.encode, lambda x: pyon.encode(x, True):
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with self.subTest(enc=enc):
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self.assertEqual(pyon.decode(enc(_pyon_test_object)),
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_pyon_test_object)
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# NaNs don't compare equal, so test separately.
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assert np.isnan(pyon.decode(enc(np.nan)))
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def test_encdec_array(self):
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orig = {k: (np.array(v), np.array([v]))
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for k, v in _pyon_test_object.items()
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if np.isscalar(v)}
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for enc in pyon.encode, lambda x: pyon.encode(x, True):
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result = pyon.decode(enc(orig))
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for k in orig:
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with self.subTest(enc=enc, k=k, v=orig[k]):
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np.testing.assert_equal(result[k], orig[k])
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_json_test_object = {
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"a": "b",
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"x": [1, 2, {}],
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"foo\nbaz\\qux\"\r2": ["bar", 1.2, {"x": "y"}],
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"bar": [True, False, None]
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}
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class JSONPYON(unittest.TestCase):
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def test_encdec(self):
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for enc in pyon.encode, lambda x: pyon.encode(x, True), json.dumps:
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for dec in pyon.decode, json.loads:
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self.assertEqual(dec(enc(_json_test_object)),
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_json_test_object)
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