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4 Commits
87ffa1e67e
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5c17e04b38
Author | SHA1 | Date | |
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5c17e04b38 | |||
16233e2f2c | |||
62705da6f3 | |||
b4486ff265 |
@ -10,4 +10,5 @@ dependencies = [
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"pandas",
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"dask",
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"pathos",
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"tables"
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]
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@ -261,6 +261,7 @@ class CoordinatesMap:
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self.frames = self.coordinates.frames
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self.atom_subset = self.coordinates.atom_subset
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self.function = function
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self._slice = slice(None)
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if isinstance(function, partial):
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self._description = self.function.func.__name__
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else:
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@ -5,11 +5,11 @@ import numpy as np
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def test_checksum():
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salt = checksum.SALT
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checksum.SALT = ''
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checksum.SALT = ""
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assert checksum.checksum(1) == 304942582444936629325699363757435820077590259883
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assert checksum.checksum('42') == checksum.checksum(42)
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assert checksum.checksum("42") == checksum.checksum(42)
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cs1 = checksum.checksum(999)
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checksum.SALT = '999'
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checksum.SALT = "999"
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assert cs1 != checksum.checksum(999)
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a = np.array([1, 2, 3])
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@ -19,7 +19,6 @@ def test_checksum():
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def test_version():
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@checksum.version(1)
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def f1():
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pass
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@ -7,7 +7,7 @@ from mdevaluate import coordinates
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@pytest.fixture
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def trajectory(request):
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return mdevaluate.open(os.path.join(os.path.dirname(__file__), 'data/water'))
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return mdevaluate.open(os.path.join(os.path.dirname(__file__), "data/water"))
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def test_coordinates_getitem(trajectory):
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@ -9,6 +9,6 @@ def test_pbc_diff():
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y = np.random.rand(10, 3)
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box = np.ones((3,))
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assert (pbc.pbc_diff(x, x, box) == approx(0))
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dxy = (pbc.pbc_diff(x, y, box)**2).sum(axis=1)**0.5
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assert pbc.pbc_diff(x, x, box) == approx(0)
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dxy = (pbc.pbc_diff(x, y, box) ** 2).sum(axis=1) ** 0.5
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assert (dxy <= 0.75**0.5).all()
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@ -8,7 +8,7 @@ from mdevaluate import utils
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@pytest.fixture
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def logdata(request):
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xdata = np.logspace(-1, 3, 50)
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ydata = np.exp(- (xdata)**0.7)
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ydata = np.exp(-((xdata) ** 0.7))
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return xdata, ydata
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@ -18,16 +18,16 @@ def test_filon_fourier_transformation(logdata):
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xdata_zero = copy(xdata)
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xdata_zero[0] = 0
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_, filon = utils.filon_fourier_transformation(xdata_zero, ydata)
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assert not np.isnan(filon).any(), 'There are NaN values in the filon result!'
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assert not np.isnan(filon).any(), "There are NaN values in the filon result!"
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freqs = np.logspace(-4, 1)
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filon_freqs, filon_imag = utils.filon_fourier_transformation(
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xdata, xdata, frequencies=freqs, derivative='linear', imag=True
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)
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xdata, xdata, frequencies=freqs, derivative="linear", imag=True
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)
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assert (freqs == filon_freqs).all()
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freqs, filon_real = utils.filon_fourier_transformation(
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xdata, xdata, frequencies=freqs, derivative='linear', imag=False
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)
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xdata, xdata, frequencies=freqs, derivative="linear", imag=False
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)
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assert np.isclose(filon_imag.real, filon_real).all()
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