IPKM/mdevaluate
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compare: IPKM:4394f7053017b79b99151cb77112438d50149e81
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2 changed files with 4 additions and 4 deletions
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2
pyproject.toml
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@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project] [project]
name = "mdevaluate" name = "mdevaluate"
version = "24.02" version = "24.01"
dependencies = [ dependencies = [
"mdanalysis", "mdanalysis",
"pandas", "pandas",

6
src/mdevaluate/correlation.py
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@ -219,13 +219,13 @@ def isf(
return np.sinc(distance * q / np.pi).mean() return np.sinc(distance * q / np.pi).mean()
elif axis == "xy" or axis == "yx": elif axis == "xy" or axis == "yx":
distance = (displacements[:, [0, 1]]**2).sum(axis=1) ** 0.5 distance = (displacements[:, [0, 1]]**2).sum(axis=1) ** 0.5
return np.real(jn(0, distance * q)).mean() return np.real(jn(0, distance * q / np.pi)).mean()
elif axis == "xz" or axis == "zx": elif axis == "xz" or axis == "zx":
distance = (displacements[:, [0, 2]]**2).sum(axis=1) ** 0.5 distance = (displacements[:, [0, 2]]**2).sum(axis=1) ** 0.5
return np.real(jn(0, distance * q)).mean() return np.real(jn(0, distance * q / np.pi)).mean()
elif axis == "yz" or axis == "zy": elif axis == "yz" or axis == "zy":
distance = (displacements[:, [1, 2]]**2).sum(axis=1) ** 0.5 distance = (displacements[:, [1, 2]]**2).sum(axis=1) ** 0.5
return np.real(jn(0, distance * q)).mean() return np.real(jn(0, distance * q / np.pi)).mean()
elif axis == "x": elif axis == "x":
distance = np.abs(displacements[:, 0]) distance = np.abs(displacements[:, 0])
return np.mean(np.cos(np.abs(q * distance))) return np.mean(np.cos(np.abs(q * distance)))