diff --git a/docs/source/conf.py b/docs/source/conf.py index 0ddbd6e..7ca2dad 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -24,7 +24,8 @@ author = "Sascha Vowe, Bastian Leykauf" # The full version, including alpha/beta/rc tags -release = "0.2.1" + +release = "0.2.2" # -- General configuration --------------------------------------------------- diff --git a/docs/source/examples.ipynb b/docs/source/examples.ipynb index d28ed3d..25df5a2 100644 --- a/docs/source/examples.ipynb +++ b/docs/source/examples.ipynb @@ -43,7 +43,7 @@ "output_type": "execute_result", "data": { "text/plain": [ - "[]" + "[]" ] }, "metadata": {}, @@ -53,7 +53,7 @@ "output_type": "display_data", "data": { "text/plain": "
", - "image/svg+xml": "\n\n\n\n \n \n \n \n 2020-11-11T11:53:14.599737\n image/svg+xml\n \n \n Matplotlib v3.3.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "image/svg+xml": "\n\n\n\n \n \n \n \n 2020-11-11T14:39:46.493421\n image/svg+xml\n \n \n Matplotlib v3.3.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", 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\n" }, "metadata": { @@ -105,7 +105,7 @@ "metadata": {}, "source": [ "## Free expansion with initial momentum\n", - "The wave funciton can be given an initial momentum of $k$ by multiplying it with $\\exp (-ikx)$." + "The wave funciton can be given an initial momentum of $k$ by multiplying it with $\\exp (ikx)$." ] }, { @@ -114,7 +114,7 @@ "metadata": {}, "outputs": [], "source": [ - "psi = pt.Wavefunction('exp(-(x-x0)**2)*exp(-1j*k*x)',\n", + "psi = pt.Wavefunction('exp(-(x-x0)**2)*exp(1j*k*x)',\n", " variables={'x0': -5.0, 'k': 10.0}, number_of_grid_points=(128,),\n", " spatial_ext=(-10,10))" ] @@ -135,7 +135,7 @@ "output_type": "display_data", "data": { "text/plain": "
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "image/svg+xml": "\n\n\n\n \n \n \n \n 2020-11-11T14:39:48.566489\n image/svg+xml\n \n \n Matplotlib v3.3.2, https://matplotlib.org/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", "image/png": 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\n" }, "metadata": { @@ -292,8 +292,8 @@ "output_type": "stream", "name": "stdout", "text": [ - "18.1 ms ± 65.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n", - "26.2 ms ± 245 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "19.8 ms ± 191 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", + "28.5 ms ± 433 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] } ], @@ -437,7 +437,7 @@ "output_type": "execute_result", "data": { "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -447,7 +447,7 @@ "output_type": "display_data", "data": { "text/plain": "
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\n" }, "metadata": { @@ -459,7 +459,7 @@ "import numexpr as ne\n", "\n", "psi = pt.Wavefunction(\n", - " \"exp(-((x-x0)/sigmax)**2)*exp(-((y-y0)/sigmay)**2)*exp(-1j*ky*y)\", \n", + " \"exp(-((x-x0)/sigmax)**2)*exp(-((y-y0)/sigmay)**2)*exp(1j*ky*y)\", \n", " variables={'x0': 0, 'y0': -3, 'sigmax':5, 'sigmay': 1, 'ky': 3 },\n", " number_of_grid_points=(256,256),\n", " spatial_ext=[(-10,10),(-10,10)],\n", @@ -590,7 +590,7 @@ " return (line1,line2,)\n", "\n", "psi = pt.Wavefunction(\n", - " [\"exp(-(x/2/sigmax)**2)\",\"exp(-((x+x0)/2/sigmax)**2)*exp(-1j*k*x)\"], \n", + " [\"exp(-(x/2/sigmax)**2)\",\"exp(-((x+x0)/2/sigmax)**2)*exp(1j*k*x)\"], \n", " variables={'x0': 20, 'sigmax':2, 'k': 20 },\n", " number_of_grid_points=(512,),\n", " spatial_ext=(-30,30),\n", diff --git a/pytalises/propagator.py b/pytalises/propagator.py index 653c31d..181b6b4 100644 --- a/pytalises/propagator.py +++ b/pytalises/propagator.py @@ -208,7 +208,7 @@ def nondiag_potential_prop(self, delta_t): "xyzij,xyzj,xyzkj,xyzk->xyzi", self.V_eval_array, ne.evaluate( - "exp(1j*eigval*delta_t)", + "exp(-1j*eigval*delta_t)", local_dict={"eigval": self.V_eval_eigval_array, "delta_t": delta_t}, ), np.conjugate(self.V_eval_array), @@ -231,7 +231,7 @@ def diag_potential_prop(self, delta_t): np.einsum( "xyzii,xyzi->xyzi", ne.evaluate( - "exp(1j*V*delta_t)", + "exp(-1j*V*delta_t)", local_dict={"V": self.V_eval_array, "delta_t": delta_t}, ), self.psi._amp, @@ -252,7 +252,7 @@ def kinetic_prop(self, delta_t): np.einsum( "xyz,xyzi->xyzi", ne.evaluate( - "exp(1j*alpha*delta_t*(kx**2+ky**2+kz**2))", + "exp(-1j*alpha*delta_t*(kx**2+ky**2+kz**2))", local_dict={ "kx": self.psi.kmesh[0], "ky": self.psi.kmesh[1], diff --git a/setup.py b/setup.py index c5d86dc..f8564e8 100644 --- a/setup.py +++ b/setup.py @@ -5,7 +5,8 @@ setup( name="pytalises", - version="0.2.1", + version="0.2.2", + description=""" TALISES (This Ain't a LInear Schrödinger Equation Solver) is an easy-to-use Python implementation of the Split-Step Fourier Method, for numeric calculation of a wave function's time-propagation