From 1245e3c49aa7468c6df541f17068bbda3c68573c Mon Sep 17 00:00:00 2001 From: ppegolo Date: Tue, 15 Oct 2024 16:57:59 +0200 Subject: [PATCH] Avoid stashing --- .gitignore | 4 + examples/08_example_optimize_prior .ipynb | 97 ++++++++++------------- 2 files changed, 48 insertions(+), 53 deletions(-) diff --git a/.gitignore b/.gitignore index caf174f..f922c29 100644 --- a/.gitignore +++ b/.gitignore @@ -122,3 +122,7 @@ examples/data_manager/gpumd/thermo.out examples/data_manager/lammps/config.lammpsdata examples/data_manager/lammps/dump.sample.lammpstrj examples/data_manager/lammps/sample.lammps +examples/07_example_negative_log_likelihood copy.ipynb +examples/08_example_optimize_prior .ipynb +examples/stress_flux_hacked.npy +sportran/md/maxlike copy.py diff --git a/examples/08_example_optimize_prior .ipynb b/examples/08_example_optimize_prior .ipynb index 51625be..5f7bc49 100644 --- a/examples/08_example_optimize_prior .ipynb +++ b/examples/08_example_optimize_prior .ipynb @@ -5,9 +5,18 @@ "execution_count": 1, "metadata": {}, "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], "source": [ "import sys\n", - "sys.path.append('../')\n", "import sportran as st\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", @@ -16,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -70,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -79,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -90,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -106,11 +115,11 @@ " Resampling freq f* = 20.00000 THz\n", " Sampling time TSKIP = 25 steps\n", " = 25.000 fs\n", - " Original n. of frequencies = 50001\n", - " Resampled n. of frequencies = 2001\n", - " min(PSD) (pre-filter&sample) = 0.00208\n", - " min(PSD) (post-filter&sample) = 1856.32621\n", - " % of original PSD Power f" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.plot(flux_resample.maxlike.alpha, flux_resample.maxlike.best_alpha['lev_s'])\n", "plt.axvline(flux_resample.maxlike.best_alpha['alpha_s'], color='red')" @@ -248,7 +239,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.5" + "version": "3.11.8" } }, "nbformat": 4,