diff --git a/notebooks/3d.ipynb b/notebooks/3d.ipynb index cab87ed..c71db85 100644 --- a/notebooks/3d.ipynb +++ b/notebooks/3d.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "collapsed": true }, @@ -12,556 +12,17 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipy\n", - "from glob import glob" + "from glob import glob\n", + "from notebooks.lib import read_xyz, read_load" ] }, - { - "cell_type": "code", - "execution_count": 2, - "outputs": [], - "source": [ - "def read_xyz(path: str):\n", - " df = pd.read_csv(path)\n", - " df['N'] = df.index + 1\n", - " df['r'] = (df.x ** 2 + df.y ** 2 + df.z ** 2) ** 0.5\n", - " df['cr'] = df.r.cummax()\n", - " df['fd'] = np.log(df.N) / np.log(df.cr)\n", - "\n", - " return df\n", - "\n", - "def read_all(load_dir: str, reader):\n", - " paths = glob(f'{load_dir}/*.csv')\n", - " return [reader(path) for path in paths]" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 27, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n", - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", - " result = getattr(ufunc, method)(*inputs, **kwargs)\n" - ] - } - ], - "source": [ - "c_direct_neighbours = read_all(\"/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/data-analysis/data/c-3d-direct-neighbours\", read_xyz)\n", - "c_off_axis_neighbours = read_all(\"/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/data-analysis/data/c-3d-off-axis-neighbours\", read_xyz)" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 28, - "outputs": [ - { - "data": { - "text/plain": "
", - "image/png": "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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "for c in c_direct_neighbours:\n", - " plt.plot(c.fd)\n", - "\n", - "for c in c_off_axis_neighbours:\n", - " plt.plot(c.fd)\n", - "\n", - "plt.show()" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 22, - "outputs": [], - "source": [ - "def convergent_tail_index(series, tol):\n", - " diffs = np.abs(np.ediff1d(series))\n", - " for i in range(0, len(diffs)):\n", - " if np.max(diffs[i:]) <= tol:\n", - " return i\n", - "\n", - " # No convergence found\n", - " raise Exception(\"No convergence found\")\n", - "\n", - "def compute_fd(df, tol=0.05):\n", - " tail_index = convergent_tail_index(df.fd, tol)\n", - " return np.mean(df.fd[tail_index:]), np.std(df.fd[tail_index:])" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 29, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/numpy/lib/arraysetops.py:89: RuntimeWarning: invalid value encountered in subtract\n", - " return ary[1:] - ary[:-1]\n" - ] - } - ], - "source": [ - "aa = [compute_fd(c) for c in c_direct_neighbours]\n", - "bb = [compute_fd(c) for c in c_off_axis_neighbours]" - ], - "metadata": { - "collapsed": false - } - }, { "cell_type": "code", "execution_count": 30, - "outputs": [ - { - "data": { - "text/plain": "
", - "image/png": "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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "plt.plot(list(list(zip(*aa))[0]))\n", - "plt.plot(list(list(zip(*bb))[0]))\n", - "plt.show()" - ], - "metadata": { - "collapsed": false - } - }, - { - "cell_type": "code", - "execution_count": 21, - "outputs": [ - { - "data": { - "text/plain": "100" - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(bb)" + "def linear(x, a, b):\n", + " return x * a + b\n" ], "metadata": { "collapsed": false @@ -572,7 +33,172 @@ "execution_count": null, "outputs": [], "source": [ - "read_" + "c_direct_neighbours = read_load(\n", + " \"/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/data-analysis/data/c-3d-direct-neighbours\", read_xyz)\n", + "c_off_axis_neighbours = read_load(\n", + " \"/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/data-analysis/data/c-3d-off-axis-neighbours\", read_xyz)" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 51, + "outputs": [ + { + "data": { + "text/plain": "
", + "image/png": "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" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": "
", + "image/png": "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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for _, c in c_direct_neighbours.groupby('run'):\n", + " plt.plot(c.fd)\n", + "\n", + "for _, c in c_off_axis_neighbours.groupby('run'):\n", + " plt.plot(c.fd)\n", + "\n", + "plt.show()\n", + "\n", + "for _, run in c_direct_neighbours.groupby('run'):\n", + " plt.plot(run.N, run.cr)" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "for _, run in c_direct_neighbours.groupby('run'):\n", + " plt.plot(run.N, run.cr)" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 34, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/joshuacoles/Library/Caches/pypoetry/virtualenvs/data-analysis-B4Au_hWl-py3.10/lib/python3.10/site-packages/pandas/core/arraylike.py:402: RuntimeWarning: divide by zero encountered in log\n", + " result = getattr(ufunc, method)(*inputs, **kwargs)\n" + ] + }, + { + "data": { + "text/plain": "
", + "image/png": "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" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": "(array([1.68571639, 1.41007603]),\n array([[ 6.66524704e-07, -2.46788968e-06],\n [-2.46788968e-06, 9.25357395e-06]]))" + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "meaned_by_N = c_direct_neighbours.groupby('N').agg({'fd': ['mean', 'std']}) \\\n", + " .reset_index() \\\n", + " .replace([np.inf, -np.inf], np.nan)\n", + "\n", + "without_prefix = c_direct_neighbours[c_direct_neighbours.N > 200]\n", + "\n", + "p, pcov = scipy.optimize.curve_fit(linear, np.log(without_prefix.cr), np.log(without_prefix.N))\n", + "linear_extent = np.linspace(0, np.max(np.log(c_direct_neighbours.cr)))\n", + "\n", + "plt.scatter(np.log(c_direct_neighbours.cr), np.log(c_direct_neighbours.N), s=1, marker='.', color=\"tab:blue\")\n", + "plt.plot(linear_extent, linear(linear_extent, *p), color=\"tab:red\")\n", + "\n", + "plt.xlabel(\"$\\\\log r_{max}$\")\n", + "plt.ylabel(\"$\\\\log N$\")\n", + "plt.show()\n", + "p, pcov" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 50, + "outputs": [ + { + "data": { + "text/plain": "" + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "direct_meaned_by_N = c_direct_neighbours.groupby('N').agg({'fd': ['mean', 'std']}) \\\n", + " .reset_index() \\\n", + " .replace([np.inf, -np.inf], np.nan)\n", + "\n", + "offaxis_meaned_by_N = c_off_axis_neighbours.groupby('N').agg({'fd': ['mean', 'std']}) \\\n", + " .reset_index() \\\n", + " .replace([np.inf, -np.inf], np.nan)\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 10))\n", + "\n", + "def nc_fd(df, label, color=None):\n", + " plt.fill_between(\n", + " df.N,\n", + " # TODO Check error math here\n", + " (df['fd']['mean'] - df['fd']['std'] / np.sqrt(20)),\n", + " (df['fd']['mean'] + df['fd']['std'] / np.sqrt(20)),\n", + " color=color,\n", + " alpha=0.2,\n", + " label=f\"{label}, standard error band\"\n", + " )\n", + "\n", + " plt.plot(\n", + " df.N,\n", + " df['fd']['mean'],\n", + " color=color,\n", + " label=f\"{label}, fd mean\"\n", + " )\n", + "\n", + "\n", + "nc_fd(direct_meaned_by_N[:], label=\"Direct\", color=\"tab:blue\")\n", + "nc_fd(offaxis_meaned_by_N[:], label=\"Off-axis\", color=\"tab:green\")\n", + "\n", + "plt.plot([np.min(without_prefix.N), np.max(without_prefix.N)], [2.5, 2.5], color='tab:red', label='Theory')\n", + "plt.fill_between(without_prefix.N, 2.5 - 0.01, 2.5 + 0.01, alpha=0.2, color='tab:red', label='Theory error band')\n", + "plt.legend()" ], "metadata": { "collapsed": false diff --git a/notebooks/lib.py b/notebooks/lib.py index 38a1238..e039014 100644 --- a/notebooks/lib.py +++ b/notebooks/lib.py @@ -17,6 +17,17 @@ def read_xy(path: str): return df.replace([np.inf, -np.inf], np.nan).dropna() +def read_xyz(path: str): + df = pd.read_csv(path) + df['N'] = df.index + 1 + df['r'] = (df.x ** 2 + df.y ** 2 + df.z ** 2) ** 0.5 + df['cr'] = df.r.cummax() + df['fd'] = np.log(df.N) / np.log(df.cr) + df['run'] = os.path.splitext(Path(path).name)[0] + + return df + + def read_load(load_dir: str, reader=read_xy): paths = glob(f'{load_dir}/*.csv') return pd.concat([reader(path) for path in paths])