joshuacoles/compb-dla-data-analysis
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
a56f3158cb
compb-dla-data-analysis/notebooks/3d.ipynb
Joshua Coles a56f3158cb Stash
2023-03-17 14:55:33 +00:00

604 lines
172 KiB
Plaintext
Raw Blame History

{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import scipy\n",
"from glob import glob"
]
},
{
"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": "<Figure size 640x480 with 1 Axes>",
"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": "<Figure size 640x480 with 1 Axes>",
"image/png": "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"
},
"metadata": {},
"output_type": "display_data"
}
],
"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)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [
"read_"
],
"metadata": {
"collapsed": false
}
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Reference in New Issue View Git Blame Copy Permalink