Stash

notebooks/minimal-viable-alteration.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 2,
    "metadata": {
     "collapsed": true
    },
@@ -17,7 +17,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 3,
    "outputs": [],
    "source": [
     "def read_xy(path: str):\n",
@@ -391,6 +391,47 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "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"
+     ]
+    }
+   ],
+   "source": [
+    "data = read_xy(\"/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/data-analysis/data/minimal-viable-alteration/2-5000.csv\")"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "        x   y     N           r          cr        fd\n0       0   0     1    0.000000    0.000000 -0.000000\n1       0  -1     2    1.000000    1.000000       inf\n2      -1   0     3    1.000000    1.000000       inf\n3      -1   1     4    1.414214    1.414214  4.000000\n4       0  -2     5    2.000000    2.000000  2.321928\n...   ...  ..   ...         ...         ...       ...\n4995   48  77  4996   90.735880  137.931142  1.728601\n4996  -12  84  4997   84.852814  137.931142  1.728642\n4997  -33  83  4998   89.319651  137.931142  1.728682\n4998 -118  20  4999  119.682914  137.931142  1.728723\n4999  132 -29  5000  135.148067  137.931142  1.728763\n\n[5000 rows x 6 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>x</th>\n      <th>y</th>\n      <th>N</th>\n      <th>r</th>\n      <th>cr</th>\n      <th>fd</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>-0.000000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>-1</td>\n      <td>2</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>inf</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>-1</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>inf</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-1</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1.414214</td>\n      <td>1.414214</td>\n      <td>4.000000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>-2</td>\n      <td>5</td>\n      <td>2.000000</td>\n      <td>2.000000</td>\n      <td>2.321928</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>4995</th>\n      <td>48</td>\n      <td>77</td>\n      <td>4996</td>\n      <td>90.735880</td>\n      <td>137.931142</td>\n      <td>1.728601</td>\n    </tr>\n    <tr>\n      <th>4996</th>\n      <td>-12</td>\n      <td>84</td>\n      <td>4997</td>\n      <td>84.852814</td>\n      <td>137.931142</td>\n      <td>1.728642</td>\n    </tr>\n    <tr>\n      <th>4997</th>\n      <td>-33</td>\n      <td>83</td>\n      <td>4998</td>\n      <td>89.319651</td>\n      <td>137.931142</td>\n      <td>1.728682</td>\n    </tr>\n    <tr>\n      <th>4998</th>\n      <td>-118</td>\n      <td>20</td>\n      <td>4999</td>\n      <td>119.682914</td>\n      <td>137.931142</td>\n      <td>1.728723</td>\n    </tr>\n    <tr>\n      <th>4999</th>\n      <td>132</td>\n      <td>-29</td>\n      <td>5000</td>\n      <td>135.148067</td>\n      <td>137.931142</td>\n      <td>1.728763</td>\n    </tr>\n  </tbody>\n</table>\n<p>5000 rows × 6 columns</p>\n</div>"
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.r"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

notebooks/rust-3d.py

@@ -0,0 +1,57 @@
+from pathlib import Path
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import scipy
+from glob import glob
+
+
+def read_3d(path: str):
+    df = pd.read_csv(path, skipinitialspace=True)
+    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)
+
+    return df
+
+
+def read_load_dir(load_dir: str):
+    paths = glob(f'{load_dir}/*.csv')
+    return [read_3d(path) for path in paths]
+
+
+def convergent_tail_index(series, tol):
+    diffs = np.abs(np.ediff1d(series))
+    for i in range(0, len(diffs)):
+        if np.max(diffs[i:]) <= tol:
+            return i
+
+    # No convergence found
+    return None
+
+
+def mean_of_tail(series, tol=0.05):
+    tail_index = convergent_tail_index(series, tol)
+    if tail_index is None:
+        raise Exception("No convergence found.")
+
+    return np.mean(series[tail_index:])
+
+
+def fd_stats(dfs):
+    fds = [mean_of_tail(df.fd, 0.01) for df in dfs]
+    fds_clean = [f for f in fds if f < np.inf]
+    return np.mean(fds_clean), np.std(fds_clean)
+
+df = read_3d("/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/c-codebase/out-2.csv")
+print(mean_of_tail(df.fd, 0.01))
+
+df = read_3d("/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/c-codebase/out-26n.csv")
+print(mean_of_tail(df.fd, 0.01))
+
+df = read_3d("/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/c-codebase/out-26nn.csv")
+print(mean_of_tail(df.fd, 0.01))
+
+# dfs = read_load_dir("/Users/joshuacoles/Developer/checkouts/jc3091/CompB DLA/data-analysis/data/rust-3d-1/1")
+# print(fd_stats(dfs))

tools/3d-things.py

@@ -0,0 +1,4 @@
+for i in [-1, 0, 1]:
+    for j in [-1, 0, 1]:
+        for k in [-1, 0, 1]:
+            print(f"{i}, {j}, {k},")

tools/obtain-all-executables.bash

@@ -4,3 +4,5 @@ CMD="$(dirname "$(realpath "$0")")/obtain-executable.bash"
 
 "$CMD" minimal-viable-alteration models/minimal-viable-alteration
 "$CMD" stick-probability models/stick-probability
+"$CMD" 3d-direct-neighbours models/c-3d-direct-neighbours
+"$CMD" 3d-off-axis-neighbours models/c-3d-off-axis-neighbours