diff --git a/nbs/99_manuscript/time_test/07-time_test-plot.ipynb b/nbs/99_manuscript/time_test/07-time_test-plot.ipynb
index 9d044c7b..bf1924bf 100644
--- a/nbs/99_manuscript/time_test/07-time_test-plot.ipynb
+++ b/nbs/99_manuscript/time_test/07-time_test-plot.ipynb
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@@ -353,36 +407,36 @@
"
0 | \n",
" 100 | \n",
" p-1 | \n",
- " 0.000098 | \n",
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+ " 0.000096 | \n",
+ " -0.014058 | \n",
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" \n",
" 1 | \n",
" 100 | \n",
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- " 0.000035 | \n",
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+ " 0.000041 | \n",
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" 3 | \n",
" 100 | \n",
" p-1 | \n",
- " 0.000031 | \n",
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" 100 | \n",
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@@ -390,11 +444,11 @@
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@@ -411,11 +465,17 @@
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@@ -425,7 +485,8 @@
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"array(['p-1', 's-1', 'cm-1', 'mic_e-1', 'mic-1', 'p-3', 's-3', 'cm-3',\n",
- " 'mic_e-3', 'mic-3'], dtype=object)"
+ " 'mic_e-3', 'mic-3', 'p-6', 's-6', 'cm-6', 'mic_e-6', 'mic-6'],\n",
+ " dtype=object)"
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@@ -442,10 +503,10 @@
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@@ -459,11 +520,17 @@
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@@ -483,6 +550,11 @@
" \"cm-3\": \"CCC (3 cores)\",\n",
" \"mic-3\": \"MIC (3 cores)\",\n",
" \"mic_e-3\": \"MICe (3 cores)\",\n",
+ " \"p-6\": \"Pearson (6 cores)\",\n",
+ " \"s-6\": \"Spearman (6 cores)\",\n",
+ " \"cm-6\": \"CCC (6 cores)\",\n",
+ " \"mic-6\": \"MIC (6 cores)\",\n",
+ " \"mic_e-6\": \"MICe (6 cores)\",\n",
" }\n",
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@@ -493,11 +565,17 @@
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@@ -565,36 +649,36 @@
" 0 | \n",
" 100 | \n",
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+ " 0.000096 | \n",
+ " -0.014058 | \n",
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" 1 | \n",
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+ " -0.019761 | \n",
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\n",
" \n",
" 2 | \n",
" 100 | \n",
" Pearson (1 core) | \n",
- " 0.000037 | \n",
- " 0.004494 | \n",
+ " 0.000041 | \n",
+ " -0.274154 | \n",
"
\n",
" \n",
" 3 | \n",
" 100 | \n",
" Pearson (1 core) | \n",
- " 0.000031 | \n",
- " -0.035394 | \n",
+ " 0.000034 | \n",
+ " -0.071098 | \n",
"
\n",
" \n",
" 4 | \n",
" 100 | \n",
" Pearson (1 core) | \n",
- " 0.000030 | \n",
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+ " 0.000032 | \n",
+ " 0.016989 | \n",
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@@ -602,11 +686,11 @@
],
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" data_size method time sim\n",
- "0 100 Pearson (1 core) 0.000098 -0.085291\n",
- "1 100 Pearson (1 core) 0.000035 -0.174309\n",
- "2 100 Pearson (1 core) 0.000037 0.004494\n",
- "3 100 Pearson (1 core) 0.000031 -0.035394\n",
- "4 100 Pearson (1 core) 0.000030 0.066687"
+ "0 100 Pearson (1 core) 0.000096 -0.014058\n",
+ "1 100 Pearson (1 core) 0.000038 -0.019761\n",
+ "2 100 Pearson (1 core) 0.000041 -0.274154\n",
+ "3 100 Pearson (1 core) 0.000034 -0.071098\n",
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+ "start_time": "2023-09-11T17:28:48.068354",
"status": "completed"
},
"tags": []
@@ -640,11 +724,17 @@
"execution_count": 14,
"id": "3eafa2a7-c008-46b9-9119-a745fe873535",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.075562Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.075481Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.076854Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.076707Z"
+ },
"papermill": {
- "duration": 0.004096,
- "end_time": "2023-09-11T14:41:55.609966",
+ "duration": 0.004353,
+ "end_time": "2023-09-11T17:28:48.077291",
"exception": false,
- "start_time": "2023-09-11T14:41:55.605870",
+ "start_time": "2023-09-11T17:28:48.072938",
"status": "completed"
},
"tags": []
@@ -659,11 +749,17 @@
"execution_count": 15,
"id": "e1279b36-295c-45d2-a2f1-0388161c724f",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.082121Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.082034Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.132615Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.132405Z"
+ },
"papermill": {
- "duration": 0.04498,
- "end_time": "2023-09-11T14:41:55.657149",
+ "duration": 0.05359,
+ "end_time": "2023-09-11T17:28:48.133198",
"exception": false,
- "start_time": "2023-09-11T14:41:55.612169",
+ "start_time": "2023-09-11T17:28:48.079608",
"status": "completed"
},
"tags": []
@@ -715,530 +811,629 @@
" \n",
" \n",
" \n",
- " 100 | \n",
+ " 100 | \n",
" CCC (1 core) | \n",
" 1000.0 | \n",
- " 0.000641 | \n",
- " 0.000025 | \n",
- " 0.000623 | \n",
- " 0.000631 | \n",
- " 0.000635 | \n",
- " 0.000640 | \n",
- " 0.001048 | \n",
+ " 0.000700 | \n",
+ " 0.000022 | \n",
+ " 0.000681 | \n",
+ " 0.000690 | \n",
+ " 0.000693 | \n",
+ " 0.000700 | \n",
+ " 0.000963 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 1000.0 | \n",
- " 0.001110 | \n",
- " 0.000416 | \n",
- " 0.000853 | \n",
- " 0.000913 | \n",
- " 0.000944 | \n",
- " 0.001109 | \n",
- " 0.004993 | \n",
+ " 0.001244 | \n",
+ " 0.000507 | \n",
+ " 0.000927 | \n",
+ " 0.000983 | \n",
+ " 0.001027 | \n",
+ " 0.001304 | \n",
+ " 0.006013 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 1000.0 | \n",
+ " 0.002549 | \n",
+ " 0.001363 | \n",
+ " 0.001193 | \n",
+ " 0.001497 | \n",
+ " 0.002142 | \n",
+ " 0.003099 | \n",
+ " 0.007773 | \n",
"
\n",
" \n",
" MIC (1 core) | \n",
" 1000.0 | \n",
- " 0.000724 | \n",
- " 0.000026 | \n",
- " 0.000635 | \n",
- " 0.000707 | \n",
" 0.000723 | \n",
- " 0.000741 | \n",
- " 0.000879 | \n",
+ " 0.000027 | \n",
+ " 0.000652 | \n",
+ " 0.000704 | \n",
+ " 0.000723 | \n",
+ " 0.000743 | \n",
+ " 0.000821 | \n",
"
\n",
" \n",
" MICe (1 core) | \n",
" 1000.0 | \n",
- " 0.000675 | \n",
+ " 0.000674 | \n",
" 0.000022 | \n",
- " 0.000604 | \n",
+ " 0.000620 | \n",
" 0.000659 | \n",
- " 0.000676 | \n",
- " 0.000691 | \n",
- " 0.000740 | \n",
+ " 0.000673 | \n",
+ " 0.000689 | \n",
+ " 0.000756 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 1000.0 | \n",
- " 0.000031 | \n",
- " 0.000002 | \n",
- " 0.000028 | \n",
+ " 0.000033 | \n",
+ " 0.000005 | \n",
" 0.000030 | \n",
" 0.000031 | \n",
- " 0.000031 | \n",
- " 0.000098 | \n",
+ " 0.000032 | \n",
+ " 0.000033 | \n",
+ " 0.000145 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 1000.0 | \n",
+ " 0.000228 | \n",
+ " 0.000011 | \n",
" 0.000217 | \n",
- " 0.000017 | \n",
- " 0.000205 | \n",
- " 0.000213 | \n",
- " 0.000215 | \n",
- " 0.000218 | \n",
- " 0.000483 | \n",
+ " 0.000224 | \n",
+ " 0.000226 | \n",
+ " 0.000229 | \n",
+ " 0.000393 | \n",
"
\n",
" \n",
- " 500 | \n",
+ " 500 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 0.000932 | \n",
- " 0.000034 | \n",
- " 0.000911 | \n",
- " 0.000918 | \n",
- " 0.000921 | \n",
- " 0.000927 | \n",
- " 0.001028 | \n",
+ " 0.001014 | \n",
+ " 0.000037 | \n",
+ " 0.000985 | \n",
+ " 0.000997 | \n",
+ " 0.001006 | \n",
+ " 0.001010 | \n",
+ " 0.001116 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 0.001258 | \n",
- " 0.000292 | \n",
- " 0.001080 | \n",
- " 0.001103 | \n",
- " 0.001132 | \n",
- " 0.001268 | \n",
- " 0.002005 | \n",
+ " 0.001573 | \n",
+ " 0.000316 | \n",
+ " 0.001127 | \n",
+ " 0.001449 | \n",
+ " 0.001490 | \n",
+ " 0.001747 | \n",
+ " 0.002150 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.001548 | \n",
+ " 0.000512 | \n",
+ " 0.001313 | \n",
+ " 0.001332 | \n",
+ " 0.001356 | \n",
+ " 0.001383 | \n",
+ " 0.002961 | \n",
"
\n",
" \n",
" MIC (1 core) | \n",
" 10.0 | \n",
- " 0.011612 | \n",
- " 0.000258 | \n",
- " 0.011189 | \n",
- " 0.011426 | \n",
- " 0.011671 | \n",
- " 0.011797 | \n",
- " 0.011964 | \n",
+ " 0.011557 | \n",
+ " 0.000165 | \n",
+ " 0.011262 | \n",
+ " 0.011459 | \n",
+ " 0.011552 | \n",
+ " 0.011663 | \n",
+ " 0.011803 | \n",
"
\n",
" \n",
" MICe (1 core) | \n",
" 10.0 | \n",
- " 0.008890 | \n",
- " 0.000098 | \n",
- " 0.008685 | \n",
- " 0.008851 | \n",
- " 0.008900 | \n",
- " 0.008963 | \n",
- " 0.008996 | \n",
+ " 0.008868 | \n",
+ " 0.000115 | \n",
+ " 0.008696 | \n",
+ " 0.008778 | \n",
+ " 0.008870 | \n",
+ " 0.008926 | \n",
+ " 0.009037 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.000041 | \n",
- " 0.000013 | \n",
+ " 0.000039 | \n",
+ " 0.000014 | \n",
" 0.000033 | \n",
" 0.000034 | \n",
" 0.000035 | \n",
- " 0.000042 | \n",
- " 0.000075 | \n",
+ " 0.000036 | \n",
+ " 0.000079 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.000273 | \n",
- " 0.000023 | \n",
- " 0.000260 | \n",
- " 0.000264 | \n",
+ " 0.000280 | \n",
+ " 0.000022 | \n",
" 0.000266 | \n",
- " 0.000268 | \n",
- " 0.000336 | \n",
+ " 0.000271 | \n",
+ " 0.000272 | \n",
+ " 0.000278 | \n",
+ " 0.000340 | \n",
"
\n",
" \n",
- " 1000 | \n",
+ " 1000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 0.001398 | \n",
- " 0.000047 | \n",
- " 0.001332 | \n",
- " 0.001362 | \n",
- " 0.001389 | \n",
- " 0.001438 | \n",
- " 0.001465 | \n",
+ " 0.001520 | \n",
+ " 0.000021 | \n",
+ " 0.001473 | \n",
+ " 0.001508 | \n",
+ " 0.001526 | \n",
+ " 0.001532 | \n",
+ " 0.001544 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 0.001564 | \n",
- " 0.000341 | \n",
- " 0.001332 | \n",
- " 0.001383 | \n",
- " 0.001409 | \n",
- " 0.001685 | \n",
- " 0.002411 | \n",
+ " 0.001457 | \n",
+ " 0.000246 | \n",
+ " 0.001307 | \n",
+ " 0.001323 | \n",
+ " 0.001328 | \n",
+ " 0.001477 | \n",
+ " 0.002081 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.001665 | \n",
+ " 0.000511 | \n",
+ " 0.001367 | \n",
+ " 0.001426 | \n",
+ " 0.001455 | \n",
+ " 0.001562 | \n",
+ " 0.003018 | \n",
"
\n",
" \n",
" MIC (1 core) | \n",
" 10.0 | \n",
- " 0.037072 | \n",
- " 0.000457 | \n",
- " 0.036463 | \n",
- " 0.036848 | \n",
- " 0.036995 | \n",
- " 0.037238 | \n",
- " 0.037937 | \n",
+ " 0.037375 | \n",
+ " 0.000440 | \n",
+ " 0.036806 | \n",
+ " 0.037103 | \n",
+ " 0.037231 | \n",
+ " 0.037689 | \n",
+ " 0.038242 | \n",
"
\n",
" \n",
" MICe (1 core) | \n",
" 10.0 | \n",
- " 0.024851 | \n",
- " 0.000125 | \n",
- " 0.024646 | \n",
- " 0.024754 | \n",
- " 0.024871 | \n",
- " 0.024943 | \n",
- " 0.025019 | \n",
+ " 0.024938 | \n",
+ " 0.000247 | \n",
+ " 0.024583 | \n",
+ " 0.024758 | \n",
+ " 0.024965 | \n",
+ " 0.025059 | \n",
+ " 0.025344 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.000040 | \n",
- " 0.000017 | \n",
- " 0.000033 | \n",
- " 0.000034 | \n",
- " 0.000035 | \n",
+ " 0.000041 | \n",
+ " 0.000013 | \n",
" 0.000035 | \n",
- " 0.000087 | \n",
+ " 0.000036 | \n",
+ " 0.000037 | \n",
+ " 0.000037 | \n",
+ " 0.000077 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.000319 | \n",
- " 0.000024 | \n",
- " 0.000301 | \n",
- " 0.000304 | \n",
+ " 0.000318 | \n",
+ " 0.000009 | \n",
" 0.000310 | \n",
- " 0.000321 | \n",
- " 0.000376 | \n",
+ " 0.000312 | \n",
+ " 0.000313 | \n",
+ " 0.000323 | \n",
+ " 0.000337 | \n",
"
\n",
" \n",
- " 5000 | \n",
+ " 5000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 0.006685 | \n",
- " 0.000091 | \n",
- " 0.006585 | \n",
- " 0.006639 | \n",
- " 0.006668 | \n",
- " 0.006692 | \n",
- " 0.006896 | \n",
+ " 0.006788 | \n",
+ " 0.000060 | \n",
+ " 0.006672 | \n",
+ " 0.006755 | \n",
+ " 0.006799 | \n",
+ " 0.006819 | \n",
+ " 0.006884 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 0.004830 | \n",
- " 0.001123 | \n",
- " 0.003883 | \n",
- " 0.004018 | \n",
- " 0.004404 | \n",
- " 0.005185 | \n",
- " 0.007427 | \n",
+ " 0.003255 | \n",
+ " 0.000450 | \n",
+ " 0.002939 | \n",
+ " 0.003033 | \n",
+ " 0.003085 | \n",
+ " 0.003135 | \n",
+ " 0.004291 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.002966 | \n",
+ " 0.000383 | \n",
+ " 0.002287 | \n",
+ " 0.002790 | \n",
+ " 0.002943 | \n",
+ " 0.003094 | \n",
+ " 0.003766 | \n",
"
\n",
" \n",
" MIC (1 core) | \n",
" 10.0 | \n",
- " 0.510705 | \n",
- " 0.001836 | \n",
- " 0.507880 | \n",
- " 0.509280 | \n",
- " 0.510705 | \n",
- " 0.512287 | \n",
- " 0.513345 | \n",
+ " 0.511068 | \n",
+ " 0.002535 | \n",
+ " 0.508058 | \n",
+ " 0.509063 | \n",
+ " 0.511166 | \n",
+ " 0.511689 | \n",
+ " 0.516697 | \n",
"
\n",
" \n",
" MICe (1 core) | \n",
" 10.0 | \n",
- " 0.228000 | \n",
- " 0.000698 | \n",
- " 0.227258 | \n",
- " 0.227605 | \n",
- " 0.227923 | \n",
- " 0.228074 | \n",
- " 0.229758 | \n",
+ " 0.228089 | \n",
+ " 0.000724 | \n",
+ " 0.226995 | \n",
+ " 0.227600 | \n",
+ " 0.227992 | \n",
+ " 0.228596 | \n",
+ " 0.229304 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.000050 | \n",
- " 0.000012 | \n",
- " 0.000044 | \n",
+ " 0.000052 | \n",
+ " 0.000013 | \n",
" 0.000045 | \n",
" 0.000046 | \n",
- " 0.000049 | \n",
- " 0.000084 | \n",
+ " 0.000047 | \n",
+ " 0.000051 | \n",
+ " 0.000088 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.000661 | \n",
- " 0.000026 | \n",
- " 0.000634 | \n",
- " 0.000651 | \n",
+ " 0.000672 | \n",
+ " 0.000034 | \n",
+ " 0.000647 | \n",
" 0.000657 | \n",
- " 0.000660 | \n",
- " 0.000731 | \n",
+ " 0.000661 | \n",
+ " 0.000673 | \n",
+ " 0.000766 | \n",
"
\n",
" \n",
- " 10000 | \n",
+ " 10000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 0.014375 | \n",
- " 0.000187 | \n",
- " 0.014085 | \n",
- " 0.014274 | \n",
- " 0.014354 | \n",
- " 0.014452 | \n",
- " 0.014767 | \n",
+ " 0.013911 | \n",
+ " 0.000139 | \n",
+ " 0.013680 | \n",
+ " 0.013838 | \n",
+ " 0.013906 | \n",
+ " 0.014009 | \n",
+ " 0.014104 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 0.008727 | \n",
- " 0.001044 | \n",
- " 0.007567 | \n",
- " 0.008029 | \n",
- " 0.008367 | \n",
- " 0.009145 | \n",
- " 0.010723 | \n",
+ " 0.006295 | \n",
+ " 0.000917 | \n",
+ " 0.005360 | \n",
+ " 0.005587 | \n",
+ " 0.006078 | \n",
+ " 0.006806 | \n",
+ " 0.008178 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.003929 | \n",
+ " 0.000618 | \n",
+ " 0.003467 | \n",
+ " 0.003497 | \n",
+ " 0.003648 | \n",
+ " 0.004185 | \n",
+ " 0.005180 | \n",
"
\n",
" \n",
" MIC (1 core) | \n",
" 10.0 | \n",
- " 1.592554 | \n",
- " 0.010670 | \n",
- " 1.575866 | \n",
- " 1.587393 | \n",
- " 1.593111 | \n",
- " 1.599259 | \n",
- " 1.610753 | \n",
+ " 1.604225 | \n",
+ " 0.005336 | \n",
+ " 1.594926 | \n",
+ " 1.600615 | \n",
+ " 1.606042 | \n",
+ " 1.607014 | \n",
+ " 1.610589 | \n",
"
\n",
" \n",
" MICe (1 core) | \n",
" 10.0 | \n",
- " 0.572581 | \n",
- " 0.001167 | \n",
- " 0.570966 | \n",
- " 0.571873 | \n",
- " 0.572358 | \n",
- " 0.573227 | \n",
- " 0.574736 | \n",
+ " 0.571711 | \n",
+ " 0.001157 | \n",
+ " 0.569632 | \n",
+ " 0.570982 | \n",
+ " 0.571727 | \n",
+ " 0.572616 | \n",
+ " 0.573363 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.000064 | \n",
+ " 0.000066 | \n",
" 0.000015 | \n",
- " 0.000056 | \n",
" 0.000058 | \n",
" 0.000059 | \n",
- " 0.000063 | \n",
+ " 0.000060 | \n",
+ " 0.000062 | \n",
" 0.000106 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.001158 | \n",
- " 0.000027 | \n",
+ " 0.001157 | \n",
+ " 0.000035 | \n",
" 0.001128 | \n",
- " 0.001147 | \n",
- " 0.001153 | \n",
- " 0.001155 | \n",
- " 0.001231 | \n",
+ " 0.001146 | \n",
+ " 0.001149 | \n",
+ " 0.001152 | \n",
+ " 0.001253 | \n",
"
\n",
" \n",
- " 50000 | \n",
+ " 50000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 0.082006 | \n",
- " 0.000460 | \n",
- " 0.081297 | \n",
- " 0.081652 | \n",
- " 0.082052 | \n",
- " 0.082178 | \n",
- " 0.082773 | \n",
+ " 0.080398 | \n",
+ " 0.001983 | \n",
+ " 0.079082 | \n",
+ " 0.079508 | \n",
+ " 0.079843 | \n",
+ " 0.080196 | \n",
+ " 0.085907 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 0.043132 | \n",
- " 0.000550 | \n",
- " 0.042416 | \n",
- " 0.042617 | \n",
- " 0.043109 | \n",
- " 0.043533 | \n",
- " 0.043936 | \n",
+ " 0.028311 | \n",
+ " 0.000604 | \n",
+ " 0.027584 | \n",
+ " 0.027964 | \n",
+ " 0.028092 | \n",
+ " 0.028674 | \n",
+ " 0.029486 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.016299 | \n",
+ " 0.001369 | \n",
+ " 0.015058 | \n",
+ " 0.015353 | \n",
+ " 0.015880 | \n",
+ " 0.016453 | \n",
+ " 0.019071 | \n",
"
\n",
" \n",
" MICe (1 core) | \n",
" 10.0 | \n",
- " 4.843016 | \n",
- " 0.005246 | \n",
- " 4.832381 | \n",
- " 4.842152 | \n",
- " 4.843082 | \n",
- " 4.846897 | \n",
- " 4.849092 | \n",
+ " 4.869085 | \n",
+ " 0.007489 | \n",
+ " 4.855632 | \n",
+ " 4.865442 | \n",
+ " 4.869943 | \n",
+ " 4.874358 | \n",
+ " 4.877798 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.000182 | \n",
- " 0.000026 | \n",
- " 0.000163 | \n",
- " 0.000165 | \n",
- " 0.000169 | \n",
- " 0.000190 | \n",
- " 0.000248 | \n",
+ " 0.000216 | \n",
+ " 0.000107 | \n",
+ " 0.000164 | \n",
+ " 0.000168 | \n",
+ " 0.000181 | \n",
+ " 0.000200 | \n",
+ " 0.000515 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.006136 | \n",
- " 0.000160 | \n",
- " 0.005979 | \n",
- " 0.006003 | \n",
- " 0.006108 | \n",
- " 0.006233 | \n",
- " 0.006459 | \n",
+ " 0.006197 | \n",
+ " 0.000197 | \n",
+ " 0.005992 | \n",
+ " 0.006033 | \n",
+ " 0.006152 | \n",
+ " 0.006320 | \n",
+ " 0.006609 | \n",
"
\n",
" \n",
- " 100000 | \n",
+ " 100000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 0.175137 | \n",
- " 0.000671 | \n",
- " 0.174232 | \n",
- " 0.174719 | \n",
- " 0.175010 | \n",
- " 0.175541 | \n",
- " 0.176207 | \n",
+ " 0.169880 | \n",
+ " 0.004015 | \n",
+ " 0.166682 | \n",
+ " 0.168021 | \n",
+ " 0.168410 | \n",
+ " 0.170365 | \n",
+ " 0.180720 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 0.090907 | \n",
- " 0.001929 | \n",
- " 0.088514 | \n",
- " 0.089994 | \n",
- " 0.090318 | \n",
- " 0.091081 | \n",
- " 0.095571 | \n",
+ " 0.059719 | \n",
+ " 0.001602 | \n",
+ " 0.057553 | \n",
+ " 0.058915 | \n",
+ " 0.059804 | \n",
+ " 0.060159 | \n",
+ " 0.063151 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.032267 | \n",
+ " 0.001531 | \n",
+ " 0.031124 | \n",
+ " 0.031255 | \n",
+ " 0.031849 | \n",
+ " 0.032394 | \n",
+ " 0.036092 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.000417 | \n",
- " 0.000249 | \n",
- " 0.000313 | \n",
- " 0.000318 | \n",
- " 0.000320 | \n",
- " 0.000336 | \n",
- " 0.001109 | \n",
+ " 0.000487 | \n",
+ " 0.000159 | \n",
+ " 0.000307 | \n",
+ " 0.000354 | \n",
+ " 0.000430 | \n",
+ " 0.000628 | \n",
+ " 0.000748 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.011882 | \n",
- " 0.000409 | \n",
- " 0.011642 | \n",
- " 0.011671 | \n",
- " 0.011746 | \n",
- " 0.011826 | \n",
- " 0.012993 | \n",
+ " 0.013500 | \n",
+ " 0.000201 | \n",
+ " 0.013329 | \n",
+ " 0.013438 | \n",
+ " 0.013453 | \n",
+ " 0.013498 | \n",
+ " 0.014044 | \n",
"
\n",
" \n",
- " 1000000 | \n",
+ " 1000000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 2.296490 | \n",
- " 0.065356 | \n",
- " 2.219242 | \n",
- " 2.255166 | \n",
- " 2.270925 | \n",
- " 2.352809 | \n",
- " 2.407563 | \n",
+ " 2.374975 | \n",
+ " 0.028419 | \n",
+ " 2.312148 | \n",
+ " 2.365298 | \n",
+ " 2.373448 | \n",
+ " 2.391214 | \n",
+ " 2.421613 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 1.275980 | \n",
- " 0.008927 | \n",
- " 1.265975 | \n",
- " 1.268516 | \n",
- " 1.273530 | \n",
- " 1.282357 | \n",
- " 1.291811 | \n",
+ " 0.908605 | \n",
+ " 0.005742 | \n",
+ " 0.900301 | \n",
+ " 0.904757 | \n",
+ " 0.906894 | \n",
+ " 0.912644 | \n",
+ " 0.917324 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 0.536444 | \n",
+ " 0.003756 | \n",
+ " 0.531334 | \n",
+ " 0.534186 | \n",
+ " 0.536558 | \n",
+ " 0.538229 | \n",
+ " 0.543839 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.007408 | \n",
- " 0.001242 | \n",
- " 0.006026 | \n",
- " 0.006245 | \n",
- " 0.007732 | \n",
- " 0.007757 | \n",
- " 0.009899 | \n",
+ " 0.008685 | \n",
+ " 0.001105 | \n",
+ " 0.007643 | \n",
+ " 0.007773 | \n",
+ " 0.008315 | \n",
+ " 0.009787 | \n",
+ " 0.010285 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 0.172611 | \n",
- " 0.001251 | \n",
- " 0.170362 | \n",
- " 0.171784 | \n",
- " 0.172625 | \n",
- " 0.173215 | \n",
- " 0.174503 | \n",
+ " 0.175823 | \n",
+ " 0.003502 | \n",
+ " 0.171767 | \n",
+ " 0.173853 | \n",
+ " 0.175242 | \n",
+ " 0.176227 | \n",
+ " 0.183476 | \n",
"
\n",
" \n",
- " 10000000 | \n",
+ " 10000000 | \n",
" CCC (1 core) | \n",
" 10.0 | \n",
- " 40.157600 | \n",
- " 0.173438 | \n",
- " 39.843292 | \n",
- " 40.088204 | \n",
- " 40.151353 | \n",
- " 40.259280 | \n",
- " 40.429066 | \n",
+ " 42.292236 | \n",
+ " 0.110967 | \n",
+ " 42.121878 | \n",
+ " 42.227472 | \n",
+ " 42.277608 | \n",
+ " 42.331981 | \n",
+ " 42.507820 | \n",
"
\n",
" \n",
" CCC (3 cores) | \n",
" 10.0 | \n",
- " 21.885837 | \n",
- " 0.103896 | \n",
- " 21.705721 | \n",
- " 21.845108 | \n",
- " 21.876476 | \n",
- " 21.949155 | \n",
- " 22.039508 | \n",
+ " 15.907279 | \n",
+ " 0.039598 | \n",
+ " 15.831335 | \n",
+ " 15.897137 | \n",
+ " 15.911772 | \n",
+ " 15.932641 | \n",
+ " 15.959610 | \n",
+ "
\n",
+ " \n",
+ " CCC (6 cores) | \n",
+ " 10.0 | \n",
+ " 9.102648 | \n",
+ " 0.049330 | \n",
+ " 8.999230 | \n",
+ " 9.080815 | \n",
+ " 9.099392 | \n",
+ " 9.143470 | \n",
+ " 9.161670 | \n",
"
\n",
" \n",
" Pearson (1 core) | \n",
" 10.0 | \n",
- " 0.094267 | \n",
- " 0.000529 | \n",
- " 0.093734 | \n",
- " 0.093855 | \n",
- " 0.094105 | \n",
- " 0.094493 | \n",
- " 0.095369 | \n",
+ " 0.094251 | \n",
+ " 0.000763 | \n",
+ " 0.093191 | \n",
+ " 0.093785 | \n",
+ " 0.094238 | \n",
+ " 0.094759 | \n",
+ " 0.095648 | \n",
"
\n",
" \n",
" Spearman (1 core) | \n",
" 10.0 | \n",
- " 2.954011 | \n",
- " 0.010732 | \n",
- " 2.941881 | \n",
- " 2.946117 | \n",
- " 2.951748 | \n",
- " 2.962198 | \n",
- " 2.971911 | \n",
+ " 2.952096 | \n",
+ " 0.007759 | \n",
+ " 2.937117 | \n",
+ " 2.950214 | \n",
+ " 2.952338 | \n",
+ " 2.954561 | \n",
+ " 2.967408 | \n",
"
\n",
" \n",
"\n",
@@ -1247,103 +1442,121 @@
"text/plain": [
" count mean std min \\\n",
"data_size method \n",
- "100 CCC (1 core) 1000.0 0.000641 0.000025 0.000623 \n",
- " CCC (3 cores) 1000.0 0.001110 0.000416 0.000853 \n",
- " MIC (1 core) 1000.0 0.000724 0.000026 0.000635 \n",
- " MICe (1 core) 1000.0 0.000675 0.000022 0.000604 \n",
- " Pearson (1 core) 1000.0 0.000031 0.000002 0.000028 \n",
- " Spearman (1 core) 1000.0 0.000217 0.000017 0.000205 \n",
- "500 CCC (1 core) 10.0 0.000932 0.000034 0.000911 \n",
- " CCC (3 cores) 10.0 0.001258 0.000292 0.001080 \n",
- " MIC (1 core) 10.0 0.011612 0.000258 0.011189 \n",
- " MICe (1 core) 10.0 0.008890 0.000098 0.008685 \n",
- " Pearson (1 core) 10.0 0.000041 0.000013 0.000033 \n",
- " Spearman (1 core) 10.0 0.000273 0.000023 0.000260 \n",
- "1000 CCC (1 core) 10.0 0.001398 0.000047 0.001332 \n",
- " CCC (3 cores) 10.0 0.001564 0.000341 0.001332 \n",
- " MIC (1 core) 10.0 0.037072 0.000457 0.036463 \n",
- " MICe (1 core) 10.0 0.024851 0.000125 0.024646 \n",
- " Pearson (1 core) 10.0 0.000040 0.000017 0.000033 \n",
- " Spearman (1 core) 10.0 0.000319 0.000024 0.000301 \n",
- "5000 CCC (1 core) 10.0 0.006685 0.000091 0.006585 \n",
- " CCC (3 cores) 10.0 0.004830 0.001123 0.003883 \n",
- " MIC (1 core) 10.0 0.510705 0.001836 0.507880 \n",
- " MICe (1 core) 10.0 0.228000 0.000698 0.227258 \n",
- " Pearson (1 core) 10.0 0.000050 0.000012 0.000044 \n",
- " Spearman (1 core) 10.0 0.000661 0.000026 0.000634 \n",
- "10000 CCC (1 core) 10.0 0.014375 0.000187 0.014085 \n",
- " CCC (3 cores) 10.0 0.008727 0.001044 0.007567 \n",
- " MIC (1 core) 10.0 1.592554 0.010670 1.575866 \n",
- " MICe (1 core) 10.0 0.572581 0.001167 0.570966 \n",
- " Pearson (1 core) 10.0 0.000064 0.000015 0.000056 \n",
- " Spearman (1 core) 10.0 0.001158 0.000027 0.001128 \n",
- "50000 CCC (1 core) 10.0 0.082006 0.000460 0.081297 \n",
- " CCC (3 cores) 10.0 0.043132 0.000550 0.042416 \n",
- " MICe (1 core) 10.0 4.843016 0.005246 4.832381 \n",
- " Pearson (1 core) 10.0 0.000182 0.000026 0.000163 \n",
- " Spearman (1 core) 10.0 0.006136 0.000160 0.005979 \n",
- "100000 CCC (1 core) 10.0 0.175137 0.000671 0.174232 \n",
- " CCC (3 cores) 10.0 0.090907 0.001929 0.088514 \n",
- " Pearson (1 core) 10.0 0.000417 0.000249 0.000313 \n",
- " Spearman (1 core) 10.0 0.011882 0.000409 0.011642 \n",
- "1000000 CCC (1 core) 10.0 2.296490 0.065356 2.219242 \n",
- " CCC (3 cores) 10.0 1.275980 0.008927 1.265975 \n",
- " Pearson (1 core) 10.0 0.007408 0.001242 0.006026 \n",
- " Spearman (1 core) 10.0 0.172611 0.001251 0.170362 \n",
- "10000000 CCC (1 core) 10.0 40.157600 0.173438 39.843292 \n",
- " CCC (3 cores) 10.0 21.885837 0.103896 21.705721 \n",
- " Pearson (1 core) 10.0 0.094267 0.000529 0.093734 \n",
- " Spearman (1 core) 10.0 2.954011 0.010732 2.941881 \n",
+ "100 CCC (1 core) 1000.0 0.000700 0.000022 0.000681 \n",
+ " CCC (3 cores) 1000.0 0.001244 0.000507 0.000927 \n",
+ " CCC (6 cores) 1000.0 0.002549 0.001363 0.001193 \n",
+ " MIC (1 core) 1000.0 0.000723 0.000027 0.000652 \n",
+ " MICe (1 core) 1000.0 0.000674 0.000022 0.000620 \n",
+ " Pearson (1 core) 1000.0 0.000033 0.000005 0.000030 \n",
+ " Spearman (1 core) 1000.0 0.000228 0.000011 0.000217 \n",
+ "500 CCC (1 core) 10.0 0.001014 0.000037 0.000985 \n",
+ " CCC (3 cores) 10.0 0.001573 0.000316 0.001127 \n",
+ " CCC (6 cores) 10.0 0.001548 0.000512 0.001313 \n",
+ " MIC (1 core) 10.0 0.011557 0.000165 0.011262 \n",
+ " MICe (1 core) 10.0 0.008868 0.000115 0.008696 \n",
+ " Pearson (1 core) 10.0 0.000039 0.000014 0.000033 \n",
+ " Spearman (1 core) 10.0 0.000280 0.000022 0.000266 \n",
+ "1000 CCC (1 core) 10.0 0.001520 0.000021 0.001473 \n",
+ " CCC (3 cores) 10.0 0.001457 0.000246 0.001307 \n",
+ " CCC (6 cores) 10.0 0.001665 0.000511 0.001367 \n",
+ " MIC (1 core) 10.0 0.037375 0.000440 0.036806 \n",
+ " MICe (1 core) 10.0 0.024938 0.000247 0.024583 \n",
+ " Pearson (1 core) 10.0 0.000041 0.000013 0.000035 \n",
+ " Spearman (1 core) 10.0 0.000318 0.000009 0.000310 \n",
+ "5000 CCC (1 core) 10.0 0.006788 0.000060 0.006672 \n",
+ " CCC (3 cores) 10.0 0.003255 0.000450 0.002939 \n",
+ " CCC (6 cores) 10.0 0.002966 0.000383 0.002287 \n",
+ " MIC (1 core) 10.0 0.511068 0.002535 0.508058 \n",
+ " MICe (1 core) 10.0 0.228089 0.000724 0.226995 \n",
+ " Pearson (1 core) 10.0 0.000052 0.000013 0.000045 \n",
+ " Spearman (1 core) 10.0 0.000672 0.000034 0.000647 \n",
+ "10000 CCC (1 core) 10.0 0.013911 0.000139 0.013680 \n",
+ " CCC (3 cores) 10.0 0.006295 0.000917 0.005360 \n",
+ " CCC (6 cores) 10.0 0.003929 0.000618 0.003467 \n",
+ " MIC (1 core) 10.0 1.604225 0.005336 1.594926 \n",
+ " MICe (1 core) 10.0 0.571711 0.001157 0.569632 \n",
+ " Pearson (1 core) 10.0 0.000066 0.000015 0.000058 \n",
+ " Spearman (1 core) 10.0 0.001157 0.000035 0.001128 \n",
+ "50000 CCC (1 core) 10.0 0.080398 0.001983 0.079082 \n",
+ " CCC (3 cores) 10.0 0.028311 0.000604 0.027584 \n",
+ " CCC (6 cores) 10.0 0.016299 0.001369 0.015058 \n",
+ " MICe (1 core) 10.0 4.869085 0.007489 4.855632 \n",
+ " Pearson (1 core) 10.0 0.000216 0.000107 0.000164 \n",
+ " Spearman (1 core) 10.0 0.006197 0.000197 0.005992 \n",
+ "100000 CCC (1 core) 10.0 0.169880 0.004015 0.166682 \n",
+ " CCC (3 cores) 10.0 0.059719 0.001602 0.057553 \n",
+ " CCC (6 cores) 10.0 0.032267 0.001531 0.031124 \n",
+ " Pearson (1 core) 10.0 0.000487 0.000159 0.000307 \n",
+ " Spearman (1 core) 10.0 0.013500 0.000201 0.013329 \n",
+ "1000000 CCC (1 core) 10.0 2.374975 0.028419 2.312148 \n",
+ " CCC (3 cores) 10.0 0.908605 0.005742 0.900301 \n",
+ " CCC (6 cores) 10.0 0.536444 0.003756 0.531334 \n",
+ " Pearson (1 core) 10.0 0.008685 0.001105 0.007643 \n",
+ " Spearman (1 core) 10.0 0.175823 0.003502 0.171767 \n",
+ "10000000 CCC (1 core) 10.0 42.292236 0.110967 42.121878 \n",
+ " CCC (3 cores) 10.0 15.907279 0.039598 15.831335 \n",
+ " CCC (6 cores) 10.0 9.102648 0.049330 8.999230 \n",
+ " Pearson (1 core) 10.0 0.094251 0.000763 0.093191 \n",
+ " Spearman (1 core) 10.0 2.952096 0.007759 2.937117 \n",
"\n",
" 25% 50% 75% max \n",
"data_size method \n",
- "100 CCC (1 core) 0.000631 0.000635 0.000640 0.001048 \n",
- " CCC (3 cores) 0.000913 0.000944 0.001109 0.004993 \n",
- " MIC (1 core) 0.000707 0.000723 0.000741 0.000879 \n",
- " MICe (1 core) 0.000659 0.000676 0.000691 0.000740 \n",
- " Pearson (1 core) 0.000030 0.000031 0.000031 0.000098 \n",
- " Spearman (1 core) 0.000213 0.000215 0.000218 0.000483 \n",
- "500 CCC (1 core) 0.000918 0.000921 0.000927 0.001028 \n",
- " CCC (3 cores) 0.001103 0.001132 0.001268 0.002005 \n",
- " MIC (1 core) 0.011426 0.011671 0.011797 0.011964 \n",
- " MICe (1 core) 0.008851 0.008900 0.008963 0.008996 \n",
- " Pearson (1 core) 0.000034 0.000035 0.000042 0.000075 \n",
- " Spearman (1 core) 0.000264 0.000266 0.000268 0.000336 \n",
- "1000 CCC (1 core) 0.001362 0.001389 0.001438 0.001465 \n",
- " CCC (3 cores) 0.001383 0.001409 0.001685 0.002411 \n",
- " MIC (1 core) 0.036848 0.036995 0.037238 0.037937 \n",
- " MICe (1 core) 0.024754 0.024871 0.024943 0.025019 \n",
- " Pearson (1 core) 0.000034 0.000035 0.000035 0.000087 \n",
- " Spearman (1 core) 0.000304 0.000310 0.000321 0.000376 \n",
- "5000 CCC (1 core) 0.006639 0.006668 0.006692 0.006896 \n",
- " CCC (3 cores) 0.004018 0.004404 0.005185 0.007427 \n",
- " MIC (1 core) 0.509280 0.510705 0.512287 0.513345 \n",
- " MICe (1 core) 0.227605 0.227923 0.228074 0.229758 \n",
- " Pearson (1 core) 0.000045 0.000046 0.000049 0.000084 \n",
- " Spearman (1 core) 0.000651 0.000657 0.000660 0.000731 \n",
- "10000 CCC (1 core) 0.014274 0.014354 0.014452 0.014767 \n",
- " CCC (3 cores) 0.008029 0.008367 0.009145 0.010723 \n",
- " MIC (1 core) 1.587393 1.593111 1.599259 1.610753 \n",
- " MICe (1 core) 0.571873 0.572358 0.573227 0.574736 \n",
- " Pearson (1 core) 0.000058 0.000059 0.000063 0.000106 \n",
- " Spearman (1 core) 0.001147 0.001153 0.001155 0.001231 \n",
- "50000 CCC (1 core) 0.081652 0.082052 0.082178 0.082773 \n",
- " CCC (3 cores) 0.042617 0.043109 0.043533 0.043936 \n",
- " MICe (1 core) 4.842152 4.843082 4.846897 4.849092 \n",
- " Pearson (1 core) 0.000165 0.000169 0.000190 0.000248 \n",
- " Spearman (1 core) 0.006003 0.006108 0.006233 0.006459 \n",
- "100000 CCC (1 core) 0.174719 0.175010 0.175541 0.176207 \n",
- " CCC (3 cores) 0.089994 0.090318 0.091081 0.095571 \n",
- " Pearson (1 core) 0.000318 0.000320 0.000336 0.001109 \n",
- " Spearman (1 core) 0.011671 0.011746 0.011826 0.012993 \n",
- "1000000 CCC (1 core) 2.255166 2.270925 2.352809 2.407563 \n",
- " CCC (3 cores) 1.268516 1.273530 1.282357 1.291811 \n",
- " Pearson (1 core) 0.006245 0.007732 0.007757 0.009899 \n",
- " Spearman (1 core) 0.171784 0.172625 0.173215 0.174503 \n",
- "10000000 CCC (1 core) 40.088204 40.151353 40.259280 40.429066 \n",
- " CCC (3 cores) 21.845108 21.876476 21.949155 22.039508 \n",
- " Pearson (1 core) 0.093855 0.094105 0.094493 0.095369 \n",
- " Spearman (1 core) 2.946117 2.951748 2.962198 2.971911 "
+ "100 CCC (1 core) 0.000690 0.000693 0.000700 0.000963 \n",
+ " CCC (3 cores) 0.000983 0.001027 0.001304 0.006013 \n",
+ " CCC (6 cores) 0.001497 0.002142 0.003099 0.007773 \n",
+ " MIC (1 core) 0.000704 0.000723 0.000743 0.000821 \n",
+ " MICe (1 core) 0.000659 0.000673 0.000689 0.000756 \n",
+ " Pearson (1 core) 0.000031 0.000032 0.000033 0.000145 \n",
+ " Spearman (1 core) 0.000224 0.000226 0.000229 0.000393 \n",
+ "500 CCC (1 core) 0.000997 0.001006 0.001010 0.001116 \n",
+ " CCC (3 cores) 0.001449 0.001490 0.001747 0.002150 \n",
+ " CCC (6 cores) 0.001332 0.001356 0.001383 0.002961 \n",
+ " MIC (1 core) 0.011459 0.011552 0.011663 0.011803 \n",
+ " MICe (1 core) 0.008778 0.008870 0.008926 0.009037 \n",
+ " Pearson (1 core) 0.000034 0.000035 0.000036 0.000079 \n",
+ " Spearman (1 core) 0.000271 0.000272 0.000278 0.000340 \n",
+ "1000 CCC (1 core) 0.001508 0.001526 0.001532 0.001544 \n",
+ " CCC (3 cores) 0.001323 0.001328 0.001477 0.002081 \n",
+ " CCC (6 cores) 0.001426 0.001455 0.001562 0.003018 \n",
+ " MIC (1 core) 0.037103 0.037231 0.037689 0.038242 \n",
+ " MICe (1 core) 0.024758 0.024965 0.025059 0.025344 \n",
+ " Pearson (1 core) 0.000036 0.000037 0.000037 0.000077 \n",
+ " Spearman (1 core) 0.000312 0.000313 0.000323 0.000337 \n",
+ "5000 CCC (1 core) 0.006755 0.006799 0.006819 0.006884 \n",
+ " CCC (3 cores) 0.003033 0.003085 0.003135 0.004291 \n",
+ " CCC (6 cores) 0.002790 0.002943 0.003094 0.003766 \n",
+ " MIC (1 core) 0.509063 0.511166 0.511689 0.516697 \n",
+ " MICe (1 core) 0.227600 0.227992 0.228596 0.229304 \n",
+ " Pearson (1 core) 0.000046 0.000047 0.000051 0.000088 \n",
+ " Spearman (1 core) 0.000657 0.000661 0.000673 0.000766 \n",
+ "10000 CCC (1 core) 0.013838 0.013906 0.014009 0.014104 \n",
+ " CCC (3 cores) 0.005587 0.006078 0.006806 0.008178 \n",
+ " CCC (6 cores) 0.003497 0.003648 0.004185 0.005180 \n",
+ " MIC (1 core) 1.600615 1.606042 1.607014 1.610589 \n",
+ " MICe (1 core) 0.570982 0.571727 0.572616 0.573363 \n",
+ " Pearson (1 core) 0.000059 0.000060 0.000062 0.000106 \n",
+ " Spearman (1 core) 0.001146 0.001149 0.001152 0.001253 \n",
+ "50000 CCC (1 core) 0.079508 0.079843 0.080196 0.085907 \n",
+ " CCC (3 cores) 0.027964 0.028092 0.028674 0.029486 \n",
+ " CCC (6 cores) 0.015353 0.015880 0.016453 0.019071 \n",
+ " MICe (1 core) 4.865442 4.869943 4.874358 4.877798 \n",
+ " Pearson (1 core) 0.000168 0.000181 0.000200 0.000515 \n",
+ " Spearman (1 core) 0.006033 0.006152 0.006320 0.006609 \n",
+ "100000 CCC (1 core) 0.168021 0.168410 0.170365 0.180720 \n",
+ " CCC (3 cores) 0.058915 0.059804 0.060159 0.063151 \n",
+ " CCC (6 cores) 0.031255 0.031849 0.032394 0.036092 \n",
+ " Pearson (1 core) 0.000354 0.000430 0.000628 0.000748 \n",
+ " Spearman (1 core) 0.013438 0.013453 0.013498 0.014044 \n",
+ "1000000 CCC (1 core) 2.365298 2.373448 2.391214 2.421613 \n",
+ " CCC (3 cores) 0.904757 0.906894 0.912644 0.917324 \n",
+ " CCC (6 cores) 0.534186 0.536558 0.538229 0.543839 \n",
+ " Pearson (1 core) 0.007773 0.008315 0.009787 0.010285 \n",
+ " Spearman (1 core) 0.173853 0.175242 0.176227 0.183476 \n",
+ "10000000 CCC (1 core) 42.227472 42.277608 42.331981 42.507820 \n",
+ " CCC (3 cores) 15.897137 15.911772 15.932641 15.959610 \n",
+ " CCC (6 cores) 9.080815 9.099392 9.143470 9.161670 \n",
+ " Pearson (1 core) 0.093785 0.094238 0.094759 0.095648 \n",
+ " Spearman (1 core) 2.950214 2.952338 2.954561 2.967408 "
]
},
"metadata": {},
@@ -1355,6 +1568,7 @@
" plot_data[\n",
" plot_data[\"method\"].str.contains(\"1 core\", regex=False)\n",
" | plot_data[\"method\"].str.contains(\"CCC (3 cores)\", regex=False)\n",
+ " | plot_data[\"method\"].str.contains(\"CCC (6 cores)\", regex=False)\n",
" ]\n",
" .groupby([\"data_size\", \"method\"])[\"time\"]\n",
" .describe()\n",
@@ -1364,9 +1578,24 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 16,
"id": "ffb6a620-e832-4b8e-bfe2-e211a381000e",
- "metadata": {},
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.139005Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.138877Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.140296Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.140169Z"
+ },
+ "papermill": {
+ "duration": 0.00487,
+ "end_time": "2023-09-11T17:28:48.140852",
+ "exception": false,
+ "start_time": "2023-09-11T17:28:48.135982",
+ "status": "completed"
+ },
+ "tags": []
+ },
"outputs": [],
"source": [
"# this is necessary to make sure we did not mix results when running the time test notebooks\n",
@@ -1379,10 +1608,10 @@
"id": "772f2cd8-22b9-4106-93e2-1c8063370356",
"metadata": {
"papermill": {
- "duration": 0.002476,
- "end_time": "2023-09-11T14:41:55.662125",
+ "duration": 0.002383,
+ "end_time": "2023-09-11T17:28:48.145748",
"exception": false,
- "start_time": "2023-09-11T14:41:55.659649",
+ "start_time": "2023-09-11T17:28:48.143365",
"status": "completed"
},
"tags": []
@@ -1393,14 +1622,20 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 17,
"id": "3b4ffedd-661b-40da-b323-4d29f38c3b72",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.151034Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.150919Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.152531Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.152405Z"
+ },
"papermill": {
- "duration": 0.004783,
- "end_time": "2023-09-11T14:41:55.669379",
+ "duration": 0.004754,
+ "end_time": "2023-09-11T17:28:48.153036",
"exception": false,
- "start_time": "2023-09-11T14:41:55.664596",
+ "start_time": "2023-09-11T17:28:48.148282",
"status": "completed"
},
"tags": []
@@ -1412,14 +1647,20 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 18,
"id": "cc263e22-bbc0-4d20-953f-ec6fd0a624b8",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.158303Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.158201Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.159715Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.159592Z"
+ },
"papermill": {
- "duration": 0.004689,
- "end_time": "2023-09-11T14:41:55.676431",
+ "duration": 0.004683,
+ "end_time": "2023-09-11T17:28:48.160221",
"exception": false,
- "start_time": "2023-09-11T14:41:55.671742",
+ "start_time": "2023-09-11T17:28:48.155538",
"status": "completed"
},
"tags": []
@@ -1430,17 +1671,22 @@
"text/plain": [
"['CCC (1 core)',\n",
" 'CCC (3 cores)',\n",
+ " 'CCC (6 cores)',\n",
" 'MIC (1 core)',\n",
" 'MIC (3 cores)',\n",
+ " 'MIC (6 cores)',\n",
" 'MICe (1 core)',\n",
" 'MICe (3 cores)',\n",
+ " 'MICe (6 cores)',\n",
" 'Pearson (1 core)',\n",
" 'Pearson (3 cores)',\n",
+ " 'Pearson (6 cores)',\n",
" 'Spearman (1 core)',\n",
- " 'Spearman (3 cores)']"
+ " 'Spearman (3 cores)',\n",
+ " 'Spearman (6 cores)']"
]
},
- "execution_count": 17,
+ "execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
@@ -1451,14 +1697,20 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 19,
"id": "e3c79816-6703-4236-b55a-c6dc38d4d600",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.165472Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.165391Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.167382Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.167260Z"
+ },
"papermill": {
- "duration": 0.005063,
- "end_time": "2023-09-11T14:41:55.683918",
+ "duration": 0.005015,
+ "end_time": "2023-09-11T17:28:48.167768",
"exception": false,
- "start_time": "2023-09-11T14:41:55.678855",
+ "start_time": "2023-09-11T17:28:48.162753",
"status": "completed"
},
"tags": []
@@ -1495,14 +1747,20 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 20,
"id": "59249512-0a19-4868-b5a0-5dc4e271c8af",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.173097Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.173050Z",
+ "iopub.status.idle": "2023-09-11T17:28:48.176105Z",
+ "shell.execute_reply": "2023-09-11T17:28:48.175969Z"
+ },
"papermill": {
- "duration": 0.006262,
- "end_time": "2023-09-11T14:41:55.692678",
+ "duration": 0.006171,
+ "end_time": "2023-09-11T17:28:48.176484",
"exception": false,
- "start_time": "2023-09-11T14:41:55.686416",
+ "start_time": "2023-09-11T17:28:48.170313",
"status": "completed"
},
"tags": []
@@ -1526,10 +1784,10 @@
"id": "c581b4df-26fe-43e2-ba23-3595534c7ea2",
"metadata": {
"papermill": {
- "duration": 0.002402,
- "end_time": "2023-09-11T14:41:55.697550",
+ "duration": 0.002467,
+ "end_time": "2023-09-11T17:28:48.181543",
"exception": false,
- "start_time": "2023-09-11T14:41:55.695148",
+ "start_time": "2023-09-11T17:28:48.179076",
"status": "completed"
},
"tags": []
@@ -1543,10 +1801,10 @@
"id": "5fcb16ca-07a6-41b9-aa18-f22b84194e71",
"metadata": {
"papermill": {
- "duration": 0.002429,
- "end_time": "2023-09-11T14:41:55.702447",
+ "duration": 0.002486,
+ "end_time": "2023-09-11T17:28:48.186599",
"exception": false,
- "start_time": "2023-09-11T14:41:55.700018",
+ "start_time": "2023-09-11T17:28:48.184113",
"status": "completed"
},
"tags": []
@@ -1557,14 +1815,20 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 21,
"id": "09151d37-4dd2-4c1f-ab4a-94b4d3e79018",
"metadata": {
+ "execution": {
+ "iopub.execute_input": "2023-09-11T17:28:48.191895Z",
+ "iopub.status.busy": "2023-09-11T17:28:48.191845Z",
+ "iopub.status.idle": "2023-09-11T17:28:49.105140Z",
+ "shell.execute_reply": "2023-09-11T17:28:49.104904Z"
+ },
"papermill": {
- "duration": 0.661136,
- "end_time": "2023-09-11T14:41:56.366016",
+ "duration": 0.916625,
+ "end_time": "2023-09-11T17:28:49.105757",
"exception": false,
- "start_time": "2023-09-11T14:41:55.704880",
+ "start_time": "2023-09-11T17:28:48.189132",
"status": "completed"
},
"tags": []
@@ -1572,7 +1836,7 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
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\n",
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