Commit 5740c193 authored by Noric Couderc's avatar Noric Couderc

Updated notebooks.

parent f3d81fbb
......@@ -16,16 +16,25 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 10,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"%load_ext autoreload"
]
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
......@@ -34,7 +43,18 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Add the JBrainy directory to the path\n",
"import sys\n",
"sys.path.append('../')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
......@@ -53,7 +73,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
......@@ -71,20 +91,20 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"data = load_training_data(\"data/jmh-results-9307f70f.csv\",\n",
" \"software-perf.csv\",\n",
" \"data/hardware-perf-data.csv\")\n",
"data = load_training_data(\"../data/jmh-results-9307f70f.csv\",\n",
" \"../data/software-counters-21-01-20.csv\",\n",
" \"../data/hardware-perf-data.csv\")\n",
"\n",
"benchmark_data = data[\"data\"]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 15,
"metadata": {},
"outputs": [
{
......@@ -383,7 +403,7 @@
"[8 rows x 101 columns]"
]
},
"execution_count": 4,
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
......@@ -401,7 +421,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 16,
"metadata": {},
"outputs": [
{
......@@ -419,7 +439,7 @@
" 'addAll(int, Collection)', 'clear()', 'contains(Object)',\n",
" 'containsAll(Collection)', 'containsKey(Object)',\n",
" 'containsValue(Object)', 'entrySet()', 'equals(Object)',\n",
" 'get(Object)', 'hashCode()', 'indexOf(Object)', 'isEmpty()',\n",
" 'get(int)', 'hashCode()', 'indexOf(Object)', 'isEmpty()',\n",
" 'iterator()', 'keySet()', 'lastIndexOf(Object)', 'listIterator()',\n",
" 'listIterator(int)', 'put(Object, Object)', 'putAll(Map)',\n",
" 'remove(Object)', 'remove(int)', 'removeAll(Collection)',\n",
......@@ -441,7 +461,7 @@
" dtype=object)"
]
},
"execution_count": 5,
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
......@@ -459,7 +479,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
......@@ -509,7 +529,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
......@@ -518,7 +538,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
......@@ -529,7 +549,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 20,
"metadata": {},
"outputs": [
{
......@@ -828,7 +848,7 @@
"[8 rows x 101 columns]"
]
},
"execution_count": 9,
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
......@@ -843,7 +863,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
......@@ -857,7 +877,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
......@@ -867,7 +887,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
......@@ -4507,14 +4527,14 @@
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"pygments_lexer": "ipython2",
"version": "2.7.15+"
}
},
"nbformat": 4,
This source diff could not be displayed because it is too large. You can view the blob instead.
......@@ -8407,7 +8407,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
......@@ -8417,7 +8417,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 3,
"metadata": {},
"outputs": [
{
......@@ -8493,7 +8493,7 @@
"│ 638529 │ Set │ 499 │ 1000 │ 10000 │ LinkedHashSet │"
]
},
"execution_count": 5,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
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