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feat: Add launch.json for Python debugger configuration

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This commit adds a new file, `.vscode/launch.json`, which contains the configuration for launching the Python debugger. The configuration includes the necessary attributes such as the debugger type, request type, program file, console type, and command-line arguments. This configuration allows developers to easily debug Python files in the integrated terminal.
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nuluh
2024-08-20 11:32:22 +07:00
parent 57c0e03a4f
commit de902b2a8c
2 changed files with 102 additions and 5 deletions
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91
code/notebooks/03_feature_extraction.ipynb
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@@ -25,7 +25,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
@@ -154,7 +154,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 12,
"metadata": {},
"outputs": [
{
@@ -186,12 +186,12 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"### Print Time-domain Features"
"### Print Time-domain Features (Single Mockup Data)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 13,
"metadata": {},
"outputs": [
{
@@ -264,7 +264,7 @@
"0 2.067638 1.917716 0.412307 "
]
},
"execution_count": 23,
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -272,10 +272,12 @@
"source": [
"import pandas as pd\n",
"import sys\n",
"import os\n",
"# Assuming the src directory is one level up from the notebooks directory\n",
"sys.path.append('../src/features')\n",
"from time_domain_features import FeatureExtractor\n",
"\n",
"\n",
"# Extract features\n",
"extracted = FeatureExtractor(mock_df['SampleData'])\n",
"\n",
@@ -283,6 +285,85 @@
"features = pd.DataFrame(extracted.features, index=[0])\n",
"features\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Print Time-domain Features (Multiple CSV Mockup Data)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import sys\n",
"import os\n",
"# Assuming the src directory is one level up from the notebooks directory\n",
"sys.path.append('../src/features')\n",
"from time_domain_features import ExtractTimeFeatures # use wrapper function instead of class for easy use\n",
"\n",
"def build_features(input_dir):\n",
" all_features = []\n",
" for nth_damage in os.listdir(input_dir):\n",
" nth_damage_path = os.path.join(input_dir, nth_damage)\n",
" if os.path.isdir(nth_damage_path):\n",
" # print(nth_damage)\n",
" for nth_test in os.listdir(nth_damage_path):\n",
" nth_test_path = os.path.join(nth_damage_path, nth_test)\n",
" # print(nth_test_path)\n",
" features = ExtractTimeFeatures(nth_test_path) # return the one csv file feature in dictionary {}\n",
" all_features.append(features)\n",
"\n",
" # Create a DataFrame from the list of dictionaries\n",
" df = pd.DataFrame(all_features)\n",
" return df\n",
"\n",
"data_dir = \"../../data/raw\"\n",
"# Extract features\n",
"df = build_features(data_dir)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 50 entries, 0 to 49\n",
"Data columns (total 14 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Mean 50 non-null float64\n",
" 1 Max 50 non-null float64\n",
" 2 Peak (Pm) 50 non-null float64\n",
" 3 Peak-to-Peak (Pk) 50 non-null float64\n",
" 4 RMS 50 non-null float64\n",
" 5 Variance 50 non-null float64\n",
" 6 Standard Deviation 50 non-null float64\n",
" 7 Power 50 non-null float64\n",
" 8 Crest Factor 50 non-null float64\n",
" 9 Form Factor 50 non-null float64\n",
" 10 Pulse Indicator 50 non-null float64\n",
" 11 Margin 50 non-null float64\n",
" 12 Kurtosis 50 non-null float64\n",
" 13 Skewness 50 non-null float64\n",
"dtypes: float64(14)\n",
"memory usage: 5.6 KB\n"
]
}
],
"source": [
"df.info()"
]
}
],
"metadata": {