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added missing function

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This commit is contained in:
Radek Ludačka
2021-09-22 21:16:27 +02:00
parent 9135028145
commit 4197c0b9db
2 changed files with 32 additions and 221 deletions
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235
electrical-network-frequency-analysis/notebooks/enf_extraction_example.ipynb
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@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "raw",
"id": "gross-fever",
"id": "needed-surface",
"metadata": {},
"source": [
"Notebook extracts ENF signal by pyenf_extraction application\n",
@@ -12,7 +12,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "complete-exchange",
"id": "endangered-scott",
"metadata": {
"scrolled": true,
"tags": []
@@ -21,146 +21,35 @@
"source": [
"!wget https://github.com/ghuawhu/ENF-WHU-Dataset/blob/master/ENF-WHU-Dataset/H1/002.wav?raw=true\n",
"!wget https://github.com/ghuawhu/ENF-WHU-Dataset/blob/master/ENF-WHU-Dataset/H1_ref/002_ref.wav?raw=true\n",
"!git clone https://github.com/deerajnagothu/pyenf_extraction"
]
},
{
"cell_type": "raw",
"id": "fixed-aging",
"metadata": {},
"source": [
"pip install scipy==1.1.0\n",
"pip install numpy==1.21.0\n",
"pip install matplotlib==3.4.2\n",
"pip install librosa==0.8.1"
"!git clone https://github.com/deerajnagothu/pyenf_extraction\n",
" \n",
"!pip install scipy==1.1.0\n",
"!pip install numpy==1.21.0\n",
"!pip install matplotlib==3.4.2\n",
"!pip install librosa==0.8.1"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "premier-minimum",
"id": "failing-upset",
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import numpy as np"
"import numpy as np\n",
"from lib import extract_enf_signal"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "regular-boundary",
"metadata": {},
"outputs": [],
"source": [
"sys.path.append('./pyenf_extraction/')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "remarkable-ready",
"id": "helpful-employer",
"metadata": {
"scrolled": true,
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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"/Users/radekludacka/miniconda3/envs/enf/lib/python3.7/site-packages/numpy/core/fromnumeric.py:1970: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
" result = asarray(a).shape\n"
]
},
{
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"source": [
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},
{
"cell_type": "code",
"execution_count": 5,
"id": "cutting-click",
"execution_count": 3,
"id": "genuine-grass",
"metadata": {},
"outputs": [],
"source": [

18
electrical-network-frequency-analysis/notebooks/lib.py Normal file
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import sys
from io import StringIO
from pyenf_extraction.pyenf import pyENF
def extract_enf_signal(wav_file_path):
mysignal = pyENF(filename=wav_file_path, nominal=50, harmonic_multiples=8, duration=0.1, strip_index=0)
x, fs = mysignal.read_initial_data()
spectro_strip, frequency_support = mysignal.compute_spectrogam_strips()
sys.stdout = StringIO()
weights = mysignal.compute_combining_weights_from_harmonics()
sys.stdout = sys.__stdout__
OurStripCell, initial_frequency = mysignal.compute_combined_spectrum(
spectro_strip, weights, frequency_support
)
return mysignal.compute_ENF_from_combined_strip(OurStripCell,initial_frequency)