# plt.suptitle(file + '(' + meta[file[0:-4]]['appliance']['type'] + '-' +
# meta[file[0:-4]]['appliance']['status'] + ')')
# plt.savefig('model/knowledge_model_temp/jpg/total/' + file[0:-4] + '.jpg',
# dpi=600)
# plt.close()
# print('dealing...:%03d/%03d' % (count, total_len))
for file, start_point in start_index.items():
plt.figure(figsize=(8, 6))
plt.cla()
count += 1
file_dir = source_dir + file
Voltage, Current = read_source_data(file_dir,
offset=start_point,
length=length1)
Stable_V, Stable_I = read_source_data(file_dir,
offset=start_point + 3000,
length=length2)
tem = np.array(Current) - np.array(Stable_I)
ax1 = plt.subplot(411)
plt.plot(t1, Voltage)
plt.grid(alpha=0.5, linestyle='-.')
plt.title('Voltage')
plt.xticks([])
ax2 = plt.subplot(412)
plt.plot(t1, Current)
plt.grid(alpha=0.5, linestyle='-.')
import sys
import os
import numpy as np
sys.path.append('data/')
from read_PLAID_data import read_source_data, read_index
source_dir = 'data/source/submetered_new_pured/source/'
type_index = read_index('type')
skip_list = type_index['Compact Fluorescent Lamp'] + type_index['Laptop']
csv_dir = os.listdir(source_dir)
record = {}
for file in csv_dir:
if int(file[0:-4]) in skip_list:
continue
file_dir = source_dir + file
Switch_V, Switch_I = read_source_data(file_dir, offset=0, length=1500)
Total_V, Total_I = read_source_data(file_dir, offset=0)
I_max = np.max(abs(Switch_I))
# slide_arr = np.zeros(10)
value0 = 0
# Threshold = np.sum(slide_arr) / len(slide_arr)
Threshold = 0.01256 * I_max
# diff = 0
slide_width = 10
for i, value in enumerate(Total_I):
if i == 0:
value0 = value
continue
if abs(value - value0) > 10 * Threshold:
from pyhht.visualization import plot_imfs
import matplotlib.pyplot as plt
sys.path.append('data/')
from read_PLAID_data import read_source_data
source_dir = 'data/source/submetered_new_pured/source/'
with open(
'/home/chaofan/powerknowledge/data/source/metadata_submetered2.1.json',
'r',
encoding='utf8') as load_meta:
meta = json.load(load_meta)
length1 = 3000
length2 = 3000
t = range(3000)
csv_dir = os.listdir(source_dir)
for file in csv_dir:
file_dir = source_dir + file
Switch_V, Switch_I = read_source_data(file_dir, offset=0, length=length1)
Stable_V, Stable_I = read_source_data(file_dir,
offset=3000,
length=length2)
tem = np.array(Switch_I) - np.array(Stable_I)
decomposer = EMD(tem, n_imfs=3)
imfs = decomposer.decompose()
plot_imfs(tem, imfs, t)
import os
sys.path.append('data/')
from read_PLAID_data import read_source_data, slider_plot
source_dir = 'data/source/submetered_new/'
file_list = os.listdir(source_dir)
# with open('model/find_result.txt', 'r') as f:
# file_list = []
# for line in f.readlines():
# line = line.strip('\n')
# line = line.split(':')
# file = line[0][1:-1]
# if '.csv' in file:
# file_list.append(file)
file_dir = source_dir + '1.csv'
Switch_V, Switch_I = read_source_data(file_dir)
slider_plot(Switch_I)
# with open(
# '/home/chaofan/powerknowledge/data/source/metadata_submetered2.1.json',
# 'r',
# encoding='utf8') as load_meta:
# meta = json.load(load_meta)
# count = 0
# for i, file in enumerate(file_list):
# file_dir = source_dir + file
# Switch_V, Switch_I = read_source_data(file_dir)
# print(file + '(' + meta[file[0:-4]]['appliance']['type'] + '-' +
# meta[file[0:-4]]['appliance']['status'] + ')')
# slider_plot(Switch_I)