Help on recreating dict per house #2
Comments
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Hi, Aleonnet,
I am too busy for my final thesis these days and I will help you to recode this when I am free. Forgive me for my busyness.
Regards,
Raymond
…________________________________
发件人: aleonnet <notifications@github.com>
发送时间: Saturday, April 20, 2019 11:38:36 AM
收件人: ZhangRaymond/Neural-NILM
抄送: Raymond, Zhang Yuanmeng; Mention
主题: [ZhangRaymond/Neural-NILM] Help on recreating dict per house (#2)
Hi @ZhangRaymond<https://github.com/ZhangRaymond>,
I really tried to recreate this dict, but I could not handle nilmtk/REDD adequately I think :( I'm sorry.
Please help me. I'd really like to try your code out.
[image]<https://user-images.githubusercontent.com/20618327/56451834-14b5f980-6304-11e9-9fc2-5ac7c6e2313f.png>
Thank you.
import pickle
from nilmtk import DataSet, TimeFrame
import pandas as pd
datafolder = '/Users/alessandro/Documents/data/'
redd = DataSet(datafolder + 'redd.h5')
metadata = dict(redd.metadata)
deviceName = set()
appName = set()
mains={}
appliances={}
for i in range(1,7):
mains[i] = {}
for house in range(1,7):
print('house_',house)
elec = redd.buildings[house].elec
appliancelist = elec.appliances
mainsvalues = elec.mains().power_series_all_data()
mains[house]=mainsvalues
for app in appliancelist:
label = app.label('unknown')
print(' '*3,label)
appName.add(label)
appliances[house][label] = elec[label].power_series(ac_type='active')
deviceName = list(appName)
with open('house_{}.pickle'.format(house), 'wb') as file:
pickle.dump([deviceName], file)
print('End')
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Hi Raymond,
Sorry to trouble you, I perfectly undeserving.
I’d really like to follow up your results on the article and code.
Thank you.
Regards,
Alessandro
…On Sat, 27 Apr 2019 at 02:48 Raymond Zhang ***@***.***> wrote:
Hi, Aleonnet,
I am too busy for my final thesis these days and I will help you to recode
this when I am free. Forgive me for my busyness.
Regards,
Raymond
________________________________
发件人: aleonnet ***@***.***>
发送时间: Saturday, April 20, 2019 11:38:36 AM
收件人: ZhangRaymond/Neural-NILM
抄送: Raymond, Zhang Yuanmeng; Mention
主题: [ZhangRaymond/Neural-NILM] Help on recreating dict per house (#2)
Hi @ZhangRaymond<https://github.com/ZhangRaymond>,
I really tried to recreate this dict, but I could not handle nilmtk/REDD
adequately I think :( I'm sorry.
Please help me. I'd really like to try your code out.
[image]<
https://user-images.githubusercontent.com/20618327/56451834-14b5f980-6304-11e9-9fc2-5ac7c6e2313f.png>
Thank you.
import pickle
from nilmtk import DataSet, TimeFrame
import pandas as pd
datafolder = '/Users/alessandro/Documents/data/'
redd = DataSet(datafolder + 'redd.h5')
metadata = dict(redd.metadata)
deviceName = set()
appName = set()
mains={}
appliances={}
for i in range(1,7):
mains[i] = {}
for house in range(1,7):
print('house_',house)
elec = redd.buildings[house].elec
appliancelist = elec.appliances
mainsvalues = elec.mains().power_series_all_data()
mains[house]=mainsvalues
for app in appliancelist:
label = app.label('unknown')
print(' '*3,label)
appName.add(label)
appliances[house][label] = elec[label].power_series(ac_type='active')
deviceName = list(appName)
with open('house_{}.pickle'.format(house), 'wb') as file:
pickle.dump([deviceName], file)
print('End')
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Hi Raymond,
I was able to recreate the house pickle structure with the following code:
[image: image.png]
[image: image.png]
But a few other issues came up:
1- The 'deviceName' names refer to the nilmtk standard types. I've not
found any documented method/metadata to get 'original_name' appliances from
REDD.
2- Only house_2, shows the right structure according to the picture you
sent me.
For example, check house_1 below. Some appliances have more samples than
others. How to solve that?
[image: image.png]
house_ 1
unknown (745878, 1)
unknown (745878, 1)
fridge (745878, 1)
sockets (745878, 1)
electric oven
Loading data for meter ElecMeterID(instance=4, building=1,
dataset='REDD')
Done loading data all meters for this chunk.
(1044688, 1)
3- The pickle file struture(keys) seems to be correct, but
get_house_raw_data in lib.py is still raising an AttributeError: 'list'
object has no attribute 'deviceName' and it has it as you can see above.
[image: image.png]
*Would you help me pls?* It took me a lot of time to get to this point.
Thank you.
Alessandro
…On Sat, Apr 27, 2019 at 2:48 AM Raymond Zhang ***@***.***> wrote:
Hi, Aleonnet,
I am too busy for my final thesis these days and I will help you to recode
this when I am free. Forgive me for my busyness.
Regards,
Raymond
________________________________
发件人: aleonnet ***@***.***>
发送时间: Saturday, April 20, 2019 11:38:36 AM
收件人: ZhangRaymond/Neural-NILM
抄送: Raymond, Zhang Yuanmeng; Mention
主题: [ZhangRaymond/Neural-NILM] Help on recreating dict per house (#2)
Hi @ZhangRaymond<https://github.com/ZhangRaymond>,
I really tried to recreate this dict, but I could not handle nilmtk/REDD
adequately I think :( I'm sorry.
Please help me. I'd really like to try your code out.
[image]<
https://user-images.githubusercontent.com/20618327/56451834-14b5f980-6304-11e9-9fc2-5ac7c6e2313f.png>
Thank you.
import pickle
from nilmtk import DataSet, TimeFrame
import pandas as pd
datafolder = '/Users/alessandro/Documents/data/'
redd = DataSet(datafolder + 'redd.h5')
metadata = dict(redd.metadata)
deviceName = set()
appName = set()
mains={}
appliances={}
for i in range(1,7):
mains[i] = {}
for house in range(1,7):
print('house_',house)
elec = redd.buildings[house].elec
appliancelist = elec.appliances
mainsvalues = elec.mains().power_series_all_data()
mains[house]=mainsvalues
for app in appliancelist:
label = app.label('unknown')
print(' '*3,label)
appName.add(label)
appliances[house][label] = elec[label].power_series(ac_type='active')
deviceName = list(appName)
with open('house_{}.pickle'.format(house), 'wb') as file:
pickle.dump([deviceName], file)
print('End')
―
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#2>, or mute the thread<
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<#2 (comment)>,
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Hi
On Sun, 2 Jun 2019 at 17:03 Alessandro Barbosa <barbosa.alessandro@gmail.com>
wrote:
… Hi Raymond,
I was able to recreate the house pickle structure with the following code:
[image: image.png]
[image: image.png]
But a few other issues came up:
1- The 'deviceName' names refer to the nilmtk standard types. I've not
found any documented method/metadata to get 'original_name' appliances from
REDD.
2- Only house_2, shows the right structure according to the picture you
sent me.
For example, check house_1 below. Some appliances have more samples than
others. How to solve that?
[image: image.png]
house_ 1
unknown (745878, 1)
unknown (745878, 1)
fridge (745878, 1)
sockets (745878, 1)
electric oven
Loading data for meter ElecMeterID(instance=4, building=1,
dataset='REDD')
Done loading data all meters for this chunk.
(1044688, 1)
3- The pickle file struture(keys) seems to be correct, but
get_house_raw_data in lib.py is still raising an AttributeError: 'list'
object has no attribute 'deviceName' and it has it as you can see above.
[image: image.png]
*Would you help me pls?* It took me a lot of time to get to this point.
Thank you.
Alessandro
On Sat, Apr 27, 2019 at 2:48 AM Raymond Zhang ***@***.***>
wrote:
> Hi, Aleonnet,
>
> I am too busy for my final thesis these days and I will help you to
> recode this when I am free. Forgive me for my busyness.
>
> Regards,
> Raymond
>
> ________________________________
> 发件人: aleonnet ***@***.***>
> 发送时间: Saturday, April 20, 2019 11:38:36 AM
> 收件人: ZhangRaymond/Neural-NILM
> 抄送: Raymond, Zhang Yuanmeng; Mention
> 主题: [ZhangRaymond/Neural-NILM] Help on recreating dict per house (#2)
>
>
> Hi @ZhangRaymond<https://github.com/ZhangRaymond>,
> I really tried to recreate this dict, but I could not handle nilmtk/REDD
> adequately I think :( I'm sorry.
> Please help me. I'd really like to try your code out.
>
> [image]<
> https://user-images.githubusercontent.com/20618327/56451834-14b5f980-6304-11e9-9fc2-5ac7c6e2313f.png>
>
>
> Thank you.
> import pickle
> from nilmtk import DataSet, TimeFrame
> import pandas as pd
>
> datafolder = '/Users/alessandro/Documents/data/'
>
> redd = DataSet(datafolder + 'redd.h5')
> metadata = dict(redd.metadata)
>
> deviceName = set()
> appName = set()
> mains={}
> appliances={}
> for i in range(1,7):
> mains[i] = {}
>
> for house in range(1,7):
> print('house_',house)
> elec = redd.buildings[house].elec
> appliancelist = elec.appliances
> mainsvalues = elec.mains().power_series_all_data()
> mains[house]=mainsvalues
> for app in appliancelist:
> label = app.label('unknown')
> print(' '*3,label)
> appName.add(label)
> appliances[house][label] = elec[label].power_series(ac_type='active')
> deviceName = list(appName)
> with open('house_{}.pickle'.format(house), 'wb') as file:
> pickle.dump([deviceName], file)
> print('End')
>
> ―
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub<
> #2>, or mute the
> thread<
> https://github.com/notifications/unsubscribe-auth/AD23A4QEUICH7QMPLOWFU4TPRKF3ZANCNFSM4HHI3CDQ>.
>
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <#2 (comment)>,
> or mute the thread
> <https://github.com/notifications/unsubscribe-auth/AE5JYV7PDJ5LD766H37MGILPSPSJVANCNFSM4HHI3CDQ>
> .
>
|
Hi, Aleonnet, Sorry for the late reply, I have just finished my thesis. Regards, |
|
Hi，@aleonnet， I am currently using the extracted data, one file per house. It didn't uploaded to github before because these files are too large (341MB). Just now I am surprised to find that there is only 7MB after compression, so I uploaded the compressed package and committed just now, please unzip it and use it directly. I'll take the time to rewrite the generating code. |
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Hi Raymond,
I’ve got the code working!
I’ll send it to you.
I’m surprised to learn that the training is taking so long about 31h per
epoch.
Is this correct?
Regards,
…On Mon, 10 Jun 2019 at 12:29 Raymond Zhang ***@***.***> wrote:
***@***.*** <https://github.com/aleonnet>，
I am currently using the extracted data, one file per house. It didn't
uploaded to github before because these files are too large (341MB). Just
now I am surprised to find that there is only 7MB after compression, so I
uploaded the compressed package and committed just now, please unzip it and
use it directly. I'll take the time to rewrite the generating code.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
<#2?email_source=notifications&email_token=AE5JYV355GHSMYQGPXYACHDPZZXORA5CNFSM4HHI3CD2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXKGUOA#issuecomment-500460088>,
or mute the thread
<https://github.com/notifications/unsubscribe-auth/AE5JYV5VBXAL2WLQT7HDTVDPZZXORANCNFSM4HHI3CDQ>
.
|
|
Hi，@aleonnet， Good luck for you! Regards, |
|
Hi @ZhangRaymond Regards, PS: Check my contributions at https://github.com/aleonnet/GSP_energy_disaggregator |
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In line 25 of Seq2point.py (from packages import *), the run shows ModuleNotFoundError: No module named 'packages'.What caused this? |
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Hi @ZhangRaymond, |
hi，aleonnet, |
Hi, aleonnet， I have found the code for get_house_data.py in your repository. I am new to Github and thank you very much for providing the code. Regards, |
|
Have you finished recreating this dict? |
Hi， |
你好，请问你找到了么，能提供个链接吗 |
Hi @ZhangRaymond,
I really tried to recreate this dict, but I could not handle nilmtk/REDD adequately I think :( I'm sorry.
Please help me. I'd really like to try your code out.
Thank you.
import pickle
from nilmtk import DataSet, TimeFrame
import pandas as pd
datafolder = '/Users/alessandro/Documents/data/'
redd = DataSet(datafolder + 'redd.h5')
metadata = dict(redd.metadata)
deviceName = set()
appName = set()
mains={}
appliances={}
for i in range(1,7):
mains[i] = {}
for house in range(1,7):
print('house_',house)
elec = redd.buildings[house].elec
appliancelist = elec.appliances
mainsvalues = elec.mains().power_series_all_data()
mains[house]=mainsvalues
for app in appliancelist:
label = app.label('unknown')
print(' '*3,label)
appName.add(label)
appliances[house][label] = elec[label].power_series(ac_type='active')
deviceName = list(appName)
with open('house_{}.pickle'.format(house), 'wb') as file:
pickle.dump([deviceName], file)
print('End')
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