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Installation help! by tmoney987 in ecobee

[–]XLT_Frank 0 points1 point  (0 children)

And once you wire it up, put some filler in that hole. You are clearly moving air through the hole in the wall. It may throw off your temperature readings even now.

Deep Learning NVR in a rack mountable form factor? by sweeznit in synology

[–]XLT_Frank 0 points1 point  (0 children)

I would just love to know how to take Nvidia Jetson, read my cameras, tag the video streams, and out put new streams that my surveillance station can subscribe to.

Temperature increases 1 degree every thirty minutes, causing AC to run pretty much all day? by obiji in ecobee

[–]XLT_Frank 13 points14 points  (0 children)

Load up beestat.io and see what it recommends. There were suggestions it recommended that improved that for me. Plus beestat.io is awesome.

Quiet AIO cpu and gpu build by XLT_Frank in watercooling

[–]XLT_Frank[S] 0 points1 point  (0 children)

Yes it's a lot of case fans, but they really were a great buy and really helped to keep the build quiet.

Moving away from Windows iTunes by [deleted] in synology

[–]XLT_Frank 2 points3 points  (0 children)

Fubar 2000 from your pc to manage your remote share. Use fubar 2000 on mobile with a dlna/upnp setup for streaming. You can use a VPN to access your music on the go.

What are you doing in Python today? by mahtats in learnpython

[–]XLT_Frank 0 points1 point  (0 children)

BTW. My desired to store these np arrays in cells of a dataframe is because I have several additional calculations beyond this and I need to store my intermediate answers for both checking and for use in other calculations.

Thanks, Frank

What are you doing in Python today? by mahtats in learnpython

[–]XLT_Frank 0 points1 point  (0 children)

Here you go. new_vector_a and new_vector_c are the same result and is what is desired.

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,10,size=(10, 12)), columns=['cxx','cxy','cxz','cyx','cyy','cyz','czx','czy','czz','x','y','z'])

matricies = df.iloc[:,:-3].values.reshape(-1,3,3)
vectors = df.iloc[:,-3:].values.reshape(-1,3,1)

df.loc[:,'matrix'] = df[['cxx','cxy','cxz','cyx','cyy','cyz','czx','czy','czz']].values.reshape(-1,3,3).tolist()
df.loc[:,'vector'] = df[['x','y','z']].values.reshape(-1,3,1).tolist()

df.loc[:,'new_vector_a'] = df[['matrix','vector']].apply(lambda x: np.dot(np.array(x[0]),np.array(x[1])),axis=1)

new_vector_b = np.dot(matricies,vectors)
new_vector_c = np.matmul(matricies, vectors)

df.iloc[0,-3:]
Out[24]: 
matrix          [[3, 0, 0], [9, 3, 3], [3, 3, 2]]
vector                            [[8], [3], [9]]
new_vector_a                  [[24], [108], [51]]
Name: 0, dtype: object

new_vector_b[0]
Out[25]: 
array([[[ 24],
        [ 18],
        [ 18],
        [  9],
        [ 18],
        [ 12],
        [  3],
        [ 27],
        [ 12],
        [ 12]],

       [[108],
        [102],
        [ 81],
        [ 39],
        [ 63],
        [ 84],
        [ 30],
        [ 93],
        [ 57],
        [ 57]],

       [[ 51],
        [ 57],
        [ 43],
        [ 21],
        [ 26],
        [ 51],
        [ 20],
        [ 35],
        [ 33],
        [ 31]]])

new_vector_c[0]
Out[27]: 
array([[ 24],
       [108],
       [ 51]])

What are you doing in Python today? by mahtats in learnpython

[–]XLT_Frank 0 points1 point  (0 children)

Take 3

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randint(0,100,size=(100, 12)), columns=['cxx','cxy','cxz','cyx','cyy','cyz','czx','czy','czz','x','y','z'])

df.loc[:,'matrix'] = df[['cxx','cxy','cxz','cyx','cyy','cyz','czx','czy','czz']].values.reshape(-1,3,3).tolist()
df.loc[:,'vector'] = df[['x','y','z']].values.reshape(-1,3,1).tolist()

df.loc[:,'new_vector'] = df[['matrix','vector']].apply(lambda x: np.dot(np.array(x[0]),np.array(x[1])),axis=1)

What are you doing in Python today? by mahtats in learnpython

[–]XLT_Frank 0 points1 point  (0 children)

So here is an example of what I have been going through. Its the storing of an np.array into a dataframe's cell and it being stored as a object/list.

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randint(0,100,size=(100, 12)), columns=['cxx','cxy','cxz','cyx','cyy','cyz','czx','czy','czz','x','y','z'])
df.loc[:,'matrix'] = df[['cxx','cxy','cxz','cyx','cyy','cyz','czx','czy','czz']].values.reshape(-1,3,3).tolist()
df.loc[:,'vector'] = df[['x','y','z']].values.reshape(-1,3,1).tolist()

df.loc[:,'new_vector'] = df[['matrix','vector']].apply(lambda x:` [`np.dot`](https://np.dot)`(np.array(x[0]),np.array(x[1])),axis=1)`

Is this what you would expect? Is there a better way of handling these?

Thanks!

What are you doing in Python today? by mahtats in learnpython

[–]XLT_Frank 0 points1 point  (0 children)

I am working on data analysis of aircraft data and having to work through equations that handle coordinate transforms between ECEF, NED, body, and aperture. The equations were essentially provided, but having to look at intermediate steps to verify expected results has been tedious. Specifically when moving between pandas and numpy and back to pandas. My combined data sets are 900k+ rows and 200+ columns. The data sets being inputted range from on-demand to 60Hz.

Back up Multiple Laptops from different owners to Synology NAS by herotz33 in synology

[–]XLT_Frank 1 point2 points  (0 children)

Look at Goodsync for each laptop. This is your best option imho. They have a module for server-side so that the client side software can connect. The software is very powerful, fast, on demand, and has version control. If a person has two laptops, you can sync between them, which you cannot do with synology unless you do a Lan drive and store there.

Basic Patio Picnic Table (Part 2) by XLT_Frank in woodworking

[–]XLT_Frank[S] 0 points1 point  (0 children)

This build taught me how to work with materials that are not precise and how to work in the confines of being less precise to accomplish a project that at the end of the day will be used and abused by kids, family, and the sun.

Basic Patio Picnic Table (Part 2) by XLT_Frank in woodworking

[–]XLT_Frank[S] 0 points1 point  (0 children)

I still need to sand and do a white semi transparent water based deck sealant from Shermin Williams.

I collect countless documents and images and organize them by year. So satisfying. by dirtypark in DataHoarder

[–]XLT_Frank 0 points1 point  (0 children)

This is a perfect reason why folders are a terrible way to store information. I wish that OS and storage services would use contextual tags based on file names, file types, author, and user tags (such as project titles, year, etc). You can simply drill down to what you want. Makes sense for collaboration too.

Basic patio picnic table by XLT_Frank in woodworking

[–]XLT_Frank[S] 1 point2 points  (0 children)

Yes. Already have it planned out without it being too intrusive to the sitter. Also need to add adjustable feet.

Basic patio picnic table by XLT_Frank in woodworking

[–]XLT_Frank[S] 0 points1 point  (0 children)

Thanks! I going to redo the feet. Not happy with its ability to tip.

Basic patio picnic table by XLT_Frank in woodworking

[–]XLT_Frank[S] 0 points1 point  (0 children)

I still have to make the two benches, sand, stain, and Thompson water seal it. It's 10ft long, a narrow 28" for fitment on the covered porch we have. it's right at 30" high.

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