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NUMBER_BUCKETS = 600

def hash_bucket(data, num_buckets=NUMBER_BUCKETS, seed=42):
    """MurmurHash3 was written by Austin Appleby, and is placed in the
     public domain. The author hereby disclaims copyright to this source
    code."""

    c1 = 0xcc9e2d51
    c2 = 0x1b873593

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import json
import geojson
from shapely.geometry import shape

o = {
   "coordinates": [[[23.314208, 37.768469], [24.039306, 37.768469], [24.039306, 38.214372], [23.314208, 38.214372], [23.314208, 37.768469]]], 
   "type": "Polygon"
}

s = json.dumps(o)

sbatururimi

Author: Sean Gillies Version: 1.0

Abstract

This document describes a GeoJSON-like protocol for geo-spatial (GIS) vector data.

Introduction

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def hash_bucket(data, num_buckets=NUMBER_BUCKETS, seed=42):
    """MurmurHash3 was written by Austin Appleby, and is placed in the
     public domain. The author hereby disclaims copyright to this source
    code."""

    c1 = 0xcc9e2d51
    c2 = 0x1b873593

    length = len(data)
    h1 = seed

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Intel for display, NVIDIA for computing

This guide will show you how to use Intel graphics for rendering display and NVIDIA graphics for CUDA computing on Ubuntu 18.04 desktop.

I made this work on an ordinary gaming PC with two graphics devices, an Intel UHD Graphics 630 plus an NVIDIA GeForce GTX 1080 Ti. Both of them can be shown via lspci | grep VGA.

00:02.0 VGA compatible controller: Intel Corporation Device 3e92
01:00.0 VGA compatible controller: NVIDIA Corporation GP102 [GeForce GTX 1080 Ti] (rev a1)

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Building TensorFlow from source (TF 2.3.0, Ubuntu 20.04)

Why build from source?

The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.

I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).

So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht

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Remove

sudo dpkg  --force-depends --purge  libpython3.9-minimal

Or

sudo dpkg --remove --force-depends python3.6 python3.6-minimal libpython3.6-minimal libpython3.6-stdlib

https://askubuntu.com/a/1069440

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Searching Git commit history

This should be one of the core features of Git, but for some reason it's impossible to figure out how to search for a string in your commit history and see the diffs that that string is in. Here's the best I've come up with:

To find which commits and which files a string was added or removed in:

git log -S'search string' --oneline --name-status

To see the diff of that

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def percentile(n):
    def percentile_(x):
        return np.percentile(x, n)
    percentile_.__name__ = 'percentile_%s' % n
    return percentile_

df.groupby(['id'])[cols].agg(['min', 'max', np.mean, np.std, np.median, percentile(50), percentile(95)])

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brew install ffmpeg  
ffmpeg -i /path/to/input/file /path/to/output.mp4