planetceres

Installation Notes for pipenv on Ubuntu 18.04

1. Add ~/.local/bin to PATH

pypa/pipenv#2122 (comment)

echo 'export PATH="${HOME}/.local/bin:$PATH"' >> ~/.bashrc

planetceres

#!/bin/bash

# https://gist.github.com/robwierzbowski/5430952/
# Create and push to a new github repo from the command line.  
# Grabs sensible defaults from the containing folder and `.gitconfig`.  
# Refinements welcome.

# Gather constant vars
CURRENTDIR=${PWD##*/}
GITHUBUSER=$(git config github.user)

planetceres

#!/bin/sh

export PATH=$ORIGINAL_PATH
unset ORIGINAL_PATH

export LD_LIBRARY_PATH=$ORIGINAL_LD_LIBRARY_PATH
unset ORIGINAL_LD_LIBRARY_PATH

planetceres

#!/bin/sh
ORIGINAL_PATH=$PATH
export PATH=/usr/local/cuda-9.0/bin:$PATH

ORIGINAL_LD_LIBRARY_PATH=$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:/usr/local/cuda-9.0/extras/CUPTI/lib64:/lib/nccl/cuda-9:$LD_LIBRARY_PATH

planetceres

#!/bin/bash

# Don't actually run this file as a script, just follow directions in the pdf which doesn't copy/paste
# https://www.intel.com/content/www/us/en/support/articles/000028171/emerging-technologies/intel-realsense-technology.html
# Copy/paste instructions https://github.com/IntelRealSense/librealsense/issues/2884#issuecomment-448049644

echo 'deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo xenial main'| sudo tee /etc/apt/sources.list.d/realsense-public.list

sudo apt-key adv--keyserverkeys.gnupg.net --recv-key 6F3EFCDE
sudo apt-get update

planetceres

#!/bin/bash
## This gist contains step by step instructions to install cuda v9.0 and cudnn 7.2 in ubuntu 18.04

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

planetceres

import cProfile
import pstats
import my_slow_module
cProfile.run('my_slow_module.run()', 'restats')
p = pstats.Stats('restats')
p.sort_stats('cumulative').print_stats(30)

planetceres

planetceres

# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()

# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])

# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!

planetceres

def rgb_from_prob(value, minimum=0, maximum=1):
    '''
    Based on: https://stackoverflow.com/a/20792531/3450793
    ''' 
    minimum, maximum = float(minimum), float(maximum)
    ratio = 2 * (value-minimum) / (maximum - minimum)
    g = int(max(0, 255*(1 - ratio)))
    r = int(max(0, 255*(ratio - 1)))
    b = 255 - g - r