23ccozad

deeplycloudy

# Here’s the URL to a journal’s search results page for papers from the Geostationary Lightning Mapper that
# were published from 2018-2021. There are several pages of results; below is an example of the third and final URL

# Download the webpage. Do this for each page of the search results, changing the URL and output filename:

curl "https://journals.ametsoc.org/search?access_0=all&fromDate=2018&page=3&pageSize=50&q1=geostationary+lightning+mapper&sort=relevance&toDate=2021" > page3dois.txt

# Then concatenate all three files, and save out just the DOIs linked on each page.

cat page[1-3]dois.txt | grep -Eoi '<a [^>]+>' | 

mcnees

%%-----------------------------------------------------------------------
%% Make your own quadrille, graph, hex, etc paper!
%% Uses the pgf/TikZ package for LaTeX, which should be part of
%% any modern TeX installation.
%% Email: mcnees@gmail.com 
%% Twitter: @mcnees
%%-----------------------------------------------------------------------

\documentclass[11pt]{article}

teoliphant

import numpy as np

def array_for_sliding_window(x, wshape):
    """Build a sliding-window representation of x.

    The last dimension(s) of the output array contain the data of
    the specific window.  The number of dimensions in the output is 
    twice that of the input.

    Parameters

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

splinterofchaos

#ifndef PY_H
#define PY_H

#include <Python.h>
#include <type_traits>
#include <utility>
#include <string>

template<typename R, typename...X>

sklam

import json
from pprint import pprint as pp

import numpy as np
from numba import autojit, typeof, int32

INF = float('inf')

@autojit
def jenks_matrics_init(data, n_classes, ):

vene

# Author: Vlad Niculae <vlad@vene.ro>
# Makes use of memory_profiler from Fabian Pedregosa
# available at https://github.com/fabianp/memory_profiler

from IPython.core.magic import Magics, line_magic, magics_class


class MemMagics(Magics):
    @line_magic
    def memit(self, line='', setup='pass'):

deeplycloudy

""" Play an audio file with pyaudio while concurrently showing audio playhead 
on a matplotlib plot of the audio time series and spectrogram.

Adjust duration and filename in the script below to reflect your audio file.

v. 0.1
21 Mar 2012 
Eric Bruning
"""

WeatherGod

So, provided you have some image files of form "_tmp0000.png", you can run generate_movies.sh to create a "result.txt" file which contains a list of the files successfully generated.

Additional columns are used to indicate testing status: '1' (failed), '0' (successful), '0.5' (works, but serious artifacts), '?' (couldn't try).

The script will provide the first column by testing if the movie plays using ffplay. Note, no movie gets displayed to the screen, so this is fairly quick. I have included my "result.txt" file which contains testing results for additional platforms. Platforms are:
* LibreOffice Impress on Linux
* QuickTime on Mac
* MS Office PowerPoint on Mac
* OpenOffice Impress on Mac