MartinNowak

#!/usr/bin/env bash

set -ueEo pipefail

if ! dnf needs-restarting --reboothint; then
  systemctl reboot --message='Rebooting after dnf-automatic updates'
fi

mapfile -t services < <(dnf needs-restarting --services)
if [[ "${#services[*]}" -ne 0 ]]; then

MartinNowak

#!python

from numpy import cos, sin, pi, absolute, arange
from scipy.signal import windows, kaiserord, lfilter, firwin, freqz
from pylab import figure, clf, plot, xlabel, ylabel, xlim, ylim, title, grid, axes, show


N = window_size_in_days = 20

#------------------------------------------------

MartinNowak

#!/usr/bin/env python
# coding: utf-8

# # scikit-hts showcase: [M5 kaggle competition](https://www.kaggle.com/c/m5-forecasting-accuracy)
#
# In this notebook we will use the data from the Kaggle competiton to perform some hierarchical forecasting. The problem is particularly well suited for the library, as there is a clear hierarchical relationship between each of the series: we have states, stores, categories, departments, and items; sum of sales of items resolve to departments, which summed resolved to categories and so forth.
#
#
# We will however limit the scope of the forecasting task to producing forecasts at the
# department level, rather than going to the full extent and forecasting for single items.

MartinNowak

Orchestration for dlang release building

send aws credentials

add gpg key

gpg –keyring $PWD/d-keyring.gpg –no-default-keyring –list-keys –with-fingerprint

Bump ldc version with major dlang releases, keep it for minor dlang release

Bump D version (to -beta.1)

Bump Dub version (mostly only with major release, compare e.g. dub v1.26.0…stable to check for bugfixes and minor releases)

We do -beta.1 for all releases and an additional -rc.1 for major releases

(status quo: 2 weeks beta+rc phase for major, 1 week beta for minor releases)

MartinNowak

#!/usr/bin/env bash

set -ueo pipefail

function cleanup {
    rm -rf "$TMP"
}
TMP=$(mktemp -d)
trap cleanup EXIT
cd "$TMP"

MartinNowak

import os, sys

import google.protobuf
from tensorflow.core.protobuf import saved_model_pb2
import tensorflow as tf


def convert_saved_model_to_pbtxt(path):
    saved_model = saved_model_pb2.SavedModel()
    with open(os.path.join(path, 'saved_model.pb'), 'rb') as f:

MartinNowak

//==============================================================================
//

struct String
{
    /// clone string, doesn't escape, but return value must have independent lifetime
    String clone() scope
    {
        return String();
    }

MartinNowak

library(ggplot2)
library(dplyr)
library(plyr)

data <- read.csv('capacities.csv')
data <- ddply(data, .(growth_factor), mutate, step = seq_along(capacity))
data$growth_factor <- factor(data$growth_factor)

p <- ggplot(data, aes(x=step, y=capacity, color=growth_factor)) + geom_step() + geom_point(size = 0.5)
ggsave("capacity_steps.png", p)

MartinNowak

// ==== phobos
// git log --grep='convert docstring examples to unittests' --pretty=%H
ba596549cc76547e1cb78177ed3d3d99668f9212
04654c071d1b7e59b53aa6f269dfe209966263cf
afc40287e02042df43bc763595869bedee15e8de
66e0dc39c5212821208b496800080210f7146ff9
ce795612149097cc6f2bcaa32da4a1023dedaa28
167b28679bd3b9f2639341e78b102616e2223efb
6c386d6f3165f062d0722155dc64a87de4c3e1b2
d81030ab8a15de5353735c646807308ec3bbf3b0

MartinNowak

#!/usr/bin/env bash

set -ueo pipefail

set -x

ROOT="$PWD"
LATEST_D_VER=v$(curl -fsS http://downloads.dlang.org/releases/LATEST)
BUILD_LDC_VER=v1.30.0
D_VER=v2.101.0-beta.1