zacharybell

resource "google_storage_bucket" "website" {
  name          = "${local.prefix}-sbt-website"
  location      = "US"
  force_destroy = true

  website {
    main_page_suffix = "index.html"
  }
}

zacharybell

provider "aws" {
  region = "us-east-1"
  alias  = "us_east_1"
}

resource "aws_acm_certificate" "cert" {
  provider                  = aws.us_east_1
  domain_name               = var.site_domain
  subject_alternative_names = ["*.${var.site_domain}"]
  validation_method         = "DNS"

zacharybell

import { Configuration } from 'webpack';

import MiniCssExtractPlugin from 'mini-css-extract-plugin';
import HtmlWebpackPlugin from 'html-webpack-plugin';

const electron: Configuration = {
  target: 'electron-main',
  entry: './src/main/index.ts',
  output: {
    filename: 'main.js',

zacharybell

from datetime import datetime

import re

long_date       = r"(January|February|March|April|May|June|July|August|September|October|November|December) (0?[1-9]|1[0-9]|2[0-9]|30|31), (19|20)[0-9][0-9]"
short_date      = r"(0?[1-9]|1[0-2])(-|\/)(0?[1-9]|1[0-9]|2[0-9]|30|31)\2(19|20)[0-9][0-9]"
extra_long_date = r"the (1st|2nd|3rd|[4-9]th|1[0-9]th|20th|21st|22nd|23rd|2[4-9]th|30th|31st) of (January|February|March|April|May|June|July|August|September|October|November|December), (19|20)[0-9][0-9]"

def convert_long_date(long_date):  
    return datetime.strptime(long_date, '%B %d, %Y').strftime('%Y-%-m-%-d')

zacharybell

import numpy as np

def get_region(matrix, x1, x2, y1, y2):
  return matrix[y1:y2,x1:x2]

def compute_gradients(matrix, axis):
  gradients = np.zeros(shape=matrix.shape)
  if axis == 0:
    for i in range(matrix.shape[0] - 1):
      gradients[i,:] = matrix[i+1,:] - matrix[i,:]

zacharybell

def k_fold(X, y, estimator, k):
  # assuming that the data is already shuffled
  n = len(X)
  s = n / k
  
  score = 0
  
  for i in range(k):
    X_train = X[0:i*s] + X[(i+1)*s:-1]
    y_train = y[0:i*s] + y[(i+1)*s:-1]

zacharybell

import numpy as np

def mean_iou(labels, predictions, n_classes):
    mean_iou = 0.0
    seen_classes = 0

    for c in range(n_classes):
        labels_c = (labels == c)
        pred_c = (predictions == c)

zacharybell

set shiftwidth=2
set tabstop=2
set smarttab
set autoindent
set smartindent

set number

highlight LineNr ctermfg=green