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View Sentence Transformer: all-MiniLM-L6-v2
Type your search: What is Germany?
(Document(page_content="Germany has been described as a [[great power]] with [[Economy of Germany|a strong economy]]; it has the [[List of sovereign states in Europe by GDP (nominal)|largest economy in Europe]], the world's [[List of countries by GDP (nominal)|fourth-largest economy by nominal GDP]] and the [[List of countries by GDP (PPP)|fifth-largest by PPP]]. As a global power in industrial, [[Science and technology in Germany|scientific and technological]] sectors, it is both the world's [[List of countries by exports|third-largest exporter]] and [[List of countries by imports|importer]]. As a [[developed country]] it [[Social security in Germany|offers social security]], [[Healthcare in Germany|a universal health care system]] and [[Higher education in Germany|a tuition-free university education]]. Germany is a member of the [[United Nations]], the European Union, [[NATO]], the [[Council of Europe]], the [[G7]], the [[G20]] and the [[OECD]]. It has the [[List of World
@anbnyc
anbnyc / README.md
Last active September 24, 2021 13:15
Unofficial README for NYC Ranked Choice Voting Cast Vote Record (CVR)
View README.md

Unofficial README for NYC Ranked Choice Voting Cast Vote Record (CVR)

The NYC BOE released the data files, but no metadata or explanation, so we have to do this ourselves.

What is in the files?

Each row is a cast vote, and each column is a preference for a candidate. These are the columns that appear in all spreadsheets, regardless of what borough or ballot type they are:

Column Explanation
Cast Vote Record unique ID number
Precinct AD (assembly district) and ED (election district) where the voter is registered(your polling place is determined by your AD/ED)
@jpivarski
jpivarski / final-notebook.ipynb
Last active August 11, 2021 11:58
Replaced vibrating string's overtones with hydrogen atom in https://gist.github.com/endolith/3066664
View final-notebook.ipynb
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View Culture Drone Nanomissile Firepower.md

In the accommodation block behind her, the nanomissile embedded in Visquile’s brain sensed his Soulkeeper about to read and save his mind. The explosion of the missile’s warhead destroyed the whole building. Debris rained down, around and through her as she walked calmly away.

  • Look To The Windward, Closure
View C5E Nanomissile Acceleration.md

The nanomissiles fired at the Affronter ship accelerated towards it in a cloud of sparkling light ahead of the drone; they were picked off, one by one, over the course of a millisecond, in a dizzy flaring scatter of light-blossoms, their tiny warheads and the remains of their anti-matter fuel erupting together; the last one to be targeted by the Affronter’s effector and forced to self-destruct had closed the range to the ship by less than a kilometre.

Behind, all nine of the tumbling nanomissiles must have been picked out by the effector as well, because they detonated too.

  • Excession, Chapter 4 - Page 135
@on2air
on2air / same-table-backlinks.js
Last active May 20, 2023 08:49
Same Table Backlinks
View same-table-backlinks.js
@FedeMiorelli
FedeMiorelli / turbo_colormap_mpl.py
Last active March 31, 2023 02:45
Turbo Colormap for Matplotlib
View turbo_colormap_mpl.py
# -*- coding: utf-8 -*-
"""
Created on 2019-08-22 09:37:36
@author: fmiorell
"""
# This script registers the "turbo" colormap to matplotlib, and the reversed version as "turbo_r"
# Reference: https://ai.googleblog.com/2019/08/turbo-improved-rainbow-colormap-for.html
View turbo_colormap.R
# License: Apache 2.0
# A straightforward translation of the Python code:
turbo_colormap_data <- matrix(
c(
c(0.18995, 0.07176, 0.23217),
c(0.19483, 0.08339, 0.26149),
c(0.19956, 0.09498, 0.29024),
c(0.20415, 0.10652, 0.31844),
@mikhailov-work
mikhailov-work / turbo_colormap.py
Created August 8, 2019 23:31
Turbo Colormap Look-up Table
View turbo_colormap.py
# Copyright 2019 Google LLC.
# SPDX-License-Identifier: Apache-2.0
# Author: Anton Mikhailov
turbo_colormap_data = [[0.18995,0.07176,0.23217],[0.19483,0.08339,0.26149],[0.19956,0.09498,0.29024],[0.20415,0.10652,0.31844],[0.20860,0.11802,0.34607],[0.21291,0.12947,0.37314],[0.21708,0.14087,0.39964],[0.22111,0.15223,0.42558],[0.22500,0.16354,0.45096],[0.22875,0.17481,0.47578],[0.23236,0.18603,0.50004],[0.23582,0.19720,0.52373],[0.23915,0.20833,0.54686],[0.24234,0.21941,0.56942],[0.24539,0.23044,0.59142],[0.24830,0.24143,0.61286],[0.25107,0.25237,0.63374],[0.25369,0.26327,0.65406],[0.25618,0.27412,0.67381],[0.25853,0.28492,0.69300],[0.26074,0.29568,0.71162],[0.26280,0.30639,0.72968],[0.26473,0.31706,0.74718],[0.26652,0.32768,0.76412],[0.26816,0.33825,0.78050],[0.26967,0.34878,0.79631],[0.27103,0.35926,0.81156],[0.27226,0.36970,0.82624],[0.27334,0.38008,0.84037],[0.27429,0.39043,0.85393],[0.27509,0.40072,0.86692],[0.27576,0.41097,0.87936],[0.27628,0.42118,0.89123],[0.27667,0.43134,0.90254],[0.27691,0.44145,0.913
@suvojit-0x55aa
suvojit-0x55aa / gaussian.py
Created August 1, 2019 12:39
Python Numpy Gaussian Function
View gaussian.py
def gauss_map(size_x, size_y=None, sigma_x=5, sigma_y=None):
if size_y == None:
size_y = size_x
if sigma_y == None:
sigma_y = sigma_x
assert isinstance(size_x, int)
assert isinstance(size_y, int)
x0 = size_x // 2