Anurag Saha Roy lazyoracle

Combining two git repositories

Use case: You have repository A with remote location rA, and repository B (which may or may not have remote location rB). You want to do one of two things:

preserve all commits of both repositories, but replace everything from A with the contents of B, and use rA as your remote location
actually combine the two repositories, as if they are two branches that you want to merge, using rA as the remote location

NB: Check out git subtree/git submodule and this Stack Overflow question before going through the steps below. This gist is just a record of how I solved this problem on my own one day.

Before starting, make sure your local and remote repositories are up-to-date with all changes you need. The following steps use the general idea of changing the remote origin and renaming the local master branch of one of the repos in order to combine the two master branches.

	import numpy as np
	import matplotlib.pyplot as plt

	E_J = 20e9
	w = 5e9
	anharm = -300e6

	N_phis = 101
	phis = np.linspace(-np.pi,np.pi,N_phis)
	mid_idx = int((N_phis+1)/2)

	from qiskit import *
	import qiskit

	circ = QuantumCircuit(1)
	circ.h(0)

	transpiled_circ = qiskit.compiler.transpile(circ, basis_gates = ['rx', 'ry', 'rz'])

	transpiled_circ.draw()
	print(transpiled_circ)

	# https://github.com/CMA-ES/pycma/tree/master
	import cma
	from pprint import pprint
	import argparse

	parser = argparse.ArgumentParser(description='search term for pycma options')
	parser.add_argument('-s', '--search', type=str, help='search for options containing this term')
	args = parser.parse_args()

	pprint(cma.CMAOptions(args.search))

	# install miniforge for arm64
	# https://github.com/conda-forge/miniforge
	name: tensorflow
	channels:
	- apple
	- conda-forge
	dependencies:
	- ipykernel=6.6
	- jupyter=1.0
	- matplotlib=3.5

	name: c3-dev
	channels:
	- conda-forge
	dependencies:
	- ipykernel=6.6
	- jupyter=1.0
	- matplotlib=3.5
	- notebook=6.4
	- pip=21.3
	- python=3.8

	from typing import Callable
	from numba import njit, prange
	import numpy as np

	@njit()
	def my_square(x: float) -> float:
	return x**2

	def bayes_numr(x: float, t: float) -> float:
	return (1. / np.sqrt(2. * np.pi)) * np.exp(-np.square(x) / 2.) * np.square(np.cos(x * t / 2.0))

	pip install -U pyan3==1.1.1
	pyan3 <path/to/file> --uses --no-defines --colored --grouped --annotated --dot > call-graph.dot
	pip install graphviz
	python
	>>> from graphviz import render
	>>> render('dot', 'png', 'call-graph.dot')
	'call-graph.dot.png'
	>>> render('dot', 'svg', 'call-graph.dot')
	'call-graph.dot.svg'