basic_cga_benchmarkipynb

Basic Benchmark.ipynb

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      "source": "from clifford import MVArray\nfrom clifford.g3c import *\nimport numpy as np\nimport itertools\n\ndef chunk(it, n):\n    try:\n        while True:\n            xs = []  # The buffer to hold the next n items\n            for _ in range(n):\n                xs.append(next(it))\n            yield xs\n    except StopIteration:\n        yield xs",
      "execution_count": null,
      "outputs": []
    },
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      "source": "%%prun -s cumulative\n\n# Generate 9999 random conformal points\nP = MVArray([up(np.random.randn()*e1 + np.random.randn()*e2 + np.random.randn()*e3) for _ in range(9999)])\n\n# Translate them with a rotor\nt = np.random.randn()*e1 + np.random.randn()*e2 + np.random.randn()*e3\nR = (1 - 0.5*t*einf).normal()\nP2 = R*P*~R\n\n# Wedge them together\nP2 = MVArray([MVArray(X).op()(3).normal() for X in chunk(P2.__iter__(), 3) if len(X) > 0])\nP2",
      "execution_count": null,
      "outputs": []
    }
  ],
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