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        "value": "By default, the end of the resampled data rises to meet the first\nsample of the next cycle for the FFT method, and gets closer to zero\nfor the polyphase method:\n\n"
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        "__type": "Code",
        "__tag": 4050,
        "value": "import numpy as np\nfrom scipy import signal\nimport matplotlib.pyplot as plt\n",
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        "value": "\n"
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        "value": "x = np.linspace(0, 10, 20, endpoint=False)\ny = np.cos(-x**2/6.0)\nf_fft = signal.resample(y, 100)\nf_poly = signal.resample_poly(y, 100, 20)\nxnew = np.linspace(0, 10, 100, endpoint=False)\n",
        "execution_status": "success"
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        "value": "\n"
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        "value": "plt.plot(xnew, f_fft, 'b.-', xnew, f_poly, 'r.-')\nplt.plot(x, y, 'ko-')\nplt.plot(10, y[0], 'bo', 10, 0., 'ro')  # boundaries\nplt.legend(['resample', 'resamp_poly', 'data'], loc='best')\n",
        "execution_status": "failure"
      },
      {
        "__type": "Code",
        "__tag": 4050,
        "value": "plt.show()\n",
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          "__tag": 4000,
          "module": "scipy",
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        "value": "\nThis default behaviour can be changed by using the padtype option:\n\n"
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        "__tag": 4050,
        "value": "N = 5\nx = np.linspace(0, 1, N, endpoint=False)\ny = 2 + x**2 - 1.7*np.sin(x) + .2*np.cos(11*x)\ny2 = 1 + x**3 + 0.1*np.sin(x) + .1*np.cos(11*x)\nY = np.stack([y, y2], axis=-1)\nup = 4\nxr = np.linspace(0, 1, N*up, endpoint=False)\n",
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        "value": "\n"
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        "value": "y2 = signal.resample_poly(Y, up, 1, padtype='constant')\ny3 = signal.resample_poly(Y, up, 1, padtype='mean')\ny4 = signal.resample_poly(Y, up, 1, padtype='line')\n",
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        "value": "\n"
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        "value": "for i in [0,1]:\n    plt.figure()\n    plt.plot(xr, y4[:,i], 'g.', label='line')\n    plt.plot(xr, y3[:,i], 'y.', label='mean')\n    plt.plot(xr, y2[:,i], 'r.', label='constant')\n    plt.plot(x, Y[:,i], 'k-')\n    plt.legend()\n",
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