# Understanding the FFT phase spectrum with a simple example

I'm trying to compute the DFT using scipy's functions. I don't understand why the phase spectrum of a simple sine wave with 2 Hz frequency doesn't show $$\pm\pi/2$$ at the $$\pm 2Hz$$ frequencies. Instead, the phase plot seems to have some linear dependence in the frequency, which I don't understand. I provide the code for assistance. How can this be fixed? Looks like a simple issue I'm not grasping. Please help.

import numpy as np
import matplotlib.pyplot as plt
from scipy.fftpack import fft, fftfreq

# 1Hz sine wave
npts  = 100
tmax  = 10
t     = np.linspace(0, tmax, npts)
y     = np.sin(2*np.pi*2*t)
dt    = tmax/npts

# FFT computation
Y      = fft(y)
freq   = fftfreq(npts, d=dt)
amplit = abs(Y)/npts
phase  = np.angle(Y)
phase  = phase / np.pi

fig, ax = plt.subplots(1, 2, figsize=(10,4))
ax.plot(freq, amplit)
ax.plot(freq, phase)

ax.plot([2,2], [0,0.5], '--')
ax.plot([-2,-2], [0,0.5], '--')
ax.plot([2,2], [-1,1], '--')
ax.plot([-2,-2], [-1,1], '--') As @hotpaw2 says, the FFT assumes periodic boundary conditions, that is the next point on the right should be equal to the first point on the left. It's not the case in your code because the time $$t=10$$ is included in your time array. The next point on the right is thus $$t=10+dt$$ and you get the discontinuity because $$y(10+dt) \neq y(0)$$. You can fix this by defining the time array as t=np.linspace(0, tmax, npts, endpoint=False). Now this fix will only work as long as the time span is an integer number of the signal period. If it's not you'll have to rely on @hotpaw2's more general solution.
PS: if your version of scipy allows it, you should use the newer submodule scipy.fft instead of the legacy submodule scipy.fftpack.