See also #14877, where some questions were raised about the correctness of this function.

See also #14877, where some questions were raised about the correctness of this function.

@eric-wieser, thank you for your prompt reply.
I read #14877.
However, the current source would not be correct. I show an example as below.

The following code draws two normalized phase response, one is calculated in radian and another is in degree.
The result in radian is correct, it is not necessary to wrap 2*pi at the point shifted just pi though.
The result in degree is not correct. The phase is changed 180 degree at the point shifted pi.

Code (Python ver 3.7.7):

# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal

deg_180 = 180

# HPF frequency response
Fs = 5000
Fc = 20
win = 'hamming'

numtaps = 501
res = 65536

b = signal.firwin(numtaps, Fc, window=win, fs=Fs, pass_zero=False)
w, h = signal.freqz(b, fs=Fs, worN=res)

# Radian
p_wrap = np.angle(h)
p_unwrap = np.unwrap(p_wrap)

p_wrap_n = p_wrap / (2 * np.pi)
p_unwrap_n = p_unwrap / (2 * np.pi)

plt.figure()
plt.plot(w, p_wrap_n, label="Wrapped")
plt.plot(w, p_unwrap_n, label="Unwrapped")
plt.axis([0, 100, -6, 6])
plt.ylabel('Normalized phase [*2*PI rad]')
plt.xlabel('Frequency [Hz]')
plt.legend(loc='best', framealpha=.5, numpoints=1)
plt.title('Radian')
plt.show()

# Degree
p_wrap_deg = np.angle(h, deg=True)
p_unwrap_deg = np.unwrap(p_wrap_deg, discont=deg_180)

p_wrap_deg_n = p_wrap_deg / (2 * deg_180)
p_unwrap_deg_n = p_unwrap_deg / (2 * deg_180)

plt.figure()
plt.plot(w, p_wrap_deg_n, label="Wrapped")
plt.plot(w, p_unwrap_deg_n, label="Unwrapped")
plt.axis([0, 100, -6, 6])
plt.ylabel('Normalized phase [*2*180 deg]')
plt.xlabel('Frequency [Hz]')
plt.legend(loc='best', framealpha=.5, numpoints=1)
plt.title('Degree')
plt.show()

Result:

The correct result is obtained in degree by using the pull request code.

Result:

@scimax also mentioned about the problem in the case discont=180 in #14877.
My pull request may not be good but could you please confirm the above?

I withdraw about L1543. It was wrong. I am sorry to bother you.
Still, regarding L1540 and L1541, it looks correct.

I have to say I took a quick look yesterday and was very confused about the factor 1.5, but as I had no time to think this through I didn't want to ask yet.

I compared it to my solution, and, from a semantics point of view I came up with the same solution. But I couldn't solve the issue with integers returning floats, which are mentioned in #14877 .
And I think you misused the parameter discont here. It's purpose was to restrict the size of jumps to be corrected while still dealing with an interval size of 2 pi. But I would like to test your examples.

@eric-wieser , the tests you mentioned in #14877 which failed, are working with this. It's just a mistake in L1540.

I just realized, I can't propose corrections. Neither here nor in #14877 . Shall I open another PR for that?

I misunderstood that unwrap() could also be used in degree by changing discont to 180.
Now, I know that this function is only for radian.
I apologize for taking your time and thank you all for your polite answer. @eric-wieser @scimax
This pull request will be deleted.

Also, I confirmed #16987.
This solves what I wanted to do. I agree with this change.

Thanks for the thorough summary @tatsuoka999, reports with graphs make a nice change :)