Correct for flake8.

libraries/base/common/python/try_round.py

@@ -22,23 +22,14 @@
 
 # Author: Eric Kooistra
 # Date: may 2021
-# Purpose:
-#   Simulate linearity of rounding
-# Description:
-#   Usage:
-#   > python3 try_round.py -N 1024 -ampl 12 --useplot
-
-
-import argparse
-import numpy as np
-import matplotlib
-matplotlib.use('tkagg')  # to make X11 forwarding work
-import matplotlib.pylab as plt
 
 """Try rounding
 
+Simulate linearity of rounding.
+
 Usage:
 > python try_round.py -h
+> python3 try_round.py -N 1024 -w 8 -f 3 --useplot
 
 Note:
 . For values exactly halfway between rounded decimal values, NumPy rounds to
@@ -47,8 +38,11 @@ Note:
 """
 
 import argparse
+
 import numpy as np
-import matplotlib.pylab as plt
+import matplotlib
+matplotlib.use('tkagg')  # to make X11 forwarding work
+import matplotlib.pyplot as plt
 import common as cm
 
 figNr = 1
@@ -57,7 +51,7 @@ figNr = 1
 _parser = argparse.ArgumentParser('try_round')
 _parser.add_argument('-N', default=1024, type=int, help='Number of points of FFT')
 _parser.add_argument('-w', default=8, type=int, help='Total number of bits')
-_parser.add_argument('-f', default=0, type=int, help='Number of bits of fraction that gets rounded')
+_parser.add_argument('-f', default=1, type=int, help='Number of bits of fraction that gets rounded')
 _parser.add_argument('--useplot', action='store_true', dest='useplot', default=False, help='Default without plotting, else with plotting')
 args = _parser.parse_args()
 
@@ -71,8 +65,8 @@ useplot = args.useplot
 # Sinus
 t = 2 * np.pi * np.arange(0, N) / N
 a_adc = np.round(ampl*np.sin(t))
-a_away = [cm.int_round(inp = x, r = fraction, direction="HALF_AWAY") for x in a_adc]
-a_even = [cm.int_round(inp = x, r = fraction, direction="HALF_EVEN") for x in a_adc]
+a_away = [cm.int_round(inp=x, r=fraction, direction="HALF_AWAY") for x in a_adc]
+a_even = [cm.int_round(inp=x, r=fraction, direction="HALF_EVEN") for x in a_adc]
 a_adc = a_adc / scale
 
 # Spectrum

libraries/base/common/python/try_round_weight.py

@@ -62,8 +62,6 @@ import matplotlib
 matplotlib.use('tkagg')  # to make X11 forwarding work
 import matplotlib.pyplot as plt
 
-import common as cm
-
 # Parse arguments to derive user parameters
 _parser = argparse.ArgumentParser(
     description="".join(textwrap.dedent("""\
@@ -145,29 +143,29 @@ sigmas_ratio_sq_input = np.nan * np.zeros((N_weights, N_sigmas))  # w rows, s co
 sigmas_qq = np.zeros((N_weights, N_sigmas))
 sigmas_sq = np.zeros((N_weights, N_sigmas))
 for s, sigma in enumerate(sigmas):
-   noise_s = noise * sigma
-   if resolution == 0:
-       if fraction == 0:
-           # Default use full double resolution of fraction of noise_s
-           noise_q = np.round(noise_s)
-       else:
-           # First use round() to get noise_f with a fraction of fraction number of LSbits
-           noise_f = np.round(noise_s * fraction_factor) / fraction_factor
-           # Then use round to round the fraction of fraction number of LSbits in noise_f
-           noise_q = np.round(noise_f)
-   else:
-       noise_q = np.round(noise_s * resolution_factor) / resolution_factor
+    noise_s = noise * sigma
+    if resolution == 0:
+        if fraction == 0:
+            # Default use full double resolution of fraction of noise_s
+            noise_q = np.round(noise_s)
+        else:
+            # First use round() to get noise_f with a fraction of fraction number of LSbits
+            noise_f = np.round(noise_s * fraction_factor) / fraction_factor
+            # Then use round to round the fraction of fraction number of LSbits in noise_f
+            noise_q = np.round(noise_f)
+    else:
+        noise_q = np.round(noise_s * resolution_factor) / resolution_factor
 
-   for w, weight in enumerate(weights):
-       noise_q_weighted_q = np.round(noise_q * weight)  # apply weight to rounded noise
-       noise_s_weighted_q = np.round(noise_s * weight)  # apply weight to original noise
-       s_qq = np.std(noise_q_weighted_q)
-       s_sq = np.std(noise_s_weighted_q)
-       sigmas_qq[w][s] = s_qq
-       sigmas_sq[w][s] = s_sq
-       if s_sq != 0:
-           sigmas_ratio_qq_sq[w][s] = s_qq / s_sq  # weighted rounded noise sigma / weighted noise sigma
-           sigmas_ratio_sq_input[w][s] = s_sq / sigma  # weighted noise sigma / input noise sigma
+    for w, weight in enumerate(weights):
+        noise_q_weighted_q = np.round(noise_q * weight)  # apply weight to rounded noise
+        noise_s_weighted_q = np.round(noise_s * weight)  # apply weight to original noise
+        s_qq = np.std(noise_q_weighted_q)
+        s_sq = np.std(noise_s_weighted_q)
+        sigmas_qq[w][s] = s_qq
+        sigmas_sq[w][s] = s_sq
+        if s_sq != 0:
+            sigmas_ratio_qq_sq[w][s] = s_qq / s_sq  # weighted rounded noise sigma / weighted noise sigma
+            sigmas_ratio_sq_input[w][s] = s_sq / sigma  # weighted noise sigma / input noise sigma
 # Transpose [w][s] to have index ranges [s][w]
 sigmas_ratio_qq_sq_T = sigmas_ratio_qq_sq.transpose()
 sigmas_ratio_sq_input_T = sigmas_ratio_sq_input.transpose()

libraries/base/common/python/try_wrap.py

@@ -31,11 +31,6 @@
 import argparse
 import textwrap
 
-import numpy as np
-import matplotlib
-matplotlib.use('tkagg')  # to make X11 forwarding work
-import matplotlib.pyplot as plt
-
 import random
 
 import common as cm
@@ -86,4 +81,3 @@ else:
     print('Error:')
     print(x_wrap_sum_wrap)
     print(x_wrap_sum)
-