PEP 8 check

kontrol/__init__.py

@@ -1,14 +1,14 @@
 from .complementary_filter.complementary_filter import ComplementaryFilter
 from .transfer_function import *
-from .sensact.matrix  import Matrix, SensingMatrix
+from .sensact.matrix import Matrix, SensingMatrix
 from .sensact.optical_lever import (
     OpticalLeverSensingMatrix, HorizontalOpticalLeverSensingMatrix,
     VerticalOpticalLeverSensingMatrix)
 from .core import spectral, foton
 from . import dmd
 
 
-## for ad hoc/optional packages
+# for ad hoc/optional packages
 import importlib
 ezca_spec = importlib.util.find_spec("ezca")
 ezca_exist = ezca_spec is not None

kontrol/complementary_filter/complementary_filter.py

@@ -1,6 +1,5 @@
 """Complementary filter class for sythesis
 """
-import control
 import numpy as np
 
 
@@ -53,7 +52,7 @@ class ComplementaryFilter():
         :math:`\mathcal{H}_\infty`-norm
         of the super sensor noise. The noise must be specified
         before using this method.
-    
+
     Notes
     -----
     This is a utility class for complementary filter synthesis,
@@ -120,7 +119,7 @@ def __init__(self, noise1=None, noise2=None, weight1=None, weight2=None,
 
     def h2synthesis(self, clean_filter=True, **kwargs):
         """Synthesize complementary filters using H2 synthesis.
-        
+
         Returns
         -------
         filter1 : TransferFunction
@@ -138,7 +137,7 @@ def h2synthesis(self, clean_filter=True, **kwargs):
 
     def hinfsynthesis(self, clean_filter=True, **kwargs):
         """Synthesize complementary filters using H-inifinity synthesis.
-        
+
         Returns
         -------
         filter1 : TransferFunction
@@ -242,7 +241,7 @@ def noise_super(self, f=None, noise1=None, noise2=None,
             The complementary filter for filtering noise1
             Use self.filter2 if not specified.
             Defaults None
-        
+
         Returns
         -------
         array

kontrol/complementary_filter/predefined.py

@@ -41,15 +41,6 @@ def sekiguchi(coefs):
 
     blend_freq = coefs[0]
     _coefs = [blend_freq]*4
-    # hpf_numerator = [
-    #     1,
-    #     7*blend_freq,
-    #     21*blend_freq**2,
-    #     35*blend_freq**3,
-    #     0, 0, 0, 0,
-    # ]
-    # hpf = control.tf(hpf_numerator, [1]) * control.tf([1], [1, blend_freq])**7
-    # lpf = 1 - hpf
     return modified_sekiguchi(_coefs)
 
 
@@ -94,7 +85,7 @@ def modified_sekiguchi(coefs):
 
 def generalized_sekiguchi(fb, order_low_pass, order_high_pass):
     """Generalized Sekiguchi Filter
-    
+
     Parameters
     ----------
     fb : float
@@ -103,7 +94,7 @@ def generalized_sekiguchi(fb, order_low_pass, order_high_pass):
         Order of roll-off of the low-pass filter
     order_high_pass : int
         Order of roll-off of the high-pass filter
-    
+
     Returns
     -------
     lpf : kontrol.TransferFunction
@@ -114,7 +105,7 @@ def generalized_sekiguchi(fb, order_low_pass, order_high_pass):
     nl = order_low_pass
     nh = order_high_pass
     den = (scipy.special.comb(nl+nh-1, np.arange(0, nl+nh))
-           *(2*np.pi*fb)**np.arange(0, nl+nh))
+           * (2*np.pi*fb)**np.arange(0, nl+nh))
     lpf_num = den[nl:]
     lpf = kontrol.TransferFunction(lpf_num, den)
     return lpf, 1-lpf
@@ -150,8 +141,9 @@ def lucia(coefs):
     p1, p2, z1, w1, q1, w2, q2 = coefs
     hpf = control.tf([1], [1/p1, 1])**5 * control.tf([1], [1/p2, 1])**3
     hpf *= control.tf([1/z1, 1], [1])
-    hpf *= control.tf([1, w1/q1, w1**2], [w1**2]) * control.tf([1, w2/q2, w2**2], [w2**2])
-    hpf *= control.tf([1, 0],[1])**3
+    hpf *= control.tf(
+        [1, w1/q1, w1**2], [w1**2]) * control.tf([1, w2/q2, w2**2], [w2**2])
+    hpf *= control.tf([1, 0], [1])**3
     hpf *= hpf.den[0][0][0]/hpf.num[0][0][0]
     lpf = 1 - hpf
     return (lpf, hpf)

kontrol/complementary_filter/synthesis.py

@@ -7,7 +7,7 @@
 
 def generalized_plant(noise1, noise2, weight1, weight2):
     """Return the generalized plant of a 2 complementary filter system
-    
+
     Parameters
     ----------
     noise1 : TransferFunction
@@ -45,7 +45,7 @@ def generalized_plant(noise1, noise2, weight1, weight2):
 #          [tf([1],[1]), tf([0],[1])]]
     p = kontrol.core.controlutils.tfmatrix2tf(p)
     return p
-    
+
 
 def h2complementary(noise1, noise2, weight1=None, weight2=None):
     """H2 optimal complementary filter synthesis

kontrol/core/algorithm.py

@@ -31,7 +31,7 @@ def bisection_method(
     x1 : float
         The first endpoint.
     x2 : float
-        The second endpoint. 
+        The second endpoint.
     val : float
         The target value.
     ftol : float, optional,
@@ -87,6 +87,3 @@ def bisection_method(
                 x2 = xm
     kontrol.logger.logger.error("Maximum number of iteration reached")
     return None
-
-
-

kontrol/core/controlutils.py

@@ -81,7 +81,7 @@ def zpk(zeros, poles, gain, unit='f', negate=True):
         for i in range(len(poles)):
             poles[i] = -poles[i]
 
-    zpk_tf = control.tf([gain],[1])
+    zpk_tf = control.tf([gain], [1])
     for z in zeros:
         zpk_tf *= control.tf([1/z, 1], [1])
     for p in poles:
@@ -283,7 +283,7 @@ def generic_tf(zeros=None, poles=None,
         poles_wn = []
     if poles_q is None:
         poles_q = []
-    
+
     zeros = np.array(zeros)
     poles = np.array(poles)
     zeros_wn = np.array(zeros_wn)
@@ -392,13 +392,7 @@ def tf_order_split(tf, max_order=20):
     zeros = tf.zeros()
     poles = tf.poles()
     gain = tf.minreal().num[0][0][0]
-    # for i in range(len(zeros)):
-        # if zeros[i]
-    nzero = len(zeros)
-    npole = len(poles)
-    niter_zero = int(np.ceil(nzero/max_order))
-    niter_pole = int(np.ceil(npole/max_order))
-
+
     global order_running
     global zero_running
     global tf_zero_list
@@ -409,7 +403,7 @@ def tf_order_split(tf, max_order=20):
     tf_zero_list = []
     pole_running = []
     tf_pole_list = []
-    
+
     def put_tf_zeros_into_list():
         """Use zeros in zero_running to create an all zero transfer function
         and put store them into tf_zero_list, and reset order_running to 0.
@@ -497,11 +491,11 @@ def put_tf_poles_into_list():
             order_running += 2
             zero_running += [zeros[i]]
         else:
-            pass  ## Ignore negative part of the complex pair.
-   
-    ## Add the reminders
+            pass  # Ignore negative part of the complex pair.
+
+    # Add the reminders
     put_tf_zeros_into_list()
-            
+
     for i in range(len(poles)):
         if poles[i].imag == 0:
             if order_running+1 > max_order:
@@ -514,8 +508,8 @@ def put_tf_poles_into_list():
             order_running += 2
             pole_running += [poles[i]]
         else:
-            pass  ## Ignore negative part of the complex pair.
-    
+            pass  # Ignore negative part of the complex pair.
+
     put_tf_poles_into_list()
 
     n_tf = max(len(tf_pole_list), len(tf_zero_list))
@@ -613,7 +607,7 @@ def clean_tf2(tf, tol_order=5, small_number=1e-25):
             tf_cleaned *= (s+abs(zero))/abs(zero)
         elif zero == 0:
             tf_cleaned *= s
-        
+
     for i, pole in enumerate(poles):
         if mask_poles[i]:  # Remove outliers
             continue
@@ -639,7 +633,7 @@ def clean_tf2(tf, tol_order=5, small_number=1e-25):
 
 def clean_tf3(tf, tol_order=5, small_number=1e-25):
     """Remove first coefficient if it is much smaller than the second
-    
+
     Parameters
     ----------
     tf : TransferFunction
@@ -651,7 +645,7 @@ def clean_tf3(tf, tol_order=5, small_number=1e-25):
         numerator and denominator.
     small_number : float, optional
         A small number to be added to the log10() in case 0 is encountered.
-    
+
     Returns
     -------
     tf_cleaned : TransferFunction
@@ -660,7 +654,7 @@ def clean_tf3(tf, tol_order=5, small_number=1e-25):
     num = tf.num[0][0].copy()
     den = tf.den[0][0].copy()
     if (abs(np.log10(num[0]) - np.log10(num[1])) > tol_order
-        and abs(np.log10(den[0]) - np.log10(den[1])) > tol_order):
+       and abs(np.log10(den[0]) - np.log10(den[1])) > tol_order):
         #
         tf_cleaned = control.tf(tf.num[0][0][1:], tf.den[0][0][1:])
     else:

kontrol/core/foton.py

@@ -48,9 +48,9 @@ def tf2foton(
         raise ValueError("expression {} not available."
                          "Please select expression from [\"zpk\", \"rpoly\"."
                          "".format(expression))
-    ## Divide tf into tfs with less than 20 order.
-    ## Do tf conversion.
-    ## Stack the string
+    # Divide tf into tfs with less than 20 order.
+    # Do tf conversion.
+    # Stack the string
     foton_expression = ""
     tf_list = kontrol.core.controlutils.tf_order_split(tf, max_order=20)
     if len(tf_list) > 1:
@@ -123,23 +123,23 @@ def tf2zpk(tf, root_location="s", significant_figures=6,
     str_zeros = ""  # String of list of zeros (placeholder)
     str_poles = ""  # String of list of poles (placeholder)
 
-    ## get zeros and poles.
+    # get zeros and poles.
     if root_location in ["f", "n"]:
         zeros /= 2*np.pi
         poles /= 2*np.pi
     if root_location == "n":
         zeros = -zeros.conjugate()
         poles = -poles.conjugate()
 
-    ## get zeros and poles list, and sort.
+    # get zeros and poles list, and sort.
     z_wn = np.sqrt(tf.zeros().real**2 + tf.zeros().imag**2)
     p_wn = np.sqrt(tf.poles().real**2 + tf.poles().imag**2)
     z_sort_arg = z_wn.argsort()
     p_sort_arg = p_wn.argsort()
     z_wn.sort()
     p_wn.sort()
 
-    ## get gain
+    # get gain
     gain = tf.minreal().num[0][0][0]
     if root_location in ["n"]:
         for wn in p_wn:
@@ -153,7 +153,7 @@ def tf2zpk(tf, root_location="s", significant_figures=6,
             else:
                 gain *= 2*np.pi
 
-    ## Convert to zpk expressing string
+    # Convert to zpk expressing string
     for zero in zeros[z_sort_arg]:
         if abs(zero.imag)/abs(zero.real+epsilon) < itol:
             str_zeros += "{:.{}g}".format(zero.real, significant_figures)
@@ -201,8 +201,8 @@ def tf2rpoly(tf, significant_figures=6):
 
     num = tf.minreal().num[0][0]
     den = tf.minreal().den[0][0]
-    str_num = ""  ## String of numerator coefficients
-    str_den = ""  ## String of numerator coefficients
+    str_num = ""  # String of numerator coefficients
+    str_den = ""  # String of numerator coefficients
     gain = num[0]
     num /= num[0]
 
@@ -260,12 +260,12 @@ def _order_gt(tf, order):
 
 def foton2tf(foton_string):
     """Convert a Foton string to TransferFunction
-    
+
     Parameters
     ----------
     foton_string : str
         The Foton string, e.g. zpk([0], [1; 1], 1, "n").
-    
+
     Returns
     -------
     tf : TransferFunction
@@ -283,7 +283,7 @@ def foton2tf(foton_string):
 
 def zpk2tf(foton_string):
     """Convert a Foton ZPK string to TransferFunction
-    
+
     Paramters
     ---------
     foton_string : str
@@ -311,7 +311,7 @@ def process_zp_string(zp_string):
         if zp_string == [""]:
             return np.array(zp)
         for string in zp_string:
-            #split real and imaginary
+            # split real and imaginary
             split = string.split("i*")
             if len(split) == 2:
                 real_string, imag_string = split
@@ -322,7 +322,7 @@ def process_zp_string(zp_string):
                 sign = "+"
             real_string = real_string.rstrip("+")
             real_string = real_string.rstrip("-")
-            
+
             zp_complex = f"{real_string}{sign}{imag_string}j"
             zp.append(complex(zp_complex))
         zp = np.array(zp)
@@ -346,7 +346,7 @@ def process_zp_string(zp_string):
         zeros = -zeros
         poles = -poles
 
-    tf = control.tf([1],[1])
+    tf = control.tf([1], [1])
     s = control.tf("s")
 
     for zero in zeros:
@@ -379,7 +379,7 @@ def process_zp_string(zp_string):
         tf *= gain
     elif root_location in "sf":
         tf *= gain / (tf.num[0][0][0]/tf.den[0][0][0])
-    
+
     return kontrol.TransferFunction(tf)
 
 
@@ -396,14 +396,15 @@ def rpoly2tf(foton_string):
     foton_string = foton_string.replace("(", "")
     foton_string = foton_string.replace(")", "")
     num_string, den_string, gain_string = foton_string.split(",")
+
     def string2floatarray(string):
         """Convert a string of float array to array"""
         string = string.replace("[", "")
         string = string.replace("]", "")
         string = string.split(";")
         float_array = []
         if string == [""]:
-            return np.array(float_array) 
+            return np.array(float_array)
         for value in string:
             float_array.append(float(value))
         return np.array(float_array)
@@ -417,7 +418,7 @@ def string2floatarray(string):
 
 def notch(frequency, q, depth, significant_figures=6):
     """Returns the foton expression of a notch filter.
-    
+
     Parameters
     ----------
     frequency : float