notebooks/tests.md

+#tests.ipynb [notebook](tests.ipynb) [html](tests.html)
+
+
+```python
+import sys
+from __future__ import division
+```
+
+
+```python
+import numpy as np
+from phasor.utilities.ipynb.displays import *
+from phasor.utilities.ipynb.sympy import *
+
+import declarative
+```
+
+    Populating the interactive namespace from numpy and matplotlib
+    Sympy version:  1.0
+
+
+
+```python
+import phasor.utilities.version as version
+print(version.phasor_git_version())
+
+from phasor.utilities.np import logspaced
+import scipy.signal
+import iirrational
+```
+
+    b'2017-10-09 22:05:43 -0400 (8b71fced6ae3697741af9b5085e7f7509ba0dc98)'
+
+
+
+```python
+F_nyquist = 16384 / 2
+F_AC = F_nyquist * 2 * np.arange(0, 1001) / 301
+    
+F_AC = logspaced(1, 7000, 500)
+ZPKz = (
+    [
+        .9,
+        -.3,
+        .1+.95j,
+        .1-.95j,
+        #.999 * np.exp(1j * np.pi * .001),
+        #.999 * np.exp(1j * np.pi * -.001),
+    ], 
+    [
+        #.9,
+        .99,
+        #.999 * np.exp(1j * np.pi * .002),
+        #.999 * np.exp(1j * np.pi * -.002),
+        #.97,
+        -0.03+.95j,
+        -.03-.95j,
+        .95 + .2j,
+        .95 - .2j,
+        #-.2,
+    ], 
+    10
+)
+
+ZPKz = (
+    [
+        .9,
+        -.3,
+        .1+.95j,
+        .1-.95j,
+    ], 
+    [
+        #.9,
+        .99,
+        #.97,
+        -0.03+.95j,
+        -.03-.95j,
+        #-.2,
+    ], 
+    10
+)
+
+
+
+
+b,a = scipy.signal.zpk2tf(*ZPKz)
+
+
+Fb = mplfigB(Nrows=2)
+w, h = scipy.signal.freqz_zpk(*ZPKz , worN = F_AC / F_nyquist * np.pi)
+F_exact = h
+Fb.ax0.loglog(F_AC, abs(h), label = 'discrete_ZPK')
+Fb.ax1.semilogx(F_AC, np.angle(h), label = 'discrete_ZPK')
+
+w, h = scipy.signal.freqz(b, a , worN = F_AC / F_nyquist * np.pi)
+#F_exact = h
+Fb.ax0.loglog(F_AC, abs(h), label = 'discrete_BA')
+Fb.ax1.semilogx(F_AC, np.angle(h), label = 'discrete_BA')
+
+Fb.ax0.legend()
+```
+
+
+
+
+    <matplotlib.legend.Legend at 0x7f2b55882240>
+
+
+
+
+![png](tests-ipynb/tests_3_1.png)
+
+
+
+```python
+b
+```
+
+
+
+
+    array([ 10.     ,  -8.     ,   7.625  ,  -4.935  ,  -2.46375])
+
+
+
+
+```python
+R = np.random.randn(len(F_AC)) + 1j*np.random.randn(len(F_AC))
+F_noise = F_exact * (1 + R / 10)
+```
+
+
+```python
+
+fitz = [iirrational.fit_zeros(
+    F_AC, 
+    F_noise, 
+    W = 10, 
+    #npoles = 10, 
+    nzeros = len(ZPKz[0]), 
+    F_nyquist = F_nyquist,
+    ZPK=ZPKz,
+)]
+```
+
+
+```python
+fitz = iirrational.fit_series(
+    F_AC, 
+    F_noise, 
+    W = 10, 
+    npoles_seq = np.arange(5, 10), 
+    nzeros_seq = 7, 
+    F_nyquist= F_nyquist,
+    max_size = 100,
+    func = iirrational.fit_pzpz,
+)
+
+
+#fits
+```
+
+
+```python
+fitz = [iirrational.fit_poles(
+    F_AC, 
+    F_noise, 
+    W = 10, 
+    npoles = len(ZPKz[1]), 
+    F_nyquist = F_nyquist,
+    ZPK=ZPKz,
+)]
+```
+
+
+```python
+fitz = [iirrational.fit_pzpz(
+    F_AC, 
+    F_noise, 
+    W = 10, 
+    npoles = 10, 
+    nzeros = 10, 
+    F_nyquist = F_nyquist,
+    #ZPK=ZPKz,
+)]
+```
+
+
+```python
+Fb = mplfigB(Nrows=3)
+
+Fb.ax0.loglog(F_AC, abs(F_exact), label = 'Fexact')
+Fb.ax1.semilogx(F_AC, np.angle(F_exact), label = 'Fex')
+
+Fb.ax0.loglog(F_AC, abs(F_noise), label = 'Fnoise')
+Fb.ax1.semilogx(F_AC, np.angle(F_noise), label = 'Fnoise')
+
+
+for fB in fitz[:4]:
+    Fb.ax0.loglog(
+        fB.F_bal, 
+        abs(fB.data_fit), 
+        label = 'fit {npoles} ({res})'.format(
+            npoles = len(fB.ZPK[1]), 
+            res     = fB.res,
+        ),
+        #color = 'green',
+    )
+    Fb.ax1.semilogx(fB.F_bal, np.angle(fB.data_fit), label = 'fit')
+    Fb.ax2.semilogx(fB.F_bal, abs(fB.resP), label = 'fit')
+
+Fb.ax0.legend(ncol = 3, fontsize = 6)
+```
+
+
+
+
+    <matplotlib.legend.Legend at 0x7f2b5306ff28>
+
+
+
+
+![png](tests-ipynb/tests_10_1.png)
+
+
+
+```python
+fits = [iirrational.fit_pzpz(
+    F_AC, 
+    F_noise, 
+    W = 10, 
+    npoles = 10, 
+    nzeros = 10, 
+    F_nyquist = None,
+)]
+```
+
+
+```python
+Fb = mplfigB(Nrows=3)
+
+Fb.ax0.loglog(F_AC, abs(F_exact), label = 'Fexact')
+Fb.ax1.semilogx(F_AC, np.angle(F_exact), label = 'Fex')
+
+Fb.ax0.loglog(F_AC, abs(F_noise), label = 'Fnoise')
+Fb.ax1.semilogx(F_AC, np.angle(F_noise), label = 'Fnoise')
+
+
+for fB in fits[:4]:
+    Fb.ax0.loglog(
+        fB.F_bal, 
+        abs(fB.data_fit), 
+        label = 'fit {npoles} ({res})'.format(
+            npoles = len(fB.ZPK[1]), 
+            res     = fB.res,
+        ),
+        #color = 'green',
+    )
+    Fb.ax1.semilogx(fB.F_bal, np.angle(fB.data_fit), label = 'fit')
+    Fb.ax2.semilogx(fB.F_bal, abs(fB.resP), label = 'fit')
+
+Fb.ax0.legend(ncol = 3, fontsize = 6)
+```
+
+
+
+
+    <matplotlib.legend.Legend at 0x7f2b556c1518>
+
+
+
+
+![png](tests-ipynb/tests_12_1.png)
+
+
+
+```python
+scipy.linalg.svd??
+```
+
+
+```python
+
+```