Merge branch 'master' into bene_master

FindPrimesBokeh.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Dec 22 17:15:45 2020
+
+@author: bruns01
+"""
+import numpy as np
+
+from bokeh.io import curdoc
+from bokeh.layouts import column, row
+from bokeh.models import ColumnDataSource, Slider, TextInput,Div
+from bokeh.plotting import figure
+
+from primes import primes
+
+# Set up callbacks
+def update_data(attrname, old, new):
+    f_std = np.array([1.0, 1.25, 1.6, 2.0, 2.5, 3.2, 4.0, 5.0, 6.3, 8.0 ])
+    p0 = primes[new]
+#    pri = primes[(primes<=10*p0) & (primes>p0)]
+    pri = primes[(primes<=10*p0)] 
+    d = []
+    p = []
+    for fs in f_std:
+        try:
+            pr1 = (pri[pri/p0<=fs])[-1] # lower limit prime
+            f1 = pr1/p0  # lower limit frequency
+            r1 = (f1-fs)/fs
+        except:
+            r1 = 0.5
+        pr2 = (pri[pri/p0>fs])[0] # upper limit prime
+        f2 = pr2/p0  # upper limit frequency
+        r2 = (f2-fs)/fs
+
+        r = r1 if (np.abs(r1)<np.abs(r2)) else r2
+        d.append(r)
+        p.append((pr1 if (np.abs(r1)<np.abs(r2)) else pr2))
+        #print( f1 if (np.abs(r1)<np.abs(r2)) else f2)
+        #print( ("%d/%d" % (pr1,p0))  if (np.abs(r1)<np.abs(r2)) else ("%d/%d" % (pr2,p0)))
+    source.data = dict(x=f_std,y=np.array(d))
+    base.value = """Base = %d """ % p0
+    deviation.text = str(np.amax(np.abs(d))) # display maximum deviation
+    dd = 100*np.amax(np.abs(np.array(d)))
+    print("%2.2f %%" % dd)
+    print(p)
+
+f_std = np.array([1.0, 1.25, 1.6, 2.0, 2.5, 3.2, 4.0, 5.0, 6.3, 8.0 ])
+p0 = 7
+
+base = TextInput(value="""Base = xx""")
+deviation = Div(text="max")
+
+# Set up plot
+source = ColumnDataSource(data=dict(x=[], y=[]))
+
+update_data("offset",0,5)
+
+plot = figure(plot_height=400, plot_width=800, title="prime ratio frequencies",
+              tools="crosshair,pan,reset,save,wheel_zoom",
+              x_range=[1.0, 10.0], y_range=[-0.1, 0.2])
+
+plot.circle('x', 'y', source=source, radius=.05)
+
+
+# Set up widgets
+offset = Slider(title="offset", value=5, start=0, end=50, step=1)
+
+offset.on_change('value', update_data)
+
+
+# Set up layouts and add to document
+inputs = row(offset, base, deviation)
+
+curdoc().add_root(column(inputs, plot, width=800))
+curdoc().title = "Sliders"

SingleSequentialTest.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Sat Dec 12 18:16:02 2020
+
+@author: bruns01
+Sequentieller Multisinusfit mit einer 
+schwachbesetzten Designmatrix 
+"""
+
+import numpy as np
+from scipy.sparse import coo_matrix
+from scipy.sparse.linalg import lsqr
+import matplotlib.pyplot as mp
+from datetime import datetime
+
+import SineTools as st
+
+from primes import primes
+    
+f0 = 0.1
+Np0 = 7.0
+primes = np.array([7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, ])
+primes = primes[1::2]
+
+f = f0 * primes/Np0
+T = 3*Np0 /f0
+f_max = np.amax(f)
+
+t = st.sampletimes(200,T)
+p = 45.0+180.0*np.array([i for i in range(len(f))])
+m = [1.0]*len(f)
+y = st.multi_waveform_mp(f,m,p,t)+.3 + 0.5*(np.random.rand((len(t)))-0.5)
+
+mp.plot(y,lw=3)
+mp.show()
+
+start = datetime.now()
+for i in range(1):
+    print(i)
+    abc = st.seq_multi_threeparsinefit(f,y,t,periods=5)
+end = datetime.now()
+
+print("Delta=" + str((end-start)))
+#print(st.seq_multi_amplitude(abc[0]))   
+mag = st.seq_multi_amplitude(abc[0])
+print(np.mean(mag[:,1]))
+print(np.sqrt(np.var(mag[:,1])))
+mp.figure(1)
+mp.clf()
+mp.plot(y,".",ms=1)
+mp.plot(abc[1],lw=1)
+mp.show()