fixed spelling of directory

experiments/gh.py

@@ -0,0 +1,136 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Thu May 15 16:07:26 2014
+
+@author: RL
+"""
+from __future__ import division
+import matplotlib.pyplot as plt
+import numpy.random as random
+
+
+
+
+
+
+def g_h_filter (data, x, dx, g, h, dt=1.):
+    results = []
+    for z in data:
+        x_est = x + (dx*dt)
+        residual = z - x_est
+
+        dx = dx    + h * (residual / float(dt))
+        x  = x_est + g * residual
+        print('gx',dx,)
+
+        results.append(x)
+
+
+    return results
+
+
+'''
+computation of x
+x_est = weight + gain
+residual = z - weight - gain
+x  = weight + gain + g (z - weight - gain)
+
+w + gain + gz -wg -ggain
+w -wg + gain - ggain + gz
+
+w(1-g) + gain(1-g) +gz
+
+(w+g)(1-g) +gz
+
+'''
+'''
+gain computation
+
+gain = gain + h/t* (z - weight - gain)
+= gain + hz/t -hweight/t - hgain/t
+
+= gain(1-h/t) + h/t(z-weight)
+
+'''
+'''
+gain+ h*(z-w -gain*t)/t
+
+gain + hz/t -hw/t -hgain
+
+gain*(1-h) + h/t(z-w)
+
+
+'''
+def weight2():
+    w = 0
+    gain = 200
+    t = 10.
+    weight_scale = 1./6
+    gain_scale = 1./10
+
+    weights=[2060]
+    for i in range (len(weights)):
+        z = weights[i]
+        w_pre = w + gain*t
+
+        new_w = w_pre * (1-weight_scale) +  z * (weight_scale)
+
+        print('new_w',new_w)
+
+        gain = gain *(1-gain_scale) + (z - w) * gain_scale/t
+
+        print (z)
+        print(w)
+
+        #gain = new_gain * (gain_scale) + gain * (1-gain_scale)
+        w = new_w
+        print ('w',w,)
+        print ('gain=',gain)
+
+
+def weight3():
+    w = 160.
+    gain = 1.
+    t = 1.
+    weight_scale = 6/10.
+    gain_scale = 2./3
+
+    weights=[158]
+    for i in range (len(weights)):
+        z = weights[i]
+        w_pre = w + gain*t
+
+        new_w = w_pre * (1-weight_scale) +  z * (weight_scale)
+
+        print('new_w',new_w)
+
+        gain = gain *(1-gain_scale) + (z - w) * gain_scale/t
+
+        print (z)
+        print(w)
+
+        #gain = new_gain * (gain_scale) + gain * (1-gain_scale)
+        w = new_w
+        print ('w',w,)
+        print ('gain=',gain)
+weight3()
+'''
+#zs = [i + random.randn()*50 for i in range(200)]
+zs = [158.0, 164.2, 160.3, 159.9, 162.1, 164.6, 169.6, 167.4, 166.4, 171.0]
+
+#zs = [2060]
+data= g_h_filter(zs, 160, 1, .6, 0, 1.)
+
+'''
+
+data = g_h_filter([2060], x=0, dx=200, g=1./6, h = 1./10, dt=10)
+print data
+
+
+'''
+print data
+print data2
+plt.plot(data)
+plt.plot(zs, 'g')
+plt.show()
+'''