Added more algos

diffadjust/blkdiff.py

@@ -1,47 +1,106 @@
-import math
-import random
+import math, random
 
 hashpower = [float(x) for x in open('hashpower.csv').readlines()]
 
 target = 12
-seconds_in_day = 8640
-ema_factor = 0.005
-f = 80
+seconds_in_day = 86400
+ema_factor = 0.01
+f = 20
+sqrf = 3
 threshold = 1.3
-maxadjust = 0.1
+adj_factor = 0.01
+maxadjust = 0.5
+blks_back = 10
 
 
 def expdiff(t):
     return -math.log(random.random()) * t
 
 
-def adjust(timestamps, diffs):
-    if len(timestamps) < 7:
+def calc_threshold_time(p, t):
+    return t * -math.log(1 - p)
+
+
+def abs_sqr(x):
+    return -(x**2) if x < 0 else x**2
+
+
+def simple_adjust(timestamps, diffs):
+    if len(timestamps) < blks_back + 2:
         return diffs[-1]
-    blks_back = 5
-    delta = timestamps[-2] - timestamps[-2-blks_back]
-    expected = target * 0.693 * blks_back
-    if delta < expected / threshold:
-        fac = max(1 + 1. * delta / expected / f, 1 + maxadjust) ** 2
-    elif delta > expected * threshold:
-        fac = max(1 - 1. * delta / expected / f, 1 - maxadjust) ** 2
+    # Total interval between previous block and block a bit further back
+    delta = timestamps[-2] - timestamps[-2-blks_back] + 0.0
+    # Expected interval
+    expected = target * blks_back
+    fac = max(min(1 - (delta / expected - 1) / f, 1+maxadjust), 1-maxadjust)
+    return diffs[-1] * fac
+
+
+def quadratic_adjust(timestamps, diffs):
+    if len(timestamps) < blks_back + 2:
+        return diffs[-1]
+    # Total interval between previous block and block a bit further back
+    delta = timestamps[-2] - timestamps[-2-blks_back] + 0.0
+    # Expected interval
+    expected = target * blks_back
+    fac = max(min(1 - abs_sqr(delta / expected - 1) / sqrf,
+                  1+maxadjust), 1-maxadjust)
+    return diffs[-1] * fac
+
+
+def bounded_adjust(timestamps, diffs):
+    if len(timestamps) < blks_back + 2:
+        return diffs[-1]
+    # Total interval between previous block and block a bit further back
+    delta = timestamps[-2] - timestamps[-2-blks_back] + 0.0
+    # Expected interval
+    expected = target * blks_back
+    if delta / expected > threshold:
+        fac = (1 - adj_factor)
+    elif delta / expected < 1 / threshold:
+        fac = (1 + adj_factor) ** (delta / expected)
     else:
         fac = 1
     return diffs[-1] * fac
 
 
 def test(source, adjust):
-    ema = target
-    chain = [0]
-    d = [source[0]]
-    emachain = [target] 
-    sourcechain = [0]
-    while chain[-1] < len(source) * seconds_in_day:
-        hashpower = source[int(chain[-1] // seconds_in_day)]
-        d.append(adjust(chain, d))
-        chain.append(chain[-1] + expdiff(d[-1] / hashpower))
-        ema = ema * (1 - ema_factor) + (chain[-1] - chain[-2]) * ema_factor
-        emachain.append(ema)
-        sourcechain.append(hashpower)
-    print 'min', min(emachain[500:]), 'max', max(emachain[500:]), 'avg', sum(emachain) / len(emachain)
-    return zip(emachain[500:], sourcechain[500:], chain[500:])
+    ema = maxema = minema = target
+    lthalf, gtdouble, lttq, gtft = 0, 0, 0, 0
+    times = [0]
+    diffs = [source[0]]
+    nextprint = 10**6
+    count = 0
+    while times[-1] < len(source) * seconds_in_day:
+        if times[-1] > nextprint:
+            print '%d out of %d processed' % \
+                (times[-1], len(source) * seconds_in_day)
+            nextprint += 10**6
+        # Grab hashpower from data source
+        hashpower = source[int(times[-1] // seconds_in_day)]
+        # Calculate new difficulty
+        diffs.append(adjust(times, diffs))
+        # Calculate next block time
+        times.append(times[-1] + expdiff(diffs[-1] / hashpower))
+        # Calculate min and max ema
+        ema = ema * (1 - ema_factor) + (times[-1] - times[-2]) * ema_factor
+        minema = min(minema, ema)
+        maxema = max(maxema, ema)
+        count += 1
+        if ema < target * 0.75:
+            lttq += 1
+            if ema < target * 0.5:
+                lthalf += 1
+        elif ema > target * 1.33333:
+            gtft += 1
+            if ema > target * 2:
+                gtdouble += 1
+        # Pop items to save memory
+        if len(times) > 2000:
+            times.pop(0)
+            diffs.pop(0)
+    print 'min', minema, 'max', maxema, 'avg', times[-1] / count, \
+        'ema < half', lthalf * 1.0 / count, \
+        'ema > double', gtdouble * 1.0 / count, \
+        'ema < 3/4', lttq * 1.0 / count, \
+        'ema > 4/3', gtft * 1.0 / count