kmcallister · July 28, 2019 17:11 · Jul 28, 2019
diff --git a/calc b/calc
@@ -0,0 +1,17 @@
+#!/bin/sh
+
+#set -e
+
+./ewma.py < log > smoothed
+echo
+./progress.py "$@" < smoothed
+echo
+
+gnuplot < weight-graph.gpl
+#./maintain.py < log
+#echo
+
+./rate.py < smoothed > rate
+gnuplot < rate-graph.gpl
+
+cp log backup/$(tail -n 1 log | awk '{print $1}')
diff --git a/ewma.py b/ewma.py
@@ -0,0 +1,48 @@
+#!/usr/bin/python
+import sys
+import argparse
+import time
+import datetime
+
+argparser = argparse.ArgumentParser()
+argparser.add_argument('--verbose', '-v', action='store_true')
+argparser.add_argument('--alpha', '-a', type=float, default=0.1)
+args = argparser.parse_args()
+
+if args.alpha < 0.0 or args.alpha > 1.0:
+    raise ValueError, "you suck"
+
+ewma = 0.0
+def update(weight):
+    global ewma
+    ewma = args.alpha*weight + (1.0 - args.alpha)*ewma
+
+last_ordinal = None
+last_weight = None
+for ln in sys.stdin:
+    date, weight = ln.split()
+    date = datetime.datetime.strptime(date, '%Y-%m-%d')
+    weight = float(weight)
+    ordinal = date.toordinal()
+
+    if args.verbose:
+        print (date.toordinal(), weight)
+
+    if last_ordinal is None:
+        last_ordinal = ordinal
+        last_weight = weight
+        ewma = weight
+    else:
+        last_ordinal += 1
+        while last_ordinal < ordinal:
+            if args.verbose:
+                print 'Missing day, using', last_weight
+            update(last_weight)
+            last_ordinal += 1
+
+    if args.verbose:
+            print 'Update with', weight
+    update(weight)
+    last_weight = weight
+
+    print date.strftime('%Y-%m-%d'), ewma
diff --git a/maintain.py b/maintain.py
@@ -0,0 +1,32 @@
+#!/usr/bin/env python
+import datetime
+import sys
+import math
+import argparse
+import numpy
+from scipy import stats
+
+goal = 234
+window = 30
+points = []
+confidence = 0.05
+
+for ln in sys.stdin:
+    date, weight = ln.split()
+    date = datetime.datetime.strptime(date, '%Y-%m-%d')
+    weight = float(weight)
+    points.append((date, weight))
+    points = points[-window:]
+
+weights = [p[1] for p in points]
+minw, maxw, avgw = (min(weights), max(weights), numpy.average(weights))
+
+t_stat, p_value = stats.ttest_1samp(weights, goal)
+
+print 'Target:         %6.2f lbs' % (goal,)
+print 'Range:          %6.2f lbs' % (maxw-minw,)
+print 'Std deviation:  %6.2f lbs' % (numpy.std(weights),)
+print 'Min/avg/max:    %6.2f  /  %6.2f  /  %6.2f' % (minw, avgw, maxw)
+print 'Deltas:         %6.2f  /  %6.2f  /  %6.2f' % (minw-goal, avgw-goal, maxw-goal)
+print
+print 'Verdict:       ', 'Maintaining!' if p_value > confidence else 'Not maintaining', '(p = %.2f)' % (p_value,)
diff --git a/progress.py b/progress.py
@@ -0,0 +1,104 @@
+#!/usr/bin/env python
+import datetime
+import sys
+import math
+import argparse
+from scipy import stats
+
+argparser = argparse.ArgumentParser()
+argparser.add_argument('--reddit', '-r', action='store_true')
+args = argparser.parse_args()
+
+parse_date = lambda s: datetime.datetime.strptime(s, "%Y-%m-%d")
+
+goal = 225
+goal_date = parse_date("2019-06-01")
+window = 30
+height = 1.91  # meters
+
+kg_per_lb = 0.453592
+points = []
+
+def parse(ln):
+    date, weight = ln.split()
+    date = datetime.datetime.strptime(date, '%Y-%m-%d')
+    weight = float(weight)
+    return (date, weight)
+
+lines = list(sys.stdin)
+start_date, start = parse(lines[0])
+
+points = map(parse, lines)
+num_points = len(points)
+num_decrease = sum(1 for p, q in zip(points, points[1:]) if p[1] > q[1])
+
+points = points[-window:]
+
+first = points[0]
+last  = points[-1]
+
+reg_x = [p[0].toordinal() for p in points]
+reg_y = [p[1] for p in points]
+
+slope, intercept, r_value, p_value, stderr = stats.linregress(reg_x, reg_y)
+
+#rate = (first[1] - last[1]) / (last[0] - first[0]).days
+rate = -slope
+
+if rate <= 0.0:
+    print "Sorry, you're getting fatter at %.2f lb/wk (r^2 = %.2f)" % (-7.0*rate, r_value**2.0)
+    sys.exit(1)
+
+def output_stat(label, value):
+    if args.reddit:
+        print '**' + label + '**|' + value.lstrip()
+    else:
+        print (label + ':').ljust(17) + value
+
+done = start - last[1]
+days_done = (last[0] - start_date).days
+remainder = last[1] - goal
+remaining_time = datetime.timedelta(days = remainder / rate)
+finish_date = last[0] + remaining_time
+margin = (goal_date - finish_date).days + 1
+
+required_rate = remainder / (goal_date - last[0]).days
+excess_rate = rate - required_rate
+
+def project(date):
+    projection = last[1] - (rate * (parse_date(date) - last[0]).days)
+    print 'Weight on %s:   %6.2f lbs = %6.2f lbs lost' % (date, projection, start - projection)
+
+
+if args.reddit:
+    print 'Stat|Value'
+    print ':-|:-'
+output_stat('Current weight', '%6.2f lbs' % (last[1],))
+#output_stat('BMI', '%6.2f' % ((kg_per_lb * last[1]) / (height ** 2.0),))
+output_stat('Lost so far', '%6.2f lbs = %5.2f%% of starting weight' % (done, 100.0 * done / start))
+output_stat('Remaining', '%6.2f lbs = %5.2f%% of current  weight' % (remainder, 100.0 * remainder / last[1]))
+output_stat('Progress', '%6.2f %%' % (done / (start - goal) * 100.0,))
+output_stat('Required rate', '%6.2f lbs / wk' % (7.0 * required_rate,))
+output_stat('Actual rate', '%6.2f lbs / wk = %.2f%% per week  (r^2 = %4.2f)' % (7.0*rate, 100*7.0*rate / last[1], r_value**2.0))
+#output_stat('Excess rate', '%6.2f lbs / wk' % (7.0*excess_rate,))
+output_stat('Deficit', '  %4d kcal / day' % (rate*3500,))
+#output_stat('Excess deficit', '  %4d kcal/day' % (excess_rate*3500,))
+output_stat('All-time rate', '%6.2f lbs / wk' % (7.0 * done / days_done,))
+output_stat('Average drops', '%6.2f %% of the time (%d out of %d points)' % (100.0 * num_decrease / float(num_points), num_decrease, num_points))
+print
+print 'Goal will be reached on %s' % (finish_date.strftime('%Y-%m-%d'),),
+if margin > 0:
+    print '(%d days early)' % (margin,)
+else:
+    print '(%d days late)' % (-margin,)
+if args.reddit:
+    print
+print days_done, 'days done, only', remaining_time.days, 'left to go! Keep it up, you\'re doing great!'
+
+print
+project('2019-06-01')
+
+with open('regression_line', 'w') as f:
+    line_out = lambda pt: f.write(pt[0].strftime('%Y-%m-%d') + ' ' + str(intercept + slope*pt[0].toordinal()) + '\n')
+    line_out(points[0])
+    line_out(points[-1])
diff --git a/rate-graph.gpl b/rate-graph.gpl
@@ -0,0 +1,14 @@
+set title "Weight loss rate"
+set ylabel "Pounds per week"
+#set y2label "r^2"
+
+set term png size 1400,900
+set output "rate-graph.png"
+set timefmt "%Y-%m-%d"
+set xdata time
+set format x "%b\n%d"
+
+#set xrange ["2018-02-18":]
+
+plot "rate" using 1:2 with lines lw 3 title "Rate", \
+    #"rate" using 1:3 with lines lw 1 title "r^2" axes x1y2
diff --git a/rate.py b/rate.py
@@ -0,0 +1,26 @@
+#!/usr/bin/env python
+import datetime
+import sys
+import math
+import argparse
+from scipy import stats
+
+window = 14
+points = []
+
+for ln in sys.stdin:
+    date, weight = ln.split()
+    date = datetime.datetime.strptime(date, '%Y-%m-%d')
+    weight = float(weight)
+    points.append((date, weight))
+    points = points[-window:]
+
+    if len(points) < window:
+        continue
+
+    reg_x = [p[0].toordinal() for p in points]
+    reg_y = [p[1] for p in points]
+
+    slope, intercept, r_value, p_value, stderr = stats.linregress(reg_x, reg_y)
+
+    print date.strftime("%Y-%m-%d"), -7.0*slope, r_value**2.0
diff --git a/weight-graph.gpl b/weight-graph.gpl
@@ -0,0 +1,16 @@
+set title "Weight loss progress"
+set ylabel "Weight (lbs)"
+
+set term png size 1400,900
+set output "weight-graph.png"
+set timefmt "%Y-%m-%d"
+set xdata time
+set format x "%b\n%d"
+
+#set xrange ["2018-08-01":]
+#set yrange [240:290]
+
+plot "log" using 1:2 with linespoints pointtype 6 title "Daily weight", \
+     "smoothed" using 1:2 with lines lw 3 title "Moving average", \
+     "regression_line" using 1:2 title "Trend line" with lines lw 2 lt rgb "#c01f1f", \
+#     "raw_line" using 1:2 title "Raw trend line" with lines lw 2 lt rgb "blue"