tabs -> spaces

1 files changed, 127 insertions, 109 deletions

diff --git a/bin/msp430-etv b/bin/msp430-etv
index 5fe896f..810c7ce 100755
--- a/bin/msp430-etv
+++ b/bin/msp430-etv
@@ -1,4 +1,5 @@
 #!/usr/bin/env python3
+# vim:tabstop=4:softtabstop=4:shiftwidth=4:textwidth=160:smarttab:expandtab
 
 import getopt
 import matplotlib.pyplot as plt
@@ -11,22 +12,22 @@ import sys
 opt = dict()
 
 def measure_data(time):
-	if not 'LD_LIBRARY_PATH' in os.environ:
-		os.environ['LD_LIBRARY_PATH'] = '{}/var/projects/msp430/MSP430Flasher_1.3.7'.format(os.environ['HOME'])
+    if not 'LD_LIBRARY_PATH' in os.environ:
+        os.environ['LD_LIBRARY_PATH'] = '{}/var/projects/msp430/MSP430Flasher_1.3.7'.format(os.environ['HOME'])
 
-	energytrace_cmd = '{}/var/source/energytrace-util/energytrace'.format(os.environ['HOME'])
+    energytrace_cmd = '{}/var/source/energytrace-util/energytrace'.format(os.environ['HOME'])
 
-	res = subprocess.run([energytrace_cmd, str(duration)], stdout = subprocess.PIPE, universal_newlines = True)
+    res = subprocess.run([energytrace_cmd, str(duration)], stdout = subprocess.PIPE, universal_newlines = True)
 
-	return res.stdout
+    return res.stdout
 
 def show_help():
-	print('''msp430-etv - MSP430 EnergyTrace Visualizer
+    print('''msp430-etv - MSP430 EnergyTrace Visualizer
 
 USAGE
 
 msp430-etv [--load <file> | <measurement duration>] [--save <file>]
-	[--skip <count>] [--threshold <power>] [--plot] [--stat]
+    [--skip <count>] [--threshold <power>] [--plot] [--stat]
 
 DESCRIPTION
 
@@ -44,111 +45,128 @@ OPTIONS
   --skip <count>
     Skip <count> data samples. This is useful to avoid startup code
     influencing the results of a long-running measurement
+  --threshold <watts>|auto
+    Partition data into points with mean power >= <watts> and points with
+    mean power < <watts>, and print some statistics. higher power is handled
+    as peaks, whereas low-power measurements constitute the baseline.
+    If the threshold is set to "auto", the mean power of all measurements
+    will be used
   --plot
     Show power/time plot
   --stat
     Show mean voltage, current, and power as well as total energy consumption.
-	''')
+    ''')
 
 if __name__ == '__main__':
-	try:
-		optspec = ('help load= save= skip= threshold= plot stat')
-		raw_opts, args = getopt.getopt(sys.argv[1:], "", optspec.split(' '))
-
-		for option, parameter in raw_opts:
-			optname = re.sub(r'^--', '', option)
-			opt[optname] = parameter
-
-		if 'help' in opt:
-			show_help()
-			sys.exit(0)
-
-		if not 'load' in opt:
-			duration = int(args[0])
-
-		if 'skip' in opt:
-			opt['skip'] = int(opt['skip'])
-		else:
-			opt['skip'] = 0
-
-		if 'threshold' in opt:
-			opt['threshold'] = float(opt['threshold'])
-
-	except getopt.GetoptError as err:
-		print(err)
-		sys.exit(2)
-	except IndexError:
-		print('Usage: msp430-etv <duration>')
-		sys.exit(2)
-	except ValueError:
-		print('Error: duration or skip is not a number')
-		sys.exit(2)
-
-	if 'load' in opt:
-		with open(opt['load'], 'r') as f:
-			log_data = f.read()
-	else:
-		log_data = measure_data(duration)
-
-	lines = log_data.split('\n')
-	data_count = sum(map(lambda x: len(x) > 0 and x[0] != '#', lines))
-	data_lines = filter(lambda x: len(x) > 0 and x[0] != '#', lines)
-
-	data = np.empty((data_count - opt['skip'], 4))
-
-	for i, line in enumerate(data_lines):
-		if i >= opt['skip']:
-			timestamp, current, voltage, total_energy = map(float, line.split(' '))
-			data[i - opt['skip']] = [timestamp, current, voltage, total_energy]
-
-	m_duration = data[-1, 0] - data[0, 0]
-	m_energy = data[-1, 3] - data[0, 3]
-	m_calc_energy = np.sum(data[1:, 1] * data[1:, 2] * (data[1:, 0] - data[:-1, 0]))
-	m_energy_deviation = np.abs(m_energy - m_calc_energy) / np.max([m_energy, m_calc_energy])
-
-	print('{:d} measurements in {:.2f} s = {:.0f} Hz sample rate'.format(
-		data_count, m_duration, data_count / m_duration))
-
-	print('Reported energy: E = {:f} J'.format(m_energy))
-	print('Calculated energy: U*I*t = {:f} J'.format(m_calc_energy))
-	print('Energy deviation: {:.1f}%'.format(m_energy_deviation * 100))
-
-
-	if 'threshold' in opt:
-		power = data[:, 1] * data[:, 2]
-
-		peaks = []
-		peak_start = -1
-		for i, dp in enumerate(power):
-			if dp >= opt['threshold'] and peak_start == -1:
-				peak_start = i
-			elif dp < opt['threshold'] and peak_start != -1:
-				peaks.append((peak_start, i))
-				peak_start = -1
-
-		for peak in peaks:
-			duration = data[peak[1]-1, 0] - data[peak[0], 0]
-			print('{:.2f}ms peak ({:f} -> {:f})'.format(duration * 1000,
-				data[peak[0], 0], data[peak[1]-1, 0]))
-			print('    {:f} µJ / mean {:f} µW'.format(
-				np.mean(power[peak[0] : peak[1]]) * duration * 1e6,
-				np.mean(power[peak[0] : peak[1]]) * 1e6 ))
-
-	if 'save' in opt:
-		with open(opt['save'], 'w') as f:
-			f.write(log_data)
-
-	if 'stat' in opt:
-		print('Mean voltage: {:f}'.format(np.mean(data[:, 2])))
-		print('Mean current: {:f}'.format(np.mean(data[:, 1])))
-		print('Mean power: {:f}'.format(np.mean(data[:, 1] * data[:, 2])))
-		print('Total energy: {:f}'.format(m_energy))
-
-	if 'plot' in opt:
-		pwrhandle, = plt.plot(data[:, 0], data[:, 1] * data[:, 2], 'b-', label='U*I', markersize=1)
-		#energyhandle, = plt.plot(data[1:, 0], (data[1:, 3] - data[:-1, 3]) / (data[1:, 0] - data[:-1, 0]), 'r-', label='E/Δt', markersize=1)
-		plt.legend(handles=[pwrhandle])
-		plt.xlabel('Time [s]')
-		plt.ylabel('Power [W]')
-		plt.grid(True)
-		plt.show()
+    try:
+        optspec = ('help load= save= skip= threshold= plot stat')
+        raw_opts, args = getopt.getopt(sys.argv[1:], "", optspec.split(' '))
+
+        for option, parameter in raw_opts:
+            optname = re.sub(r'^--', '', option)
+            opt[optname] = parameter
+
+        if 'help' in opt:
+            show_help()
+            sys.exit(0)
+
+        if not 'load' in opt:
+            duration = int(args[0])
+
+        if 'skip' in opt:
+            opt['skip'] = int(opt['skip'])
+        else:
+            opt['skip'] = 0
+
+        if 'threshold' in opt and opt['threshold'] != 'auto':
+            opt['threshold'] = float(opt['threshold'])
+
+    except getopt.GetoptError as err:
+        print(err)
+        sys.exit(2)
+    except IndexError:
+        print('Usage: msp430-etv <duration>')
+        sys.exit(2)
+    except ValueError:
+        print('Error: duration or skip is not a number')
+        sys.exit(2)
+
+    if 'load' in opt:
+        with open(opt['load'], 'r') as f:
+            log_data = f.read()
+    else:
+        log_data = measure_data(duration)
+
+    lines = log_data.split('\n')
+    data_count = sum(map(lambda x: len(x) > 0 and x[0] != '#', lines))
+    data_lines = filter(lambda x: len(x) > 0 and x[0] != '#', lines)
+
+    data = np.empty((data_count - opt['skip'], 4))
+
+    for i, line in enumerate(data_lines):
+        if i >= opt['skip']:
+            timestamp, current, voltage, total_energy = map(float, line.split(' '))
+            data[i - opt['skip']] = [timestamp, current, voltage, total_energy]
+
+    m_duration = data[-1, 0] - data[0, 0]
+    m_energy = data[-1, 3] - data[0, 3]
+    m_calc_energy = np.sum(data[1:, 1] * data[1:, 2] * (data[1:, 0] - data[:-1, 0]))
+    m_energy_deviation = np.abs(m_energy - m_calc_energy) / np.max([m_energy, m_calc_energy])
+
+    print('{:d} measurements in {:.2f} s = {:.0f} Hz sample rate'.format(
+        data_count, m_duration, data_count / m_duration))
+
+    print('Reported energy: E = {:f} J'.format(m_energy))
+    print('Calculated energy: U*I*t = {:f} J'.format(m_calc_energy))
+    print('Energy deviation: {:.1f}%'.format(m_energy_deviation * 100))
+
+
+    if 'threshold' in opt:
+        power = data[:, 1] * data[:, 2]
+
+        if opt['threshold'] == 'auto':
+            opt['threshold'] = np.mean(power)
+            print('Threshold set to {:.0f} µW'.format(opt['threshold'] * 1e6))
+
+        if np.any(power < opt['threshold']):
+            print('Baseline mean: {:.0f} µW'.format(
+                np.mean(power[power < opt['threshold']]) * 1e6 ))
+        if np.any(power >= opt['threshold']):
+            print('Peak mean: {:.0f} µW'.format(
+                np.mean(power[power >= opt['threshold']]) * 1e6))
+
+        peaks = []
+        peak_start = -1
+        for i, dp in enumerate(power):
+            if dp >= opt['threshold'] and peak_start == -1:
+                peak_start = i
+            elif dp < opt['threshold'] and peak_start != -1:
+                peaks.append((peak_start, i))
+                peak_start = -1
+
+        for peak in peaks:
+            duration = data[peak[1]-1, 0] - data[peak[0], 0]
+            print('{:.2f}ms peak ({:f} -> {:f})'.format(duration * 1000,
+                data[peak[0], 0], data[peak[1]-1, 0]))
+            print('    {:f} µJ / mean {:f} µW'.format(
+                np.mean(power[peak[0] : peak[1]]) * duration * 1e6,
+                np.mean(power[peak[0] : peak[1]]) * 1e6 ))
+
+    if 'save' in opt:
+        with open(opt['save'], 'w') as f:
+            f.write(log_data)
+
+    if 'stat' in opt:
+        print('Mean voltage: {:f}'.format(np.mean(data[:, 2])))
+        print('Mean current: {:f}'.format(np.mean(data[:, 1])))
+        print('Mean power: {:f}'.format(np.mean(data[:, 1] * data[:, 2])))
+        print('Total energy: {:f}'.format(m_energy))
+
+    if 'plot' in opt:
+        pwrhandle, = plt.plot(data[:, 0], data[:, 1] * data[:, 2], 'b-', label='U*I', markersize=1)
+        #energyhandle, = plt.plot(data[1:, 0], (data[1:, 3] - data[:-1, 3]) / (data[1:, 0] - data[:-1, 0]), 'r-', label='E/Δt', markersize=1)
+        plt.legend(handles=[pwrhandle])
+        plt.xlabel('Time [s]')
+        plt.ylabel('Power [W]')
+        plt.grid(True)
+        plt.show()