def __call__(self, filename):
""" Process the file """
print(f"ax3_seconds_stats.py processing {filename}")
# Count number of lines in file to get array dimension
print("Count lines in file")
count = 0
with open(filename, "rt", newline="\n") as self.fh:
line = self.fh.readline().strip()
while line:
row = Row(line)
if row.skip:
pass
else:
count += 1
if count % 1000000 == 0:
print(f"{count} lines counted")
line = self.fh.readline().strip()
self.filename = filename
self.timestamp = np.array(["(empty)" for _ in range(count)])
self.epoch = np.zeros((count,))
self.x = np.zeros((count,))
self.y = np.zeros((count,))
self.z = np.zeros((count,))
self.tot = np.zeros((count,))
print("Read file")
self.firstLine = None
with open(filename, "rt", newline="\n") as self.fh:
line = self.fh.readline().strip()
index = 0
while line:
row = Row(line)
if row.skip:
pass
else:
if self.firstLine is None:
self.firstLine = row.timestamp
self.timestamp[index] = row.timestamp
self.epoch[index] = row.getEpoch()
self.x[index] = row.val[0]
self.y[index] = row.val[1]
self.z[index] = row.val[2]
self.tot[index] = row.getTotAcc()
index += 1
if index % 1000000 == 0:
print(f"{index} data lines read")
line = self.fh.readline().strip()
def __call__(self, filename):
""" Process the file """
# Count number of valid lines in file to get array dimension
count = 0
with open(filename, "rt", newline="\n") as self.fh:
line = self.fh.readline().strip()
while line:
row = Row(line, decode=False)
if row.skip:
pass
else:
count += 1
if count % 1000000 == 0:
print(f"{count} lines counted")
line = self.fh.readline().strip()
self.filename = filename
self.timestamp = np.array(["(empty)" for _ in range(count)])
self.epoch = np.zeros((count,))
self.x = np.zeros((count,))
self.y = np.zeros((count,))
self.z = np.zeros((count,))
self.tot = np.zeros((count,))
rowAbove8 = [0,0,0]
rowAbove7 = [0,0,0]
rowAbove6 = [0,0,0]
rowAbove1 = [0,0,0]
self.firstLine = None
with open(filename, "rt", newline="\n") as self.fh:
line = self.fh.readline().strip()
index = 0
while line:
row = Row(line)
if row.skip:
pass
else:
if self.firstLine is None:
self.firstLine = row.timestamp
self.timestamp[index] = row.timestamp
self.epoch[index] = row.getEpoch()
self.x[index] = row.val[0]
self.y[index] = row.val[1]
self.z[index] = row.val[2]
self.tot[index] = row.getTotAcc()
index += 1
if index % 1000000 == 0:
print(f"{index} lines read")
for axis in range(len(row.val)):
if abs(row.val[axis]) >= 8:
rowAbove8[axis] = rowAbove8[axis] + 1
if abs(row.val[axis]) >= 7:
rowAbove7[axis] = rowAbove7[axis] + 1
if abs(row.val[axis]) >= 6:
rowAbove6[axis] = rowAbove6[axis] + 1
if abs(row.val[axis]) >= 1:
rowAbove1[axis] = rowAbove1[axis] + 1
line = self.fh.readline().strip()
for axis in range(len(row.val)):
# size of x is the same as y and z
proportion = rowAbove8[axis]/self.x.size
print(f"axis {axis}, +/-8 or more {rowAbove8[axis]} times")
print(f"axis {axis}, +/-7 or more {rowAbove7[axis]} times")
print(f"axis {axis}, +/-6 or more {rowAbove6[axis]} times")
print(f"axis {axis}, +/-1 or more {rowAbove1[axis]} times")
print()
outputFilename = self.makeOutFile(filename, self.firstLine)
outfile = open(outputFilename, "w")
with outfile:
writer = csv.writer(outfile)
for index in range(self.epoch.size):
writer.writerow([self.epoch[index], self.x[index],
self.y[index], self.z[index],
self.tot[index]])
return outputFilename
def __call__(self, filename, threshold):
""" Process the file """
# Count number of seconds in the file
count = 0
firstEpoch = None
lastEpoch = None
with open(filename, "rt", newline="\n") as self.fh:
line = self.fh.readline().strip()
while line:
row = Row(line)
if row.skip:
pass
elif firstEpoch is None:
firstEpoch = row.getEpoch()
line = self.fh.readline().strip()
lastEpoch = row.getEpoch()
secondsInFile = int(lastEpoch) - int(firstEpoch) + 1
days = round(secondsInFile / 86400, 1)
print(
f"File contains {days} days ({secondsInFile} seconds) worth of data"
)
epochTimestamps = np.zeros(secondsInFile)
maxAccPerSecond = np.zeros(secondsInFile)
firstSecondEpoch = int(firstEpoch)
# Now scan through the file and pick out the highest acceleration
# in each second
with open(filename, "rt", newline="\n") as self.fh:
line = self.fh.readline().strip()
while line:
row = Row(line)
if row.skip:
pass
else:
second = int(row.getEpoch()) - firstSecondEpoch
epochTimestamps[second] = int(row.getEpoch())
totalAcc = row.getTotAcc()
if totalAcc > maxAccPerSecond[second]:
maxAccPerSecond[second] = totalAcc
line = self.fh.readline().strip()
print(f"Max per second accelerations extracted")
aboveThresholdValues = np.copy(maxAccPerSecond)
# Now scan through looking for movement above a threshold
for second in range(len(aboveThresholdValues)):
if aboveThresholdValues[second] < threshold:
aboveThresholdValues[second] = 0
print(f"Determining periods of movement")
# Scan through the above threshold values to set +/-5 minutes to
# 1 when there is an above threshold value
inUse = np.zeros(secondsInFile)
for second in range(len(aboveThresholdValues)):
if aboveThresholdValues[second] > 0:
# Set the previous 5 * 60 values, less one, to 1
backIndex = second - ((4 * 60) + 59)
for index in range(backIndex, second):
inUse[index] = 1
# Set the next 5 * 60 values to 1
for index in range(second, second + (5 * 60)):
aboveThresholdValues[second] = 1
plotFilename, outputFilename = self.makeOutFile(filename, threshold)
self._plot(plotFilename, threshold, epochTimestamps, maxAccPerSecond,
aboveThresholdValues, inUse)
# Output this as a data file
outfile = open(outputFilename, "w")
with outfile:
writer = csv.writer(outfile)
for second in range(len(aboveThresholdValues)):
writer.writerow([
int(firstEpoch) + second, second,
round(maxAccPerSecond[second], 6),
aboveThresholdValues[second], inUse[second]
])
return [plotFilename, outputFilename]