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More statistics to detect bad/over polling for fast continuous example #61

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Merged
merged 5 commits into from
Dec 2, 2020
Merged

More statistics to detect bad/over polling for fast continuous example #61

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More statistics to detect bad/over polling
WizardTim Dec 1, 2020
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WizardTim Dec 1, 2020
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Reformat code with psf/black
WizardTim Dec 1, 2020
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24 changes: 22 additions & 2 deletions examples/ads1x15_fast_read.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,16 +22,36 @@
ads.mode = Mode.CONTINUOUS
ads.data_rate = RATE

repeats = 0

data = [None] * SAMPLES

start = time.monotonic()

# Read the same channel over and over
for i in range(SAMPLES):
data[i] = chan0.value
# Detect repeated values due to over polling
if data[i] == data[i - 1]:
repeats += 1


end = time.monotonic()
total_time = end - start

print("Time of capture: {}s".format(total_time))
print("Sample rate requested={} actual={}".format(RATE, SAMPLES / total_time))
rate_reported = SAMPLES / total_time
rate_actual = (SAMPLES - repeats) / total_time
# NOTE: leave input floating to pickup some random noise
# This cannot estimate conversion rates higher than polling rate

print("Took {:5.3f} s to acquire {:d} samples.".format(total_time, SAMPLES))
print("")
print("Configured:")
print(" Requested = {:5d} sps".format(RATE))
print(" Reported = {:5d} sps".format(ads.data_rate))
print("")
print("Actual:")
print(" Polling Rate = {:8.2f} sps".format(rate_reported))
print(" {:9.2%}".format(rate_reported / RATE))
print(" Repeats = {:5d}".format(repeats))
print(" Conversion Rate = {:8.2f} sps (estimated)".format(rate_actual))