3D-printing/klipper
1
0
Fork 0
mirror of https://github.com/Klipper3d/klipper.git synced 2025-07-15 02:37:52 -06:00
Code Issues Projects Releases Packages Wiki Activity Actions 3

shaper_calibrate: Choose input shapers accounting smoothing

Browse source 
Improved algorithm to choose the 'optimal' shaper frequency taking
shaper smoothing into account. This may choose a frequency with
slightly more vibrations but less smoothing. Also allow users to
limit the maximum input shaper smoothing.

Signed-off-by: Dmitry Butyugin <dmbutyugin@google.com>
This commit is contained in:
Dmitry Butyugin 2020-12-19 22:53:50 +01:00 • committed by KevinOConnor
parent a637c2f110
commit 1b1a97e8bd
3 changed files with 120 additions and 83 deletions
Download patch file Download diff file Expand all files Collapse all files

36
scripts/calibrate_shaper.py
View file

@ -40,7 +40,7 @@ def parse_log(logname):
######################################################################
# Find the best shaper parameters
def calibrate_shaper(datas, csv_output):
def calibrate_shaper(datas, csv_output, max_smoothing):
helper = ShaperCalibrate(printer=None)
if isinstance(datas[0], CalibrationData):
calibration_data = datas[0]
@ -52,19 +52,19 @@ def calibrate_shaper(datas, csv_output):
for data in datas[1:]:
calibration_data.join(helper.process_accelerometer_data(data))
calibration_data.normalize_to_frequencies()
shaper_name, shaper_freq, shapers_vals = helper.find_best_shaper(
calibration_data, print)
print("Recommended shaper is %s @ %.1f Hz" % (shaper_name, shaper_freq))
shaper, all_shapers = helper.find_best_shaper(
calibration_data, max_smoothing, print)
print("Recommended shaper is %s @ %.1f Hz" % (shaper.name, shaper.freq))
if csv_output is not None:
helper.save_calibration_data(
csv_output, calibration_data, shapers_vals)
return shaper_name, shapers_vals, calibration_data
csv_output, calibration_data, all_shapers)
return shaper.name, all_shapers, calibration_data
######################################################################
# Plot frequency response and suggested input shapers
######################################################################
def plot_freq_response(lognames, calibration_data, shapers_vals,
def plot_freq_response(lognames, calibration_data, shapers,
selected_shaper, max_freq):
freqs = calibration_data.freq_bins
psd = calibration_data.psd_sum[freqs <= max_freq]
@ -99,13 +99,15 @@ def plot_freq_response(lognames, calibration_data, shapers_vals,
ax2 = ax.twinx()
ax2.set_ylabel('Shaper vibration reduction (ratio)')
best_shaper_vals = None
for name, freq, vals in shapers_vals:
label = "%s (%.1f Hz)" % (name.upper(), freq)
for shaper in shapers:
label = "%s (%.1f Hz, vibr=%.1f%%, sm~=%.2f)" % (
shaper.name.upper(), shaper.freq,
shaper.vibrs * 100., shaper.smoothing)
linestyle = 'dotted'
if name == selected_shaper:
if shaper.name == selected_shaper:
linestyle = 'dashdot'
best_shaper_vals = vals
ax2.plot(freqs, vals, label=label, linestyle=linestyle)
best_shaper_vals = shaper.vals
ax2.plot(freqs, shaper.vals, label=label, linestyle=linestyle)
ax.plot(freqs, psd * best_shaper_vals,
label='After\nshaper', color='cyan')
# A hack to add a human-readable shaper recommendation to legend
@ -140,22 +142,26 @@ def main():
default=None, help="filename of output csv file")
opts.add_option("-f", "--max_freq", type="float", default=200.,
help="maximum frequency to graph")
opts.add_option("-s", "--max_smoothing", type="float", default=None,
help="maximum shaper smoothing to allow")
options, args = opts.parse_args()
if len(args) < 1:
opts.error("Incorrect number of arguments")
if options.max_smoothing is not None and options.max_smoothing < 0.05:
opts.error("Too small max_smoothing specified (must be at least 0.05)")
# Parse data
datas = [parse_log(fn) for fn in args]
# Calibrate shaper and generate outputs
selected_shaper, shapers_vals, calibration_data = calibrate_shaper(
datas, options.csv)
selected_shaper, shapers, calibration_data = calibrate_shaper(
datas, options.csv, options.max_smoothing)
if not options.csv or options.output:
# Draw graph
setup_matplotlib(options.output is not None)
fig = plot_freq_response(args, calibration_data, shapers_vals,
fig = plot_freq_response(args, calibration_data, shapers,
selected_shaper, options.max_freq)
# Show graph