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added proper use of damping ratio and SCV to compute shaper recommendations

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This commit is contained in:
Félix Boisselier
2024-02-19 22:53:47 +01:00
parent b42e377ac6
commit 80c8da622d
4 changed files with 45 additions and 20 deletions
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33
K-ShakeTune/scripts/graph_shaper.py
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@@ -42,17 +42,22 @@ KLIPPAIN_COLORS = {
# Computation
######################################################################
# Find the best shaper parameters using Klipper's official algorithm selection
def calibrate_shaper(datas, max_smoothing):
# Find the best shaper parameters using Klipper's official algorithm selection with
# a proper precomputed damping ratio (zeta) and using the configured printer SQV value
def calibrate_shaper(datas, max_smoothing, scv, max_freq):
helper = shaper_calibrate.ShaperCalibrate(printer=None)
calibration_data = helper.process_accelerometer_data(datas)
calibration_data.normalize_to_frequencies()
shaper, all_shapers = helper.find_best_shaper(calibration_data, max_smoothing, print_with_c_locale)
fr, zeta, _ = compute_mechanical_parameters(calibration_data.psd_sum, calibration_data.freq_bins)
print_with_c_locale("Recommended shaper is %s @ %.1f Hz" % (shaper.name, shaper.freq))
print_with_c_locale("Axis has a main resonant frequency at %.1fHz with an estimated damping ratio of %.3f" % (fr, zeta))
shaper, all_shapers = helper.find_best_shaper(
calibration_data, shapers=None, damping_ratio=zeta,
scv=scv, shaper_freqs=None, max_smoothing=max_smoothing,
test_damping_ratios=None, max_freq=max_freq,
logger=print_with_c_locale)
print_with_c_locale("\n-> Recommended shaper is %s @ %.1f Hz (when using a square corner velocity of %.1f and a computed damping ratio of %.3f)" % (shaper.name.upper(), shaper.freq, scv, zeta))
return shaper.name, all_shapers, calibration_data, fr, zeta
@@ -198,7 +203,7 @@ def plot_spectrogram(ax, t, bins, pdata, peaks, max_freq):
# Startup and main routines
######################################################################
def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, max_freq=200.):
def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, scv=5. , max_freq=200.):
set_locale()
global shaper_calibrate
shaper_calibrate = setup_klipper_import(klipperdir)
@@ -209,7 +214,7 @@ def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, max
print_with_c_locale("Warning: incorrect number of .csv files detected. Only the first one will be used!")
# Compute shapers, PSD outputs and spectrogram
performance_shaper, shapers, calibration_data, fr, zeta = calibrate_shaper(datas[0], max_smoothing)
performance_shaper, shapers, calibration_data, fr, zeta = calibrate_shaper(datas[0], max_smoothing, scv, max_freq)
pdata, bins, t = compute_spectrogram(datas[0])
del datas
@@ -231,7 +236,7 @@ def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, max
# Print the peaks info in the console
peak_freqs_formated = ["{:.1f}".format(f) for f in peaks_freqs]
num_peaks_above_effect_threshold = np.sum(calibration_data.psd_sum[peaks] > peaks_threshold[1])
print_with_c_locale("Peaks detected on the graph: %d @ %s Hz (%d above effect threshold)" % (num_peaks, ", ".join(map(str, peak_freqs_formated)), num_peaks_above_effect_threshold))
print_with_c_locale("\nPeaks detected on the graph: %d @ %s Hz (%d above effect threshold)" % (num_peaks, ", ".join(map(str, peak_freqs_formated)), num_peaks_above_effect_threshold))
# Create graph layout
fig, (ax1, ax2) = plt.subplots(2, 1, gridspec_kw={
@@ -245,17 +250,23 @@ def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, max
})
fig.set_size_inches(8.3, 11.6)
# Add title
# Add a title with some test info
title_line1 = "INPUT SHAPER CALIBRATION TOOL"
fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
try:
filename_parts = (lognames[0].split('/')[-1]).split('_')
dt = datetime.strptime(f"{filename_parts[1]} {filename_parts[2]}", "%Y%m%d %H%M%S")
title_line2 = dt.strftime('%x %X') + ' -- ' + filename_parts[3].upper().split('.')[0] + ' axis'
title_line3 = '| Square corner velocity: ' + str(scv) + 'mm/s'
title_line4 = '| Max allowed smoothing: ' + str(max_smoothing)
except:
print_with_c_locale("Warning: CSV filename look to be different than expected (%s)" % (lognames[0]))
title_line2 = lognames[0].split('/')[-1]
title_line3 = ''
title_line4 = ''
fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
fig.text(0.58, 0.960, title_line3, ha='left', va='top', fontsize=10, color=KLIPPAIN_COLORS['dark_purple'])
fig.text(0.58, 0.946, title_line4, ha='left', va='top', fontsize=10, color=KLIPPAIN_COLORS['dark_purple'])
# Plot the graphs
plot_freq_response(ax1, calibration_data, shapers, performance_shaper, peaks, peaks_freqs, peaks_threshold, fr, zeta, max_freq)
@@ -284,6 +295,8 @@ def main():
help="maximum frequency to graph")
opts.add_option("-s", "--max_smoothing", type="float", default=None,
help="maximum shaper smoothing to allow")
opts.add_option("--scv", "--square_corner_velocity", type="float",
dest="scv", default=5., help="square corner velocity")
opts.add_option("-k", "--klipper_dir", type="string", dest="klipperdir",
default="~/klipper", help="main klipper directory")
options, args = opts.parse_args()
@@ -294,7 +307,7 @@ def main():
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)")
fig = shaper_calibration(args, options.klipperdir, options.max_smoothing, options.max_freq)
fig = shaper_calibration(args, options.klipperdir, options.max_smoothing, options.scv, options.max_freq)
fig.savefig(options.output, dpi=150)

10
K-ShakeTune/scripts/is_workflow.py
View File

@@ -93,7 +93,7 @@ def create_belts_graph(keep_csv):
return
def create_shaper_graph(keep_csv):
def create_shaper_graph(keep_csv, max_smoothing, scv):
current_date = datetime.now().strftime('%Y%m%d_%H%M%S')
# Get all the files and sort them based on last modified time to select the most recent one
@@ -120,7 +120,7 @@ def create_shaper_graph(keep_csv):
time.sleep(2)
# Generate the shaper graph and its name
fig = shaper_calibration([new_file], KLIPPER_FOLDER)
fig = shaper_calibration([new_file], KLIPPER_FOLDER, max_smoothing=max_smoothing, scv=scv)
png_filename = os.path.join(RESULTS_FOLDER, RESULTS_SUBFOLDERS[1], f'resonances_{current_date}_{axis}.png')
fig.savefig(png_filename, dpi=150)
@@ -263,6 +263,10 @@ def main():
help="number of results to keep in the result folder after each run of the script")
opts.add_option("-c", "--keep_csv", action="store_true", default=False, dest="keep_csv",
help="weither or not to keep the CSV files alongside the PNG graphs image results")
opts.add_option("--scv", "--square_corner_velocity", type="float", dest="scv", default=5.,
help="square corner velocity used to compute max accel for axis shapers graphs")
opts.add_option("--max_smoothing", type="float", dest="max_smoothing", default=None,
help="maximum shaper smoothing to allow")
options, args = opts.parse_args()
if options.type is None:
@@ -282,7 +286,7 @@ def main():
create_belts_graph(keep_csv=options.keep_csv)
print(f"Belt graph created. You will find the results in {RESULTS_FOLDER}/{RESULTS_SUBFOLDERS[0]}")
elif graph_mode.lower() == 'shaper':
axis = create_shaper_graph(keep_csv=options.keep_csv)
axis = create_shaper_graph(keep_csv=options.keep_csv, max_smoothing=options.max_smoothing, scv=options.scv)
print(f"{axis} input shaper graph created. You will find the results in {RESULTS_FOLDER}/{RESULTS_SUBFOLDERS[1]}")
elif graph_mode.lower() == 'vibrations':
create_vibrations_graph(axis_name=options.axis_name, accel=options.accel_used, chip_name=options.chip_name, keep_csv=options.keep_csv)