QIDITECH/klipper
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plus4的klipper版本

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whb0514
2024-09-02 13:37:34 +08:00
parent 653d7a8f6e
commit b90736975b
1006 changed files with 1195894 additions and 11114 deletions
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56
scripts/graph_accelerometer.py
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@@ -17,35 +17,50 @@ MAX_TITLE_LENGTH=65
def parse_log(logname, opts):
with open(logname) as f:
for header in f:
if not header.startswith('#'):
if header.startswith('#'):
continue
if header.startswith('freq,psd_x,psd_y,psd_z,psd_xyz'):
# Processed power spectral density file
break
if not header.startswith('freq,psd_x,psd_y,psd_z,psd_xyz'):
# Raw accelerometer data
return np.loadtxt(logname, comments='#', delimiter=',')
# Power spectral density data or shaper calibration data
opts.error("File %s does not contain raw accelerometer data and therefore "
"is not supported by graph_accelerometer.py script. Please use "
"calibrate_shaper.py script to process it instead." % (logname,))
# Parse power spectral density data
data = np.loadtxt(logname, skiprows=1, comments='#', delimiter=',')
calibration_data = shaper_calibrate.CalibrationData(
freq_bins=data[:,0], psd_sum=data[:,4],
psd_x=data[:,1], psd_y=data[:,2], psd_z=data[:,3])
calibration_data.set_numpy(np)
return calibration_data
######################################################################
# Raw accelerometer graphing
######################################################################
def plot_accel(data, logname):
first_time = data[0, 0]
times = data[:,0] - first_time
def plot_accel(datas, lognames):
fig, axes = matplotlib.pyplot.subplots(nrows=3, sharex=True)
axes[0].set_title("\n".join(wrap("Accelerometer data (%s)" % (logname,),
MAX_TITLE_LENGTH)))
axes[0].set_title("\n".join(wrap(
"Accelerometer data (%s)" % (', '.join(lognames)), MAX_TITLE_LENGTH)))
axis_names = ['x', 'y', 'z']
for data, logname in zip(datas, lognames):
if isinstance(data, shaper_calibrate.CalibrationData):
raise error("Cannot plot raw accelerometer data using the processed"
" resonances, raw_data input is required")
first_time = data[0, 0]
times = data[:,0] - first_time
for i in range(len(axis_names)):
avg = data[:,i+1].mean()
adata = data[:,i+1] - data[:,i+1].mean()
ax = axes[i]
label = '\n'.join(wrap(logname, 60)) + ' (%+.3f mm/s^2)' % (-avg,)
ax.plot(times, adata, alpha=0.8, label=label)
axes[-1].set_xlabel('Time (s)')
fontP = matplotlib.font_manager.FontProperties()
fontP.set_size('x-small')
for i in range(len(axis_names)):
avg = data[:,i+1].mean()
adata = data[:,i+1] - data[:,i+1].mean()
ax = axes[i]
ax.plot(times, adata, alpha=0.8)
ax.grid(True)
ax.set_ylabel('%s accel (%+.3f)\n(mm/s^2)' % (axis_names[i], -avg))
axes[-1].set_xlabel('Time (%+.3f)\n(s)' % (-first_time,))
ax.legend(loc='best', prop=fontP)
ax.set_ylabel('%s accel' % (axis_names[i],))
fig.tight_layout()
return fig
@@ -56,10 +71,15 @@ def plot_accel(data, logname):
# Calculate estimated "power spectral density"
def calc_freq_response(data, max_freq):
if isinstance(data, shaper_calibrate.CalibrationData):
return data
helper = shaper_calibrate.ShaperCalibrate(printer=None)
return helper.process_accelerometer_data(data)
def calc_specgram(data, axis):
if isinstance(data, shaper_calibrate.CalibrationData):
raise error("Cannot calculate the spectrogram using the processed"
" resonances, raw_data input is required")
N = data.shape[0]
Fs = N / (data[-1,0] - data[0,0])
# Round up to a power of 2 for faster FFT
@@ -235,9 +255,7 @@ def main():
# Draw graph
if options.raw:
if len(args) > 1:
opts.error("Only 1 input is supported in raw mode")
fig = plot_accel(datas[0], args[0])
fig = plot_accel(datas, args)
elif options.specgram:
if len(args) > 1:
opts.error("Only 1 input is supported in specgram mode")