diff options
Diffstat (limited to 'scripts/calibrate_shaper.py')
| -rwxr-xr-x | scripts/calibrate_shaper.py | 47 |
1 files changed, 25 insertions, 22 deletions
diff --git a/scripts/calibrate_shaper.py b/scripts/calibrate_shaper.py index 22b32b23..82c15ed1 100755 --- a/scripts/calibrate_shaper.py +++ b/scripts/calibrate_shaper.py @@ -7,11 +7,14 @@ # This file may be distributed under the terms of the GNU GPLv3 license. from __future__ import print_function import optparse, os, sys +from textwrap import wrap import numpy as np, matplotlib sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', 'klippy', 'extras')) from shaper_calibrate import CalibrationData, ShaperCalibrate +MAX_TITLE_LENGTH=65 + def parse_log(logname): with open(logname) as f: for header in f: @@ -61,7 +64,7 @@ def calibrate_shaper(datas, csv_output): # Plot frequency response and suggested input shapers ###################################################################### -def plot_freq_response(calibration_data, shapers_vals, +def plot_freq_response(lognames, calibration_data, shapers_vals, selected_shaper, max_freq): freqs = calibration_data.freq_bins psd = calibration_data.psd_sum[freqs <= max_freq] @@ -83,10 +86,8 @@ def plot_freq_response(calibration_data, shapers_vals, ax.plot(freqs, py, label='Y', color='green') ax.plot(freqs, pz, label='Z', color='blue') - if shapers_vals: - ax.set_title("Frequency response and shapers") - else: - ax.set_title("Frequency response") + title = "Frequency response and shapers (%s)" % (', '.join(lognames)) + ax.set_title("\n".join(wrap(title, MAX_TITLE_LENGTH))) ax.xaxis.set_minor_locator(matplotlib.ticker.AutoMinorLocator()) ax.yaxis.set_minor_locator(matplotlib.ticker.AutoMinorLocator()) ax.xaxis.set_minor_locator(matplotlib.ticker.AutoMinorLocator()) @@ -94,23 +95,25 @@ def plot_freq_response(calibration_data, shapers_vals, ax.ticklabel_format(axis='y', style='scientific', scilimits=(0,0)) ax.grid(which='major', color='grey') ax.grid(which='minor', color='lightgrey') - ax.legend(loc='upper right', prop=fontP) - if 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) - linestyle = 'dotted' - if name == selected_shaper: - label += ' (selected)' - linestyle = 'dashdot' - best_shaper_vals = vals - ax2.plot(freqs, vals, label=label, linestyle=linestyle) - ax.plot(freqs, psd * best_shaper_vals, - label='After\nshaper', color='cyan') - ax2.legend(loc='upper left', prop=fontP) + 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) + linestyle = 'dotted' + if name == selected_shaper: + linestyle = 'dashdot' + best_shaper_vals = vals + ax2.plot(freqs, 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 + ax2.plot([], [], ' ', + label="Recommended shaper: %s" % (selected_shaper.upper())) + + ax.legend(loc='upper left', prop=fontP) + ax2.legend(loc='upper right', prop=fontP) fig.tight_layout() return fig @@ -152,7 +155,7 @@ def main(): # Draw graph setup_matplotlib(options.output is not None) - fig = plot_freq_response(calibration_data, shapers_vals, + fig = plot_freq_response(args, calibration_data, shapers_vals, selected_shaper, options.max_freq) # Show graph |