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Code cleanup before release (#114)

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Félix Boisselier
2024-06-10 23:42:10 +02:00
committed by GitHub
parent 9739f6220e
commit 6db1d394ae
24 changed files with 575 additions and 471 deletions
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shaketune/graph_creators/static_graph_creator.py Normal file
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#!/usr/bin/env python3
import optparse
import os
from datetime import datetime
from typing import List, Optional
import matplotlib
import matplotlib.font_manager
import matplotlib.pyplot as plt
import matplotlib.ticker
import numpy as np
matplotlib.use('Agg')
from ..helpers.common_func import compute_spectrogram, parse_log
from ..helpers.console_output import ConsoleOutput
from ..shaketune_config import ShakeTuneConfig
from .graph_creator import GraphCreator
PEAKS_DETECTION_THRESHOLD = 0.05
PEAKS_EFFECT_THRESHOLD = 0.12
SPECTROGRAM_LOW_PERCENTILE_FILTER = 5
MAX_VIBRATIONS = 5.0
KLIPPAIN_COLORS = {
'purple': '#70088C',
'orange': '#FF8D32',
'dark_purple': '#150140',
'dark_orange': '#F24130',
'red_pink': '#F2055C',
}
class StaticGraphCreator(GraphCreator):
def __init__(self, config: ShakeTuneConfig):
super().__init__(config, 'static frequency')
self._freq: Optional[float] = None
self._duration: Optional[float] = None
self._accel_per_hz: Optional[float] = None
def configure(self, freq: float, duration: float, accel_per_hz: Optional[float] = None) -> None:
self._freq = freq
self._duration = duration
self._accel_per_hz = accel_per_hz
def create_graph(self) -> None:
if not self._freq or not self._duration or not self._accel_per_hz:
raise ValueError('freq, duration and accel_per_hz must be set to create the static frequency graph!')
lognames = self._move_and_prepare_files(
glob_pattern='shaketune-staticfreq_*.csv',
min_files_required=1,
custom_name_func=lambda f: f.stem.split('_')[1].upper(),
)
fig = static_frequency_tool(
lognames=[str(path) for path in lognames],
klipperdir=str(self._config.klipper_folder),
freq=self._freq,
duration=self._duration,
max_freq=200.0,
accel_per_hz=self._accel_per_hz,
st_version=self._version,
)
self._save_figure_and_cleanup(fig, lognames, lognames[0].stem.split('_')[-1])
def clean_old_files(self, keep_results: int = 3) -> None:
files = sorted(self._folder.glob('*.png'), key=lambda f: f.stat().st_mtime, reverse=True)
if len(files) <= keep_results:
return # No need to delete any files
for old_file in files[keep_results:]:
csv_file = old_file.with_suffix('.csv')
csv_file.unlink(missing_ok=True)
old_file.unlink()
######################################################################
# Graphing
######################################################################
def plot_spectrogram(ax: plt.Axes, t: np.ndarray, bins: np.ndarray, pdata: np.ndarray, max_freq: float) -> None:
ax.set_title('Time-Frequency Spectrogram', fontsize=14, color=KLIPPAIN_COLORS['dark_orange'], weight='bold')
vmin_value = np.percentile(pdata, SPECTROGRAM_LOW_PERCENTILE_FILTER)
cm = 'inferno'
norm = matplotlib.colors.LogNorm(vmin=vmin_value)
ax.imshow(
pdata.T,
norm=norm,
cmap=cm,
aspect='auto',
extent=[t[0], t[-1], bins[0], bins[-1]],
origin='lower',
interpolation='antialiased',
)
ax.set_xlim([0.0, max_freq])
ax.set_ylabel('Time (s)')
ax.set_xlabel('Frequency (Hz)')
return
def plot_energy_accumulation(ax: plt.Axes, t: np.ndarray, bins: np.ndarray, pdata: np.ndarray) -> None:
# Integrate the energy over the frequency bins for each time step and plot this vertically
ax.plot(np.trapz(pdata, t, axis=0), bins, color=KLIPPAIN_COLORS['orange'])
ax.set_title('Vibrations', fontsize=14, color=KLIPPAIN_COLORS['dark_orange'], weight='bold')
ax.set_xlabel('Cumulative Energy')
ax.set_ylabel('Time (s)')
ax.set_ylim([bins[0], bins[-1]])
ax.xaxis.set_minor_locator(matplotlib.ticker.AutoMinorLocator())
ax.yaxis.set_minor_locator(matplotlib.ticker.AutoMinorLocator())
ax.ticklabel_format(axis='x', style='scientific', scilimits=(0, 0))
ax.grid(which='major', color='grey')
ax.grid(which='minor', color='lightgrey')
# ax.legend()
######################################################################
# Startup and main routines
######################################################################
def static_frequency_tool(
lognames: List[str],
klipperdir: str = '~/klipper',
freq: Optional[float] = None,
duration: Optional[float] = None,
max_freq: float = 500.0,
accel_per_hz: Optional[float] = None,
st_version: str = 'unknown',
) -> plt.Figure:
if freq is None or duration is None:
raise ValueError('Error: missing frequency or duration parameters!')
datas = [data for data in (parse_log(fn) for fn in lognames) if data is not None]
if len(datas) > 1:
ConsoleOutput.print('Warning: incorrect number of .csv files detected. Only the first one will be used!')
pdata, bins, t = compute_spectrogram(datas[0])
del datas
fig, ((ax1, ax3)) = plt.subplots(
1,
2,
gridspec_kw={
'width_ratios': [5, 3],
'bottom': 0.080,
'top': 0.840,
'left': 0.050,
'right': 0.985,
'hspace': 0.166,
'wspace': 0.138,
},
)
fig.set_size_inches(15, 7)
title_line1 = 'STATIC FREQUENCY HELPER TOOL'
fig.text(
0.060, 0.947, 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 = f'| Maintained frequency: {freq}Hz for {duration}s'
title_line4 = f'| Accel per Hz used: {accel_per_hz} mm/s²/Hz' if accel_per_hz is not None else ''
except Exception:
ConsoleOutput.print(f'Warning: CSV filename look to be different than expected ({lognames[0]})')
title_line2 = lognames[0].split('/')[-1]
title_line3 = ''
title_line4 = ''
fig.text(0.060, 0.939, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
fig.text(0.55, 0.985, title_line3, ha='left', va='top', fontsize=14, color=KLIPPAIN_COLORS['dark_purple'])
fig.text(0.55, 0.950, title_line4, ha='left', va='top', fontsize=11, color=KLIPPAIN_COLORS['dark_purple'])
plot_spectrogram(ax1, t, bins, pdata, max_freq)
plot_energy_accumulation(ax3, t, bins, pdata)
ax_logo = fig.add_axes([0.001, 0.894, 0.105, 0.105], anchor='NW')
ax_logo.imshow(plt.imread(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'klippain.png')))
ax_logo.axis('off')
if st_version != 'unknown':
fig.text(0.995, 0.980, st_version, ha='right', va='bottom', fontsize=8, color=KLIPPAIN_COLORS['purple'])
return fig
def main():
usage = '%prog [options] <logs>'
opts = optparse.OptionParser(usage)
opts.add_option('-o', '--output', type='string', dest='output', default=None, help='filename of output graph')
opts.add_option('-f', '--freq', type='float', default=None, help='frequency maintained during the measurement')
opts.add_option('-d', '--duration', type='float', default=None, help='duration of the measurement')
opts.add_option('--max_freq', type='float', default=500.0, help='maximum frequency to graph')
opts.add_option('--accel_per_hz', type='float', default=None, help='accel_per_hz used during the measurement')
opts.add_option(
'-k', '--klipper_dir', type='string', dest='klipperdir', default='~/klipper', help='main klipper directory'
)
options, args = opts.parse_args()
if len(args) < 1:
opts.error('Incorrect number of arguments')
if options.output is None:
opts.error('You must specify an output file.png to use the script (option -o)')
fig = static_frequency_tool(
args, options.klipperdir, options.freq, options.duration, options.max_freq, options.accel_per_hz, 'unknown'
)
fig.savefig(options.output, dpi=150)
if __name__ == '__main__':
main()