reijii/klippain-shaketune-telegramm
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code cleanup

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This commit is contained in:
Félix Boisselier
2024-06-29 23:56:16 +02:00
parent 3d919898a6
commit 8d59e33775
3 changed files with 8 additions and 12 deletions
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2
README.md
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@@ -34,7 +34,7 @@ Follow these steps to install Shake&Tune on your printer:
# motor_freq: # motor_freq:
# /!\ This option has limitations in stock Klipper and is best used with DangerKlipper /!\ # /!\ This option has limitations in stock Klipper and is best used with DangerKlipper /!\
# Frequencies of X and Y motor resonances to filter them using # Frequencies of X and Y motor resonances to filter them by using
# composite shapers. This requires the `[input_shaper]` config # composite shapers. This requires the `[input_shaper]` config
# section to be defined in your printer.cfg file to work. # section to be defined in your printer.cfg file to work.
# motor_freq_x: # motor_freq_x:

5
shaketune/graph_creators/vibrations_graph_creator.py
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@@ -39,6 +39,7 @@ from ..helpers.motors_config_parser import Motor, MotorsConfigParser
from ..shaketune_config import ShakeTuneConfig from ..shaketune_config import ShakeTuneConfig
from .graph_creator import GraphCreator from .graph_creator import GraphCreator
DEFAULT_LOW_FREQ_MAX = 30
PEAKS_DETECTION_THRESHOLD = 0.05 PEAKS_DETECTION_THRESHOLD = 0.05
PEAKS_RELATIVE_HEIGHT_THRESHOLD = 0.04 PEAKS_RELATIVE_HEIGHT_THRESHOLD = 0.04
CURVE_SIMILARITY_SIGMOID_K = 0.5 CURVE_SIMILARITY_SIGMOID_K = 0.5
@@ -115,7 +116,7 @@ def calc_freq_response(data) -> Tuple[np.ndarray, np.ndarray]:
def find_motor_characteristics(motor: str, freqs: np.ndarray, psd: np.ndarray) -> Tuple[float, float, int]: def find_motor_characteristics(motor: str, freqs: np.ndarray, psd: np.ndarray) -> Tuple[float, float, int]:
motor_fr, motor_zeta, motor_res_idx, lowfreq_max = compute_mechanical_parameters(psd, freqs, 30) motor_fr, motor_zeta, motor_res_idx, lowfreq_max = compute_mechanical_parameters(psd, freqs, DEFAULT_LOW_FREQ_MAX)
if lowfreq_max: if lowfreq_max:
ConsoleOutput.print( ConsoleOutput.print(
@@ -151,7 +152,7 @@ def compute_motor_profiles(freqs: np.ndarray, psds: dict, measured_angles: Optio
motor_profiles = {} motor_profiles = {}
conv_filter = np.ones(20) / 20 conv_filter = np.ones(20) / 20
# Creating the PSD motor profiles for each angles by summing the PSDs for each speeds # Creating the PSD motor profiles for each angle by summing the PSDs for each speed
for angle in measured_angles: for angle in measured_angles:
sum_curve = np.sum(np.array([psds[angle][speed] for speed in psds[angle]]), axis=0) sum_curve = np.sum(np.array([psds[angle][speed] for speed in psds[angle]]), axis=0)
motor_profiles[angle] = np.convolve(sum_curve / len(psds[angle]), conv_filter, mode='same') motor_profiles[angle] = np.convolve(sum_curve / len(psds[angle]), conv_filter, mode='same')

5
shaketune/motor_res_filter.py
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@@ -99,11 +99,6 @@ class MotorResonanceFilter:
a3 = a1 * K * K a3 = a1 * K * K
motor_filter_A = [a1, a2, a3] motor_filter_A = [a1, a2, a3]
motor_filter_T = [0.0, 0.375 * t_d, 0.75 * t_d] motor_filter_T = [0.0, 0.375 * t_d, 0.75 * t_d]
combined_filter_A, combined_filter_T = MotorResonanceFilter.convolve_shapers(
(axis_shaper_A, axis_shaper_T),
(motor_filter_A, motor_filter_T),
)
else: else:
# In stock Klipper, the pulse train is too small for most shapers # In stock Klipper, the pulse train is too small for most shapers
# to be convolved. So we need to use the ZV shaper instead for the # to be convolved. So we need to use the ZV shaper instead for the