diff options
| -rwxr-xr-x | scripts/graph_extruder.py | 122 |
1 files changed, 74 insertions, 48 deletions
diff --git a/scripts/graph_extruder.py b/scripts/graph_extruder.py index 1a5bfb6c..241f727f 100755 --- a/scripts/graph_extruder.py +++ b/scripts/graph_extruder.py @@ -1,7 +1,7 @@ #!/usr/bin/env python2 # Generate extruder pressure advance motion graphs # -# Copyright (C) 2019 Kevin O'Connor <kevin@koconnor.net> +# Copyright (C) 2019-2020 Kevin O'Connor <kevin@koconnor.net> # # This file may be distributed under the terms of the GNU GPLv3 license. import math, optparse, datetime @@ -17,7 +17,7 @@ INV_SEG_TIME = 1. / SEG_TIME # List of moves: [(start_v, end_v, move_t), ...] Moves = [ - (0., 0., .200), + (0., 0., .100), (0., 100., None), (100., 100., .200), (100., 60., None), (60., 100., None), (100., 100., .200), (100., 0., None), (0., 0., .300) @@ -47,85 +47,111 @@ def gen_positions(): start_t = end_t return out + +###################################################################### +# List helper functions +###################################################################### + +MARGIN_TIME = 0.050 + +def time_to_index(t): + return int(t * INV_SEG_TIME + .5) + +def indexes(positions): + drop = time_to_index(MARGIN_TIME) + return range(drop, len(positions)-drop) + +def trim_lists(*lists): + keep = len(lists[0]) - time_to_index(2. * MARGIN_TIME) + for l in lists: + del l[keep:] + + +###################################################################### +# Common data filters +###################################################################### + +# Generate estimated first order derivative def gen_deriv(data): return [0.] + [(data[i+1] - data[i]) * INV_SEG_TIME for i in range(len(data)-1)] -def time_to_index(t): - return int(t * INV_SEG_TIME + .5) +# Simple average between two points smooth_time away +def calc_average(positions, smooth_time): + offset = time_to_index(smooth_time * .5) + out = [0.] * len(positions) + for i in indexes(positions): + out[i] = .5 * (positions[i-offset] + positions[i+offset]) + return out + +# Average (via integration) of smooth_time range +def calc_smooth(positions, smooth_time): + offset = time_to_index(smooth_time * .5) + weight = 1. / (2*offset - 1) + out = [0.] * len(positions) + for i in indexes(positions): + out[i] = sum(positions[i-offset+1:i+offset]) * weight + return out + +# Time weighted average (via integration) of smooth_time range +def calc_weighted(positions, smooth_time): + offset = time_to_index(smooth_time * .5) + weight = 1. / offset**2 + out = [0.] * len(positions) + for i in indexes(positions): + weighted_data = [positions[j] * (offset - abs(j-i)) + for j in range(i-offset, i+offset)] + out[i] = sum(weighted_data) * weight + return out ###################################################################### # Pressure advance ###################################################################### -PA_HALF_SMOOTH_T = .040 / 2. +SMOOTH_TIME = .040 PRESSURE_ADVANCE = .045 # Calculate raw pressure advance positions -def calc_pa_raw(t, positions): +def calc_pa_raw(positions): pa = PRESSURE_ADVANCE * INV_SEG_TIME - i = time_to_index(t) - return positions[i] + pa * (positions[i+1] - positions[i]) - -# Pressure advance smoothed using average velocity (for reference only) -def calc_pa_average(t, positions): - pa_factor = PRESSURE_ADVANCE / (2. * PA_HALF_SMOOTH_T) - base_pos = positions[time_to_index(t)] - start_pos = positions[time_to_index(t - PA_HALF_SMOOTH_T)] - end_pos = positions[time_to_index(t + PA_HALF_SMOOTH_T)] - return base_pos + (end_pos - start_pos) * pa_factor - -# Pressure advance with simple time smoothing (for reference only) -def calc_pa_smooth(t, positions): - start_index = time_to_index(t - PA_HALF_SMOOTH_T) + 1 - end_index = time_to_index(t + PA_HALF_SMOOTH_T) - pa = PRESSURE_ADVANCE * INV_SEG_TIME - pa_data = [positions[i] + pa * (positions[i+1] - positions[i]) - for i in range(start_index, end_index)] - return sum(pa_data) / (end_index - start_index) + out = [0.] * len(positions) + for i in indexes(positions): + out[i] = positions[i] + pa * (positions[i+1] - positions[i]) + return out -# Calculate pressure advance smoothed using a "weighted average" -def calc_pa_weighted(t, positions): - base_index = time_to_index(t) - start_index = time_to_index(t - PA_HALF_SMOOTH_T) + 1 - end_index = time_to_index(t + PA_HALF_SMOOTH_T) - diff = .5 * (end_index - start_index) - pa = PRESSURE_ADVANCE * INV_SEG_TIME - pa_data = [(positions[i] + pa * (positions[i+1] - positions[i])) - * (diff - abs(i-base_index)) - for i in range(start_index, end_index)] - return sum(pa_data) / diff**2 +# Pressure advance after smoothing +def calc_pa(positions): + return calc_weighted(calc_pa_raw(positions), SMOOTH_TIME) ###################################################################### # Plotting and startup ###################################################################### -MARGIN_TIME = 0.100 - def plot_motion(): # Nominal motion positions = gen_positions() - drop = int(MARGIN_TIME * INV_SEG_TIME) - times = [SEG_TIME * t for t in range(len(positions))][drop:-drop] - velocities = gen_deriv(positions[drop:-drop]) + velocities = gen_deriv(positions) + accels = gen_deriv(velocities) # Motion with pressure advance - pa_positions = [calc_pa_raw(t, positions) for t in times] + pa_positions = calc_pa_raw(positions) pa_velocities = gen_deriv(pa_positions) # Smoothed motion - sm_positions = [calc_pa_weighted(t, positions) for t in times] + sm_positions = calc_pa(positions) sm_velocities = gen_deriv(sm_positions) # Build plot - shift_times = [t - MARGIN_TIME for t in times] + times = [SEG_TIME * i for i in range(len(positions))] + trim_lists(times, velocities, accels, + pa_positions, pa_velocities, + sm_positions, sm_velocities) fig, ax1 = matplotlib.pyplot.subplots(nrows=1, sharex=True) ax1.set_title("Extruder Velocity") ax1.set_ylabel('Velocity (mm/s)') - pa_plot, = ax1.plot(shift_times, pa_velocities, 'r', + pa_plot, = ax1.plot(times, pa_velocities, 'r', label='Pressure Advance', alpha=0.3) - nom_plot, = ax1.plot(shift_times, velocities, 'black', label='Nominal') - sm_plot, = ax1.plot(shift_times, sm_velocities, 'g', label='Smooth PA', - alpha=0.9) + nom_plot, = ax1.plot(times, velocities, 'black', label='Nominal') + sm_plot, = ax1.plot(times, sm_velocities, 'g', label='Smooth PA', alpha=0.9) fontP = matplotlib.font_manager.FontProperties() fontP.set_size('x-small') ax1.legend(handles=[nom_plot, pa_plot, sm_plot], loc='best', prop=fontP) |