switched to accel vs vibrations

Frix-x · Jul 15, 2024 · 8fd286b · 8fd286b
1 parent e364b90
commit 8fd286b
Showing 1 changed file with 54 additions and 23 deletions.
diff --git a/shaketune/graph_creators/shaper_graph_creator.py b/shaketune/graph_creators/shaper_graph_creator.py
@@ -47,8 +47,8 @@
 PEAKS_EFFECT_THRESHOLD = 0.12
 SPECTROGRAM_LOW_PERCENTILE_FILTER = 5
 MAX_VIBRATIONS = 5.0
-SMOOTHING_LIST = [0.1]
-# SMOOTHING_LIST = np.arange(0.001, 0.80, 0.05)
+MAX_VIBRATIONS_PLOTTED = 25.0
+SMOOTHING_TESTS = 10  # Number of smoothing values to test (it will significantly increase the computation time)
 KLIPPAIN_COLORS = {
     'purple': '#70088C',
     'orange': '#FF8D32',
@@ -178,7 +178,7 @@ def calibrate_shaper(datas: List[np.ndarray], max_smoothing: Optional[float], sc
                 max_smoothing = shaper.smoothing
 
     # Then we create a list of smoothing values to test (no need to test the max smoothing value as it was already tested)
-    smoothing_test_list = np.linspace(0.001, max_smoothing, 10)[:-1]
+    smoothing_test_list = np.linspace(0.001, max_smoothing, SMOOTHING_TESTS)[:-1]
     additional_all_shapers = {}
     for smoothing in smoothing_test_list:
         if compat:
@@ -294,9 +294,9 @@ def plot_freq_response(
         and perf_shaper_choice != klipper_shaper_choice
         and perf_shaper_accel >= klipper_shaper_accel
     ):
-        perf_shaper_string = f'Recommended performance shaper: {perf_shaper_choice.upper()} @ {perf_shaper_freq:.1f} Hz'
+        perf_shaper_string = f'Recommended for performance: {perf_shaper_choice.upper()} @ {perf_shaper_freq:.1f} Hz'
         lowvibr_shaper_string = (
-            f'Recommended low vibrations shaper: {klipper_shaper_choice.upper()} @ {klipper_shaper_freq:.1f} Hz'
+            f'Recommended for low vibrations: {klipper_shaper_choice.upper()} @ {klipper_shaper_freq:.1f} Hz'
         )
         shaper_table_data['recommendations'].append(perf_shaper_string)
         shaper_table_data['recommendations'].append(lowvibr_shaper_string)
@@ -421,7 +421,7 @@ def plot_smoothing_vs_accel(
     fontP = matplotlib.font_manager.FontProperties()
     fontP.set_size('x-small')
 
-    ax.xaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(1000))
+    ax.xaxis.set_minor_locator(matplotlib.ticker.MultipleLocator(500))
     ax.yaxis.set_minor_locator(matplotlib.ticker.AutoMinorLocator())
     ax.grid(which='major', color='grey')
     ax.grid(which='minor', color='lightgrey')
@@ -436,7 +436,7 @@ def plot_smoothing_vs_accel(
                 shaper_data[shaper_type] = []
             shaper_data[shaper_type].append(
                 {
-                    'smoothing': shaper.smoothing,
+                    # 'smoothing': shaper.smoothing,
                     'max_accel': shaper.max_accel,
                     'vibrs': shaper.vibrs * 100.0,
                 }
@@ -449,34 +449,37 @@ def plot_smoothing_vs_accel(
             shaper_data[shaper_type] = []
         shaper_data[shaper_type].append(
             {
-                'smoothing': float(shaper['smoothing']),
+                # 'smoothing': float(shaper['smoothing']),
                 'max_accel': float(shaper['max_accel']),
                 'vibrs': float(shaper['vibrations']) * 100.0,
             }
         )
 
-    # Plot each shaper type and add colorbar for vibrations
+    # Calculate the maximum `max_accel` for points below MAX_VIBRATIONS_PLOTTED
+    max_accel_limit = 0
+    min_accel_limit = 99999
+    for data in shaper_data.values():
+        min_accel_limit = min(min_accel_limit, min(d['max_accel'] for d in data))
+        max_accel_limit = max(max_accel_limit, max(d['max_accel'] for d in data if d['vibrs'] < MAX_VIBRATIONS_PLOTTED))
+
+    # Plot each shaper type response over acceleration in regards to vibrations
     for _, (shaper_type, data) in enumerate(shaper_data.items()):
-        smoothing_values = [d['smoothing'] for d in data]
+        # smoothing_values = [d['smoothing'] for d in data]
         max_accel_values = [d['max_accel'] for d in data]
         vibrs_values = [d['vibrs'] for d in data]
-        ax.plot(max_accel_values, smoothing_values, linestyle=':', label=f'{shaper_type}', zorder=10)
-        scatter = ax.scatter(
-            max_accel_values, smoothing_values, c=vibrs_values, cmap='plasma', s=100, edgecolors='w', zorder=15
-        )
+        ax.plot(max_accel_values, vibrs_values, linestyle='-', label=f'{shaper_type}', zorder=10)
 
-    # Add colorbar for vibrations
-    cbar = plt.colorbar(scatter, ax=ax)
-    cbar.set_label('Remaining Vibrations (%)')
     ax.set_xlabel('Max Acceleration')
-    ax.set_ylabel('Smoothing')
+    ax.set_ylabel('Remaining Vibrations (%)')
+    ax.set_xlim([min_accel_limit, max_accel_limit])
+    ax.set_ylim([0, MAX_VIBRATIONS_PLOTTED])
     ax.set_title(
-        'Smoothing vs Max Acceleration',
+        'Max Acceleration related to Vibrations',
         fontsize=14,
         color=KLIPPAIN_COLORS['dark_orange'],
         weight='bold',
     )
-    ax.legend(loc='upper right', prop=fontP)
+    ax.legend(loc='best', prop=fontP)
 
 
 def print_shaper_table(fig: plt.Figure, shaper_table_data: Dict[str, List[Dict[str, str]]]) -> None:
@@ -492,15 +495,43 @@ def print_shaper_table(fig: plt.Figure, shaper_table_data: Dict[str, List[Dict[s
             f'{round(shaper_info["max_accel"] / 10) * 10:.0f}',
         ]
         table_data.append(row)
-    table = plt.table(cellText=table_data, colLabels=columns, bbox=[1.12, -0.4, 0.75, 0.25], cellLoc='center')
+    table = plt.table(cellText=table_data, colLabels=columns, bbox=[1.130, -0.4, 0.803, 0.25], cellLoc='center')
     table.auto_set_font_size(False)
     table.set_fontsize(10)
     table.auto_set_column_width([0, 1, 2, 3, 4])
     table.set_zorder(100)
 
     # Add the recommendations and damping ratio using fig.text
-    fig.text(0.58, 0.235, f'Estimated damping ratio (ζ): {shaper_table_data["damping_ratio"]:.3f}', fontsize=14)
-    fig.text(0.58, 0.210, '\n'.join(shaper_table_data['recommendations']), fontsize=14)
+    fig.text(
+        0.585,
+        0.235,
+        f'Estimated damping ratio (ζ): {shaper_table_data["damping_ratio"]:.3f}',
+        fontsize=14,
+        color=KLIPPAIN_COLORS['purple'],
+    )
+    if len(shaper_table_data['recommendations']) == 1:
+        fig.text(
+            0.585,
+            0.200,
+            shaper_table_data['recommendations'][0],
+            fontsize=14,
+            color=KLIPPAIN_COLORS['red_pink'],
+        )
+    elif len(shaper_table_data['recommendations']) == 2:
+        fig.text(
+            0.585,
+            0.200,
+            shaper_table_data['recommendations'][0],
+            fontsize=14,
+            color=KLIPPAIN_COLORS['red_pink'],
+        )
+        fig.text(
+            0.585,
+            0.175,
+            shaper_table_data['recommendations'][1],
+            fontsize=14,
+            color=KLIPPAIN_COLORS['red_pink'],
+        )
 
 
 ######################################################################