fixed MHI LUT to give values on all the range

K-ShakeTune/scripts/graph_belts.py

@@ -330,15 +330,15 @@ def compute_mhi(combined_data, similarity_coefficient, num_unpaired_peaks):
 def mhi_lut(mhi):
     if 0 <= mhi <= 30:
         return "Excellent mechanical health"
-    elif 31 <= mhi <= 45:
+    elif 30 < mhi <= 45:
         return "Good mechanical health"
-    elif 46 <= mhi <= 55:
+    elif 45 < mhi <= 55:
         return "Acceptable mechanical health"
-    elif 56 <= mhi <= 70:
+    elif 55 < mhi <= 70:
         return "Potential signs of a mechanical issue"
-    elif 71 <= mhi <= 85:
+    elif 70 < mhi <= 85:
         return "Likely a mechanical issue"
-    elif 86 <= mhi <= 100:
+    elif 85 < mhi <= 100:
         return "Mechanical issue detected"
 
 
@@ -570,11 +570,15 @@ def belts_calibration(lognames, klipperdir="~/klipper", max_freq=200.):
     ax2 = fig.add_subplot(gs[1])
 
     # Add title
-    filename = lognames[0].split('/')[-1]
-    dt = datetime.strptime(f"{filename.split('_')[1]} {filename.split('_')[2]}", "%Y%m%d %H%M%S")
     title_line1 = "RELATIVE BELT CALIBRATION TOOL"
-    title_line2 = dt.strftime('%x %X')
     fig.text(0.12, 0.965, title_line1, ha='left', va='bottom', fontsize=20, color=KLIPPAIN_COLORS['purple'], weight='bold')
+    try:
+        filename = lognames[0].split('/')[-1]
+        dt = datetime.strptime(f"{filename.split('_')[1]} {filename.split('_')[2]}", "%Y%m%d %H%M%S")
+        title_line2 = dt.strftime('%x %X')
+    except:
+        print("Warning: CSV filenames look to be different than expected (%s , %s)" % (lognames[0], lognames[1]))
+        title_line2 = lognames[0].split('/')[-1] + " / " +  lognames[1].split('/')[-1]
     fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
 
     # Plot the graphs

K-ShakeTune/scripts/graph_shaper.py

@@ -311,11 +311,15 @@ def shaper_calibration(lognames, klipperdir="~/klipper", max_smoothing=None, max
     ax2 = fig.add_subplot(gs[1])
     
     # Add title
-    filename_parts = (lognames[0].split('/')[-1]).split('_')
-    dt = datetime.strptime(f"{filename_parts[3]} {filename_parts[4].split('.')[0]}", "%Y%m%d %H%M%S")
     title_line1 = "INPUT SHAPER CALIBRATION TOOL"
-    title_line2 = dt.strftime('%x %X') + ' -- ' + filename_parts[2].upper() + ' axis'
     fig.text(0.12, 0.965, 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'
+    except:
+        print("Warning: CSV filename look to be different than expected (%s)" % (lognames[0]))
+        title_line2 = lognames[0].split('/')[-1]
     fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
 
     # Plot the graphs

K-ShakeTune/scripts/graph_vibrations.py

@@ -348,7 +348,7 @@ def setup_klipper_import(kdir):
     shaper_calibrate = importlib.import_module('.shaper_calibrate', 'extras')
 
 
-def vibrations_calibration(lognames, klipperdir="~/klipper", axisname=None, max_freq=200., remove=0):
+def vibrations_calibration(lognames, klipperdir="~/klipper", axisname=None, max_freq=1000., remove=0):
     setup_klipper_import(klipperdir)
 
     # Parse the raw data and get them ready for analysis
@@ -368,11 +368,15 @@ def vibrations_calibration(lognames, klipperdir="~/klipper", axisname=None, max_
     ax1 = fig.add_subplot(gs[0])
     ax2 = fig.add_subplot(gs[1])
 
-    filename_parts = (lognames[0].split('/')[-1]).split('_')
-    dt = datetime.strptime(f"{filename_parts[1]} {filename_parts[2].split('-')[0]}", "%Y%m%d %H%M%S")
     title_line1 = "VIBRATIONS MEASUREMENT TOOL"
-    title_line2 = dt.strftime('%x %X') + ' -- ' + axisname.upper() + ' axis'
     fig.text(0.12, 0.965, 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].split('-')[0]}", "%Y%m%d %H%M%S")
+        title_line2 = dt.strftime('%x %X') + ' -- ' + axisname.upper() + ' axis'
+    except:
+        print("Warning: CSV filename look to be different than expected (%s)" % (lognames[0]))
+        title_line2 = lognames[0].split('/')[-1]
     fig.text(0.12, 0.957, title_line2, ha='left', va='top', fontsize=16, color=KLIPPAIN_COLORS['dark_purple'])
 
     # Remove speeds duplicates and graph the processed datas

README.md

@@ -39,12 +39,16 @@ For those not using the full [Klippain](https://github.com/Frix-x/klippain), fol
      managed_services: klipper
      install_script: install.sh
      ```
+   
+   > **Note**:
+   >
+   > If already using my old IS workflow scripts, please remove everything before installing this new module. This include the macros, the Python scripts, the `plot_graph.sh` and the `[gcode_shell_command plot_graph]` section.
 
 ## Usage
 
 Ensure your machine is homed, then invoke one of the following macros as needed:
   - `BELTS_SHAPER_CALIBRATION` for belt resonance graphs, useful for verifying belt tension and differential belt paths behavior.
-  - `AXES_SHAPER_CALIBRATION` for input shaper graphs to mitigate ringing/ghosting by tuning Klipper's `[input_shaper]` system.
+  - `AXES_SHAPER_CALIBRATION` for input shaper graphs to mitigate ringing/ghosting by tuning Klipper's input shaper system.
   - `VIBRATIONS_CALIBRATION` for machine vibration graphs to optimize your slicer speed profiles.
   - `EXCITATE_AXIS_AT_FREQ` to sustain a specific excitation frequency, useful to let you inspect and find out what is resonating.