Bad BPM presentation

docs/css/custom_colors.css

@@ -0,0 +1,24 @@
+/* docs/css/custom_colors.css */
+
+/* Define the specific colors using CSS variables (optional but good practice) */
+:root {
+  --color-cernniceblue: #0669b2;
+  --color-atlasgreen: #27a572;  
+  --color-cernred: #e15e32;     
+  --color-atlasorange: #f09010; 
+  --color-cernlightblue: #15b3da;
+  --color-cernpurple: #6e2466;   
+}
+
+/* General emphasis class */
+.omc-emph {
+  color: var(--md-primary-fg-color);
+  font-weight: bold;
+}
+
+/* Custom emphasis classes (for bpm_filtering.md) */
+.tbt-related { color: var(--color-atlasgreen); font-weight: bold; }
+.svd-related { color: var(--color-cernred); font-weight: bold; }
+.spec-related { color: var(--color-atlasorange); font-weight: bold; }
+.manual-related { color: var(--color-cernlightblue); font-weight: bold; }
+.iforest-related { color: var(--color-cernpurple); font-weight: bold; }

docs/measurements/physics/bpm_filtering.md

@@ -0,0 +1,92 @@
+
+
+The content of this page has been converted from the presenation given as ["OMC3 bad BPM detection" on the 31.03.2025](https://indico.cern.ch/event/1531923/) .
+
+
+## OMC-Analysis
+
+![BPM vs Owl](../../assets/images/bpm_filtering/bpmvsowl.png)
+
+* To get <span class="omc-emph">reliable</span> and <span class="omc-emph">reproducible</span> optics measurements, we cannot trust all BPM data that we are getting.
+* At <span class="omc-emph">different stages</span> of the code, we try to determine the ``trustworthyness''.
+* Some BPMs are fully <span class="omc-emph">excluded</span>, others are getting <span class="omc-emph">errorbars</span> based on their <span class="omc-emph">noise-level</span> (which are often used as *weights*, e.g. for correction calculations).
+
+
+## Automatic
+
+* First the <span class="tbt-related">Turn-by-Turn Data</span> is checked for ``obvious'' signs.
+    * <span class="tbt-related">EXACT_ZERO</span>: Any value has an <span class="tbt-related">exact zero</span> (might lead to false positives, but unlikely if happens in multiple datasets).
+    * <span class="tbt-related">NANS</span>: Data contains <span class="tbt-related">NaN-values</span> (happens in SPS BPMs).
+    * <span class="tbt-related">FLAT</span>: <span class="tbt-related">Peak-to-Peak</span> value was <span class="tbt-related">below</span> a given threshold (10nm).
+    * <span class="tbt-related">SPIKY</span>: A <span class="tbt-related">spike</span> in the data, <span class="tbt-related">above</span> a given threshold (2cm).
+* To reduce <span class="svd-related">noise</span> we perform an SVD-decomposition and keep only the <span class="svd-related">strongest modes</span>.
+    * <span class="svd-related">SVD_PEAK</span>: The BPM had a <span class="svd-related">mode</span> in the U-Matrix above a given threshold (0.925).
+* Most information about the optics come from a <span class="spec-related">spectral analysis</span>.
+    * <span class="spec-related">NO_TUNE</span>: Tune line could <span class="spec-related">not be found</span> in the spectrum.
+    * <span class="spec-related">TUNE_CLEAN</span>: Tune line found was <span class="spec-related">too far from the average</span> of the other BPMs.
+
+## Manual
+
+
+* <span class="manual-related">KNOWN</span>: Identified <span class="manual-related">manually</span>; sticking out spectrum/optics <span class="manual-related">regularly</span>.
+    * <span class="manual-related">Large error bars</span>.
+    * <span class="manual-related">Non-sensical</span> data points.
+    * Cause <span class="manual-related">analysis issues</span> (e.g. phase-offsets, negative $\beta$, NaNs).
+    * <span class="manual-related">Calibration</span> issues:
+        * $\beta$-form-phase looks normal, peak in $\beta$-from-amplitude
+        * $\beta$-ratios large.
+        * Measure in <span class="manual-related">different optics</span> to <span class="manual-related">confirm BPM issue</span>.
+* **Good hint:** <span class="manual-related">Filtering them solves observed issues</span>.
+
+![Beta Beating Example](../../assets/images/bpm_filtering/BetaBeating.png)
+
+## Isolation Forest
+
+* Using <span class="iforest-related">machine learning techniques</span> to identify Bad-BPMs.
+    * <span class="iforest-related">IFOREST</span>: Identified BPM, due to being an <span class="iforest-related">outlier in Tune, Noise and/or Amplitude</span>
+
+!!! warning "Under Re-evaluation"
+    This functionality is currently under re-evaluation and has only been used on a small amount of data in 2021-2024!
+
+![Isolation Forest Example](../../assets/images/bpm_filtering/iforest.png)
+
+
+[E. Fol - Machine Learning for BPM failure detection](https://indico.cern.ch/event/762124/contributions/3174751/attachments/1740028/2815322/hss_meeting_2410.pdf)<br>
+[E. Fol - Isolation Forest for bad BPMs: performance evaluation](https://indico.cern.ch/event/776442/contributions/3228674/attachments/1759222/2853627/omc_meeting_26nov.pdf)
+
+## Bad BPMs Summary Script
+
+* Bad-BPMs are written out in files <span class="omc-emph">per analysed TbT-Data</span>.
+* Script available to <span class="omc-emph">gather, summarize and make statistics</span>.
+
+```bash
+usage: bad_bpms_summary.py [-h] --dates DATES [DATES ...] [--root ROOT] [--outfile OUTFILE]
+                           [--print_percentage PRINT_PERCENTAGE] [--accel_glob ACCEL_GLOB]
+
+options:
+  --dates DATES [DATES ...]
+                        Dates to include in analysis. This should be either subfolders in
+                        `root` or glob-patterns for those.
+  --root ROOT           Path to the root directory, containing the dates.
+                        Default: `/user/slops/data/LHC_DATA/OP_DATA/BetaBeat/`
+  --outfile OUTFILE     Path to the file to write out.
+  --print_percentage PRINT_PERCENTAGE
+                        Print out BPMs that appear in more than this percentage of measurements.
+  --accel_glob ACCEL_GLOB
+                        Accelerator name (glob for the sub-directories).
+```
+
+Example: All bad BPMs from 2025, written into file and all &gt; 50% in terminal
+
+```
+python -m omc3.scripts.bad_bpms_summary --dates 2025-* \
+                                       --accel_glob LHCB* \
+                                       --outfile bad_bpms_2025.txt \
+                                       --print_percentage 50
+```
+
+![A Bad BPM](../../assets/images/bpm_filtering/badbpm.png)
+
+
+
+*[BPM]: Beam Position Monitor

mkdocs.yml

@@ -93,6 +93,7 @@ extra:
 # Extras to load
 extra_css:
   - css/extra.css
+  - css/custom_colors.css
   - css/hint.min.css
 
 extra_javascript:
@@ -178,6 +179,7 @@ nav:
       - Introduction: measurements/physics/about.md
       - Error Propagation: measurements/physics/error_propagation.md
       - BPM-Calibration: measurements/physics/bpm_calibration.md
+      - BPM-Filtering: measurements/physics/bpm_filtering.md
       - Coupling: measurements/physics/coupling.md
       - K-Mod: measurements/physics/kmod.md
       - Linear IR Optics: measurements/physics/ir_linear_optics.md

scripts/shift_calculations.py

@@ -326,7 +326,7 @@ def plot_all_machines_in_year(
     Returns:
         Figure: Figure of the plot.
     """
-    color_map = {name: f"C{ii}" for ii, name in enumerate(["lhc", "sps", "ps", "psb", "leir", "ad"])}
+    color_map = {name: f"C{ii}" for ii, name in enumerate(["lhc", "sps", "ps", "psb", "leir", "ad", "superkekb"])}
 
     data_map: dict[str, float] = {}
     for file_path in logbook_dir.glob(f"{year:4d}_*.md"):
@@ -387,8 +387,8 @@ def plot_all_machines_in_year(
 
     # 2022 ---------------------------------------------------------------------
 
-    shift_m = manual_shifts(logbook_dir / "2022_lhc.md")
-    plot_results(shift_m, title="OMC Shifts LHC 2022", output_path="lhc_2022_shifts.pdf")
+    # shift_m = manual_shifts(logbook_dir / "2022_lhc.md")
+    # plot_results(shift_m, title="OMC Shifts LHC 2022", output_path="lhc_2022_shifts.pdf")
 
     # 2023 ---------------------------------------------------------------------
 
@@ -398,8 +398,8 @@ def plot_all_machines_in_year(
     # shift_c = calculate_shifts(logbook_dir / "2023_ps.md") 
     # plot_results(shift_c, title="OMC Shifts PS 2023 (from Start/End)")
 
-    shift_m = manual_shifts(logbook_dir / "2023_lhc.md")
-    plot_results(shift_m, title="OMC Shifts LHC 2023", output_path="lhc_2023_shifts.pdf")
+    # shift_m = manual_shifts(logbook_dir / "2023_lhc.md")
+    # plot_results(shift_m, title="OMC Shifts LHC 2023", output_path="lhc_2023_shifts.pdf")
 
     # shift_m = manual_shifts(logbook_dir / "2023_ps.md")
     # plot_results(shift_m, title="OMC Shifts PS 2023", output_path="ps_2023_shifts.pdf")
@@ -409,8 +409,8 @@ def plot_all_machines_in_year(
 
     # 2024 ---------------------------------------------------------------------
 
-    shift_m = manual_shifts(logbook_dir / "2024_lhc.md")
-    plot_results(shift_m, title="OMC Shifts LHC 2024", output_path="lhc_2024_shifts.pdf")
+    # shift_m = manual_shifts(logbook_dir / "2024_lhc.md")
+    # plot_results(shift_m, title="OMC Shifts LHC 2024", output_path="lhc_2024_shifts.pdf")
 
     # shift_m = manual_shifts(logbook_dir / "2024_lhc.md", shift_type="Commissioning")
     # plot_results(shift_m, title="OMC Shifts LHC 2024 (Commissioning)", output_path="lhc_2024_shifts_commish.pdf")
@@ -426,8 +426,10 @@ def plot_all_machines_in_year(
 
     # shift_m = manual_shifts(logbook_dir / "2024_sps.md")
     # plot_results(shift_m, title="OMC Shifts SPS 2024", output_path="sps_2024_shifts.pdf")
+
+    # plot_all_machines_in_year(2023, additional={}, output_path="machines_2023.pdf")
 
-    # plot_all_machines_in_year(2024, {"leir": 19}, output_path="machines_2024.pdf")
+    plot_all_machines_in_year(2024, {"leir": 9, "superkekb": 4}, output_path="machines_2024.pdf")
 
 
     plt.show()