Fix InfluenceLines.get_il() IndexError for arbitrary poi values (#124)

get_il() threw IndexError when the point of interest did not land
exactly on the result grid.  Root cause: an overly tight floating-point
tolerance (dx * 1e-6) and zero-valued padding indices at span boundaries
that argmin could select.  The fix uses per-member result lookup,
skipping padding indices.

Closes #89

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: ccaprani

CHANGELOG.md

@@ -0,0 +1,6 @@
+# Changelog
+
+## Unreleased
+
+### Bug Fixes
+- Fix `InfluenceLines.get_il()` raising `IndexError` when the point of interest does not fall exactly on the result grid (#89). This occurred with longer spans where the default 100-point discretization produced a grid spacing that could not match arbitrary poi values. The fix uses per-member result lookup, avoiding both the overly tight floating-point tolerance and the zero-valued padding indices at span boundaries.

src/pycba/inf_lines.py

@@ -132,13 +132,19 @@ def get_il(self, poi: float, load_effect: str) -> (np.ndarray, np.ndarray):
             self.ba.beam.no_fixed_restraints
         )
 
-        # idx = np.abs(x - poi).argmin()
+        # Find the span containing the poi and the closest non-padding index
+        # within that span. Padding indices (first/last per span) have M/V
+        # forced to zero, so we must avoid them.
+        ispan, _ = self.ba.beam.get_local_span_coords(poi)
+        if ispan == -1:
+            ispan = self.ba.beam.no_spans - 1
+        span_x = self.vResults[0].vRes[ispan].x
+        # Skip padding at indices 0 and -1; real data is at 1:-1
+        idx_in_span = np.abs(span_x[1:-1] - poi).argmin() + 1
 
         if load_effect.upper() == "V":
-            dx = x[2] - x[1]
-            idx = np.where(np.abs(x - poi) <= dx * 1e-6)[0][0]
             for i, res in enumerate(self.vResults):
-                eta[i] = res.results.V[idx]
+                eta[i] = res.vRes[ispan].V[idx_in_span]
 
         elif load_effect.upper() == "R":
             #
@@ -182,10 +188,8 @@ def get_il(self, poi: float, load_effect: str) -> (np.ndarray, np.ndarray):
                 eta[i] = res.R[mt_sup_idx]
 
         else:
-            dx = x[2] - x[1]
-            idx = np.where(np.abs(x - poi) <= dx * 1e-6)[0][0]
             for i, res in enumerate(self.vResults):
-                eta[i] = res.results.M[idx]
+                eta[i] = res.vRes[ispan].M[idx_in_span]
 
         return (np.array(self.pos), eta)
 

tests/test_inf_lines.py

@@ -177,6 +177,33 @@ def test_parse_beam_notation():
     assert eType == [1, 2, 1, 1]
 
 
+def test_il_arbitrary_poi():
+    """
+    Regression test for issue #89: influence line plotting fails when the poi
+    does not fall exactly on the result grid (e.g. longer spans with default
+    100-point discretization).
+    """
+    beam_string = "E30R30H30R30E"
+    (L, EI, R, eType) = cba.parse_beam_string(beam_string)
+    ils = cba.InfluenceLines(L, EI, R, eType)
+    ils.create_ils(step=0.05)
+
+    # poi=40.0 does not land on the 0.3m result grid for 30m spans
+    (x, y) = ils.get_il(40.0, "M")
+    assert np.linalg.norm(y) > 0
+
+    (x, y) = ils.get_il(40.0, "V")
+    assert np.linalg.norm(y) > 0
+
+    # Also verify at support locations
+    (x, y) = ils.get_il(30.0, "M")
+    assert np.linalg.norm(y) > 0
+
+    # Moment at hinge should be zero
+    (x, y) = ils.get_il(60.0, "M")
+    assert np.linalg.norm(y) == pytest.approx(0.0, abs=1e-10)
+
+
 def test_discretization():
     """
     Confirm that poi rounding to find the closest idx for ILs works