Added summary table in report and more conistent typehinting

cmccomb · Dec 17, 2023 · d3160dc · d3160dc
1 parent 6dbe7e6
commit d3160dc
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Showing 2 changed files with 64 additions and 11 deletions.
diff --git a/trussme/evaluate.py b/trussme/evaluate.py
@@ -6,32 +6,32 @@
 TrussInfo = TypedDict(
     "TrussInfo",
     {
-        "coordinates": numpy.ndarray,
-        "connections": numpy.ndarray,
-        "loads": numpy.ndarray,
-        "reactions": numpy.ndarray,
-        "area": numpy.ndarray,
-        "elastic_modulus": numpy.ndarray,
+        "coordinates": NDArray[float],
+        "connections": NDArray[float],
+        "loads": NDArray[float],
+        "reactions": NDArray[float],
+        "area": NDArray[float],
+        "elastic_modulus": NDArray[float],
     },
 )
 
 
 def the_forces(
     truss_info: TrussInfo,
 ) -> tuple[NDArray[float], NDArray[float], NDArray[float], float]:
-    tj: numpy.ndarray = numpy.zeros([3, numpy.size(truss_info["connections"], axis=1)])
-    w: numpy.ndarray = numpy.array(
+    tj: NDArray[float] = numpy.zeros([3, numpy.size(truss_info["connections"], axis=1)])
+    w: NDArray[float] = numpy.array(
         [
             numpy.size(truss_info["reactions"], axis=0),
             numpy.size(truss_info["reactions"], axis=1),
         ]
     )
-    dof: numpy.ndarray = numpy.zeros([3 * w[1], 3 * w[1]])
-    deflections: numpy.ndarray = numpy.ones(w)
+    dof: NDArray[float] = numpy.zeros([3 * w[1], 3 * w[1]])
+    deflections: NDArray[float] = numpy.ones(w)
     deflections -= truss_info["reactions"]
 
     # This identifies joints that can be loaded
-    ff: numpy.ndarray = numpy.where(deflections.T.flat == 1)[0]
+    ff: NDArray[float] = numpy.where(deflections.T.flat == 1)[0]
 
     # Build the global stiffness matrix
     for i in range(numpy.size(truss_info["connections"], axis=1)):

diff --git a/trussme/report.py b/trussme/report.py
@@ -82,6 +82,59 @@ def generate_summary(the_truss) -> str:
                 summary += st + ","
             summary += "and " + str(failure_string[-1]) + " were not satisfied.\n"
 
+    data = []
+    rows = [
+        "Minimum Total FOS",
+        "Minimum FOS for Buckling",
+        "Minimum FOS for Yielding",
+        "Maximum Mass",
+        "Maximum Deflection",
+    ]
+    data.append(
+        [
+            the_truss.minimum_fos_total,
+            the_truss.fos_total,
+            "Yes" if the_truss.fos_total > the_truss.minimum_fos_total else "No",
+        ]
+    )
+    data.append(
+        [
+            the_truss.minimum_fos_buckling,
+            the_truss.fos_buckling,
+            "Yes" if the_truss.fos_buckling > the_truss.minimum_fos_buckling else "No",
+        ]
+    )
+    data.append(
+        [
+            the_truss.minimum_fos_yielding,
+            the_truss.fos_yielding,
+            "Yes" if the_truss.fos_yielding > the_truss.minimum_fos_yielding else "No",
+        ]
+    )
+    data.append(
+        [
+            the_truss.maximum_mass,
+            the_truss.mass,
+            "Yes" if the_truss.mass < the_truss.maximum_mass else "No",
+        ]
+    )
+    data.append(
+        [
+            the_truss.maximum_deflection,
+            the_truss.deflection,
+            "Yes" if the_truss.deflection < the_truss.maximum_deflection else "No",
+        ]
+    )
+
+    summary += (
+        "\n"
+        + pandas.DataFrame(
+            data,
+            index=rows,
+            columns=["Target", "Actual", "Ok?"],
+        ).to_markdown()
+    )
+
     return summary