Update phase/compute.py

modified PCI description to be dynamic

phase/compute.py

@@ -45,21 +45,30 @@ class ParticipationAdoptionIndex:
 
         # ----- percent-based values -----
         final_pcr = round(pcr * 100, 2)
+        final_spi_a = round(spi_a * 100, 2)
+        final_spi_b = round(spi_b * 100, 2)
         final_peg = round(peg * 100, 2)
-        final_pci = round(pci * 100, 2)
+        final_pci = round(pci, 2)
+
+        # ----- pci pivot value -----
+        pic_mid = 0.5
+        # ---------------------------
         
         self.components_1 = {
-            "PCR (Participation Coverage Ratio)": {"Value": final_pcr, "Description": "≈100 → Participation closely matches the target population. ≈0 → Participation reached very few of the intended population."},
-            "SPI-A (Silent Participation Inference - Silent Non-Adoption)": {"Value": spi_a, "Description": "High → Large segments of the target population were not reached or excluded. Low → Minimal non-participation across the target population."},
-            "SPI-B (Silent Participation Inference - Silent Adoption)": {"Value": spi_b, "Description": "High → Silent participation dominates. Low → Expressive participation dominates."},
-            "PEG (Participation-to-Expression Gap)": {"Value": final_peg, "Description": "≈100 → High expression gap among participants. ≈0 → Minimal expression gap."}
+            "PCR (Participation Coverage Ratio)": {"Value": final_pcr, "Description": f"{final_pcr}% of the target population has participated."},
+            "SPI-A (Silent Participation Inference - Silent Non-Adoption)": {"Value": final_spi_a, "Description": f"{final_spi_a}% of the target population were not reached or excluded."},
+            "SPI-B (Silent Participation Inference - Silent Adoption)": {"Value": final_spi_b, "Description": f"{final_spi_b}% of the target population has participated silently."},
+            "PEG (Participation-to-Expression Gap)": {"Value": final_peg, "Description": f"{final_peg}% of participants did not express feedback despite participating."}
         }
 
         self.components_2 = {
             "PCI (Participation Concentration Index)": 
                 {"Value": final_pci, 
-                 "Description": "≈100 → Participation is concentrated to certain groups. ≈0 → Participation is balanced across groups."
-                },
+                 "Description": (
+                    f"A PCI of {final_pci} suggests "
+                    f"{'high' if final_pci >= pci_mid else 'low'} participation concentration, "
+                    f"{'dominated by fewer groups' if final_pci >= pci_mid else 'with participation spread across groups'}."
+                ),
             "Group Summary": 
                 {"Minimum Participating Groups": f"At least {effective_groups_int} groups meaningfully participated.", 
                  "Effective Participation Groups": f"Participation is roughly equivalent to {effective_groups_rounded} equally sized groups."