Update pages/_common_m.py

pages/_common_m.py

@@ -22,27 +22,19 @@ IUCN_ASSET = f"{EE_LAMER_ROOT}/iucn_ranges"
 # =============================================================================
 
 RESIDENT_PARTS = {
-    "M_adj": ["M_adj_part1", "M_adj_part2", "M_adj_part3"],
-    "M_noadj": ["M_noadj_part1", "M_noadj_part2"],
-    "M_buffer1deg": ["M_buffer1deg_part1", "M_buffer1deg_part2"],
-    "M_occsrangehull": ["M_occsrangehull_part1", "M_occsrangehull_part2"],
+    "M": ["M"],
+    "M_ecoregions": ["M_ecoregions"],
 }
 
 MIGRANT_PARTS = {
-    ("breeding","M_adj"): ["breeding_M_adj"],
-    ("breeding","M_noadj"): ["breeding_M_noadj"],
-    ("breeding","M_buffer1deg"): ["breeding_M_buffer1deg"],
-    ("breeding","M_occsrangehull"): ["breeding_M_occsrangehull"],
-
-    ("nonbreeding","M_adj"): ["nonbreeding_M_adj_part1","nonbreeding_M_adj_part2"],
-    ("nonbreeding","M_noadj"): ["nonbreeding_M_noadj_part1","nonbreeding_M_noadj_part2"],
-    ("nonbreeding","M_buffer1deg"): ["nonbreeding_M_buffer1deg_part1","nonbreeding_M_buffer1deg_part2"],
-    ("nonbreeding","M_occsrangehull"): ["nonbreeding_M_occsrangehull_part1","nonbreeding_M_occsrangehull_part2"],
-
-    ("year_round","M_adj"): ["year_round_M_adj"],
-    ("year_round","M_noadj"): ["year_round_M_noadj"],
-    ("year_round","M_buffer1deg"): ["year_round_M_buffer1deg"],
-    ("year_round","M_occsrangehull"): ["year_round_M_occsrangehull"],
+    ("breeding","M"): ["breeding_M"],
+    ("breeding","M_ecoregions"): ["breeding_M_ecoregions"],
+
+    ("nonbreeding","M"): ["nonbreeding_M"],
+    ("nonbreeding","M_ecoregions"): ["nonbreeding_M_ecoregions"],
+
+    ("year_round","M"): ["year_round_M"],
+    ("year_round","M_ecoregions"): ["year_round_M_ecoregions"],
 }
 
 # =============================================================================
@@ -50,13 +42,11 @@ MIGRANT_PARTS = {
 # =============================================================================
 
 M_METADATA = {
-    "M_adj": ("M - Adjacent Ecoregions", "Ecoregions adjacent to occurrences"),
-    "M_noadj": ("M - No Adjacent", "Only ecoregions with occurrences"),
-    "M_buffer1deg": ("M - 1° Buffer", "Ecoregions within 1° buffer"),
-    "M_occsrangehull": ("M - Occurrence Hull", "Convex hull"),
+    "M": ("M", "M Hypothesis"),
+    "M_ecoregions": ("M Ecoregions", "Restricted by Ecoregions"),
 }
 
-M_ORDER = ["M_adj","M_noadj","M_buffer1deg","M_occsrangehull"]
+M_ORDER = ["M", "M_ecoregions"]
 BIRD_TYPES = ["Residents", "Migrants"]
 SEASONS = ["breeding", "nonbreeding", "year_round"]
 PASS_DECISIONS = ["pass","reviewed_pass","proxim_pass"]
@@ -85,6 +75,7 @@ center = solara.reactive([0, -70])
 
 reviewer_name  = solara.reactive("")
 reviewer_notes = solara.reactive("")
+reviewer_ecoregions = solara.reactive("")
 
 submission_status = solara.reactive("idle")
 submission_result = solara.reactive(None)
@@ -131,16 +122,18 @@ def get_species_list(btype=None, season=None):
 
 def get_m_fc(hyp, species, btype, season=None):
     if btype == "Residents":
-        parts = RESIDENT_PARTS[hyp]
+        parts = RESIDENT_PARTS.get(hyp, [])
         root = EE_RESIDENT_ROOT
         filt = ee.Filter.eq("species", species)
     else:
-        parts = MIGRANT_PARTS[(season, hyp)]
+        parts = MIGRANT_PARTS.get((season, hyp), [])
         root = EE_MIGRANT_ROOT
         filt = ee.Filter.And(
             ee.Filter.eq("species", species),
             ee.Filter.eq("season", season),
         )
+    if not parts:
+        return ee.FeatureCollection([])
     fcs = [ee.FeatureCollection(f"{root}/{p}") for p in parts]
     fc = ee.FeatureCollection(fcs).flatten() if len(fcs) > 1 else fcs[0]
     return fc.filter(filt)
@@ -154,6 +147,18 @@ def compute_eco_color_map(species, btype=None, season=None):
         ecos.update([e for e in vals if e])
     return {eco: ECO_PALETTE[i % len(ECO_PALETTE)] for i, eco in enumerate(sorted(ecos))}
 
+def get_species_ecoregions(species, btype=None, season=None):
+    """Fetches unique ecoregions from the M_ecoregions hypothesis layer."""
+    if not species: return ""
+    try:
+        fc = get_m_fc("M_ecoregions", species, btype, season)
+        vals = fc.aggregate_array("ECO_NAME").distinct().getInfo()
+        valid_vals = [str(e) for e in vals if e]
+        return "; ".join(sorted(valid_vals))
+    except Exception as e:
+        print("[WARN ecoregions]", e)
+        return ""
+
 def get_eco_geojson(hypothesis, species, btype=None, season=None, eco_color_map=None):
     try:
         fc = get_m_fc(hypothesis, species, btype, season)
@@ -185,7 +190,8 @@ def get_m_bounds(hypothesis, species, btype=None, season=None):
 # =============================================================================
 
 def create_m_map(hypothesis, species, eco_color_map, btype=None, season=None):
-    m = geemap.Map(zoom=zoom.value, center=center.value, toolbar_control=False, lite_mode=True)
+    # 1. Updated basemap to a simple gray map ("CartoDB.Positron")
+    m = geemap.Map(zoom=zoom.value, center=center.value, toolbar_control=False, lite_mode=True, basemap="CartoDB.Positron")
     geojson = get_eco_geojson(hypothesis, species, btype, season, eco_color_map)
     if geojson:
         m.add_geojson(geojson, layer_name="M regions", info_mode="on_click")
@@ -193,17 +199,20 @@ def create_m_map(hypothesis, species, eco_color_map, btype=None, season=None):
         occ = ee.FeatureCollection(get_pres_backg_asset(btype, season)).filter(ee.Filter.eq("species", species))
         fail = occ.filter(ee.Filter.inList("final_decision", FAIL_DECISIONS))
         passed = occ.filter(ee.Filter.inList("final_decision", PASS_DECISIONS))
-        m.addLayer(fail.style(**{"color": "ff4444", "pointSize": 6}), {}, "Fail")
-        m.addLayer(passed.style(**{"color": "2ca02c", "pointSize": 6}), {}, "Pass")
+        
+        # 2 & 3. Made points smaller and changed fail point to "triangle" 
+        # (Earth Engine Server-Side styling does not support a "teardrop" shape natively)
+        m.addLayer(fail.style(**{"color": "ff4444", "pointSize": 3, "pointShape": "triangle"}), {}, "Fail")
+        m.addLayer(passed.style(**{"color": "2ca02c", "pointSize": 3, "pointShape": "circle"}), {}, "Pass")
     except Exception as e:
         print("[WARN points]", e)
     return m
 
 # =============================================================================
-# SUBMISSION (FIXED FOR YOUR COLUMNS)
+# SUBMISSION
 # =============================================================================
 
-def submit_review(hypothesis, species, reviewer, notes, btype, season=None):
+def submit_review(hypothesis, species, reviewer, notes, ecoregions, btype, season=None):
     """Submits review data to Airtable using specific column names."""
     api_key = os.environ.get("AIRTABLE_API_KEY")
     base_id = os.environ.get("AIRTABLE_BASE_ID")
@@ -218,15 +227,14 @@ def submit_review(hypothesis, species, reviewer, notes, btype, season=None):
         "Content-Type": "application/json"
     }
     
-    # Mapping to your confirmed column names:
-    # Reviewer, Species, Selected_Hypothesis, Notes
-    # (Timestamp is usually handled automatically by Airtable if set to 'Created Time')
+    # 4. Added Ecoregions column submission data
     data = {
         "fields": {
             "Reviewer": reviewer,
             "Species": species,
             "Selected_Hypothesis": hypothesis,
-            "Notes": notes
+            "Notes": notes,
+            "Ecoregions": ecoregions
         }
     }
 
@@ -234,7 +242,6 @@ def submit_review(hypothesis, species, reviewer, notes, btype, season=None):
         response = requests.post(url, headers=headers, json=data)
         if response.status_code != 200:
             error_info = response.json().get("error", {})
-            # Provides the specific reason Airtable rejected the data
             msg = error_info.get("message", "Unknown error") if isinstance(error_info, dict) else error_info
             return {"success": False, "error": f"Airtable Error: {msg}"}