Fix links from tract table page

python/lsst/production/tools/htmlUtils.py

@@ -15,7 +15,15 @@ def mk_table_value(t, metric_defs, val_col_name, sig_col_name, n):
         sig = t[sig_col_name][n]
         sig_str = f"{sig:.3g}"
     else:
-        return None, None
+        return None, None, None, None, None
+
+    bad_val = 0
+
+    link = "metrics.report_page"
+    if val_col_name in metric_defs:
+        debug_group = metric_defs[val_col_name]["debugGroup"]
+    else:
+        debug_group = None
 
     if np.isnan(val):
         val_str = f"<FONT CLASS=nanValue>{val:.3g} </FONT>"
@@ -24,18 +32,18 @@ def mk_table_value(t, metric_defs, val_col_name, sig_col_name, n):
     if val_col_name in metric_defs:
         high_val = metric_defs[val_col_name]["highThreshold"]
         low_val = metric_defs[val_col_name]["lowThreshold"]
-        link = metric_defs[val_col_name]["debugGroup"] + "ReportPage.html"
+        debug_group = metric_defs[val_col_name]["debugGroup"]
         if val < low_val or val > high_val:
-            #valStr = "<FONT CLASS=badValue><A HREF = " + link + f">{val:.3g}</A></FONT> "
             val_str = f"<FONT CLASS=badValue>{val:.3g}</FONT>"
+            bad_val += 1
     if sig_col_name in metric_defs:
         high_sig = metric_defs[sig_col_name]["highThreshold"]
         low_sig = metric_defs[sig_col_name]["lowThreshold"]
         if sig < low_sig or sig > high_sig:
-            #sigStr = "<FONT CLASS=badValue><A HREF = " + link + f">{sig:.3g}</A></FONT>\n"
             sig_str = f"<FONT CLASS=badValue>{sig:.3g}</FONT>\n"
+            bad_val += 1
 
-    return val_str, sig_str
+    return val_str, sig_str, bad_val, link, debug_group
 
 
 def mk_table_headers(t, col_dict):
@@ -64,29 +72,28 @@ def mk_table_headers(t, col_dict):
     for header in table_headers:
         if header == "failed metrics":
             # Needs to link to metric fail page
-            header_dict[header] = "metrics.index"
+            header_dict[header] = "metrics.histograms"
         elif header == "corners":
             # Needs to link to metric summary page
-            header_dict[header] = "metrics.index"
+            header_dict[header] = "metrics.histograms"
         else:
             # Needs to link to the correct point on the histogram page
             #headerList.append("<A HREF = histPage.html#" + header.split("<BR>")[0] + f">{header}</A>")
-            header_dict[header] = "metrics.index"
+            header_dict[header] = "metrics.histograms"
 
     return header_dict, bands
 
 
 def mk_tract_cell(tract):
-    #tractStr = "<a href='summary" + str(tract) + ".html' class=tract>"
-    #tractStr += str(tract) + "</a>"
-    tract_str = str(tract)
+    tract_str = "metrics.single_tract"
 
-    return tract_str
+    return (tract_str, )
 
 
 def mk_summary_plot_cell(tract):
-    plot_str = "<IMG SRC='static/summaryCalexp_" + str(tract) + "_i.png' CLASS=thumbnail>"
-    return plot_str
+    #plot_str = "<IMG SRC='static/summaryCalexp_" + str(tract) + "_i.png' CLASS=thumbnail>"
+    plot_str = "nav link needed"
+    return (plot_str, )
 
 
 def mk_patch_num_cell(t, n, bands):
@@ -96,38 +103,58 @@ def mk_patch_num_cell(t, n, bands):
             patch_col = "coaddPatchCount_" + band + "_patchCount"
             patch_str += "<B>" + band + "</B>: " + str(int(t[patch_col][n])) + "<BR>\n"
 
-    return patch_str
+    return (patch_str, )
 
 
 def mk_shape_cols(t, metric_defs, n, bands, col_dict):
     shape_strs = []
     for col in col_dict["shape_cols"]:
         for sn in ["highSNStars", "lowSNStars"]:
             shape_str = ""
+            num_bad = 0
+            debug_group_all = None
             for band in ["g", "r", "i", "z", "y"]:
                 if band in bands:
                     val_col_name = col + "_" + band + "_" + sn + "_median"
                     sig_col_name = col + "_" + band + "_" + sn + "_sigmaMad"
-                    val_str, sig_str = mk_table_value(t, metric_defs, val_col_name, sig_col_name, n)
+                    val_str, sig_str, bad_val, link, debug_group = mk_table_value(t,
+                                                                                  metric_defs,
+                                                                                  val_col_name,
+                                                                                  sig_col_name,
+                                                                                  n)
+                    num_bad += bad_val
                     shape_str += "<B>" + band + f"</B>: " + val_str + "  <B>&sigma;</B>: "
                     shape_str += sig_str + "<BR>\n"
-            shape_strs.append(shape_str)
+                    if debug_group is not None:
+                        debug_group_all = debug_group
+            shape_strs.append((shape_str, num_bad, link, debug_group_all))
     return shape_strs
 
 
 def mk_stellar_locus_cols(t, metric_defs, n, col_dict):
     row_strs = []
     for col in col_dict["stellar_locus_cols"]:
-        for (flux, flux1) in zip(["psfFlux", "CModel"], ["PSF", "CModel"]):
-            if col[0] == "w" or col[0] == "x":
+        row_str = ""
+        num_bad = 0
+        debug_group_all = None
+        for (flux, flux1) in zip(["psfFlux", "cModelFlux"], ["PSF", "CModel"]):
+            if (col[0] == "w" or col[0] == "x") and flux1 == "PSF":
                 flux1 += "P"
             val_col_name = col + flux1 + "_" + col + "_" + flux + "_median"
             sig_col_name = col + flux1 + "_" + col + "_" + flux + "_sigmaMAD"
-            val_str, sig_str = mk_table_value(t, metric_defs, val_col_name, sig_col_name, n)
+            val_str, sig_str, bad_val, link, debug_group = mk_table_value(t,
+                                                                          metric_defs,
+                                                                          val_col_name,
+                                                                          sig_col_name,
+                                                                          n)
             if val_str is None:
                 continue
-            row_str = "<B>Med</B>: " + val_str + "  <B>&sigma;</B>: " + sig_str + "<BR>\n"
-        row_strs.append(row_str)
+            row_str += "<B>" + flux + "</B><BR><B>Med</B>: " + val_str + "  <B>&sigma;</B>: " + sig_str + "<BR>"
+            row_str += "<BR>\n"
+            num_bad += bad_val
+            if debug_group is not None:
+                debug_group_all = debug_group
+        row_strs.append((row_str, num_bad, link, debug_group_all))
 
     return row_strs
 

python/lsst/production/tools/tractTable.py

@@ -62,7 +62,7 @@ def collection(collection_urlencoded):
     t = butler.get("objectTableCore_metricsTable", collections=collection, dataId=dataId)
 
     #stellarLocusCols = ["yPerpPSF", "yPerpCModel", "wPerpCModel", "wPerpPSFP", "xPerpPSFP", "xPerpCModel"]
-    col_dict = {"table_cols": ["tract", "failed metrics", "corners", "nPatches"],
+    col_dict = {"table_cols": ["tract", "corners", "nPatches", "failed metrics"],
                 "shape_cols": ["shapeSizeFractionalDiff", "e1Diff", "e2Diff"],
                 "photom_cols": ["psfCModelScatter"],
                 "stellar_locus_cols": ["yPerp", "wPerp", "xPerp"],
@@ -88,19 +88,33 @@ def collection(collection_urlencoded):
         row_list = []
         row_list.append(mk_tract_cell(tract))
 
-        # Add a nan/bad summary cell next but need to calculate these numbers first
-        row_list.append("0")
         # Add a summary plot in the i band of the tract
         row_list.append(mk_summary_plot_cell(tract))
+        # Add the number of patches
         row_list.append(mk_patch_num_cell(t, n, bands))
-        for cell_str in mk_shape_cols(t, metric_defs, n, bands, col_dict):
-            row_list.append(cell_str)
-        for cell_str in mk_stellar_locus_cols(t, metric_defs, n, col_dict):
-            row_list.append(cell_str)
+
+        num_bad = 0
+        cell_vals = []
+        # Get the number of failed values and prep cell contents
+        for (cell_val, bad_val, link, debug_group) in mk_shape_cols(t, metric_defs, n, bands, col_dict):
+            cell_vals.append((cell_val, link, debug_group))
+            if bad_val is not None:
+                num_bad += bad_val
+
+        for (cell_val, bad_val, link, debug_group) in mk_stellar_locus_cols(t, metric_defs, n, col_dict):
+            cell_vals.append((cell_val, link, debug_group))
+            if bad_val is not None:
+                num_bad += bad_val
+
+        # Add a nan/bad summary cell next but need to calculate these numbers first
+        row_list.append((num_bad, ))
+        for val in cell_vals:
+            row_list.append(val)
 
         content_dict[tract] = row_list
 
-    return render_template("metrics/tracts.html", header_dict=header_dict, content_dict=content_dict)
+    return render_template("metrics/tracts.html", header_dict=header_dict, content_dict=content_dict,
+                           collection_urlencoded=collection_urlencoded)
 
 @bp.route("/histograms/<collection_name>")
 def histograms(collection_name):
@@ -118,4 +132,7 @@ def single_tract(collection_name, tract):
     return render_template("metrics/single_tract.html", tract=tract)
 
 
+@bp.route("/report/<collection_name>/<metric>")
+def report_page(collection_name, metric):
 
+    return render_template("metrics/report_page.html")