507 add reference lines to trajectory plot

pyciemss/visuals/schemas/trajectories.vg.json

@@ -12,8 +12,7 @@
         "fields": [
           {"data": "distributions", "field": "timepoint"},
           {"data": "traces", "field": "timepoint"},
-          {"data": "points", "field": "timepoint"},
-          {"data": "markers", "field": "timepoint"}
+          {"data": "points", "field": "timepoint"}
          ]
       }
     },
@@ -297,16 +296,16 @@
     },
     {
       "type": "group",
-      "name": "_markers",
+      "name": "_markers_v",
       "marks": [
         {
           "type": "rule",
-          "name": "_marker text",
-          "from": {"data": "markers"},
+          "name": "_marker_v text",
+          "from": {"data": "markers_v"},
           "encode": {
             "enter": {"stroke": {"value": "lightgray"}},
             "update": {
-              "x": {"scale": "xscale", "field": "timepoint"},
+              "x": {"scale": "xscale", "field": "axis_value"},
               "y2": {"value": 0},
               "y": {"signal": "height"},
               "opacity": {"value": 1}
@@ -315,8 +314,8 @@
         },
         {
           "type": "text",
-          "name": "_marker flags",
-          "from": {"data": "_marker text"},
+          "name": "_marker_v flags",
+          "from": {"data": "_marker_v text"},
           "encode": {
             "enter": {
               "text": {"field": "datum.label"},
@@ -334,7 +333,48 @@
             }
           ]
         }
-      ]}
+      ]},
+      {
+        "type": "group",
+        "name": "_markers_h",
+        "marks": [
+          {
+            "type": "rule",
+            "name": "_marker_h text",
+            "from": {"data": "markers_h"},
+            "encode": {
+              "enter": {"stroke": {"value": "lightgray"}},
+              "update": {
+                "y": {"scale": "yscale", "field": "axis_value"},
+                "x2": {"value": 0},
+                "x": {"signal": "width"},
+                "opacity": {"value": 1}
+              }
+            }
+          },
+          {
+            "type": "text",
+            "name": "_marker_h flags",
+            "from": {"data": "_marker_h text"},
+            "encode": {
+              "enter": {
+                "text": {"field": "datum.label"},
+                "x": {"signal": "width+20"},
+                "fontSize": {"value": 8}
+              }
+            },
+            "transform": [
+              {
+                "type": "label",
+                "lineAnchor": "start",
+                "as": ["_x", "y", "opacity", "align", "baseline"],
+                "offset": [1],
+                "size": {"signal": "[width, height]"}
+              }
+            ]
+          }
+        ]}
+
   ],
 
   "data": [
@@ -377,9 +417,14 @@
                  {"timepoint": 6, "value": 15, "trajectory": "e"}]
     },
     {
-      "name": "markers",
-      "values": [{"timepoint": 3, "label": "Low marker"},
-                 {"timepoint": 7, "label": "High marker"}]
+      "name": "markers_v",
+      "values": [{"axis_value": 3, "label": "Low marker"},
+                 {"axis_value": 7, "label": "High marker"}]
+    },
+    {
+      "name": "markers_h",
+      "values": [{"axis_value": 10, "label": "Low marker"},
+                 {"axis_value": 37, "label": "High marker"}]
     },
     {
       "name": "selected",

pyciemss/visuals/trajectories.py

@@ -127,7 +127,8 @@ def trajectories(
     points: Optional[pd.DataFrame] = None,
     keep: Union[str, list, Literal["all"]] = "all",
     drop: Union[str, list, None] = None,
-    base_markers: Optional[Dict[str, Number]] = None,
+    base_markers_v: Optional[Dict[str, Number]] = None,
+    base_markers_h: Optional[Dict[str, Number]] = None,
     relabel: Optional[Dict[str, str]] = None,
     colors: Optional[Dict] = None,
     qlow: float = 0.05,
@@ -147,7 +148,8 @@ def trajectories(
            These will be plotted as spans based on the qlow/qhigh parameters
         traces (None, pd.DataFrame): Example trajectories to plot.
         points (None, pd.DataFrame): Example points to plot (joined by lines)
-        markers (None, list[Number]): Timepoint markers. Key is the label, value is the timepoint
+        base_markers (None, Dict[str, Number]): Timepoint markers. Key is the label, value is the timepoint
+        base_markers_h (None, Dict[str, Number]): Horizontal markers. Key is the label, value is the horizonal value
         keep (str, list, "all"): Only keep some of the 'distributions' based on keys/values.
            - Default is the string "all", and it keeps all columns
            - If a any other string is present, it is treated as a regex and matched against the columns.
@@ -227,10 +229,15 @@ def _quantiles(g):
     else:
         points = []
 
-    if base_markers is not None:
-        markers = [{"timepoint": v, "label": k} for k, v in base_markers.items()]
+    if base_markers_v is not None:
+        markers_v = [{"axis_value": v, "label": k} for k, v in base_markers_v.items()]
     else:
-        markers = []
+        markers_v = []
+
+    if base_markers_h is not None:
+        markers_h = [{"axis_value": v, "label": k} for k, v in base_markers_h.items()]
+    else:
+        markers_h = []
 
     schema = vega.load_schema("trajectories.vg.json")
     schema["data"] = vega.replace_named_with(
@@ -244,7 +251,10 @@ def _quantiles(g):
         schema["data"], "traces", ["values"], _clean_nans(traces)
     )
     schema["data"] = vega.replace_named_with(
-        schema["data"], "markers", ["values"], _clean_nans(markers)
+        schema["data"], "markers_v", ["values"], _clean_nans(markers_v)
+    )
+    schema["data"] = vega.replace_named_with(
+        schema["data"], "markers_h", ["values"], _clean_nans(markers_h)
     )
 
     if colors is not None:

tests/visuals/test_plots.py

@@ -82,6 +82,16 @@ def test_base(self, distributions):
         df = pd.DataFrame(vega.find_named(schema["data"], "distributions")["values"])
         assert {"trajectory", "timepoint", "lower", "upper"} == set(df.columns)
 
+    def test_markers(self, distributions):
+        schema = plots.trajectories(
+            distributions,
+            base_markers_h={"Low marker": 10000000, "High marker": 20000000},
+        )
+
+        plots.save_schema(schema, "test_markers_schema.vg.json")
+        df = pd.DataFrame(vega.find_named(schema["data"], "markers_h")["values"])
+        assert {"axis_value", "label"} == set(df.columns)
+
     def test_rename(self, distributions):
         nice_labels = make_nice_labels(distributions.columns)
 

tests/visuals/test_schemas.py

@@ -160,12 +160,13 @@ def svg_matches(result):
         diffb = main.diff_texts(ref, result)
 
         for a, b in zip(diffa, diffb):
-            if a.name == b.name and a.name == "d":
-                ratio = difflib.SequenceMatcher(
-                    a=a.value, b=b.value, autojunk=False
-                ).quick_ratio()
-                if ratio < 0.95:
-                    return False
+            if hasattr(a, "name") & hasattr(b, "name"):
+                if a.name == b.name and a.name == "d":
+                    ratio = difflib.SequenceMatcher(
+                        a=a.value, b=b.value, autojunk=False
+                    ).quick_ratio()
+                    if ratio < 0.95:
+                        return False
             else:
                 # Assume its a name-issue and check it modulo numbers removed
                 simple_a = re.sub(r"\d+", "", diffa[0].value).strip()
@@ -250,7 +251,7 @@ def test_nested_mark_sources(schema_file):
     group_marks = [m for m in schema["marks"] if m["type"] == "group"]
     if "trajectories.vg.json" == schema_file.name:
         assert (
-            len(group_marks) == 4
+            len(group_marks) == 5
         ), f"{schema_file.name} spot-check number of group marks incorrect"
 
     for group in group_marks: