Merge pull request #47 from BoostV/104_option_for_no_plot

Option for no plot

.gitignore

@@ -2,4 +2,5 @@
 **.pyc
 .vscode
 /tmp
-version.txt
+version.txt
+.env

optimizerapi/optimizer.py

@@ -179,6 +179,10 @@ def process_result(result, optimizer, dimensions, cfg, extras, data, space):
         "plots": plots,
         "result": result_details
     }
+    # GraphFormat should, at the moment, be either "png" or "none". Default (legacy)
+    # behavior is "png", so the API returns png images. Any other input is interpreted
+    # as "None" at the moment.
+    graph_format = extras.get("graphFormat", "png")
 
     # In the following section details that should be reported to
     # clients should go into the "resultDetails" dictionary and plots
@@ -195,23 +199,24 @@ def process_result(result, optimizer, dimensions, cfg, extras, data, space):
         # processed more than "initialPoints" data points
         result_details["models"] = [process_model(
             model, optimizer) for model in result]
-        for idx, model in enumerate(result):
-            plot_convergence(model)
-            add_plot(plots, f"convergence_{idx}")
-
-            plot_objective(model, dimensions=dimensions,
-                           usepartialdependence=False,
-                           show_confidence=True)
-            add_plot(plots, f"objective_{idx}")
-
-        if optimizer.n_objectives == 1:
-            minimum = expected_minimum(result[0])
-
-            result_details["expected_minimum"] = [
-                round_to_length_scales(minimum[0], optimizer.space), round(minimum[1], 2)]
-        else:
-            plot_Pareto(optimizer)
-            add_plot(plots, "pareto")
+        if graph_format == "png":
+            for idx, model in enumerate(result):
+                plot_convergence(model)
+                add_plot(plots, f"convergence_{idx}")
+
+                plot_objective(model, dimensions=dimensions,
+                               usepartialdependence=False,
+                               show_confidence=True)
+                add_plot(plots, f"objective_{idx}")
+
+            if optimizer.n_objectives == 1:
+                minimum = expected_minimum(result[0])
+
+                result_details["expected_minimum"] = [
+                    round_to_length_scales(minimum[0], optimizer.space), round(minimum[1], 2)]
+            else:
+                plot_Pareto(optimizer)
+                add_plot(plots, "pareto")
 
     result_details["pickled"] = pickleToString(
         result, get_crypto())

tests/test_optimizer.py

@@ -71,6 +71,40 @@ def test_generates_plots_when_run_with_more_than_initialPoints_samples():
     assert len(result["plots"]) == 2
 
 
+def test_specifying_png_plots():
+    result = optimizer.run(body={
+        "data": sampleData,
+        "optimizerConfig": sampleConfig,
+        "extras": {"graphFormat": "png"}
+    })
+    validateResult(result)
+    assert len(result["result"]["models"]) > 0
+    assert len(result["plots"]) == 2
+
+
+def test_specifying_empty_extras_preserve_legacy_plotting():
+    result = optimizer.run(body={
+        "data": sampleData,
+        "optimizerConfig": sampleConfig,
+        "extras": {}
+    })
+    validateResult(result)
+    assert len(result["result"]["models"]) > 0
+    assert len(result["plots"]) == 2
+
+
+def test_deselecting_plots():
+    # If graphFormat is none, no plots should be returned. This should be faster.
+    result = optimizer.run(body={
+        "data": sampleData,
+        "optimizerConfig": sampleConfig,
+        "extras": {"graphFormat": "none"}
+    })
+    validateResult(result)
+    assert len(result["result"]["models"]) > 0
+    assert len(result["plots"]) == 0
+
+
 def test_can_accept_multi_objective_data():
     result = optimizer.run(body={
         "data": sampleMultiObjectiveData,