feat: add a new ternary contour plot operator

common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/LogicalOp.scala

@@ -129,6 +129,7 @@ import org.apache.texera.amber.operator.visualization.sankeyDiagram.SankeyDiagra
 import org.apache.texera.amber.operator.visualization.scatter3DChart.Scatter3dChartOpDesc
 import org.apache.texera.amber.operator.visualization.scatterplot.ScatterplotOpDesc
 import org.apache.texera.amber.operator.visualization.tablesChart.TablesPlotOpDesc
+import org.apache.texera.amber.operator.visualization.ternaryContour.TernaryContourOpDesc
 import org.apache.texera.amber.operator.visualization.ternaryPlot.TernaryPlotOpDesc
 import org.apache.texera.amber.operator.visualization.timeSeriesplot.TimeSeriesOpDesc
 import org.apache.texera.amber.operator.visualization.treeplot.TreePlotOpDesc
@@ -242,6 +243,7 @@ trait StateTransferFunc
     new Type(value = classOf[TablesPlotOpDesc], name = "TablesPlot"),
     new Type(value = classOf[ContinuousErrorBandsOpDesc], name = "ContinuousErrorBands"),
     new Type(value = classOf[FigureFactoryTableOpDesc], name = "FigureFactoryTable"),
+    new Type(value = classOf[TernaryContourOpDesc], name = "TernaryContour"),
     new Type(value = classOf[TernaryPlotOpDesc], name = "TernaryPlot"),
     new Type(value = classOf[DendrogramOpDesc], name = "Dendrogram"),
     new Type(value = classOf[NestedTableOpDesc], name = "NestedTable"),

common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/ternaryContour/TernaryContourOpDesc.scala

@@ -0,0 +1,153 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.texera.amber.operator.visualization.ternaryContour
+
+import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription}
+import com.kjetland.jackson.jsonSchema.annotations.JsonSchemaTitle
+import org.apache.texera.amber.core.tuple.{AttributeType, Schema}
+import org.apache.texera.amber.core.workflow.OutputPort.OutputMode
+import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBuilderStringContext
+import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString
+import org.apache.texera.amber.core.workflow.{InputPort, OutputPort, PortIdentity}
+import org.apache.texera.amber.operator.PythonOperatorDescriptor
+import org.apache.texera.amber.operator.metadata.annotations.AutofillAttributeName
+import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo}
+import org.apache.texera.amber.pybuilder.PythonTemplateBuilder
+
+/**
+  * Visualization Operator for Ternary Plots.
+  *
+  * This operator uses three data fields to construct a ternary plot.
+  * The points can optionally be color coded using a data field.
+  */
+
+class TernaryContourOpDesc extends PythonOperatorDescriptor {
+
+  // Add annotations for the first variable
+  @JsonProperty(value = "firstVariable", required = true)
+  @JsonSchemaTitle("Variable 1")
+  @JsonPropertyDescription("First variable data field")
+  @AutofillAttributeName var firstVariable: EncodableString = ""
+
+  // Add annotations for the second variable
+  @JsonProperty(value = "secondVariable", required = true)
+  @JsonSchemaTitle("Variable 2")
+  @JsonPropertyDescription("Second variable data field")
+  @AutofillAttributeName var secondVariable: EncodableString = ""
+
+  // Add annotations for the third variable
+  @JsonProperty(value = "thirdVariable", required = true)
+  @JsonSchemaTitle("Variable 3")
+  @JsonPropertyDescription("Third variable data field")
+  @AutofillAttributeName var thirdVariable: EncodableString = ""
+
+  // Add annotations for the fourth variable
+  @JsonProperty(value = "fourthVariable", required = true)
+  @JsonSchemaTitle("Measured Value")
+  @JsonPropertyDescription("Measured value data field")
+  @AutofillAttributeName var fourthVariable: EncodableString = ""
+
+  // OperatorInfo instance describing ternary plot
+  override def operatorInfo: OperatorInfo =
+    OperatorInfo(
+      userFriendlyName = "Ternary Contour",
+      operatorDescription =
+        "A ternary contour plot shows how a measured value changes across all mixtures of three components that always sum to a constant (usually 100%).",
+      operatorGroupName = OperatorGroupConstants.VISUALIZATION_SCIENTIFIC_GROUP,
+      inputPorts = List(InputPort()),
+      outputPorts = List(OutputPort(mode = OutputMode.SINGLE_SNAPSHOT))
+    )
+
+  override def getOutputSchemas(
+      inputSchemas: Map[PortIdentity, Schema]
+  ): Map[PortIdentity, Schema] = {
+    val outputSchema = Schema()
+      .add("html-content", AttributeType.STRING)
+    Map(operatorInfo.outputPorts.head.id -> outputSchema)
+    Map(operatorInfo.outputPorts.head.id -> outputSchema)
+  }
+
+  /** Returns a Python string that drops any tuples with missing values */
+  def manipulateTable(): PythonTemplateBuilder = {
+    // Check for any empty data field names
+    assert(
+      firstVariable.nonEmpty && secondVariable.nonEmpty && thirdVariable.nonEmpty && fourthVariable.nonEmpty
+    )
+    pyb"""
+       |        # Remove any tuples that contain missing values
+       |        table.dropna(subset=[$firstVariable, $secondVariable, $thirdVariable, $fourthVariable], inplace = True)
+       |
+       |        #Remove rows where any of the first three variables are negative
+       |        table = table[(table[[$firstVariable, $secondVariable, $thirdVariable]] >= 0).all(axis=1)]
+       |
+       |        #Remove zero-sum rows
+       |        s = table[$firstVariable] + table[$secondVariable] + table[$thirdVariable]
+       |        table = table[s > 0]
+       |"""
+  }
+
+  /** Returns a Python string that creates the ternary contour plot figure */
+  def createPlotlyFigure(): PythonTemplateBuilder = {
+    pyb"""
+         |        A = table[$firstVariable].to_numpy()
+         |        B = table[$secondVariable].to_numpy()
+         |        C = table[$thirdVariable].to_numpy()
+         |        Z = table[$fourthVariable].to_numpy()
+         |        fig = ff.create_ternary_contour(np.array([A,B,C]), Z, pole_labels=[$firstVariable, $secondVariable, $thirdVariable], interp_mode='cartesian')
+         |"""
+  }
+
+  /** Returns a Python string that yields the html content of the ternary contour plot */
+  override def generatePythonCode(): String = {
+    val finalCode =
+      pyb"""
+         |from pytexera import *
+         |
+         |import plotly.express as px
+         |import plotly.io
+         |import plotly.figure_factory as ff
+         |import numpy as np
+         |
+         |class ProcessTableOperator(UDFTableOperator):
+         |
+         |    # Generate custom error message as html string
+         |    def render_error(self, error_msg):
+         |        return '''<h1>TernaryContour is not available.</h1>
+         |                  <p>Reasons are: {} </p>
+         |               '''.format(error_msg)
+         |
+         |    @overrides
+         |    def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]:
+         |        if table.empty:
+         |            yield {'html-content': self.render_error("Input table is empty.")}
+         |            return
+         |        ${manipulateTable()}
+         |        if table.empty:
+         |            yield {'html-content': self.render_error("No valid rows left (every row has at least 1 missing value).")}
+         |            return
+         |        ${createPlotlyFigure()}
+         |        # Convert fig to html content
+         |        html = plotly.io.to_html(fig, include_plotlyjs = 'cdn', auto_play = False)
+         |        yield {'html-content':html}
+         |"""
+    finalCode.encode
+  }
+
+}