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madisonmlinaglinxinyuan
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aglinxinyuan
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feat: add Radar Plot Visualization Operator (#3500)
This PR introduces a new visualization operator for a Radar Plot (also known as a spider plot). Radar plots are used to visualize multivariate data, allowing for comparison of different entities across the multiple variables. Typically, they are used to determine strengths and weaknesses of entities compared to one another (e.g. how our product compares to a competitor’s). They are also effective in showing outliers and commonalities across the entities. This Radar Plot visualization operator allows the user to select which numeric columns will be used as the radar axes, and optionally select a column whose value will be used to determine the name or color for the corresponding radar trace (the visual representation of that entity in the plot). Users can also toggle other customization features, such as to normalize the values for each radar axis, in order to prevent a representation that skews towards axes with higher values. Changed files: - Created RadarPlot.png in core/gui/src/assets/operator_images - Created radarPlot/RadarPlotOpDesc.scala in core/workflow-operator/src/main/scala/edu/uci/ics/amber/operator/visualization - Created radarPlot/RadarPlotLinePattern.java in core/workflow-operator/src/main/scala/edu/uci/ics/amber/operator/visualization - Updated LogicalOp.scala in core/workflow-operator/src/main/scala/edu/uci/ics/amber/operator Property Selection: ![diabetes_radar_plot_properties](https://github.com/user-attachments/assets/63810a9f-9613-49a1-9ae0-a508a4cbc151) Normalized Result: ![diabetes_radar_plot_normalized](https://github.com/user-attachments/assets/e63547bd-0968-4557-9844-c2f9debb27ff) Non-Normalized Result: ![diabetes_radar_plot_non_normalized](https://github.com/user-attachments/assets/e0e180e6-85c5-4dca-9b2f-ef6572162984) Additional Example: ![product_radar_plot](https://github.com/user-attachments/assets/cc77432c-7c1d-421d-b09e-dbfa6bfb9df1) Testing Datasets: [diabetes_mini.csv](https://github.com/user-attachments/files/20912990/diabetes_mini.csv) [diabetes_mini_missing_column.csv](https://github.com/user-attachments/files/20912991/diabetes_mini_missing_column.csv) [diabetes_mini_missing_values.csv](https://github.com/user-attachments/files/20912994/diabetes_mini_missing_values.csv) [product_data.csv](https://github.com/user-attachments/files/20912995/product_data.csv) --------- Co-authored-by: Xinyuan Lin <xinyual3@uci.edu>
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‎common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/LogicalOp.scala‎

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@@ -124,6 +124,7 @@ import org.apache.texera.amber.operator.visualization.nestedTable.NestedTableOpD
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import org.apache.texera.amber.operator.visualization.networkGraph.NetworkGraphOpDesc
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import org.apache.texera.amber.operator.visualization.pieChart.PieChartOpDesc
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import org.apache.texera.amber.operator.visualization.quiverPlot.QuiverPlotOpDesc
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import org.apache.texera.amber.operator.visualization.radarPlot.RadarPlotOpDesc
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import org.apache.texera.amber.operator.visualization.radarChart.RadarChartOpDesc
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import org.apache.texera.amber.operator.visualization.rangeSlider.RangeSliderOpDesc
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import org.apache.texera.amber.operator.visualization.sankeyDiagram.SankeyDiagramOpDesc
@@ -196,6 +197,7 @@ trait StateTransferFunc
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new Type(value = classOf[RangeSliderOpDesc], name = "RangeSlider"),
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new Type(value = classOf[PieChartOpDesc], name = "PieChart"),
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new Type(value = classOf[QuiverPlotOpDesc], name = "QuiverPlot"),
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new Type(value = classOf[RadarPlotOpDesc], name = "RadarPlot"),
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new Type(value = classOf[RadarChartOpDesc], name = "RadarChart"),
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new Type(value = classOf[WordCloudOpDesc], name = "WordCloud"),
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new Type(value = classOf[HtmlVizOpDesc], name = "HTMLVisualizer"),

‎common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/radarChart/RadarChartOpDesc.scala‎

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@@ -22,8 +22,7 @@ package org.apache.texera.amber.operator.visualization.radarChart
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import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription}
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import com.kjetland.jackson.jsonSchema.annotations.{JsonSchemaInject, JsonSchemaTitle}
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import org.apache.texera.amber.core.tuple.{AttributeType, Schema}
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import org.apache.texera.amber.core.workflow.OutputPort.OutputMode
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import org.apache.texera.amber.core.workflow.{InputPort, OutputPort, PortIdentity}
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import org.apache.texera.amber.core.workflow.PortIdentity
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import org.apache.texera.amber.operator.PythonOperatorDescriptor
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import org.apache.texera.amber.operator.metadata.annotations.{
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AutofillAttributeName,

‎common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/radarPlot/RadarPlotLinePattern.java‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.texera.amber.operator.visualization.radarPlot;
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import com.fasterxml.jackson.annotation.JsonValue;
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public enum RadarPlotLinePattern {
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SOLID("solid"),
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DASH("dash"),
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DOT("dot");
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private final String linePattern;
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RadarPlotLinePattern(String linePattern) {
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this.linePattern = linePattern;
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}
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@JsonValue
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public String getLinePattern() {
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return this.linePattern;
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}
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}

‎common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/radarPlot/RadarPlotOpDesc.scala‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.texera.amber.operator.visualization.radarPlot
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import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription}
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import com.kjetland.jackson.jsonSchema.annotations.{JsonSchemaInject, JsonSchemaTitle}
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import org.apache.texera.amber.core.tuple.{AttributeType, Schema}
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import org.apache.texera.amber.operator.metadata.annotations.{
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AutofillAttributeName,
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AutofillAttributeNameList
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}
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import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo}
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import org.apache.texera.amber.operator.PythonOperatorDescriptor
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import org.apache.texera.amber.core.workflow.PortIdentity
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import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString
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import org.apache.texera.amber.pybuilder.PythonTemplateBuilder
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import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBuilderStringContext
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@JsonSchemaInject(json = """
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{
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"attributeTypeRules": {
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"selectedAttributes": {
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"enum": ["integer", "long", "double"]
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}
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}
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}
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""")
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class RadarPlotOpDesc extends PythonOperatorDescriptor {
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@JsonProperty(value = "selectedAttributes", required = true)
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@JsonSchemaTitle("Axes")
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@JsonPropertyDescription("Numeric columns to use as radar axes")
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@AutofillAttributeNameList
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var selectedAttributes: List[EncodableString] = _
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@JsonProperty(value = "traceNameAttribute", defaultValue = "No Selection", required = false)
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@JsonSchemaTitle("Trace Name Column")
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@JsonPropertyDescription("Optional - Select a column to use for naming each radar trace")
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@AutofillAttributeName
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var traceNameAttribute: EncodableString = ""
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@JsonProperty(
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value = "traceColorAttribute",
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defaultValue = "No Selection",
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required = false
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)
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@JsonSchemaTitle("Trace Color Column")
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@JsonPropertyDescription(
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"Optional - Select a column to use for coloring each radar trace (note: if there are too many traces with distinct coloring values, colors may repeat)"
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)
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@AutofillAttributeName
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var traceColorAttribute: EncodableString = ""
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@JsonProperty(value = "linePattern", defaultValue = "solid", required = true)
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@JsonPropertyDescription("Pattern of the lines connecting points on the radar plot")
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var linePattern: RadarPlotLinePattern = _
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@JsonProperty(value = "maxNormalize", defaultValue = "true", required = true)
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@JsonSchemaTitle("Max Normalize")
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@JsonPropertyDescription(
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"Normalize radar plot values by scaling them relative to the maximum value on their respective axes"
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)
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var maxNormalize: Boolean = true
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@JsonProperty(value = "fillTrace", defaultValue = "true", required = true)
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@JsonSchemaTitle("Fill Trace")
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@JsonPropertyDescription("Fill the area within each radar trace")
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var fillTrace: Boolean = true
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@JsonProperty(value = "showMarkers", defaultValue = "true", required = true)
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@JsonSchemaTitle("Show Point Markers")
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@JsonPropertyDescription("Display point markers on the radar plot")
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var showMarkers: Boolean = true
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@JsonProperty(value = "showLegend", defaultValue = "true", required = false)
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@JsonSchemaTitle("Show Legend")
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@JsonPropertyDescription(
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"Display the legend (note: without the legend, you are unable to selectively hide or show traces in the plot)"
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)
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var showLegend: Boolean = true
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override def getOutputSchemas(
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inputSchemas: Map[PortIdentity, Schema]
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): Map[PortIdentity, Schema] = {
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val outputSchema = Schema()
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.add("html-content", AttributeType.STRING)
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Map(operatorInfo.outputPorts.head.id -> outputSchema)
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}
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override def operatorInfo: OperatorInfo =
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OperatorInfo.forVisualization(
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"Radar Plot",
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"View the result in a radar plot.",
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OperatorGroupConstants.VISUALIZATION_SCIENTIFIC_GROUP
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)
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private def toPythonBool(value: Boolean): String = if (value) "True" else "False"
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private def optionalColumnExpr(column: EncodableString): PythonTemplateBuilder =
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Option(column).filterNot(col => col.isEmpty || col == "No Selection") match {
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case Some(col) => pyb"$col"
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case None => pyb"None"
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}
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def generateRadarPlotCode(): PythonTemplateBuilder = {
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val attributes = Option(selectedAttributes).getOrElse(Nil)
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val attrList = attributes.map(attr => pyb"$attr").mkString(", ")
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val traceNameCol = optionalColumnExpr(traceNameAttribute)
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val traceColorCol = optionalColumnExpr(traceColorAttribute)
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pyb"""
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| categories = [$attrList]
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| if not categories:
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| yield {'html-content': self.render_error("No columns selected as axes.")}
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| return
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|
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| trace_name_col = $traceNameCol
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| trace_color_col = $traceColorCol
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| line_pattern = "${linePattern.getLinePattern}"
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| max_normalize = ${toPythonBool(maxNormalize)}
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| fill_trace = ${toPythonBool(fillTrace)}
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| show_markers = ${toPythonBool(showMarkers)}
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| show_legend = ${toPythonBool(showLegend)}
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|
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| selected_table_df = table[categories].astype(float)
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| selected_table = selected_table_df.values
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|
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| trace_names = (
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| table[trace_name_col].values if trace_name_col
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| else np.full(len(table), "", dtype=object)
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| )
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|
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| trace_colors = [None] * len(table)
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| if trace_color_col:
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| unique_vals = table[trace_color_col].unique()
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| color_map = {val: px.colors.qualitative.Plotly[idx % len(px.colors.qualitative.Plotly)]
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| for idx, val in enumerate(unique_vals)}
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| nan_color = '#000000'
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| trace_colors = table[trace_color_col].map(color_map).fillna(nan_color).values
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|
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| hover_texts = []
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| for idx, row in enumerate(selected_table):
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| name_prefix = str(trace_names[idx]) + "<br>" if trace_names[idx] else ""
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| row_hover_texts = []
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| for attr, value in zip(categories, row):
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| row_hover_texts.append(name_prefix + attr + ": " + str(value))
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| hover_texts.append(row_hover_texts)
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|
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| if max_normalize:
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| max_vals = selected_table_df.max().values
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| max_vals[max_vals == 0] = 1
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| selected_table = selected_table / max_vals
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|
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| selected_table = np.nan_to_num(selected_table)
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|
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| fig = go.Figure()
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|
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| for idx, row in enumerate(selected_table):
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| # To connect ensure all points in the radar trace are connected
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| closed_row = row.tolist() + [row[0]]
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| closed_categories = categories + [categories[0]]
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| closed_hover_texts = hover_texts[idx] + [hover_texts[idx][0]]
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|
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| fig.add_trace(go.Scatterpolar(
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| r=closed_row,
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| theta=closed_categories,
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| fill='toself' if fill_trace else 'none',
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| name=str(trace_names[idx]) if trace_names[idx] else "",
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| text=closed_hover_texts,
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| hoverinfo="text",
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| mode="lines+markers" if show_markers else "lines",
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| line=dict(dash=line_pattern, color=trace_colors[idx] if trace_colors[idx] else None),
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| marker=dict(color=trace_colors[idx]) if trace_colors[idx] else {}
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| ))
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|
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| fig.update_layout(
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| polar=dict(radialaxis=dict(visible=True)),
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| showlegend=show_legend,
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| width=600,
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| height=600
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| )
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|"""
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}
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override def generatePythonCode(): String = {
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val finalCode =
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pyb"""
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|from pytexera import *
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|import numpy as np
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|import plotly.graph_objects as go
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|import plotly.express as px
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|import plotly.io
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|
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|class ProcessTableOperator(UDFTableOperator):
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|
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| def render_error(self, error_msg):
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| return '''<h1>Radar Plot is not available.</h1>
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| <p>Reason is: {} </p>
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| '''.format(error_msg)
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|
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| @overrides
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| def process_table(self, table: Table, port: int):
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| if table.empty:
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| yield {'html-content': self.render_error("Input table is empty.")}
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| return
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|
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| ${generateRadarPlotCode()}
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|
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| html = plotly.io.to_html(fig, include_plotlyjs='cdn', auto_play=False, config={'responsive': True})
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| yield {'html-content': html}
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|"""
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finalCode.encode
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}
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}

‎frontend/src/assets/operator_images/RadarPlot.png‎

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