Reason is: {}
+ | '''.format(error_msg) + | + |def fail(error_msg): + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error(error_msg)) + | print(f"Icicle chart error: {error_msg}") + | + |if in1df.empty: + | fail("input table is empty.") + |else: + | # On a copy: the same frame can feed another branch of the plan, and + | # both the assignment and the drop below would otherwise reach it. + | chart_df = in1df.copy() + | chart_df[$valueLit] = chart_df[chart_df[$valueLit] > 0][$valueLit] + | chart_df = chart_df.dropna(subset=[$attributes]) + | if chart_df.empty: + | fail("value column contains only non-positive numbers or nulls.") + | else: + | fig = px.icicle(chart_df, path=[$attributes], values=$valueLit, + | color=$valueLit, hover_data=[$attributes], + | color_continuous_scale='RdBu') + | fig.update_layout(margin=dict(l=0, r=0, b=0, t=0)) + | fig.write_json("output.json") + | fig.write_html("output.html") + | print("Icicle chart saved to output.html")""".stripMargin + } + } diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/PlotlyStandaloneCode.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/PlotlyStandaloneCode.scala new file mode 100644 index 00000000000..b70bb2327df --- /dev/null +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/PlotlyStandaloneCode.scala @@ -0,0 +1,42 @@ +/* + * 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 + +import org.apache.texera.amber.operator.StandaloneCodeGenerator + +/** + * A generator whose emitted code draws with plotly. + * + * Mixed in rather than stated per operator because the three modules are one + * dependency: a chart reaching for `px` today and `go` tomorrow would otherwise + * have to remember to edit a list that nothing checks. What the mixin does say, + * and the reason it is not simply always emitted, is that an operator NOT + * mixing it in draws nothing, so a script built only from those runs wherever + * pandas is installed. + */ +trait PlotlyStandaloneCode extends StandaloneCodeGenerator { + + override def standaloneImports(): Seq[String] = + Seq( + "import plotly.express as px", + "import plotly.graph_objects as go", + "import plotly.io" + ) +} diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/dendrogram/DendrogramOpDesc.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/dendrogram/DendrogramOpDesc.scala index 826cce9061b..b1f3f8620fe 100644 --- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/dendrogram/DendrogramOpDesc.scala +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/dendrogram/DendrogramOpDesc.scala @@ -23,10 +23,13 @@ import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription} import com.fasterxml.jackson.databind.annotation.JsonDeserialize import com.kjetland.jackson.jsonSchema.annotations.{JsonSchemaInject, JsonSchemaTitle} import org.apache.texera.amber.core.tuple.{AttributeType, Schema} -import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBuilderStringContext +import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.{ + PythonTemplateBuilderStringContext, + pyStringLiteral +} import org.apache.texera.amber.pybuilder.PyStringTypes.{EncodableString, PythonLiteral} import org.apache.texera.amber.core.workflow.PortIdentity -import org.apache.texera.amber.operator.PythonOperatorDescriptor +import org.apache.texera.amber.operator.{PythonOperatorDescriptor, StandaloneCodeGenerator} 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 @@ -43,7 +46,7 @@ import javax.validation.constraints.NotNull } } """) -class DendrogramOpDesc extends PythonOperatorDescriptor { +class DendrogramOpDesc extends PythonOperatorDescriptor with StandaloneCodeGenerator { @JsonProperty(value = "xVal", required = true) @JsonSchemaTitle("Value X Column") @JsonPropertyDescription("The x values of points in dendrogram") @@ -88,12 +91,15 @@ class DendrogramOpDesc extends PythonOperatorDescriptor { OperatorGroupConstants.VISUALIZATION_SCIENTIFIC_GROUP ) + /** An unset threshold reaches the generated code as Python's `None`, which is + * scipy's own 0.7 * max distance — what a blank field already meant. + */ + private def thresholdExpr: PythonLiteral = threshold.map(_.toString).getOrElse("None") + private def createDendrogram(): PythonTemplateBuilder = { assert(xVal.nonEmpty, "Value X Column cannot be empty") assert(yVal.nonEmpty, "Value Y Column cannot be empty") assert(labels.nonEmpty, "Labels cannot be empty") - // Unset means None, which is scipy's own 0.7 * max distance. - val thresholdExpr: PythonLiteral = threshold.map(_.toString).getOrElse("None") pyb""" | x = np.array(table[$xVal]) | y = np.array(table[$yVal]) @@ -146,4 +152,49 @@ class DendrogramOpDesc extends PythonOperatorDescriptor { |""" finalcode.encode } + + override def producesDataFrame(): Boolean = false + + override def generateStandaloneCode(): String = { + + // render_error's continuation line keeps the runtime path's indentation — the + // HTML is triple-quoted, so those spaces reach the browser. + s"""import numpy as np + |import plotly.figure_factory as ff + | + |def render_error(error_msg): + | return '''Reason is: {}
+ | '''.format(error_msg) + | + |def _write_error(message): + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error(message)) + | + |if in1df.empty: + | _write_error("input table is empty.") + |else: + | # A row missing either coordinate has no position to cluster from, and + | # scipy refuses a NaN anywhere in the distance matrix. Bound to a name + | # of its own: the same frame can feed another branch of the plan, which + | # must still see every row. + | chart_df = in1df.dropna(subset=[${pyStringLiteral(xVal)}, ${pyStringLiteral(yVal)}]) + | if chart_df.empty: + | _write_error("input table has no rows with all of the configured columns filled in.") + | # Clustering starts from the distances between rows, so a single row + | # leaves scipy an empty distance matrix and it raises rather than draws. + | elif len(chart_df) < 2: + | _write_error("input table has fewer than two rows to cluster.") + | else: + | x = np.array(chart_df[${pyStringLiteral(xVal)}]) + | y = np.array(chart_df[${pyStringLiteral(yVal)}]) + | data = np.column_stack((x, y)) + | labels = chart_df[${pyStringLiteral(labels)}].tolist() + | fig = ff.create_dendrogram(data, labels=labels, color_threshold=$thresholdExpr) + | fig.update_layout(yaxis_title="Linkage Distance", margin=dict(l=0, r=0, b=0, t=0)) + | fig.write_json("output.json") + | fig.write_html("output.html") + | print("Dendrogram saved to output.html")""".stripMargin + } + } diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/hierarchychart/HierarchyChartOpDesc.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/hierarchychart/HierarchyChartOpDesc.scala index 5b052ca59ab..3e5e5ad1fad 100644 --- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/hierarchychart/HierarchyChartOpDesc.scala +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/hierarchychart/HierarchyChartOpDesc.scala @@ -22,10 +22,14 @@ package org.apache.texera.amber.operator.visualization.hierarchychart import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription} import com.kjetland.jackson.jsonSchema.annotations.{JsonSchemaInject, JsonSchemaTitle} import org.apache.texera.amber.core.tuple.{AttributeType, Schema} -import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBuilderStringContext +import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.{ + PythonTemplateBuilderStringContext, + pyStringLiteral +} import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString import org.apache.texera.amber.core.workflow.PortIdentity import org.apache.texera.amber.operator.PythonOperatorDescriptor +import org.apache.texera.amber.operator.visualization.PlotlyStandaloneCode 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 @@ -42,7 +46,7 @@ import javax.validation.constraints.{NotEmpty, NotNull} } } """) -class HierarchyChartOpDesc extends PythonOperatorDescriptor { +class HierarchyChartOpDesc extends PythonOperatorDescriptor with PlotlyStandaloneCode { @JsonProperty(required = true) @JsonSchemaTitle("Chart Type") @JsonPropertyDescription("Treemap or Sunburst") @@ -137,4 +141,46 @@ class HierarchyChartOpDesc extends PythonOperatorDescriptor { finalCode.encode } + // Output is an HTML chart, not a tabular DataFrame. + // The translator skips it in the leaf-DataFrame print block. + override def producesDataFrame(): Boolean = false + + override def generateStandaloneCode(): String = { + val attributes = hierarchy.map(section => pyStringLiteral(section.attributeName)).mkString(", ") + val valueLit = pyStringLiteral(value) + // The error page is written to output.html, the same file a plotted chart lands + // in, so a reason for "no chart" is where the reader looks for the chart — + // printing it to the terminal alone left output.html absent. render_error's + // continuation line keeps the runtime path's indentation, since the HTML is + // triple-quoted and those spaces reach the browser. + s"""def render_error(error_msg): + | return '''Reason is: {}
+ | '''.format(error_msg) + | + |def fail(error_msg): + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error(error_msg)) + | print(f"Hierarchy chart error: {error_msg}") + | + |if in1df.empty: + | fail("input table is empty.") + |else: + | # On a copy: the same frame can feed another branch of the plan, and + | # both the assignment and the drop below would otherwise reach it. + | chart_df = in1df.copy() + | chart_df[$valueLit] = chart_df[chart_df[$valueLit] > 0][$valueLit] + | chart_df = chart_df.dropna(subset=[$attributes]) + | if chart_df.empty: + | fail("value column contains only non-positive numbers or nulls.") + | else: + | fig = px.${hierarchyChartType.getPlotlyExpressApiName}(chart_df, path=[$attributes], values=$valueLit, + | color=$valueLit, hover_data=[$attributes], + | color_continuous_scale='RdBu') + | fig.update_layout(margin=dict(l=0, r=0, b=0, t=0)) + | fig.write_json("output.json") + | fig.write_html("output.html") + | print("Hierarchy chart saved to output.html")""".stripMargin + } + } diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/networkGraph/NetworkGraphOpDesc.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/networkGraph/NetworkGraphOpDesc.scala index 584ee4f5a38..9baa3c1fd0c 100644 --- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/networkGraph/NetworkGraphOpDesc.scala +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/networkGraph/NetworkGraphOpDesc.scala @@ -26,13 +26,15 @@ import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBui import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString import org.apache.texera.amber.core.workflow.PortIdentity import org.apache.texera.amber.operator.PythonOperatorDescriptor +import org.apache.texera.amber.operator.visualization.PlotlyStandaloneCode 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 +import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.pyStringLiteral import javax.validation.constraints.NotNull -class NetworkGraphOpDesc extends PythonOperatorDescriptor { +class NetworkGraphOpDesc extends PythonOperatorDescriptor with PlotlyStandaloneCode { @JsonProperty(required = true) @JsonSchemaTitle("Source Column") @JsonPropertyDescription("Source node for edge in graph") @@ -66,6 +68,10 @@ class NetworkGraphOpDesc extends PythonOperatorDescriptor { OperatorGroupConstants.VISUALIZATION_SCIENTIFIC_GROUP ) + /** An edge needs both of its ends, and networkx refuses a null as a node + * outright. A row missing either one names no edge, so it goes before the + * graph is built rather than reaching add_node. + */ def manipulateTable(): PythonTemplateBuilder = { assert(source.nonEmpty, "Source Column cannot be empty") assert(destination.nonEmpty, "Destination Column cannot be empty") @@ -95,6 +101,7 @@ class NetworkGraphOpDesc extends PythonOperatorDescriptor { | | @overrides | def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]: + |${manipulateTable()} | if not table.empty: | sources = table[$source] | destinations = table[$destination] @@ -199,4 +206,121 @@ class NetworkGraphOpDesc extends PythonOperatorDescriptor { finalCode.encode } + override def producesDataFrame(): Boolean = false + + override def generateStandaloneCode(): String = { + val sourceLit = pyStringLiteral(source) + val destinationLit = pyStringLiteral(destination) + // TheReason is: {}
+ | '''.format(error_msg) + | + |if in1df.empty: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error("Table should not have any empty/null values or fields.")) + |else: + | table = in1df.dropna(subset=[$sourceLit]).dropna(subset=[$destinationLit]).copy() + | if table.empty: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error("Table should not have any empty/null values or fields.")) + | else: + | sources = table[$sourceLit] + | destinations = table[$destinationLit] + | nodes = list(dict.fromkeys(pd.concat([sources, destinations]).tolist())) + | G = nx.Graph() + | for node in nodes: + | G.add_node(node) + | for _, row in table.iterrows(): + | G.add_edges_from([(row[$sourceLit], row[$destinationLit])]) + | pos = nx.spring_layout(G, k=0.5, iterations=50, seed=0) + | for n, p in pos.items(): + | G.nodes[n]["pos"] = p + | + | edge_trace = go.Scatter( + | x=[], + | y=[], + | name="Edges", + | line=dict(width=0.5, color="#888"), + | hoverinfo="none", + | mode="lines", + | visible=True + | ) + | + | for edge in G.edges(): + | x0, y0 = G.nodes[edge[0]]["pos"] + | x1, y1 = G.nodes[edge[1]]["pos"] + | edge_trace["x"] += tuple([x0, x1, None]) + | edge_trace["y"] += tuple([y0, y1, None]) + | + | node_trace = go.Scatter( + | x=[], + | y=[], + | name="Nodes", + | text=[], + | mode="markers", + | hoverinfo="text", + | visible=True, + | marker=dict( + | showscale=True, + | colorscale="plasma", + | reversescale=True, + | color=[], + | size=15, + | colorbar=dict( + | thickness=10, + | title="Node Connections", + | xanchor="left", + | titleside="right" + | ), + | line=dict(width=0) + | ) + | ) + | + | for node in G.nodes(): + | x, y = G.nodes[node]["pos"] + | node_trace["x"] += tuple([x]) + | node_trace["y"] += tuple([y]) + | + | for _, adjacencies in enumerate(G.adjacency()): + | node_trace["marker"]["color"] += tuple([len(adjacencies[1])]) + | node_info = str(adjacencies[0]) + ": " + str(len(adjacencies[1])) + " connections." + | node_trace["text"] += tuple([node_info]) + | + | fig = go.Figure( + | data=[edge_trace, node_trace], + | layout=go.Layout( + | title=$titleLit, + | hovermode="closest", + | showlegend=False, + | margin=dict(b=20, l=5, r=5, t=40), + | annotations=[ + | dict( + | text="", + | showarrow=False, + | xref="paper", + | yref="paper" + | ) + | ], + | xaxis=dict(showgrid=False, zeroline=False, showticklabels=False), + | yaxis=dict(showgrid=False, zeroline=False, showticklabels=False) + | ) + | ) + | fig.update_layout( + | margin=dict(l=0, r=0, t=0, b=0), + | legend=dict( + | itemclick=False, + | itemdoubleclick=False + | ) + | ) + | fig.write_json("output.json") + | fig.write_html("output.html") + | print("Network graph saved to output.html")""".stripMargin + } + } diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/sankeyDiagram/SankeyDiagramOpDesc.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/sankeyDiagram/SankeyDiagramOpDesc.scala index 7e6689bd721..98cddbaa62f 100644 --- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/sankeyDiagram/SankeyDiagramOpDesc.scala +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/sankeyDiagram/SankeyDiagramOpDesc.scala @@ -26,9 +26,11 @@ import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBui import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString import org.apache.texera.amber.core.workflow.PortIdentity import org.apache.texera.amber.operator.PythonOperatorDescriptor -import org.apache.texera.amber.operator.metadata.annotations.AutofillAttributeName +import org.apache.texera.amber.operator.visualization.PlotlyStandaloneCode +import org.apache.texera.amber.operator.metadata.annotations.{AutofillAttributeName, SampleColumn} import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo} import org.apache.texera.amber.pybuilder.PythonTemplateBuilder +import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.pyStringLiteral import javax.validation.constraints.NotNull @@ -43,12 +45,13 @@ import javax.validation.constraints.NotNull } } """) -class SankeyDiagramOpDesc extends PythonOperatorDescriptor { +class SankeyDiagramOpDesc extends PythonOperatorDescriptor with PlotlyStandaloneCode { @JsonProperty(value = "Source Attribute", required = true) @JsonSchemaTitle("Source Attribute") @JsonPropertyDescription("The source node of the Sankey diagram") @AutofillAttributeName + @SampleColumn("node_src") @NotNull(message = "Source Attribute cannot be empty") var sourceAttribute: EncodableString = "" @@ -56,6 +59,7 @@ class SankeyDiagramOpDesc extends PythonOperatorDescriptor { @JsonSchemaTitle("Target Attribute") @JsonPropertyDescription("The target node of the Sankey diagram") @AutofillAttributeName + @SampleColumn("node_dst") @NotNull(message = "Target Attribute cannot be empty") var targetAttribute: EncodableString = "" @@ -63,6 +67,7 @@ class SankeyDiagramOpDesc extends PythonOperatorDescriptor { @JsonSchemaTitle("Value Attribute") @JsonPropertyDescription("The value/volume of the flow between source and target") @AutofillAttributeName + @SampleColumn("score") @NotNull(message = "Value Attribute cannot be empty") var valueAttribute: EncodableString = "" @@ -143,4 +148,48 @@ class SankeyDiagramOpDesc extends PythonOperatorDescriptor { |""" finalCode.encode } + + override def producesDataFrame(): Boolean = false + + override def generateStandaloneCode(): String = { + val sourceLit = pyStringLiteral(sourceAttribute) + val targetLit = pyStringLiteral(targetAttribute) + val valueLit = pyStringLiteral(valueAttribute) + s"""def render_error(error_msg): + | return '''Reasons are: {}
+ | '''.format(error_msg) + | + |if in1df.empty: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error("Input table is empty.")) + |else: + | table = in1df.groupby([$sourceLit, $targetLit])[$valueLit].sum().reset_index(name="value") + | if table.empty: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error("No valid rows left (every row has at least 1 missing value).")) + | else: + | labels = pd.concat([table[$sourceLit], table[$targetLit]]).unique().tolist() + | table["source_index"] = table[$sourceLit].apply(lambda x: labels.index(x)) + | table["target_index"] = table[$targetLit].apply(lambda x: labels.index(x)) + | fig = go.Figure(data=[go.Sankey( + | node=dict( + | pad=15, + | thickness=20, + | line=dict(color="black", width=0.5), + | label=labels, + | color="blue" + | ), + | link=dict( + | source=table["source_index"].tolist(), + | target=table["target_index"].tolist(), + | value=table["value"].tolist() + | ) + | )]) + | fig.update_layout(title_text="Sankey Diagram", font_size=10) + | fig.write_json("output.json") + | fig.write_html("output.html") + | print("Sankey diagram saved to output.html")""".stripMargin + } + } diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/treeplot/TreePlotOpDesc.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/treeplot/TreePlotOpDesc.scala index 63fe2cacce8..ac8545e014d 100644 --- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/treeplot/TreePlotOpDesc.scala +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/treeplot/TreePlotOpDesc.scala @@ -26,8 +26,10 @@ import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBui import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString import org.apache.texera.amber.core.workflow.PortIdentity import org.apache.texera.amber.operator.PythonOperatorDescriptor -import org.apache.texera.amber.operator.metadata.annotations.AutofillAttributeName +import org.apache.texera.amber.operator.visualization.PlotlyStandaloneCode +import org.apache.texera.amber.operator.metadata.annotations.{AutofillAttributeName, SampleColumn} import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo} +import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.pyStringLiteral import javax.validation.constraints.NotNull @@ -38,12 +40,13 @@ import javax.validation.constraints.NotNull * to construct and visualize an interactive, top-down tree that automatically * sizes itself and supports intuitive scroll/pinch zooming. */ -class TreePlotOpDesc extends PythonOperatorDescriptor { +class TreePlotOpDesc extends PythonOperatorDescriptor with PlotlyStandaloneCode { @JsonProperty(value = "Edge List Column", required = true) @JsonSchemaTitle("Edge List Column") @JsonPropertyDescription("Column with [parent, child] pairs") @AutofillAttributeName + @SampleColumn("edge_pair") @NotNull(message = "Edge List Column cannot be empty") var edgeListColumn: EncodableString = "" @@ -72,8 +75,6 @@ class TreePlotOpDesc extends PythonOperatorDescriptor { | |import plotly.graph_objects as go |import plotly.io - |import igraph - |from igraph import Graph, EdgeSeq |import pandas as pd |import ast | @@ -108,6 +109,66 @@ class TreePlotOpDesc extends PythonOperatorDescriptor { | ) | return annotations | + | def build_tree_layout(self, edges): + | # Tidy top-down tree: depth picks the row, a leaf takes the next + | # free column and a parent sits centred over its own children. + | labels = [] + | known = set() + | for parent, child in edges: + | for node in (parent, child): + | if node not in known: + | known.add(node) + | labels.append(node) + | + | children = {label: [] for label in labels} + | has_parent = set() + | seen = set() + | for parent, child in edges: + | if (parent, child) not in seen: + | seen.add((parent, child)) + | children[parent].append(child) + | has_parent.add(child) + | + | depth = {} + | column = {} + | claimed = {} + | placed = set() + | next_column = 0 + | + | def grow(root): + | nonlocal next_column + | placed.add(root) + | stack = [(root, 0, False)] + | while stack: + | node, level, folded = stack.pop() + | if folded: + | kids = claimed[node] + | if kids: + | column[node] = sum(column[kid] for kid in kids) / len(kids) + | else: + | column[node] = next_column + | next_column += 1 + | continue + | depth[node] = level + | # A node belongs to whichever parent reaches it first, so a + | # cycle or a shared child is never laid out twice. + | kids = [kid for kid in children[node] if kid not in placed] + | placed.update(kids) + | claimed[node] = kids + | stack.append((node, level, True)) + | for kid in reversed(kids): + | stack.append((kid, level + 1, False)) + | + | for label in labels: + | if label not in placed and label not in has_parent: + | grow(label) + | # Whatever is left sits in a cycle that no root can reach. + | for label in labels: + | if label not in placed: + | grow(label) + | # The y-axis is inverted here so the tree grows top-down. + | return labels, [(column[label], -depth[label]) for label in labels] + | | @overrides | def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]: | if table.empty: @@ -127,14 +188,10 @@ class TreePlotOpDesc extends PythonOperatorDescriptor { | yield {'html-content': self.render_error("No valid [parent, child] pairs found in column " + $edgeListColumn + ".")} | return | - | G = Graph.TupleList(edges, directed=True) - | labels = G.vs['name'] - | - | layout_algorithm = 'rt' | try: - | lay = G.layout(layout_algorithm) + | labels, coords = self.build_tree_layout(edges) | except Exception as e: - | yield {'html-content': self.render_error(f"Layout algorithm '{layout_algorithm}' failed: {e}")} + | yield {'html-content': self.render_error(f"Tree layout failed: {e}")} | return | | HORIZONTAL_DENSITY = 120 @@ -143,8 +200,8 @@ class TreePlotOpDesc extends PythonOperatorDescriptor { | MIN_WIDTH = 800 | MIN_HEIGHT = 600 | - | if len(lay.coords) > 1: - | x_coords, y_coords = zip(*lay.coords) + | if len(coords) > 1: + | x_coords, y_coords = zip(*coords) | x_range = max(x_coords) - min(x_coords) | y_range = max(y_coords) - min(y_coords) | plot_width = max(MIN_WIDTH, x_range * HORIZONTAL_DENSITY + PADDING) @@ -153,12 +210,13 @@ class TreePlotOpDesc extends PythonOperatorDescriptor { | plot_width = MIN_WIDTH | plot_height = MIN_HEIGHT | - | # Invert the y-axis to make the tree grow top-down. - | position = {k: (lay[k][0], -lay[k][1]) for k in range(len(labels))} + | position = {k: coords[k] for k in range(len(labels))} + | index_of = {label: k for k, label in enumerate(labels)} | | Xe = [] | Ye = [] - | for edge in G.get_edgelist(): + | for parent, child in edges: + | edge = (index_of[parent], index_of[child]) | Xe += [position[edge[0]][0], position[edge[1]][0], None] | Ye += [position[edge[0]][1], position[edge[1]][1], None] | @@ -188,4 +246,182 @@ class TreePlotOpDesc extends PythonOperatorDescriptor { | |""".encode } + + override def producesDataFrame(): Boolean = false + + override def generateStandaloneCode(): String = { + s"""import ast + | + |# Only a layout failure renders an error page; everything else propagates, + |# matching the operator's own error handling. + |class TreeLayoutError(Exception): + | pass + | + |def render_error(error_msg): + | return f'''Reason: {error_msg}
''' + | + |def make_annotations(pos): + | font_color = 'rgb(250,250,250)' + | node_color = '#6175c1' + | font_size = 10 + | annotations = [] + | for node_name, coords in pos.items(): + | annotations.append( + | dict( + | # The label goes in as it came out of the cell, the way the + | # operator passes it: plotly stringifies it, and a str() here + | # would turn a None node into the text "None". + | text=node_name, + | x=coords[0], + | y=coords[1], + | xref='x1', yref='y1', + | font=dict(color=font_color, size=font_size), + | showarrow=False, + | align='center', + | bordercolor='rgb(50,50,50)', + | borderwidth=1, + | borderpad=5, + | bgcolor=node_color, + | opacity=0.8 + | ) + | ) + | return annotations + | + |def build_tree_layout(edges): + | # Tidy top-down tree: depth picks the row, a leaf takes the next + | # free column and a parent sits centred over its own children. + | labels = [] + | known = set() + | for parent, child in edges: + | for node in (parent, child): + | if node not in known: + | known.add(node) + | labels.append(node) + | + | children = {label: [] for label in labels} + | has_parent = set() + | seen = set() + | for parent, child in edges: + | if (parent, child) not in seen: + | seen.add((parent, child)) + | children[parent].append(child) + | has_parent.add(child) + | + | depth = {} + | column = {} + | claimed = {} + | placed = set() + | next_column = 0 + | + | def grow(root): + | nonlocal next_column + | placed.add(root) + | stack = [(root, 0, False)] + | while stack: + | node, level, folded = stack.pop() + | if folded: + | kids = claimed[node] + | if kids: + | column[node] = sum(column[kid] for kid in kids) / len(kids) + | else: + | column[node] = next_column + | next_column += 1 + | continue + | depth[node] = level + | # A node belongs to whichever parent reaches it first, so a + | # cycle or a shared child is never laid out twice. + | kids = [kid for kid in children[node] if kid not in placed] + | placed.update(kids) + | claimed[node] = kids + | stack.append((node, level, True)) + | for kid in reversed(kids): + | stack.append((kid, level + 1, False)) + | + | for label in labels: + | if label not in placed and label not in has_parent: + | grow(label) + | # Whatever is left sits in a cycle that no root can reach. + | for label in labels: + | if label not in placed: + | grow(label) + | # The y-axis is inverted here so the tree grows top-down. + | return labels, [(column[label], -depth[label]) for label in labels] + | + |def compute_tree_layout(edges): + | try: + | labels, coords = build_tree_layout(edges) + | except Exception as e: + | raise TreeLayoutError(f"Tree layout failed: {e}") + | return {labels[index]: coords[index] for index in range(len(labels))} + | + |if in1df.empty: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error("Input table is empty.")) + |else: + | edges = [] + | for item in in1df[${pyStringLiteral(edgeListColumn)}].dropna(): + | try: + | edge = ast.literal_eval(str(item)) + | if isinstance(edge, (list, tuple)) and len(edge) == 2: + | edges.append(list(edge)) + | except (ValueError, SyntaxError): + | pass + | + | if not edges: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error("No valid [parent, child] pairs found in column " + ${pyStringLiteral( + edgeListColumn + )} + ".")) + | else: + | try: + | position = compute_tree_layout(edges) + | + | HORIZONTAL_DENSITY = 120 + | VERTICAL_DENSITY = 120 + | PADDING = 200 + | MIN_WIDTH = 800 + | MIN_HEIGHT = 600 + | + | if len(position) > 1: + | x_coords, y_coords = zip(*position.values()) + | x_range = max(x_coords) - min(x_coords) + | y_range = max(y_coords) - min(y_coords) + | plot_width = max(MIN_WIDTH, x_range * HORIZONTAL_DENSITY + PADDING) + | plot_height = max(MIN_HEIGHT, y_range * VERTICAL_DENSITY + PADDING) + | else: + | plot_width = MIN_WIDTH + | plot_height = MIN_HEIGHT + | + | Xe = [] + | Ye = [] + | for parent, child in edges: + | Xe += [position[parent][0], position[child][0], None] + | Ye += [position[parent][1], position[child][1], None] + | + | fig = go.Figure() + | fig.add_trace(go.Scatter(x=Xe, y=Ye, mode='lines', + | line=dict(color='rgb(210,210,210)', width=1), + | hoverinfo='none')) + | axis = dict(showline=False, zeroline=False, showgrid=False, showticklabels=False) + | fig.update_layout(title='Tree Plot', + | width=int(plot_width), + | height=int(plot_height), + | annotations=make_annotations(position), + | font_size=12, + | showlegend=False, + | xaxis=axis, + | yaxis=axis, + | margin=dict(l=40, r=40, b=85, t=100), + | dragmode='pan', + | hovermode='closest', + | plot_bgcolor='rgb(248,248,248)') + | fig.write_json("output.json") + | fig.write_html("output.html") + | print("Tree plot saved to output.html") + | except TreeLayoutError as e: + | with open("output.html", "w", encoding="utf-8") as output: + | output.write(render_error(str(e)))""".stripMargin + } + } diff --git a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/wordCloud/WordCloudOpDesc.scala b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/wordCloud/WordCloudOpDesc.scala index 2aa5b99d386..9c395cc4581 100644 --- a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/wordCloud/WordCloudOpDesc.scala +++ b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/visualization/wordCloud/WordCloudOpDesc.scala @@ -29,14 +29,25 @@ import org.apache.texera.amber.core.tuple.{AttributeType, Schema} import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBuilderStringContext import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString import org.apache.texera.amber.core.workflow.PortIdentity -import org.apache.texera.amber.operator.PythonOperatorDescriptor +import org.apache.texera.amber.operator.{PythonOperatorDescriptor, StandaloneCodeGenerator} import org.apache.texera.amber.operator.metadata.annotations.AutofillAttributeName import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo} import org.apache.texera.amber.operator.visualization.ImageUtility import org.apache.texera.amber.pybuilder.PythonTemplateBuilder +import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.pyStringLiteral import javax.validation.constraints.NotNull -class WordCloudOpDesc extends PythonOperatorDescriptor { +// type constraint: the words are counted out of the column's text, and the +// filter that finds them uses pandas' .str accessor, which refuses a column of +// anything else. A word cloud of numbers would say nothing anyway. +@JsonSchemaInject(json = """ +{ + "attributeTypeRules": { + "textColumn": { "enum": ["string"] } + } +} +""") +class WordCloudOpDesc extends PythonOperatorDescriptor with StandaloneCodeGenerator { @JsonProperty(required = true) @JsonSchemaTitle("Text column") @AutofillAttributeName @@ -113,4 +124,42 @@ class WordCloudOpDesc extends PythonOperatorDescriptor { | yield {'html-content': html} |""".encode } + + override def producesDataFrame(): Boolean = false + + // The two guards mirror generatePythonCode's: WordCloud.generate raises on a + // wordless string, so without them an input that is empty — or whose text + // column survives neither the dropna nor the word filter — crashes here where + // the runtime path explains itself. + override def generateStandaloneCode(): String = { + val textLit = pyStringLiteral(textColumn) + s"""def render_error(error_msg): + | return '''Reason is: {}
+ | '''.format(error_msg) + | + |table = in1df + |if table.empty: + | with open("output.html", "w", encoding="utf-8") as f: + | f.write(render_error("input table is empty.")) + |else: + | table = table.dropna(subset=[$textLit]) + | table = table[table[$textLit].str.contains(r'\\w', regex=True)] + | if table.empty: + | with open("output.html", "w", encoding="utf-8") as f: + | f.write(render_error("text column does not contain words or contains only nulls.")) + | else: + | text = ' '.join(table[$textLit]) + | from wordcloud import WordCloud, STOPWORDS + | wordcloud = WordCloud(width=1920, height=1080, stopwords=set(STOPWORDS), max_words=$topN, background_color='white', include_numbers=True, random_state=0).generate(text) + | from io import BytesIO + | image_stream = BytesIO() + | wordcloud.to_image().save(image_stream, format='PNG') + | binary_image_data = image_stream.getvalue() + | import base64 + | encoded_image_str = base64.b64encode(binary_image_data).decode("utf-8") + | html = f'