dzToolBox - Default Project

Select Samples

Choose at least 2 samples to compare in the matrix.

Output Title

Samples

Comparison Options

Select the metric used to compare samples.

Comparison Metric Similarity metrics range 0-1 (higher = more similar); dissimilarity is the inverse

Select Sample

Choose a sample with multivariate data for the heatmap.

Output Title

Sample

Heatmap Options

Configure the features and visualization type.

X-axis Feature

Y-axis Feature

Visualization Type Choose how to visualize the bivariate distribution

Samples
Options
Outputs

Select Samples

Choose at least 3 samples to compare using MDS.

Output Title

Samples

MDS Options

Configure how the MDS analysis is performed.

Comparison Metric Method used to compute dissimilarity between samples

MDS Type Non-metric preserves rank order; metric preserves actual distances

Output Types

Select which outputs to generate.

MDS Plot 2D scatter plot of samples in MDS space Shepard Plot Diagnostic plot comparing distances vs dissimilarities

Select Samples

Choose samples with multivariate data for tensor analysis.

Output Title

Samples

Output Types

Select which outputs to generate from the analysis.

Factors Plot Visualize the decomposed factor matrices Reconstruction Plot Compare original vs reconstructed tensor

Samples
Options
Outputs

Select Samples

Choose at least 2 source samples to model the mixture.

Output Title

Source Samples

Model Options

Configure how the mixture model is computed.

Comparison Metric Method for comparing source and target distributions

Output Types

Select which outputs to generate.

Contribution Table Table showing source contribution percentages Contribution Graph Bar chart visualizing source contributions Trials Graph Distribution of trials during optimization

Select Samples

Choose samples to view their empirical kernel density estimates.

Output Title

Samples

Output Types

Select which outputs to generate.

KDE Visualizations Interactive plots of kernel density estimates KDE Data Table Downloadable table of KDE values

Samples
Options
Outputs

Select Samples

Choose samples to analyze for optimal tensor rank.

Output Title

Samples

Analysis Options

Configure the rank search parameters.

Minimum Rank

Maximum Rank

Decomposition Model Tucker1 is recommended for most detrital zircon analyses

Normalization Method

Output Types

Select which analysis outputs to generate.

Misfit vs. Ranks Relative error for each rank value Optimum Rank Analysis Linear breakpoint analysis to find optimal rank

Samples
Options
Outputs

Select Samples

Choose samples for tensor factorization analysis.

Output Title

Samples

Factorization Options

Configure the tensor decomposition parameters.

Rank Number of source components to identify (use "Find Optimal Rank" to determine)

Output Types

Select which results to generate.

Source Attribution Plot Visual breakdown of source contributions Source Attribution Table Downloadable source contribution data Learned Source KDEs Kernel density estimates for each source Learned KDE Data Table Reconstructed KDE values Learned Coefficients Plot Visualization of mixing coefficients Learned Coefficients Table Downloadable coefficients data

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Intersample Comparison Matrix

Select Samples

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Comparison Options

Heatmap Plotter

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Heatmap Options

Multidimensional Scaling (MDS)

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MDS Options

Output Types

Maximum Depositional Age (MDA)

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Select Metrics

Calculation Options

Output Types

Tensor Factorization Analysis

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Output Types

New Distribution

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Distribution Options

New Histogram

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Chart Options

Top-Down Mixture Model

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Model Options

Output Types

View Empirical KDEs

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Output Types

Find Optimal Rank

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Analysis Options

Output Types

Run Tensor Factorization

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Factorization Options

Output Types

Project Settings

Age Range

Uncertainty Settings

Data Settings

Graph Settings

Import Data from Database

Export Data

Import Data

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