FLIM Analyzer
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Introduction
Concept
Installation
Requirements
Creating a Conda environment
Run the application
User Guide
The Application Menu
File
Settings
Data
Analysis
Plots
Window
Data Tables
Loading Data
Open Data File
Import Data Files
Adjusting Precision
Filtering Data
Filtering categorical columns
Filtering columns with numeric values
Pivoting Data
Unpivoting Data
Splitting Data
Merge Data
Order Categories
Example
Concat Data
Sort
Sorting the Data
Saving Data
Analysis
Summary Table
Running the Analysis
Example Outputs
Relative Change Analysis
Running the Analysis
Example Output
Series Analysis
Running the Analysis
Example Output
Categorize Data
Running the Analysis
Example Output
Random Forest Analysis
Running the Analysis
Example Output
Principal Component Analysis (PCA)
Running the Analysis
Example Output
K-Means
Running the Analysis
Example Output
KS - Statistics
Running the Analysis
Example Output
Autoencoder Training
Autoencoder Analysis
Autoencoder: Simulate
Plots
Select a Data Table
Create a Plot
Bar Plot
Box Plot
Line Plot
Swarm Plot
Violin Plot
Scatter Plot
Frequency Histogram
KDE Plots
Heatmap
FLIRR Plot
Save a Plot
Workflows
Test Workflow
FLIM Data Simulation Tuning
FLIM Feature Analysis
Settings
Load Settings
Save Settings
Programming Guide
Code Documentation
FLIM Analyzer
Docs
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User Guide
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Analysis
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Autoencoder Training
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Autoencoder Training
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Menu Access:
Analysis
>
Autoencoder:
Train
Toolbar Icon:
