MAterials Simulation Toolkit for Machine Learning (MAST-ML)
Version_2.0
Acknowledgements
Installing MAST-ML
Hardware and Data Requirements
Hardware
Data
Terminal installation (Linux or linux-like terminal on Mac)
Install Python3
Create a conda environment
Set up Juptyer notebooks
Install the MAST-ML package
Imports that don’t work
Windows installation
Install Python3
Create a conda environment
Set up the Spyder IDE and Jupyter notebooks
Install the MAST-ML package
Imports that don’t work
Windows 10 install: step-by-step guide (credit Joe Kern)
Startup
Locate the examples folder
Run the MASTML command
Check output
MAST-ML Input File
Input file sections
General Setup
Data Cleaning
Clustering
Feature Generation
Feature Normalization
Learning Curve
Feature Selection
Data Splits
Models
Misc Settings
MAST-ML overview slides
Running MAST-ML on Google Colab
MAST-ML tutorial
Introduction
Your first MAST-ML run
Cleaning input data
Feature generation and normalization
Training and evaluating your first model
Feature selection and learning curves
Hyperparameter optimization
Random leave-out versus leave-out-group cross-validation
Making predictions by importing a previously fit model
Predicting values for new, extrapolated data
Code Documentation: Metrics
mastml.metrics Module
Functions
adjusted_r2_score
check_and_fetch_names
r2_score_fitted
r2_score_noint
rmse_over_stdev
root_mean_squared_error
Code Documentation: Configuration file parser
mastml.conf_parser Module
Functions
fix_types
mybool
parse_conf_file
Code Documentation: Data cleaner
mastml.data_cleaner Module
Functions
columns_with_strings
flag_outliers
imputation
ppca
remove
Classes
PPCA
Class Inheritance Diagram
Code Documentation: Data loader
mastml.data_loader Module
Functions
load_data
Code Documentation: Learning curve
mastml.learning_curve Module
Functions
feature_learning_curve
sample_learning_curve
Code Documentation: Clusterers
mastml.legos.clusterers Module
Code Documentation: Data splitters
mastml.legos.data_splitters Module
Classes
Bootstrap
JustEachGroup
LeaveCloseCompositionsOut
LeaveOutPercent
NoSplit
SplittersUnion
Class Inheritance Diagram
Code Documentation: Utils
mastml.utils Module
Functions
activate_logging
log_header
nice_range
verbosalize_logger
Classes
BetweenFilter
ConfError
FileNotFoundError
FiletypeError
InvalidConfParameters
InvalidConfSection
InvalidConfSubSection
InvalidModel
InvalidValue
MastError
MissingColumnError
Class Inheritance Diagram
Code Documentation: MAST-ML Driver
mastml.mastml_driver Module
Functions
check_paths
get_commandline_args
main
mastml_run
Code Documentation: Plot Helper
mastml.plot_helper Module
Functions
get_divisor
get_histogram_bins
ipynb_maker
make_axis_same
make_error_plots
make_fig_ax
make_fig_ax_square
make_train_test_plots
nice_mean
nice_names
nice_range
nice_std
parse_error_data
plot_1d_heatmap
plot_2d_heatmap
plot_3d_heatmap
plot_average_cumulative_normalized_error
plot_average_normalized_error
plot_best_worst_per_point
plot_best_worst_split
plot_confusion_matrix
plot_cumulative_normalized_error
plot_keras_history
plot_learning_curve
plot_learning_curve_convergence
plot_metric_vs_group
plot_metric_vs_group_size
plot_normalized_error
plot_precision_recall_curve
plot_predicted_vs_true
plot_predicted_vs_true_bars
plot_real_vs_predicted_error
plot_residuals_histogram
plot_roc_curve
plot_scatter
plot_stats
plot_target_histogram
prediction_intervals
recursive_max
recursive_max_and_min
recursive_min
round_down
round_up
rounder
stat_to_string
trim_array
Code Documentation: HTML Helper
mastml.html_helper Module
Functions
is_test_image
is_train_image
make_html
make_image
make_link
show_combo
simple_section
Code Documentation: Feature Selectors
mastml.legos.feature_selectors Module
Functions
dataframify_new_column_names
dataframify_selector
fitify_just_use_values
Classes
EnsembleModelFeatureSelector
MASTMLFeatureSelector
PearsonSelector
Class Inheritance Diagram
Code Documentation: Feature Normalizers
mastml.legos.feature_normalizers Module
Functions
dataframify
Classes
MeanStdevScaler
Class Inheritance Diagram
Code Documentation: Randomizers
mastml.legos.randomizers Module
Classes
Randomizer
Class Inheritance Diagram
Code Documentation: Model Finder
mastml.legos.model_finder Module
Functions
check_models_mixed
find_model
Classes
AlwaysFive
EnsembleRegressor
KerasRegressor
ModelImport
RandomGuesser
Class Inheritance Diagram
Code Documentation: Utility Legos
mastml.legos.util_legos Module
Classes
DataFrameFeatureUnion
DoNothing
Class Inheritance Diagram
Code Documentation: Feature Generators
mastml.legos.feature_generators Module
Functions
clean_dataframe
Classes
ContainsElement
DataframeUtilities
Magpie
MagpieFeatureGeneration
MaterialsProject
MaterialsProjectFeatureGeneration
Matminer
NoGenerate
PolynomialFeatures
Class Inheritance Diagram
MAterials Simulation Toolkit for Machine Learning (MAST-ML)
Docs
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Index
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Index
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V
A
activate_logging() (in module mastml.utils)
adjusted_r2_score() (in module mastml.metrics)
AlwaysFive (class in mastml.legos.model_finder)
array_to_dataframe() (mastml.legos.feature_generators.DataframeUtilities class method)
assign_columns_as_features() (mastml.legos.feature_generators.DataframeUtilities class method)
B
BetweenFilter (class in mastml.utils)
Bootstrap (class in mastml.legos.data_splitters)
build_model() (mastml.legos.model_finder.KerasRegressor method)
build_models() (mastml.legos.model_finder.EnsembleRegressor method)
C
check_and_fetch_names() (in module mastml.metrics)
check_models_mixed() (in module mastml.legos.model_finder)
check_paths() (in module mastml.mastml_driver)
clean_dataframe() (in module mastml.legos.feature_generators)
columns_with_strings() (in module mastml.data_cleaner)
concatenate_arrays() (mastml.legos.feature_generators.DataframeUtilities class method)
ConfError
ContainsElement (class in mastml.legos.feature_generators)
D
dataframe_to_array() (mastml.legos.feature_generators.DataframeUtilities class method)
DataFrameFeatureUnion (class in mastml.legos.util_legos)
DataframeUtilities (class in mastml.legos.feature_generators)
dataframify() (in module mastml.legos.feature_normalizers)
dataframify_new_column_names() (in module mastml.legos.feature_selectors)
dataframify_selector() (in module mastml.legos.feature_selectors)
DoNothing (class in mastml.legos.util_legos)
E
EnsembleModelFeatureSelector (class in mastml.legos.feature_selectors)
EnsembleRegressor (class in mastml.legos.model_finder)
F
feature_learning_curve() (in module mastml.learning_curve)
FileNotFoundError
FiletypeError
filter() (mastml.utils.BetweenFilter method)
find_model() (in module mastml.legos.model_finder)
fit() (mastml.data_cleaner.PPCA method)
(mastml.legos.feature_generators.ContainsElement method)
(mastml.legos.feature_generators.Magpie method)
(mastml.legos.feature_generators.MaterialsProject method)
(mastml.legos.feature_generators.Matminer method)
(mastml.legos.feature_generators.NoGenerate method)
(mastml.legos.feature_generators.PolynomialFeatures method)
(mastml.legos.feature_normalizers.MeanStdevScaler method)
(mastml.legos.feature_selectors.EnsembleModelFeatureSelector method)
(mastml.legos.feature_selectors.MASTMLFeatureSelector method)
(mastml.legos.feature_selectors.PearsonSelector method)
(mastml.legos.model_finder.AlwaysFive method)
(mastml.legos.model_finder.EnsembleRegressor method)
(mastml.legos.model_finder.KerasRegressor method)
(mastml.legos.model_finder.ModelImport method)
(mastml.legos.model_finder.RandomGuesser method)
(mastml.legos.randomizers.Randomizer method)
(mastml.legos.util_legos.DataFrameFeatureUnion method)
(mastml.legos.util_legos.DoNothing method)
fitify_just_use_values() (in module mastml.legos.feature_selectors)
fix_types() (in module mastml.conf_parser)
flag_outliers() (in module mastml.data_cleaner)
G
generate_magpie_features() (mastml.legos.feature_generators.MagpieFeatureGeneration method)
generate_materialsproject_features() (mastml.legos.feature_generators.MaterialsProjectFeatureGeneration method)
get_commandline_args() (in module mastml.mastml_driver)
get_dataframe_statistics() (mastml.legos.feature_generators.DataframeUtilities class method)
get_divisor() (in module mastml.plot_helper)
get_histogram_bins() (in module mastml.plot_helper)
get_n_splits() (mastml.legos.data_splitters.Bootstrap method)
(mastml.legos.data_splitters.JustEachGroup method)
(mastml.legos.data_splitters.LeaveCloseCompositionsOut method)
(mastml.legos.data_splitters.LeaveOutPercent method)
(mastml.legos.data_splitters.NoSplit method)
(mastml.legos.data_splitters.SplittersUnion method)
I
imputation() (in module mastml.data_cleaner)
indices (mastml.legos.data_splitters.Bootstrap attribute)
InvalidConfParameters
InvalidConfSection
InvalidConfSubSection
InvalidModel
InvalidValue
inverse_transform() (mastml.legos.feature_normalizers.MeanStdevScaler method)
ipynb_maker() (in module mastml.plot_helper)
is_test_image() (in module mastml.html_helper)
is_train_image() (in module mastml.html_helper)
J
JustEachGroup (class in mastml.legos.data_splitters)
K
KerasRegressor (class in mastml.legos.model_finder)
L
LeaveCloseCompositionsOut (class in mastml.legos.data_splitters)
LeaveOutPercent (class in mastml.legos.data_splitters)
load() (mastml.data_cleaner.PPCA method)
load_data() (in module mastml.data_loader)
log_header() (in module mastml.utils)
M
Magpie (class in mastml.legos.feature_generators)
MagpieFeatureGeneration (class in mastml.legos.feature_generators)
main() (in module mastml.mastml_driver)
make_axis_same() (in module mastml.plot_helper)
make_error_plots() (in module mastml.plot_helper)
make_fig_ax() (in module mastml.plot_helper)
make_fig_ax_square() (in module mastml.plot_helper)
make_html() (in module mastml.html_helper)
make_image() (in module mastml.html_helper)
make_link() (in module mastml.html_helper)
make_train_test_plots() (in module mastml.plot_helper)
MastError
mastml.conf_parser (module)
mastml.data_cleaner (module)
mastml.data_loader (module)
mastml.html_helper (module)
mastml.learning_curve (module)
mastml.legos.clusterers (module)
mastml.legos.data_splitters (module)
mastml.legos.feature_generators (module)
mastml.legos.feature_normalizers (module)
mastml.legos.feature_selectors (module)
mastml.legos.model_finder (module)
mastml.legos.randomizers (module)
mastml.legos.util_legos (module)
mastml.mastml_driver (module)
mastml.metrics (module)
mastml.plot_helper (module)
mastml.utils (module)
mastml_run() (in module mastml.mastml_driver)
MASTMLFeatureSelector (class in mastml.legos.feature_selectors)
MaterialsProject (class in mastml.legos.feature_generators)
MaterialsProjectFeatureGeneration (class in mastml.legos.feature_generators)
Matminer (class in mastml.legos.feature_generators)
MeanStdevScaler (class in mastml.legos.feature_normalizers)
merge_dataframe_columns() (mastml.legos.feature_generators.DataframeUtilities class method)
merge_dataframe_rows() (mastml.legos.feature_generators.DataframeUtilities class method)
MissingColumnError
ModelImport (class in mastml.legos.model_finder)
mybool() (in module mastml.conf_parser)
N
nice_mean() (in module mastml.plot_helper)
nice_names() (in module mastml.plot_helper)
nice_range() (in module mastml.plot_helper)
(in module mastml.utils)
nice_std() (in module mastml.plot_helper)
NoGenerate (class in mastml.legos.feature_generators)
NoSplit (class in mastml.legos.data_splitters)
P
parse_conf_file() (in module mastml.conf_parser)
parse_error_data() (in module mastml.plot_helper)
PearsonSelector (class in mastml.legos.feature_selectors)
plot_1d_heatmap() (in module mastml.plot_helper)
plot_2d_heatmap() (in module mastml.plot_helper)
plot_3d_heatmap() (in module mastml.plot_helper)
plot_average_cumulative_normalized_error() (in module mastml.plot_helper)
plot_average_normalized_error() (in module mastml.plot_helper)
plot_best_worst_per_point() (in module mastml.plot_helper)
plot_best_worst_split() (in module mastml.plot_helper)
plot_confusion_matrix() (in module mastml.plot_helper)
plot_cumulative_normalized_error() (in module mastml.plot_helper)
plot_keras_history() (in module mastml.plot_helper)
plot_learning_curve() (in module mastml.plot_helper)
plot_learning_curve_convergence() (in module mastml.plot_helper)
plot_metric_vs_group() (in module mastml.plot_helper)
plot_metric_vs_group_size() (in module mastml.plot_helper)
plot_normalized_error() (in module mastml.plot_helper)
plot_precision_recall_curve() (in module mastml.plot_helper)
plot_predicted_vs_true() (in module mastml.plot_helper)
plot_predicted_vs_true_bars() (in module mastml.plot_helper)
plot_real_vs_predicted_error() (in module mastml.plot_helper)
plot_residuals_histogram() (in module mastml.plot_helper)
plot_roc_curve() (in module mastml.plot_helper)
plot_scatter() (in module mastml.plot_helper)
plot_stats() (in module mastml.plot_helper)
plot_target_histogram() (in module mastml.plot_helper)
PolynomialFeatures (class in mastml.legos.feature_generators)
PPCA (class in mastml.data_cleaner)
ppca() (in module mastml.data_cleaner)
predict() (mastml.legos.model_finder.AlwaysFive method)
(mastml.legos.model_finder.EnsembleRegressor method)
(mastml.legos.model_finder.KerasRegressor method)
(mastml.legos.model_finder.ModelImport method)
(mastml.legos.model_finder.RandomGuesser method)
prediction_intervals() (in module mastml.plot_helper)
R
r2_score_fitted() (in module mastml.metrics)
r2_score_noint() (in module mastml.metrics)
RandomGuesser (class in mastml.legos.model_finder)
Randomizer (class in mastml.legos.randomizers)
recursive_max() (in module mastml.plot_helper)
recursive_max_and_min() (in module mastml.plot_helper)
recursive_min() (in module mastml.plot_helper)
remove() (in module mastml.data_cleaner)
retrieve_AFLOW() (mastml.legos.feature_generators.Matminer method)
retrieve_citrine() (mastml.legos.feature_generators.Matminer method)
retrieve_MDF() (mastml.legos.feature_generators.Matminer method)
retrieve_mp() (mastml.legos.feature_generators.Matminer method)
retrieve_MPDS() (mastml.legos.feature_generators.Matminer method)
rmse_over_stdev() (in module mastml.metrics)
root_mean_squared_error() (in module mastml.metrics)
round_down() (in module mastml.plot_helper)
round_up() (in module mastml.plot_helper)
rounder() (in module mastml.plot_helper)
S
sample_learning_curve() (in module mastml.learning_curve)
save() (mastml.data_cleaner.PPCA method)
save_all_dataframe_statistics() (mastml.legos.feature_generators.DataframeUtilities class method)
setup() (mastml.legos.model_finder.EnsembleRegressor method)
show_combo() (in module mastml.html_helper)
simple_section() (in module mastml.html_helper)
split() (mastml.legos.data_splitters.Bootstrap method)
(mastml.legos.data_splitters.JustEachGroup method)
(mastml.legos.data_splitters.LeaveCloseCompositionsOut method)
(mastml.legos.data_splitters.LeaveOutPercent method)
(mastml.legos.data_splitters.NoSplit method)
(mastml.legos.data_splitters.SplittersUnion method)
SplittersUnion (class in mastml.legos.data_splitters)
stat_to_string() (in module mastml.plot_helper)
stats_check_models() (mastml.legos.model_finder.EnsembleRegressor method)
summary() (mastml.legos.model_finder.KerasRegressor method)
T
transform() (mastml.data_cleaner.PPCA method)
(mastml.legos.feature_generators.ContainsElement method)
(mastml.legos.feature_generators.Magpie method)
(mastml.legos.feature_generators.MaterialsProject method)
(mastml.legos.feature_generators.Matminer method)
(mastml.legos.feature_generators.NoGenerate method)
(mastml.legos.feature_generators.PolynomialFeatures method)
(mastml.legos.feature_normalizers.MeanStdevScaler method)
(mastml.legos.feature_selectors.EnsembleModelFeatureSelector method)
(mastml.legos.feature_selectors.MASTMLFeatureSelector method)
(mastml.legos.feature_selectors.PearsonSelector method)
(mastml.legos.randomizers.Randomizer method)
(mastml.legos.util_legos.DataFrameFeatureUnion method)
(mastml.legos.util_legos.DoNothing method)
trim_array() (in module mastml.plot_helper)
V
verbosalize_logger() (in module mastml.utils)
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v: Version_2.0
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dev_ryan_2020-12-21
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