From e01e756a41e3b300952fa44c17efd1ff4df237bf Mon Sep 17 00:00:00 2001 From: Runhai Ouyang Date: Sat, 24 Aug 2024 12:19:58 +0800 Subject: [PATCH] Add files via upload --- input_templates/SISSO.in | 38 +++++++++++++++++++ input_templates/train.dat_classification | 6 +++ .../train.dat_classification_multitask | 17 +++++++++ input_templates/train.dat_regression | 6 +++ .../train.dat_regression_multitask | 13 +++++++ 5 files changed, 80 insertions(+) create mode 100644 input_templates/SISSO.in create mode 100644 input_templates/train.dat_classification create mode 100644 input_templates/train.dat_classification_multitask create mode 100644 input_templates/train.dat_regression create mode 100644 input_templates/train.dat_regression_multitask diff --git a/input_templates/SISSO.in b/input_templates/SISSO.in new file mode 100644 index 0000000..25d96f9 --- /dev/null +++ b/input_templates/SISSO.in @@ -0,0 +1,38 @@ +!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +! Texts after a exclamation mark (!) are comments +! The (R), (C) and (R&C) denotes the keyword used by regression, classification, and both, respectively. +! A complete list and more explanations on these keywords can be found in the SISSO_Guide.pdf +! The setting below is just an example, and user may need to change them for their jobs. +!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +ptype=1 !Property type 1: regression, 2:classification. +ntask=1 !(R&C) Multi-task learning (MTL) is invoked if >1. +scmt=.false. !(R) Sign-Constrained MTL is invoked if .true. +desc_dim=2 !(R&C) Dimension of the descriptor/model. +nsample=5 !(R) Number of samples in train.dat. Set nsample=N1,N2,... for MTL. +!nsample=(n1,n2,...) !(C) Number of samples. Set nsample=(n1,n2,...),(m1,m2,...),... for MTL. +restart=0 !(R&C) 0: starts from scratch, 1: continues the job(progress in the file CONTINUE) + +!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +! Feature construction (FC) and sure independence screening (SIS) +! Implemented operators:(+)(-)(*)(/)(exp)(exp-)(^-1)(^2)(^3)(sqrt)(cbrt)(log)(|-|)(scd)(^6)(sin)(cos) +! scd: standard Cauchy distribution +!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +fstore=1 !(R&C) Features storage in memory. 1: by data (fast); 2: by S-expression (low-memory) +nsf= 3 !(R&C) Number of scalar features provided in the file train.dat +ops='(+)(-)(*)(/)' !(R&C) Operators to be customized by user from the list shown above. +fcomplexity=3 !(R&C) Maximal feature complexity (# of operators in a feature), starting from 0. +funit=(1:2)(3:3) !(R&C) Feature unit: (n1:n2), features from n1 to n2 in train.dat have the same unit +fmax_min=1e-3 !(R&C) The feature will be discarded if the max. abs. value in it is < fmax_min. +fmax_max=1e5 !(R&C) The feature will be discarded if the max. abs. value in it is > fmax_max. +nf_sis=50000 !(R&C) Number of features in each of the SIS-selected subspace. + +!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +! Descriptor identification (DI) via sparse regression (SO) +!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +method_so= 'L0' !(R&C) 'L0' or 'L1L0'(LASSO+L0). 'L0' is always recommended. +fit_intercept=.true. !(R) Fit to a nonzero (.true.) or zero (.false.) intercept for the linear model. +metric= 'RMSE' !(R) The metric for model selection in regression: RMSE or MaxAE (max absolute error) +nmodel=100 !(R&C) Number of the top-ranked models to output (see the folder 'Models') +isconvex=(1,1,...) !(C) Each data group constrained to be convex domain, 1: YES; 0: NO +bwidth=0.001 !(C) Boundary tolerance for classification + diff --git a/input_templates/train.dat_classification b/input_templates/train.dat_classification new file mode 100644 index 0000000..bb3c930 --- /dev/null +++ b/input_templates/train.dat_classification @@ -0,0 +1,6 @@ +materials feature1 feature2 feature3 +sample1_group1 0.8626 0.7043 0.6312 +sample2_group1 0.7260 0.7818 0.6119 +sample1_group2 0.4943 0.0044 0.4420 +sample2_group2 0.0106 0.0399 0.9877 +sample3_group2 0.0970 0.3199 0.5504 diff --git a/input_templates/train.dat_classification_multitask b/input_templates/train.dat_classification_multitask new file mode 100644 index 0000000..b41bb8d --- /dev/null +++ b/input_templates/train.dat_classification_multitask @@ -0,0 +1,17 @@ +materials feature1 feature2 feature3 +sample1_group1_task1 xxx xxx xxx +sample2_group1_task1 xxx xxx xxx +sample1_group2_task1 xxx xxx xxx +sample2_group2_task1 xxx xxx xxx +sample3_group2_task1 xxx xxx xxx +sample1_group1_task2 xxx xxx xxx +sample2_group1_task2 xxx xxx xxx +sample3_group1_task2 xxx xxx xxx +sample4_group1_task2 xxx xxx xxx +sample1_group2_task2 xxx xxx xxx +sample2_group2_task2 xxx xxx xxx +sample3_group2_task2 xxx xxx xxx +sample4_group2_task2 xxx xxx xxx +sample1_group3_task2 xxx xxx xxx +sample2_group3_task2 xxx xxx xxx +sample3_group3_task2 xxx xxx xxx diff --git a/input_templates/train.dat_regression b/input_templates/train.dat_regression new file mode 100644 index 0000000..8a03b97 --- /dev/null +++ b/input_templates/train.dat_regression @@ -0,0 +1,6 @@ +materials property feature1 feature2 feature3 +sample1 3.0862 0.8626 0.7043 0.6312 +sample2 2.8854 0.7260 0.7818 0.6119 +sample3 0.6907 0.4943 0.0044 0.4420 +sample4 0.9902 0.0106 0.0399 0.9877 +sample5 0.7242 0.0970 0.3199 0.5504 diff --git a/input_templates/train.dat_regression_multitask b/input_templates/train.dat_regression_multitask new file mode 100644 index 0000000..2b363f3 --- /dev/null +++ b/input_templates/train.dat_regression_multitask @@ -0,0 +1,13 @@ +materials property feature1 feature2 feature3 +sample1_task1 xxx xxx xxx xxx +sample2_task1 xxx xxx xxx xxx +sample3_task1 xxx xxx xxx xxx +sample4_task1 xxx xxx xxx xxx +sample5_task1 xxx xxx xxx xxx +sample1_task2 xxx xxx xxx xxx +sample2_task2 xxx xxx xxx xxx +sample3_task2 xxx xxx xxx xxx +sample4_task2 xxx xxx xxx xxx +sample5_task2 xxx xxx xxx xxx +sample6_task2 xxx xxx xxx xxx +sample7_task2 xxx xxx xxx xxx