diff --git a/doc_conf/index.rst b/doc_conf/index.rst index 2eb52245..171428bf 100644 --- a/doc_conf/index.rst +++ b/doc_conf/index.rst @@ -37,6 +37,9 @@ HiDimStat depends on the following packages:: numpy scipy scikit-learn + pandas + torch + torchmetrics To run examples it is neccessary to install ``matplotlib``, and to run tests it @@ -71,8 +74,8 @@ To build the documentation you will need to run: .. code-block:: - pip install -U sphinx_gallery sphinx_bootstrap_theme - cd doc + pip install -U .[doc] + cd doc_conf make html diff --git a/doc_conf/references.bib b/doc_conf/references.bib index 638f624e..1b08b32d 100644 --- a/doc_conf/references.bib +++ b/doc_conf/references.bib @@ -199,4 +199,83 @@ @article{Williamson_General_2023 pages = {1645--1658}, number = {543}, volume = {118}, -} \ No newline at end of file +} +} + +@article{benjamini1995controlling, + title={Controlling the false discovery rate: a practical and powerful approach to multiple testing}, + author={Benjamini, Yoav and Hochberg, Yosef}, + journal={Journal of the Royal statistical society: series B (Methodological)}, + volume={57}, + number={1}, + pages={289--300}, + year={1995}, + publisher={Wiley Online Library} +} + + +@article{wang2022false, + title={False discovery rate control with e-values}, + author={Wang, Ruodu and Ramdas, Aaditya}, + journal={Journal of the Royal Statistical Society Series B: Statistical Methodology}, + volume={84}, + number={3}, + pages={822--852}, + year={2022}, + publisher={Oxford University Press} +} + +@article{ramdas2017wasserstein, + title={On wasserstein two-sample testing and related families of nonparametric tests}, + author={Ramdas, Aaditya and Garc{\'\i}a Trillos, Nicol{\'a}s and Cuturi, Marco}, + journal={Entropy}, + volume={19}, + number={2}, + pages={47}, + year={2017}, + publisher={MDPI} +} + +@article{ramdas2017online, + title={Online control of the false discovery rate with decaying memory}, + author={Ramdas, Aaditya and Yang, Fanny and Wainwright, Martin J and Jordan, Michael I}, + journal={Advances in neural information processing systems}, + volume={30}, + year={2017} +} + +@article{meinshausen2008hierarchical, + title={Hierarchical testing of variable importance}, + author={Meinshausen, Nicolai}, + journal={Biometrika}, + volume={95}, + number={2}, + pages={265--278}, + year={2008}, + publisher={Oxford University Press} +} +@article{meinshausen2009p, + title={P-values for high-dimensional regression}, + author={Meinshausen, Nicolai and Meier, Lukas and B{\"u}hlmann, Peter}, + journal={Journal of the American Statistical Association}, + volume={104}, + number={488}, + pages={1671--1681}, + year={2009}, + publisher={Taylor \& Francis} +} + +@article{gaonkar_deriving_2012, + title = {Deriving statistical significance maps for {SVM} based image classification and group comparisons}, + volume = {15}, + url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3703958/}, + pages = {723--730}, + number = {0}, + journaltitle = {Medical image computing and computer-assisted intervention : {MICCAI} ... International Conference on Medical Image Computing and Computer-Assisted Intervention}, + journal = {Med Image Comput Comput Assist Interv}, + author = {Gaonkar, Bilwaj and Davatzikos, Christos}, + urldate = {2024-12-16}, + year = {2012}, + pmid = {23285616}, + pmcid = {PMC3703958}, +} diff --git a/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip b/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip index b77dbbb3..fffd4ea4 100644 Binary files a/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip and b/docs/_downloads/06bb0f682e15138dfd659b791a14e9c6/plot_variable_importance_classif.zip differ diff --git a/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip index ed0bc280..ade0efcd 100644 Binary files a/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip and b/docs/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip differ diff --git a/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip b/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip index ab63e2bd..65e0c808 100644 Binary files a/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip and b/docs/_downloads/117422582fb46cc8ed6549598a2d87de/plot_dcrt_example.zip differ diff --git a/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip b/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip index 5d799ade..8cbfbdc0 100644 Binary files a/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip and b/docs/_downloads/1a99dc8cb1c22f91072d67cf26fce26c/plot_knockoff_aggregation.zip differ diff --git a/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip b/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip index ad21dda7..72afa4b4 100644 Binary files a/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip and b/docs/_downloads/5ca231767268e6cd969e65225d673650/plot_fmri_data_example.zip differ diff --git a/docs/_downloads/642b61154cca48af8e3feb505b920e16/plot_dcrt_example.ipynb b/docs/_downloads/642b61154cca48af8e3feb505b920e16/plot_dcrt_example.ipynb index c77112f2..9e14f022 100644 --- a/docs/_downloads/642b61154cca48af8e3feb505b920e16/plot_dcrt_example.ipynb +++ b/docs/_downloads/642b61154cca48af8e3feb505b920e16/plot_dcrt_example.ipynb @@ -78,7 +78,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.8" + "version": "3.12.9" } }, "nbformat": 4, diff --git a/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip index 80d5c702..11a58a18 100644 Binary files a/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip and b/docs/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip differ diff --git a/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip b/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip index 095f3ef8..ede9cff9 100644 Binary files a/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip and b/docs/_downloads/707d94040f5ada342e781499193f46f1/plot_diabetes_variable_importance_example.zip differ diff --git a/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py b/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py index 25b89b81..dbe14c07 100644 --- a/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py +++ b/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py @@ -54,7 +54,7 @@ from sklearn.linear_model import Ridge from sklearn.utils import Bunch -from hidimstat.adaptive_permutation_threshold import ada_svr +from hidimstat.ada_svr import ada_svr from hidimstat.clustered_inference import clustered_inference from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference from hidimstat.permutation_test import permutation_test, permutation_test_cv diff --git a/docs/_downloads/7d2770a07fbe419760c9ac177df4f69e/plot_2D_simulation_example.ipynb b/docs/_downloads/7d2770a07fbe419760c9ac177df4f69e/plot_2D_simulation_example.ipynb index ef338cab..6e755c1d 100644 --- a/docs/_downloads/7d2770a07fbe419760c9ac177df4f69e/plot_2D_simulation_example.ipynb +++ b/docs/_downloads/7d2770a07fbe419760c9ac177df4f69e/plot_2D_simulation_example.ipynb @@ -240,7 +240,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.8" + "version": "3.12.9" } }, "nbformat": 4, diff --git a/docs/_downloads/8635bd4b58b2828c710e4331f35d14f6/plot_knockoff_aggregation.ipynb b/docs/_downloads/8635bd4b58b2828c710e4331f35d14f6/plot_knockoff_aggregation.ipynb index 18078a4c..b462549a 100644 --- a/docs/_downloads/8635bd4b58b2828c710e4331f35d14f6/plot_knockoff_aggregation.ipynb +++ b/docs/_downloads/8635bd4b58b2828c710e4331f35d14f6/plot_knockoff_aggregation.ipynb @@ -42,7 +42,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.8" + "version": "3.12.9" } }, "nbformat": 4, diff --git a/docs/_downloads/931385a6992917f918857d6a3ee9f780/plot_fmri_data_example.ipynb b/docs/_downloads/931385a6992917f918857d6a3ee9f780/plot_fmri_data_example.ipynb index 69c0e058..89baf7f0 100644 --- a/docs/_downloads/931385a6992917f918857d6a3ee9f780/plot_fmri_data_example.ipynb +++ b/docs/_downloads/931385a6992917f918857d6a3ee9f780/plot_fmri_data_example.ipynb @@ -22,7 +22,7 @@ }, "outputs": [], "source": [ - "import numpy as np\nimport pandas as pd\nfrom nilearn import datasets\nfrom nilearn.image import mean_img\nfrom nilearn.input_data import NiftiMasker\nfrom nilearn.plotting import plot_stat_map, show\nfrom sklearn.cluster import FeatureAgglomeration\nfrom sklearn.feature_extraction import image\nfrom sklearn.linear_model import Ridge\nfrom sklearn.utils import Bunch\n\nfrom hidimstat.adaptive_permutation_threshold import ada_svr\nfrom hidimstat.clustered_inference import clustered_inference\nfrom hidimstat.ensemble_clustered_inference import ensemble_clustered_inference\nfrom hidimstat.permutation_test import permutation_test, permutation_test_cv\nfrom hidimstat.standardized_svr import standardized_svr\nfrom hidimstat.stat_tools import pval_from_scale, zscore_from_pval" + "import numpy as np\nimport pandas as pd\nfrom nilearn import datasets\nfrom nilearn.image import mean_img\nfrom nilearn.input_data import NiftiMasker\nfrom nilearn.plotting import plot_stat_map, show\nfrom sklearn.cluster import FeatureAgglomeration\nfrom sklearn.feature_extraction import image\nfrom sklearn.linear_model import Ridge\nfrom sklearn.utils import Bunch\n\nfrom hidimstat.ada_svr import ada_svr\nfrom hidimstat.clustered_inference import clustered_inference\nfrom hidimstat.ensemble_clustered_inference import ensemble_clustered_inference\nfrom hidimstat.permutation_test import permutation_test, permutation_test_cv\nfrom hidimstat.standardized_svr import standardized_svr\nfrom hidimstat.stat_tools import pval_from_scale, zscore_from_pval" ] }, { @@ -301,7 +301,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.8" + "version": "3.12.9" } }, "nbformat": 4, diff --git a/docs/_downloads/a70e28075a283d5e3fe675ced733c459/plot_diabetes_variable_importance_example.ipynb b/docs/_downloads/a70e28075a283d5e3fe675ced733c459/plot_diabetes_variable_importance_example.ipynb index 828cd728..fdfa9b99 100644 --- a/docs/_downloads/a70e28075a283d5e3fe675ced733c459/plot_diabetes_variable_importance_example.ipynb +++ b/docs/_downloads/a70e28075a283d5e3fe675ced733c459/plot_diabetes_variable_importance_example.ipynb @@ -186,7 +186,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.8" + "version": "3.12.9" } }, "nbformat": 4, diff --git a/docs/_downloads/c983a5ad5887eff1a3df617cbd64234a/plot_variable_importance_classif.ipynb b/docs/_downloads/c983a5ad5887eff1a3df617cbd64234a/plot_variable_importance_classif.ipynb index 8485656b..4aa65391 100644 --- a/docs/_downloads/c983a5ad5887eff1a3df617cbd64234a/plot_variable_importance_classif.ipynb +++ b/docs/_downloads/c983a5ad5887eff1a3df617cbd64234a/plot_variable_importance_classif.ipynb @@ -132,7 +132,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.8" + "version": "3.12.9" } }, "nbformat": 4, diff --git a/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip b/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip index 859e5cd3..97703450 100644 Binary files a/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip and b/docs/_downloads/e08c0f6d4aade0f0eaf8ba56dbbfd9c9/plot_2D_simulation_example.zip differ diff --git a/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt b/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt index d3e0f8b0..1f57c471 100644 --- a/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt +++ b/docs/_sources/auto_examples/plot_2D_simulation_example.rst.txt @@ -554,9 +554,9 @@ randomization. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (1 minutes 7.791 seconds) + **Total running time of the script:** (1 minutes 3.434 seconds) -**Estimated memory usage:** 710 MB +**Estimated memory usage:** 722 MB .. _sphx_glr_download_auto_examples_plot_2D_simulation_example.py: diff --git a/docs/_sources/auto_examples/plot_dcrt_example.rst.txt b/docs/_sources/auto_examples/plot_dcrt_example.rst.txt index 1136a55a..7f137194 100644 --- a/docs/_sources/auto_examples/plot_dcrt_example.rst.txt +++ b/docs/_sources/auto_examples/plot_dcrt_example.rst.txt @@ -162,9 +162,9 @@ Plotting the comparison .. rst-class:: sphx-glr-timing - **Total running time of the script:** (1 minutes 3.192 seconds) + **Total running time of the script:** (1 minutes 2.836 seconds) -**Estimated memory usage:** 640 MB +**Estimated memory usage:** 658 MB .. _sphx_glr_download_auto_examples_plot_dcrt_example.py: diff --git a/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt b/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt index 48c85a40..a8d72e49 100644 --- a/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt +++ b/docs/_sources/auto_examples/plot_diabetes_variable_importance_example.rst.txt @@ -491,9 +491,9 @@ Analyze the results .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 8.885 seconds) + **Total running time of the script:** (0 minutes 8.070 seconds) -**Estimated memory usage:** 625 MB +**Estimated memory usage:** 643 MB .. _sphx_glr_download_auto_examples_plot_diabetes_variable_importance_example.py: diff --git a/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt b/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt index f3ac2d50..a63f7e66 100644 --- a/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt +++ b/docs/_sources/auto_examples/plot_fmri_data_example.rst.txt @@ -78,7 +78,7 @@ Imports needed for this script from sklearn.linear_model import Ridge from sklearn.utils import Bunch - from hidimstat.adaptive_permutation_threshold import ada_svr + from hidimstat.ada_svr import ada_svr from hidimstat.clustered_inference import clustered_inference from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference from hidimstat.permutation_test import permutation_test, permutation_test_cv @@ -182,7 +182,7 @@ You may choose a subject in [1, 2, 3, 4, 5, 6]. By default subject=2. [fetch_single_file] ...done. (0 seconds, 0 min) [fetch_single_file] Downloading data from http://data.pymvpa.org/datasets/haxby2001/subj2-2010.01.14.tar.gz ... - [_chunk_report_] Downloaded 161644544 of 291168628 bytes (55.5%%, 0.8s remaining) + [_chunk_report_] Downloaded 158236672 of 291168628 bytes (54.3%%, 0.8s remaining) [fetch_single_file] ...done. (2 seconds, 0 min) [uncompress_file] Extracting data from /home/runner/nilearn_data/haxby2001/9cabe068089e791ef0c5fe930fc20e30/subj2-2010.01.14.tar.gz... @@ -190,7 +190,7 @@ You may choose a subject in [1, 2, 3, 4, 5, 6]. By default subject=2. /home/runner/work/hidimstat/hidimstat/examples/plot_fmri_data_example.py:88: FutureWarning: From release 0.13.0 onwards, this function will, by default, copy the header of the input image to the output. Currently, the header is reset to the default Nifti1Header. To suppress this warning and use the new behavior, set `copy_header=True`. bg_img = mean_img(haxby_dataset.anat) - /opt/hostedtoolcache/Python/3.12.8/x64/lib/python3.12/site-packages/nilearn/image/resampling.py:489: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. + /opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/nilearn/image/resampling.py:489: UserWarning: The provided image has no sform in its header. Please check the provided file. Results may not be as expected. warnings.warn( @@ -287,8 +287,8 @@ Now, we compute p-values thanks to permutation tests applied to .. code-block:: none - [Parallel(n_jobs=1)]: Done 49 tasks | elapsed: 1.5s - [Parallel(n_jobs=1)]: Done 199 tasks | elapsed: 6.6s + [Parallel(n_jobs=1)]: Done 49 tasks | elapsed: 1.6s + [Parallel(n_jobs=1)]: Done 199 tasks | elapsed: 6.4s @@ -336,7 +336,7 @@ and high-dimensional inference (c.f. References). .. code-block:: none Clustered inference: n_clusters = 500, inference method = desparsified-lasso, seed = 0 - /opt/hostedtoolcache/Python/3.12.8/x64/lib/python3.12/site-packages/sklearn/linear_model/_coordinate_descent.py:681: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 1.7422256933791083, tolerance: 0.21600000000000003 + /opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/sklearn/linear_model/_coordinate_descent.py:681: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 1.7422256933791083, tolerance: 0.21600000000000003 model = cd_fast.enet_coordinate_descent_gram( @@ -369,7 +369,7 @@ However you might benefit from clustering randomization taking .. code-block:: none [Parallel(n_jobs=2)]: Using backend LokyBackend with 2 concurrent workers. - [Parallel(n_jobs=2)]: Done 5 out of 5 | elapsed: 32.3s finished + [Parallel(n_jobs=2)]: Done 5 out of 5 | elapsed: 32.1s finished @@ -575,7 +575,7 @@ called `plot_map` that wraps all these steps. .. code-block:: none - /opt/hostedtoolcache/Python/3.12.8/x64/lib/python3.12/site-packages/nilearn/plotting/displays/_slicers.py:313: UserWarning: empty mask + /opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/nilearn/plotting/displays/_slicers.py:313: UserWarning: empty mask ims = self._map_show(img, type="imshow", threshold=threshold, **kwargs) @@ -614,9 +614,9 @@ spurious discoveries. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (1 minutes 22.801 seconds) + **Total running time of the script:** (1 minutes 22.636 seconds) -**Estimated memory usage:** 3279 MB +**Estimated memory usage:** 3316 MB .. _sphx_glr_download_auto_examples_plot_fmri_data_example.py: diff --git a/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt b/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt index f1c17d1b..879fca31 100644 --- a/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt +++ b/docs/_sources/auto_examples/plot_knockoff_aggregation.rst.txt @@ -205,9 +205,9 @@ Imports needed for this script .. rst-class:: sphx-glr-timing - **Total running time of the script:** (5 minutes 45.456 seconds) + **Total running time of the script:** (5 minutes 36.077 seconds) -**Estimated memory usage:** 809 MB +**Estimated memory usage:** 823 MB .. _sphx_glr_download_auto_examples_plot_knockoff_aggregation.py: diff --git a/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt b/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt index 35c18fcb..ebdca7ac 100644 --- a/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt +++ b/docs/_sources/auto_examples/plot_variable_importance_classif.rst.txt @@ -176,7 +176,7 @@ Visualize the data .. code-block:: none - [, , , , , , , , , ] + [, , , , , , , , , ] @@ -287,7 +287,7 @@ estimate the importance of the features. .. code-block:: none - /opt/hostedtoolcache/Python/3.12.8/x64/lib/python3.12/site-packages/joblib/externals/loky/process_executor.py:752: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak. + /opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/joblib/externals/loky/process_executor.py:752: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak. warnings.warn( @@ -422,16 +422,16 @@ the features. .. code-block:: none - + .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 43.179 seconds) + **Total running time of the script:** (0 minutes 43.137 seconds) -**Estimated memory usage:** 621 MB +**Estimated memory usage:** 639 MB .. _sphx_glr_download_auto_examples_plot_variable_importance_classif.py: diff --git a/docs/_sources/auto_examples/sg_execution_times.rst.txt b/docs/_sources/auto_examples/sg_execution_times.rst.txt index 5c03805b..bdfa61ba 100644 --- a/docs/_sources/auto_examples/sg_execution_times.rst.txt +++ b/docs/_sources/auto_examples/sg_execution_times.rst.txt @@ -6,7 +6,7 @@ Computation times ================= -**10:11.305** total execution time for 6 files **from auto_examples**: +**09:56.190** total execution time for 6 files **from auto_examples**: .. container:: @@ -33,20 +33,20 @@ Computation times - Time - Mem (MB) * - :ref:`sphx_glr_auto_examples_plot_knockoff_aggregation.py` (``plot_knockoff_aggregation.py``) - - 05:45.456 - - 808.7 + - 05:36.077 + - 823.4 * - :ref:`sphx_glr_auto_examples_plot_fmri_data_example.py` (``plot_fmri_data_example.py``) - - 01:22.801 - - 3279.1 + - 01:22.636 + - 3315.7 * - :ref:`sphx_glr_auto_examples_plot_2D_simulation_example.py` (``plot_2D_simulation_example.py``) - - 01:07.791 - - 710.0 + - 01:03.434 + - 722.0 * - :ref:`sphx_glr_auto_examples_plot_dcrt_example.py` (``plot_dcrt_example.py``) - - 01:03.192 - - 640.2 + - 01:02.836 + - 658.4 * - :ref:`sphx_glr_auto_examples_plot_variable_importance_classif.py` (``plot_variable_importance_classif.py``) - - 00:43.179 - - 620.6 + - 00:43.137 + - 638.9 * - :ref:`sphx_glr_auto_examples_plot_diabetes_variable_importance_example.py` (``plot_diabetes_variable_importance_example.py``) - - 00:08.885 - - 624.9 + - 00:08.070 + - 643.3 diff --git a/docs/_sources/index.rst.txt b/docs/_sources/index.rst.txt index 2eb52245..171428bf 100644 --- a/docs/_sources/index.rst.txt +++ b/docs/_sources/index.rst.txt @@ -37,6 +37,9 @@ HiDimStat depends on the following packages:: numpy scipy scikit-learn + pandas + torch + torchmetrics To run examples it is neccessary to install ``matplotlib``, and to run tests it @@ -71,8 +74,8 @@ To build the documentation you will need to run: .. code-block:: - pip install -U sphinx_gallery sphinx_bootstrap_theme - cd doc + pip install -U .[doc] + cd doc_conf make html diff --git a/docs/_sources/sg_execution_times.rst.txt b/docs/_sources/sg_execution_times.rst.txt index b8532025..dd78a2fa 100644 --- a/docs/_sources/sg_execution_times.rst.txt +++ b/docs/_sources/sg_execution_times.rst.txt @@ -6,7 +6,7 @@ Computation times ================= -**10:11.305** total execution time for 6 files **from all galleries**: +**09:56.190** total execution time for 6 files **from all galleries**: .. container:: @@ -33,20 +33,20 @@ Computation times - Time - Mem (MB) * - :ref:`sphx_glr_auto_examples_plot_knockoff_aggregation.py` (``../examples/plot_knockoff_aggregation.py``) - - 05:45.456 - - 808.7 + - 05:36.077 + - 823.4 * - :ref:`sphx_glr_auto_examples_plot_fmri_data_example.py` (``../examples/plot_fmri_data_example.py``) - - 01:22.801 - - 3279.1 + - 01:22.636 + - 3315.7 * - :ref:`sphx_glr_auto_examples_plot_2D_simulation_example.py` (``../examples/plot_2D_simulation_example.py``) - - 01:07.791 - - 710.0 + - 01:03.434 + - 722.0 * - :ref:`sphx_glr_auto_examples_plot_dcrt_example.py` (``../examples/plot_dcrt_example.py``) - - 01:03.192 - - 640.2 + - 01:02.836 + - 658.4 * - :ref:`sphx_glr_auto_examples_plot_variable_importance_classif.py` (``../examples/plot_variable_importance_classif.py``) - - 00:43.179 - - 620.6 + - 00:43.137 + - 638.9 * - :ref:`sphx_glr_auto_examples_plot_diabetes_variable_importance_example.py` (``../examples/plot_diabetes_variable_importance_example.py``) - - 00:08.885 - - 624.9 + - 00:08.070 + - 643.3 diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js index f043c806..1b62051f 100644 --- a/docs/_static/documentation_options.js +++ b/docs/_static/documentation_options.js @@ -1,5 +1,5 @@ const DOCUMENTATION_OPTIONS = { - VERSION: '0.1.dev1+geccd3d8', + VERSION: '0.1.dev1+g5937d81', LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/api.html b/docs/api.html index b81c3373..07606c86 100644 --- a/docs/api.html +++ b/docs/api.html @@ -5,7 +5,7 @@ - API Documentation — HiDimStat 0.1.dev1+geccd3d8 documentation + API Documentation — HiDimStat 0.1.dev1+g5937d81 documentation @@ -13,7 +13,7 @@ - + @@ -133,7 +133,7 @@

Functions

ada_svr(X, y[, rcond])

-

Adaptative Permutation Threshold for SVR

+

ADA-SVR: Adaptive Permutation Threshold Support Vector Regression

aggregate_quantiles(list_one_sided_pval[, ...])

Aggregation of survival function values by adaptive quantile procedure

diff --git a/docs/auto_examples/index.html b/docs/auto_examples/index.html index 0c66192e..32df789b 100644 --- a/docs/auto_examples/index.html +++ b/docs/auto_examples/index.html @@ -5,7 +5,7 @@ - Examples Gallery — HiDimStat 0.1.dev1+geccd3d8 documentation + Examples Gallery — HiDimStat 0.1.dev1+g5937d81 documentation @@ -13,7 +13,7 @@ - + diff --git a/docs/auto_examples/plot_2D_simulation_example.html b/docs/auto_examples/plot_2D_simulation_example.html index 8423919a..afc66a31 100644 --- a/docs/auto_examples/plot_2D_simulation_example.html +++ b/docs/auto_examples/plot_2D_simulation_example.html @@ -5,7 +5,7 @@ - Support recovery on simulated data (2D) — HiDimStat 0.1.dev1+geccd3d8 documentation + Support recovery on simulated data (2D) — HiDimStat 0.1.dev1+g5937d81 documentation @@ -13,7 +13,7 @@ - + @@ -475,8 +475,8 @@

Analysis of the results -

Total running time of the script: (1 minutes 7.791 seconds)

-

Estimated memory usage: 710 MB

+

Total running time of the script: (1 minutes 3.434 seconds)

+

Estimated memory usage: 722 MB

 -Type-I Error, Power

Total running time of the script: (1 minutes 3.192 seconds)

-

Estimated memory usage: 640 MB

+Type-I Error, Power

Total running time of the script: (1 minutes 2.836 seconds)

+

Estimated memory usage: 658 MB

-
[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    1.5s
-[Parallel(n_jobs=1)]: Done 199 tasks      | elapsed:    6.6s
+
[Parallel(n_jobs=1)]: Done  49 tasks      | elapsed:    1.6s
+[Parallel(n_jobs=1)]: Done 199 tasks      | elapsed:    6.4s
 

 

 
Now, let us run the algorithm introduced by Gaonkar et al. (c.f. References).
@@ -330,7 +330,7 @@ 
Making the inference with several algorithms
Clustered inference: n_clusters = 500, inference method = desparsified-lasso, seed = 0
-/opt/hostedtoolcache/Python/3.12.8/x64/lib/python3.12/site-packages/sklearn/linear_model/_coordinate_descent.py:681: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 1.7422256933791083, tolerance: 0.21600000000000003
+/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/sklearn/linear_model/_coordinate_descent.py:681: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 1.7422256933791083, tolerance: 0.21600000000000003
   model = cd_fast.enet_coordinate_descent_gram(
@@ -347,7 +347,7 @@

Making the inference with several algorithms
[Parallel(n_jobs=2)]: Using backend LokyBackend with 2 concurrent workers.
-[Parallel(n_jobs=2)]: Done   5 out of   5 | elapsed:   32.3s finished
+[Parallel(n_jobs=2)]: Done   5 out of   5 | elapsed:   32.1s finished

@@ -448,7 +448,7 @@

Plotting the resultsplot fmri data example
  • plot fmri data example
    • -
    /opt/hostedtoolcache/Python/3.12.8/x64/lib/python3.12/site-packages/nilearn/plotting/displays/_slicers.py:313: UserWarning: empty mask
+
    /opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/nilearn/plotting/displays/_slicers.py:313: UserWarning: empty mask
   ims = self._map_show(img, type="imshow", threshold=threshold, **kwargs)
 
    
 
    
@@ -470,8 +470,8 @@ 
    Analysis of the results
    show()
    -

    Total running time of the script: (1 minutes 22.801 seconds)

    -

    Estimated memory usage: 3279 MB

    +

    Total running time of the script: (1 minutes 22.636 seconds)

    +

    Estimated memory usage: 3316 MB