[INFO] fetching crate sklears-mixture 0.1.0-alpha.1... [INFO] checking sklears-mixture-0.1.0-alpha.1 against master#e22dab387f6b4f6a87dfc54ac2f6013dddb41e68 for pr-149195 [INFO] extracting crate sklears-mixture 0.1.0-alpha.1 into /workspace/builds/worker-0-tc1/source [INFO] started tweaking crates.io crate sklears-mixture 0.1.0-alpha.1 [INFO] finished tweaking crates.io crate sklears-mixture 0.1.0-alpha.1 [INFO] tweaked toml for crates.io crate sklears-mixture 0.1.0-alpha.1 written to /workspace/builds/worker-0-tc1/source/Cargo.toml [INFO] validating manifest of crates.io crate sklears-mixture 0.1.0-alpha.1 on toolchain e22dab387f6b4f6a87dfc54ac2f6013dddb41e68 [INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }` [INFO] crate crates.io crate sklears-mixture 0.1.0-alpha.1 already has a lockfile, it will not be regenerated [INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }` [INFO] [stderr] Updating crates.io index [INFO] [stderr] Downloading crates ... [INFO] [stderr] Downloaded qhull v0.4.0 [INFO] [stderr] Downloaded friedrich v0.5.0 [INFO] [stderr] Downloaded argmin-math v0.5.1 [INFO] [stderr] Downloaded sprs v0.11.3 [INFO] [stderr] Downloaded argmin v0.11.0 [INFO] [stderr] Downloaded qhull-sys v0.4.0 [INFO] [stderr] Downloaded scirs2-sparse v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-optimize v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-cluster v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-spatial v0.1.0-rc.1 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-0-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-0-tc1/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:94a0c148923f5b2b52a63ef0eeb1882ad339ab61bce784c8077cbe41c61feb6c" "/opt/rustwide/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }` [INFO] [stdout] c958c8714b19db19c276592cb3e44763d215ca7dd4d75cb7b709f949b4b17e51 [INFO] running `Command { std: "docker" "start" "-a" "c958c8714b19db19c276592cb3e44763d215ca7dd4d75cb7b709f949b4b17e51", kill_on_drop: false }` [INFO] running `Command { std: "docker" "inspect" "c958c8714b19db19c276592cb3e44763d215ca7dd4d75cb7b709f949b4b17e51", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "c958c8714b19db19c276592cb3e44763d215ca7dd4d75cb7b709f949b4b17e51", kill_on_drop: false }` [INFO] [stdout] c958c8714b19db19c276592cb3e44763d215ca7dd4d75cb7b709f949b4b17e51 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-0-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-0-tc1/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=--cap-lints=forbid" "-e" "RUSTDOCFLAGS=--cap-lints=forbid" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:94a0c148923f5b2b52a63ef0eeb1882ad339ab61bce784c8077cbe41c61feb6c" "/opt/rustwide/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "check" "--frozen" "--all" "--all-targets" "--message-format=json", kill_on_drop: false }` [INFO] [stdout] 93bcb88f8c9a594064244275ea43bf86881f57f22a53d4467ad012fc81967f3b [INFO] running `Command { std: "docker" "start" "-a" "93bcb88f8c9a594064244275ea43bf86881f57f22a53d4467ad012fc81967f3b", kill_on_drop: false }` [INFO] [stderr] Compiling proc-macro2 v1.0.101 [INFO] [stderr] Compiling quote v1.0.41 [INFO] [stderr] Compiling matrixmultiply v0.3.10 [INFO] [stderr] Checking bytemuck v1.23.2 [INFO] [stderr] Checking getrandom v0.2.16 [INFO] [stderr] Checking num-integer v0.1.46 [INFO] [stderr] Checking approx v0.5.1 [INFO] [stderr] Compiling cc v1.2.39 [INFO] [stderr] Checking rand_chacha v0.9.0 [INFO] [stderr] Checking lapack-sys v0.14.0 [INFO] [stderr] Checking rayon v1.11.0 [INFO] [stderr] Compiling scirs2-core v0.1.0-rc.1 [INFO] [stderr] Compiling clang-sys v1.8.1 [INFO] [stderr] Checking crossbeam v0.8.4 [INFO] [stderr] Checking num_cpus v1.17.0 [INFO] [stderr] Checking digest v0.10.7 [INFO] [stderr] Compiling bitflags v2.9.4 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[stderr] Checking qhull v0.4.0 [INFO] [stderr] Checking statrs v0.18.0 [INFO] [stderr] Checking friedrich v0.5.0 [INFO] [stderr] Checking scirs2-linalg v0.1.0-rc.1 [INFO] [stderr] Checking scirs2-sparse v0.1.0-rc.1 [INFO] [stderr] Checking scirs2-spatial v0.1.0-rc.1 [INFO] [stderr] Checking scirs2-stats v0.1.0-rc.1 [INFO] [stderr] Checking scirs2-optimize v0.1.0-rc.1 [INFO] [stderr] Checking numrs2 v0.1.0-beta.3 [INFO] [stderr] Checking sklears-core v0.1.0-alpha.1 [INFO] [stderr] Checking sklears-utils v0.1.0-alpha.1 [INFO] [stderr] Checking sklears-mixture v0.1.0-alpha.1 (/opt/rustwide/workdir) [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/stochastic_variational.rs:629:9 [INFO] [stdout] | [INFO] [stdout] 629 | /// OptimizerState [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 630 | / OptimizerState { [INFO] [stdout] 631 | | m_pi: Array1::zeros(self.n_components), [INFO] [stdout] 632 | | m_mu_mean: Array2::zeros((self.n_components, n_features)), [INFO] [stdout] 633 | | m_mu_precision: Array2::zeros((self.n_components, n_features)), [INFO] [stdout] ... | [INFO] [stdout] 641 | | t: 0, [INFO] [stdout] 642 | | } [INFO] [stdout] | |_________- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:50:9 [INFO] [stdout] | [INFO] [stdout] 50 | /// HiddenMarkovModel [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 51 | HiddenMarkovModel [INFO] [stdout] | ----------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:94:9 [INFO] [stdout] | [INFO] [stdout] 94 | /// RegimeSwitchingModel [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 95 | RegimeSwitchingModel [INFO] [stdout] | -------------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:121:9 [INFO] [stdout] | [INFO] [stdout] 121 | /// SwitchingStateSpaceModel [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 122 | SwitchingStateSpaceModel [INFO] [stdout] | ------------------------ rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:144:9 [INFO] [stdout] | [INFO] [stdout] 144 | /// TemporalGaussianMixture [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 145 | TemporalGaussianMixture [INFO] [stdout] | ----------------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:178:9 [INFO] [stdout] | [INFO] [stdout] 178 | /// DynamicMixture [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 179 | DynamicMixture [INFO] [stdout] | -------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/stochastic_variational.rs:629:9 [INFO] [stdout] | [INFO] [stdout] 629 | /// OptimizerState [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 630 | / OptimizerState { [INFO] [stdout] 631 | | m_pi: Array1::zeros(self.n_components), [INFO] [stdout] 632 | | m_mu_mean: Array2::zeros((self.n_components, n_features)), [INFO] [stdout] 633 | | m_mu_precision: Array2::zeros((self.n_components, n_features)), [INFO] [stdout] ... | [INFO] [stdout] 641 | | t: 0, [INFO] [stdout] 642 | | } [INFO] [stdout] | |_________- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] = note: `#[warn(unused_doc_comments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:50:9 [INFO] [stdout] | [INFO] [stdout] 50 | /// HiddenMarkovModel [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 51 | HiddenMarkovModel [INFO] [stdout] | ----------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:94:9 [INFO] [stdout] | [INFO] [stdout] 94 | /// RegimeSwitchingModel [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 95 | RegimeSwitchingModel [INFO] [stdout] | -------------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:121:9 [INFO] [stdout] | [INFO] [stdout] 121 | /// SwitchingStateSpaceModel [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 122 | SwitchingStateSpaceModel [INFO] [stdout] | ------------------------ rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:144:9 [INFO] [stdout] | [INFO] [stdout] 144 | /// TemporalGaussianMixture [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 145 | TemporalGaussianMixture [INFO] [stdout] | ----------------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused doc comment [INFO] [stdout] --> src/time_series.rs:178:9 [INFO] [stdout] | [INFO] [stdout] 178 | /// DynamicMixture [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] 179 | DynamicMixture [INFO] [stdout] | -------------- rustdoc does not generate documentation for expressions [INFO] [stdout] | [INFO] [stdout] = help: use `//` for a plain comment [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Distribution` [INFO] [stdout] --> src/prior_sensitivity.rs:10:39 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Distribution, RandNormal, Rng, SeedableRng}; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/advi.rs:437:25 [INFO] [stdout] | [INFO] [stdout] 437 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/advi.rs:506:14 [INFO] [stdout] | [INFO] [stdout] 506 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `f0` [INFO] [stdout] --> src/advi.rs:962:13 [INFO] [stdout] | [INFO] [stdout] 962 | let f0 = self.evaluate_objective(X, params, rng)?; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_f0` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/advi.rs:1044:9 [INFO] [stdout] | [INFO] [stdout] 1044 | rng: &mut scirs2_core::random::rngs::StdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/advi.rs:1181:9 [INFO] [stdout] | [INFO] [stdout] 1181 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean_precision` [INFO] [stdout] --> src/advi.rs:1215:9 [INFO] [stdout] | [INFO] [stdout] 1215 | mean_precision: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/advi.rs:1221:25 [INFO] [stdout] | [INFO] [stdout] 1221 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/advi.rs:1597:9 [INFO] [stdout] | [INFO] [stdout] 1597 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/common.rs:43:5 [INFO] [stdout] | [INFO] [stdout] 43 | cov: &ArrayView2, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/empirical_bayes.rs:310:25 [INFO] [stdout] | [INFO] [stdout] 310 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `weights` [INFO] [stdout] --> src/empirical_bayes.rs:349:18 [INFO] [stdout] | [INFO] [stdout] 349 | let (weights, means, covariances, variational_params, marginal_likelihood) = [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `means` [INFO] [stdout] --> src/empirical_bayes.rs:349:27 [INFO] [stdout] | [INFO] [stdout] 349 | let (weights, means, covariances, variational_params, marginal_likelihood) = [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_means` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `covariances` [INFO] [stdout] --> src/empirical_bayes.rs:349:34 [INFO] [stdout] | [INFO] [stdout] 349 | let (weights, means, covariances, variational_params, marginal_likelihood) = [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/empirical_bayes.rs:477:25 [INFO] [stdout] | [INFO] [stdout] 477 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `lambda_nu` [INFO] [stdout] --> src/empirical_bayes.rs:807:9 [INFO] [stdout] | [INFO] [stdout] 807 | lambda_nu: &Array1, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_nu` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `lambda_w` [INFO] [stdout] --> src/empirical_bayes.rs:808:9 [INFO] [stdout] | [INFO] [stdout] 808 | lambda_w: &Vec>, [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/empirical_bayes.rs:841:14 [INFO] [stdout] | [INFO] [stdout] 841 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `total_responsibility` [INFO] [stdout] --> src/empirical_bayes.rs:844:13 [INFO] [stdout] | [INFO] [stdout] 844 | let total_responsibility: f64 = variational_params.pi_alpha.sum() [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_total_responsibility` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_params` [INFO] [stdout] --> src/empirical_bayes.rs:930:9 [INFO] [stdout] | [INFO] [stdout] 930 | variational_params: &VariationalParameters, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/empirical_bayes.rs:934:14 [INFO] [stdout] | [INFO] [stdout] 934 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_params` [INFO] [stdout] --> src/empirical_bayes.rs:1061:9 [INFO] [stdout] | [INFO] [stdout] 1061 | variational_params: &VariationalParameters, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/exponential_family.rs:189:14 [INFO] [stdout] | [INFO] [stdout] 189 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/exponential_family.rs:189:25 [INFO] [stdout] | [INFO] [stdout] 189 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/exponential_family.rs:555:28 [INFO] [stdout] | [INFO] [stdout] 555 | fn n_parameters(&self, n_features: usize) -> usize { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gaussian.rs:276:14 [INFO] [stdout] | [INFO] [stdout] 276 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/gaussian.rs:276:25 [INFO] [stdout] | [INFO] [stdout] 276 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k` [INFO] [stdout] --> src/gaussian.rs:445:13 [INFO] [stdout] | [INFO] [stdout] 445 | for k in 0..self.n_components { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_k` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gaussian.rs:464:14 [INFO] [stdout] | [INFO] [stdout] 464 | let (n_samples, _) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_z` [INFO] [stdout] --> src/mean_field_variational.rs:245:18 [INFO] [stdout] | [INFO] [stdout] 245 | let (new_q_z, grad_z) = self.update_q_z( [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_z` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_pi_alpha` [INFO] [stdout] --> src/mean_field_variational.rs:267:18 [INFO] [stdout] | [INFO] [stdout] 267 | let (new_q_pi_alpha, grad_pi) = self.update_q_pi(&q_z)?; [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_pi_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_mu_mean` [INFO] [stdout] --> src/mean_field_variational.rs:275:18 [INFO] [stdout] | [INFO] [stdout] 275 | let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) = [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_mu_precision` [INFO] [stdout] --> src/mean_field_variational.rs:275:33 [INFO] [stdout] | [INFO] [stdout] 275 | let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) = [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/mean_field_variational.rs:476:13 [INFO] [stdout] | [INFO] [stdout] 476 | let n_samples = q_z.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `q_lambda_w` [INFO] [stdout] --> src/mean_field_variational.rs:495:9 [INFO] [stdout] | [INFO] [stdout] 495 | q_lambda_w: &Vec>, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_q_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `means_map` [INFO] [stdout] --> src/multi_modal.rs:401:27 [INFO] [stdout] | [INFO] [stdout] 401 | let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?; [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_means_map` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `covariances_map` [INFO] [stdout] --> src/multi_modal.rs:401:38 [INFO] [stdout] | [INFO] [stdout] 401 | let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances_map` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_modal.rs:711:13 [INFO] [stdout] | [INFO] [stdout] 711 | let n_samples = X.values().next().unwrap().nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/multi_modal.rs:1039:9 [INFO] [stdout] | [INFO] [stdout] 1039 | X: &HashMap>, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/nonparametric.rs:1549:25 [INFO] [stdout] | [INFO] [stdout] 1549 | pub fn score(&self, X: &ArrayView2<'_, Float>) -> SklResult { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Distribution` [INFO] [stdout] --> src/prior_sensitivity.rs:10:39 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::{thread_rng, Distribution, RandNormal, Rng, SeedableRng}; [INFO] [stdout] | ^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/nuts.rs:354:9 [INFO] [stdout] | [INFO] [stdout] 354 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/nuts.rs:356:9 [INFO] [stdout] | [INFO] [stdout] 356 | n_features: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `subtree` [INFO] [stdout] --> src/nuts.rs:591:51 [INFO] [stdout] | [INFO] [stdout] 591 | fn check_uturn(&self, tree_state: &TreeState, subtree: &TreeState) -> bool { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_subtree` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `position` [INFO] [stdout] --> src/nuts.rs:670:9 [INFO] [stdout] | [INFO] [stdout] 670 | position: &Array1, [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_position` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/advi.rs:437:25 [INFO] [stdout] | [INFO] [stdout] 437 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/advi.rs:506:14 [INFO] [stdout] | [INFO] [stdout] 506 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `f0` [INFO] [stdout] --> src/advi.rs:962:13 [INFO] [stdout] | [INFO] [stdout] 962 | let f0 = self.evaluate_objective(X, params, rng)?; [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_f0` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/advi.rs:1044:9 [INFO] [stdout] | [INFO] [stdout] 1044 | rng: &mut scirs2_core::random::rngs::StdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/advi.rs:1181:9 [INFO] [stdout] | [INFO] [stdout] 1181 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean_precision` [INFO] [stdout] --> src/advi.rs:1215:9 [INFO] [stdout] | [INFO] [stdout] 1215 | mean_precision: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/advi.rs:1221:25 [INFO] [stdout] | [INFO] [stdout] 1221 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/prior_elicitation.rs:433:9 [INFO] [stdout] | [INFO] [stdout] 433 | rng: &mut scirs2_core::random::rngs::StdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/prior_elicitation.rs:523:9 [INFO] [stdout] | [INFO] [stdout] 523 | X: &ArrayView2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/prior_elicitation.rs:644:9 [INFO] [stdout] | [INFO] [stdout] 644 | rng: &mut scirs2_core::random::rngs::StdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/prior_elicitation.rs:701:9 [INFO] [stdout] | [INFO] [stdout] 701 | X: &ArrayView2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/advi.rs:1597:9 [INFO] [stdout] | [INFO] [stdout] 1597 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `prior_spec` [INFO] [stdout] --> src/prior_elicitation.rs:783:9 [INFO] [stdout] | [INFO] [stdout] 783 | prior_spec: &PriorSpecification, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_prior_spec` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data_characteristics` [INFO] [stdout] --> src/prior_elicitation.rs:1016:9 [INFO] [stdout] | [INFO] [stdout] 1016 | data_characteristics: &DataCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data_characteristics` [INFO] [stdout] --> src/prior_elicitation.rs:1032:9 [INFO] [stdout] | [INFO] [stdout] 1032 | data_characteristics: &DataCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/prior_elicitation.rs:1247:9 [INFO] [stdout] | [INFO] [stdout] 1247 | X: &ArrayView2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cov` [INFO] [stdout] --> src/common.rs:43:5 [INFO] [stdout] | [INFO] [stdout] 43 | cov: &ArrayView2, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_arrays` [INFO] [stdout] --> src/prior_sensitivity.rs:624:13 [INFO] [stdout] | [INFO] [stdout] 624 | let n_arrays = arrays.len(); [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_arrays` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/empirical_bayes.rs:310:25 [INFO] [stdout] | [INFO] [stdout] 310 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `weights` [INFO] [stdout] --> src/empirical_bayes.rs:349:18 [INFO] [stdout] | [INFO] [stdout] 349 | let (weights, means, covariances, variational_params, marginal_likelihood) = [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `means` [INFO] [stdout] --> src/empirical_bayes.rs:349:27 [INFO] [stdout] | [INFO] [stdout] 349 | let (weights, means, covariances, variational_params, marginal_likelihood) = [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_means` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `covariances` [INFO] [stdout] --> src/empirical_bayes.rs:349:34 [INFO] [stdout] | [INFO] [stdout] 349 | let (weights, means, covariances, variational_params, marginal_likelihood) = [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/empirical_bayes.rs:477:25 [INFO] [stdout] | [INFO] [stdout] 477 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `lambda_nu` [INFO] [stdout] --> src/empirical_bayes.rs:807:9 [INFO] [stdout] | [INFO] [stdout] 807 | lambda_nu: &Array1, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_nu` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `lambda_w` [INFO] [stdout] --> src/empirical_bayes.rs:808:9 [INFO] [stdout] | [INFO] [stdout] 808 | lambda_w: &Vec>, [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/empirical_bayes.rs:841:14 [INFO] [stdout] | [INFO] [stdout] 841 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `total_responsibility` [INFO] [stdout] --> src/empirical_bayes.rs:844:13 [INFO] [stdout] | [INFO] [stdout] 844 | let total_responsibility: f64 = variational_params.pi_alpha.sum() [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_total_responsibility` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_params` [INFO] [stdout] --> src/empirical_bayes.rs:930:9 [INFO] [stdout] | [INFO] [stdout] 930 | variational_params: &VariationalParameters, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/empirical_bayes.rs:934:14 [INFO] [stdout] | [INFO] [stdout] 934 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `variational_params` [INFO] [stdout] --> src/empirical_bayes.rs:1061:9 [INFO] [stdout] | [INFO] [stdout] 1061 | variational_params: &VariationalParameters, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_variational_params` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:144:25 [INFO] [stdout] | [INFO] [stdout] 144 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `trained_state` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:168:13 [INFO] [stdout] | [INFO] [stdout] 168 | let trained_state = GeographicMixtureTrained { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/exponential_family.rs:189:14 [INFO] [stdout] | [INFO] [stdout] 189 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/exponential_family.rs:189:25 [INFO] [stdout] | [INFO] [stdout] 189 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:253:14 [INFO] [stdout] | [INFO] [stdout] 253 | let (n_samples, n_features) = features.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:267:13 [INFO] [stdout] | [INFO] [stdout] 267 | for iteration in 0..self.max_iter { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/exponential_family.rs:555:28 [INFO] [stdout] | [INFO] [stdout] 555 | fn n_parameters(&self, n_features: usize) -> usize { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `weights` [INFO] [stdout] --> src/spatial/markov_random_field.rs:152:13 [INFO] [stdout] | [INFO] [stdout] 152 | let weights = Array1::from_elem(self.n_components, 1.0 / self.n_components as f64); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `means` [INFO] [stdout] --> src/spatial/markov_random_field.rs:155:13 [INFO] [stdout] | [INFO] [stdout] 155 | let means = self.initialize_means(X)?; [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_means` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `interaction_parameters` [INFO] [stdout] --> src/spatial/markov_random_field.rs:166:13 [INFO] [stdout] | [INFO] [stdout] 166 | let interaction_parameters: Array2 = [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_interaction_parameters` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `neighborhood_graph` [INFO] [stdout] --> src/spatial/markov_random_field.rs:170:13 [INFO] [stdout] | [INFO] [stdout] 170 | let neighborhood_graph = self.build_neighborhood_graph(X)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_neighborhood_graph` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gaussian.rs:276:14 [INFO] [stdout] | [INFO] [stdout] 276 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/gaussian.rs:276:25 [INFO] [stdout] | [INFO] [stdout] 276 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k` [INFO] [stdout] --> src/gaussian.rs:445:13 [INFO] [stdout] | [INFO] [stdout] 445 | for k in 0..self.n_components { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_k` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/gaussian.rs:464:14 [INFO] [stdout] | [INFO] [stdout] 464 | let (n_samples, _) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `w_sum` [INFO] [stdout] --> src/spatial/spatial_statistics.rs:333:49 [INFO] [stdout] | [INFO] [stdout] 333 | fn compute_morans_i_variance(&self, n: f64, w_sum: f64) -> SklResult { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `w_sum` [INFO] [stdout] --> src/spatial/spatial_statistics.rs:340:49 [INFO] [stdout] | [INFO] [stdout] 340 | fn compute_gearys_c_variance(&self, n: f64, w_sum: f64) -> SklResult { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_z` [INFO] [stdout] --> src/mean_field_variational.rs:245:18 [INFO] [stdout] | [INFO] [stdout] 245 | let (new_q_z, grad_z) = self.update_q_z( [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_z` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_pi_alpha` [INFO] [stdout] --> src/mean_field_variational.rs:267:18 [INFO] [stdout] | [INFO] [stdout] 267 | let (new_q_pi_alpha, grad_pi) = self.update_q_pi(&q_z)?; [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_pi_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_mu_mean` [INFO] [stdout] --> src/mean_field_variational.rs:275:18 [INFO] [stdout] | [INFO] [stdout] 275 | let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) = [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_mean` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `new_q_mu_precision` [INFO] [stdout] --> src/mean_field_variational.rs:275:33 [INFO] [stdout] | [INFO] [stdout] 275 | let (new_q_mu_mean, new_q_mu_precision, grad_mu_mean, grad_mu_precision) = [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_new_q_mu_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/mean_field_variational.rs:476:13 [INFO] [stdout] | [INFO] [stdout] 476 | let n_samples = q_z.nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `q_lambda_w` [INFO] [stdout] --> src/mean_field_variational.rs:495:9 [INFO] [stdout] | [INFO] [stdout] 495 | q_lambda_w: &Vec>, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_q_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `trained_state` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:197:13 [INFO] [stdout] | [INFO] [stdout] 197 | let trained_state = SpatiallyConstrainedGMMTrained { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `coords` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:379:9 [INFO] [stdout] | [INFO] [stdout] 379 | coords: &Array2, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_coords` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:385:14 [INFO] [stdout] | [INFO] [stdout] 385 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:385:25 [INFO] [stdout] | [INFO] [stdout] 385 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:386:13 [INFO] [stdout] | [INFO] [stdout] 386 | let n_components = self.config.n_components; [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:389:13 [INFO] [stdout] | [INFO] [stdout] 389 | for iteration in 0..self.config.max_iter { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `means_map` [INFO] [stdout] --> src/multi_modal.rs:401:27 [INFO] [stdout] | [INFO] [stdout] 401 | let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?; [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_means_map` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `covariances_map` [INFO] [stdout] --> src/multi_modal.rs:401:38 [INFO] [stdout] | [INFO] [stdout] 401 | let (mut weights, means_map, covariances_map) = self.initialize_parameters(X)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_covariances_map` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_pi_alpha` [INFO] [stdout] --> src/stochastic_variational.rs:718:9 [INFO] [stdout] | [INFO] [stdout] 718 | global_pi_alpha: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:722:9 [INFO] [stdout] | [INFO] [stdout] 722 | global_lambda_w: &Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `epoch` [INFO] [stdout] --> src/stochastic_variational.rs:809:9 [INFO] [stdout] | [INFO] [stdout] 809 | epoch: usize, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_epoch` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:896:9 [INFO] [stdout] | [INFO] [stdout] 896 | global_lambda_w: &mut Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:942:9 [INFO] [stdout] | [INFO] [stdout] 942 | global_lambda_w: &mut Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/multi_modal.rs:711:13 [INFO] [stdout] | [INFO] [stdout] 711 | let n_samples = X.values().next().unwrap().nrows(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:990:9 [INFO] [stdout] | [INFO] [stdout] 990 | global_lambda_w: &mut Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_pi_alpha` [INFO] [stdout] --> src/stochastic_variational.rs:1062:9 [INFO] [stdout] | [INFO] [stdout] 1062 | global_pi_alpha: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `decay_rate` [INFO] [stdout] --> src/stochastic_variational.rs:1204:39 [INFO] [stdout] | [INFO] [stdout] 1204 | fn decay_learning_rate(&mut self, decay_rate: f64) { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_decay_rate` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/multi_modal.rs:1039:9 [INFO] [stdout] | [INFO] [stdout] 1039 | X: &HashMap>, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/stochastic_variational.rs:1380:35 [INFO] [stdout] | [INFO] [stdout] 1380 | pub fn partial_fit(&mut self, X: &ArrayView2<'_, Float>) -> SklResult<()> { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:252:25 [INFO] [stdout] | [INFO] [stdout] 252 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/structured_variational.rs:324:14 [INFO] [stdout] | [INFO] [stdout] 324 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/structured_variational.rs:525:13 [INFO] [stdout] | [INFO] [stdout] 525 | for iter in 0..self.max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/structured_variational.rs:659:14 [INFO] [stdout] | [INFO] [stdout] 659 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:659:25 [INFO] [stdout] | [INFO] [stdout] 659 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/structured_variational.rs:707:14 [INFO] [stdout] | [INFO] [stdout] 707 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:707:25 [INFO] [stdout] | [INFO] [stdout] 707 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:788:9 [INFO] [stdout] | [INFO] [stdout] 788 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `structured_cov` [INFO] [stdout] --> src/structured_variational.rs:791:9 [INFO] [stdout] | [INFO] [stdout] 791 | structured_cov: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_structured_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:854:9 [INFO] [stdout] | [INFO] [stdout] 854 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:925:9 [INFO] [stdout] | [INFO] [stdout] 925 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:997:9 [INFO] [stdout] | [INFO] [stdout] 997 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/structured_variational.rs:1095:9 [INFO] [stdout] | [INFO] [stdout] 1095 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean_precision` [INFO] [stdout] --> src/structured_variational.rs:1137:9 [INFO] [stdout] | [INFO] [stdout] 1137 | mean_precision: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:1144:25 [INFO] [stdout] | [INFO] [stdout] 1144 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/structured_variational.rs:1450:9 [INFO] [stdout] | [INFO] [stdout] 1450 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/nonparametric.rs:1549:25 [INFO] [stdout] | [INFO] [stdout] 1549 | pub fn score(&self, X: &ArrayView2<'_, Float>) -> SklResult { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/nuts.rs:354:9 [INFO] [stdout] | [INFO] [stdout] 354 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/nuts.rs:356:9 [INFO] [stdout] | [INFO] [stdout] 356 | n_features: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `subtree` [INFO] [stdout] --> src/nuts.rs:591:51 [INFO] [stdout] | [INFO] [stdout] 591 | fn check_uturn(&self, tree_state: &TreeState, subtree: &TreeState) -> bool { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_subtree` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `position` [INFO] [stdout] --> src/nuts.rs:670:9 [INFO] [stdout] | [INFO] [stdout] 670 | position: &Array1, [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_position` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/variational.rs:182:25 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/variational.rs:303:14 [INFO] [stdout] | [INFO] [stdout] 303 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `degrees_of_freedom` [INFO] [stdout] --> src/variational.rs:522:9 [INFO] [stdout] | [INFO] [stdout] 522 | degrees_of_freedom: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k` [INFO] [stdout] --> src/variational.rs:580:13 [INFO] [stdout] | [INFO] [stdout] 580 | for k in 0..self.n_components { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_k` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean_precision` [INFO] [stdout] --> src/variational.rs:603:9 [INFO] [stdout] | [INFO] [stdout] 603 | mean_precision: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `degrees_of_freedom` [INFO] [stdout] --> src/variational.rs:605:9 [INFO] [stdout] | [INFO] [stdout] 605 | degrees_of_freedom: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/prior_elicitation.rs:433:9 [INFO] [stdout] | [INFO] [stdout] 433 | rng: &mut scirs2_core::random::rngs::StdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/prior_elicitation.rs:523:9 [INFO] [stdout] | [INFO] [stdout] 523 | X: &ArrayView2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/prior_elicitation.rs:644:9 [INFO] [stdout] | [INFO] [stdout] 644 | rng: &mut scirs2_core::random::rngs::StdRng, [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/prior_elicitation.rs:701:9 [INFO] [stdout] | [INFO] [stdout] 701 | X: &ArrayView2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `prior_spec` [INFO] [stdout] --> src/prior_elicitation.rs:783:9 [INFO] [stdout] | [INFO] [stdout] 783 | prior_spec: &PriorSpecification, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_prior_spec` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data_characteristics` [INFO] [stdout] --> src/prior_elicitation.rs:1016:9 [INFO] [stdout] | [INFO] [stdout] 1016 | data_characteristics: &DataCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `data_characteristics` [INFO] [stdout] --> src/prior_elicitation.rs:1032:9 [INFO] [stdout] | [INFO] [stdout] 1032 | data_characteristics: &DataCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/prior_elicitation.rs:1247:9 [INFO] [stdout] | [INFO] [stdout] 1247 | X: &ArrayView2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_arrays` [INFO] [stdout] --> src/prior_sensitivity.rs:624:13 [INFO] [stdout] | [INFO] [stdout] 624 | let n_arrays = arrays.len(); [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_arrays` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:144:25 [INFO] [stdout] | [INFO] [stdout] 144 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `trained_state` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:168:13 [INFO] [stdout] | [INFO] [stdout] 168 | let trained_state = GeographicMixtureTrained { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:253:14 [INFO] [stdout] | [INFO] [stdout] 253 | let (n_samples, n_features) = features.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/spatial/geographic_mixture.rs:267:13 [INFO] [stdout] | [INFO] [stdout] 267 | for iteration in 0..self.max_iter { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `weights` [INFO] [stdout] --> src/spatial/markov_random_field.rs:152:13 [INFO] [stdout] | [INFO] [stdout] 152 | let weights = Array1::from_elem(self.n_components, 1.0 / self.n_components as f64); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `means` [INFO] [stdout] --> src/spatial/markov_random_field.rs:155:13 [INFO] [stdout] | [INFO] [stdout] 155 | let means = self.initialize_means(X)?; [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_means` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `interaction_parameters` [INFO] [stdout] --> src/spatial/markov_random_field.rs:166:13 [INFO] [stdout] | [INFO] [stdout] 166 | let interaction_parameters: Array2 = [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_interaction_parameters` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `neighborhood_graph` [INFO] [stdout] --> src/spatial/markov_random_field.rs:170:13 [INFO] [stdout] | [INFO] [stdout] 170 | let neighborhood_graph = self.build_neighborhood_graph(X)?; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_neighborhood_graph` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `w_sum` [INFO] [stdout] --> src/spatial/spatial_statistics.rs:333:49 [INFO] [stdout] | [INFO] [stdout] 333 | fn compute_morans_i_variance(&self, n: f64, w_sum: f64) -> SklResult { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `w_sum` [INFO] [stdout] --> src/spatial/spatial_statistics.rs:340:49 [INFO] [stdout] | [INFO] [stdout] 340 | fn compute_gearys_c_variance(&self, n: f64, w_sum: f64) -> SklResult { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_w_sum` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `trained_state` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:197:13 [INFO] [stdout] | [INFO] [stdout] 197 | let trained_state = SpatiallyConstrainedGMMTrained { [INFO] [stdout] | ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_trained_state` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `coords` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:379:9 [INFO] [stdout] | [INFO] [stdout] 379 | coords: &Array2, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_coords` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:385:14 [INFO] [stdout] | [INFO] [stdout] 385 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:385:25 [INFO] [stdout] | [INFO] [stdout] 385 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_components` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:386:13 [INFO] [stdout] | [INFO] [stdout] 386 | let n_components = self.config.n_components; [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_components` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iteration` [INFO] [stdout] --> src/spatial/spatially_constrained_gmm.rs:389:13 [INFO] [stdout] | [INFO] [stdout] 389 | for iteration in 0..self.config.max_iter { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_iteration` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_pi_alpha` [INFO] [stdout] --> src/stochastic_variational.rs:718:9 [INFO] [stdout] | [INFO] [stdout] 718 | global_pi_alpha: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:722:9 [INFO] [stdout] | [INFO] [stdout] 722 | global_lambda_w: &Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `epoch` [INFO] [stdout] --> src/stochastic_variational.rs:809:9 [INFO] [stdout] | [INFO] [stdout] 809 | epoch: usize, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_epoch` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:896:9 [INFO] [stdout] | [INFO] [stdout] 896 | global_lambda_w: &mut Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:942:9 [INFO] [stdout] | [INFO] [stdout] 942 | global_lambda_w: &mut Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_lambda_w` [INFO] [stdout] --> src/stochastic_variational.rs:990:9 [INFO] [stdout] | [INFO] [stdout] 990 | global_lambda_w: &mut Vec>, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_lambda_w` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `global_pi_alpha` [INFO] [stdout] --> src/stochastic_variational.rs:1062:9 [INFO] [stdout] | [INFO] [stdout] 1062 | global_pi_alpha: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_global_pi_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `decay_rate` [INFO] [stdout] --> src/stochastic_variational.rs:1204:39 [INFO] [stdout] | [INFO] [stdout] 1204 | fn decay_learning_rate(&mut self, decay_rate: f64) { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_decay_rate` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/stochastic_variational.rs:1380:35 [INFO] [stdout] | [INFO] [stdout] 1380 | pub fn partial_fit(&mut self, X: &ArrayView2<'_, Float>) -> SklResult<()> { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:252:25 [INFO] [stdout] | [INFO] [stdout] 252 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/structured_variational.rs:324:14 [INFO] [stdout] | [INFO] [stdout] 324 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `iter` [INFO] [stdout] --> src/structured_variational.rs:525:13 [INFO] [stdout] | [INFO] [stdout] 525 | for iter in 0..self.max_iter { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_iter` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/structured_variational.rs:659:14 [INFO] [stdout] | [INFO] [stdout] 659 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:659:25 [INFO] [stdout] | [INFO] [stdout] 659 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/structured_variational.rs:707:14 [INFO] [stdout] | [INFO] [stdout] 707 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:707:25 [INFO] [stdout] | [INFO] [stdout] 707 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:788:9 [INFO] [stdout] | [INFO] [stdout] 788 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `structured_cov` [INFO] [stdout] --> src/structured_variational.rs:791:9 [INFO] [stdout] | [INFO] [stdout] 791 | structured_cov: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_structured_cov` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:854:9 [INFO] [stdout] | [INFO] [stdout] 854 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:925:9 [INFO] [stdout] | [INFO] [stdout] 925 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `precision_values` [INFO] [stdout] --> src/structured_variational.rs:997:9 [INFO] [stdout] | [INFO] [stdout] 997 | precision_values: &mut Array3, [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_precision_values` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/structured_variational.rs:1095:9 [INFO] [stdout] | [INFO] [stdout] 1095 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean_precision` [INFO] [stdout] --> src/structured_variational.rs:1137:9 [INFO] [stdout] | [INFO] [stdout] 1137 | mean_precision: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/structured_variational.rs:1144:25 [INFO] [stdout] | [INFO] [stdout] 1144 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scale_matrix` [INFO] [stdout] --> src/structured_variational.rs:1450:9 [INFO] [stdout] | [INFO] [stdout] 1450 | scale_matrix: &ArrayView2, [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scale_matrix` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_features` [INFO] [stdout] --> src/variational.rs:182:25 [INFO] [stdout] | [INFO] [stdout] 182 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/variational.rs:303:14 [INFO] [stdout] | [INFO] [stdout] 303 | let (n_samples, n_features) = X.dim(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `degrees_of_freedom` [INFO] [stdout] --> src/variational.rs:522:9 [INFO] [stdout] | [INFO] [stdout] 522 | degrees_of_freedom: f64, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `k` [INFO] [stdout] --> src/variational.rs:580:13 [INFO] [stdout] | [INFO] [stdout] 580 | for k in 0..self.n_components { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_k` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mean_precision` [INFO] [stdout] --> src/variational.rs:603:9 [INFO] [stdout] | [INFO] [stdout] 603 | mean_precision: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mean_precision` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `degrees_of_freedom` [INFO] [stdout] --> src/variational.rs:605:9 [INFO] [stdout] | [INFO] [stdout] 605 | degrees_of_freedom: &Array1, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_degrees_of_freedom` [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Finished `dev` profile [unoptimized + debuginfo] target(s) in 2m 07s [INFO] running `Command { std: "docker" "inspect" "93bcb88f8c9a594064244275ea43bf86881f57f22a53d4467ad012fc81967f3b", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "93bcb88f8c9a594064244275ea43bf86881f57f22a53d4467ad012fc81967f3b", kill_on_drop: false }` [INFO] [stdout] 93bcb88f8c9a594064244275ea43bf86881f57f22a53d4467ad012fc81967f3b