fix: tighten sequence checks and streamline competing-risk helpers (#81)

Author: DiogoRibeiro7

.github/workflows/ci.yml

@@ -41,6 +41,20 @@ jobs:
       - name: Install dependencies
         run: poetry install --with dev --no-interaction --no-root
 
+      - name: Check runtime dependencies
+        run: |
+          poetry run python - <<'PY'
+          import importlib, sys
+          missing = [m for m in ("pandas",) if importlib.util.find_spec(m) is None]
+          if missing:
+              print("Missing dependencies:", ", ".join(missing))
+              sys.exit(1)
+          PY
+
+      - name: Verify version matches tag
+        if: startsWith(github.ref, 'refs/tags/')
+        run: python scripts/check_version_match.py
+
       - name: Run tests with coverage
         run: poetry run pytest --cov=gen_surv --cov-report=xml --cov-report=term
 

benchmarks/test_validation_benchmark.py

@@ -3,7 +3,7 @@
 
 pytest.importorskip("pytest_benchmark")
 
-from gen_surv._validation import ensure_positive_sequence
+from gen_surv.validation import ensure_positive_sequence
 
 
 def test_positive_sequence_benchmark(benchmark):

docs/source/api/index.md

@@ -14,85 +14,76 @@ or `pip install scikit-survival` to enable this functionality.
 
 ## Core Interface
 
-```{eval-rst}
-.. automodule:: gen_surv.interface
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.interface
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ## Model Generators
 
 ### Cox Proportional Hazards Model
-```{eval-rst}
-.. automodule:: gen_surv.cphm
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.cphm
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Accelerated Failure Time Models
-```{eval-rst}
-.. automodule:: gen_surv.aft
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.aft
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Continuous-Time Markov Models
-```{eval-rst}
-.. automodule:: gen_surv.cmm
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.cmm
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Time-Dependent Covariate Models
-```{eval-rst}
-.. automodule:: gen_surv.tdcm
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.tdcm
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Time-Homogeneous Markov Models
-```{eval-rst}
-.. automodule:: gen_surv.thmm
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.thmm
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ## Utility Functions
 
 ### Censoring Functions
-```{eval-rst}
-.. automodule:: gen_surv.censoring
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.censoring
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Bivariate Distributions
-```{eval-rst}
-.. automodule:: gen_surv.bivariate
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.bivariate
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Validation Functions
-```{eval-rst}
-.. automodule:: gen_surv.validate
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.validation
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
 
 ### Command Line Interface
-```{eval-rst}
-.. automodule:: gen_surv.cli
-   :members:
-   :undoc-members:
-   :show-inheritance:
-```
+::: gen_surv.cli
+    options:
+      members: true
+      undoc-members: true
+      show-inheritance: true
+

docs/source/modules.md

@@ -8,48 +8,59 @@ orphan: true
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.cmm
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.tdcm
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.thmm
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.interface
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.aft
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.bivariate
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.censoring
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
 ::: gen_surv.cli
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
 
-::: gen_surv.validate
+::: gen_surv.validation
     options:
       members: true
       undoc-members: true
+      show-inheritance: true
+

gen_surv/_covariates.py

@@ -1,13 +1,14 @@
 """Utilities for generating covariate matrices with validation."""
 
-from typing import Literal, cast
+from typing import Literal
 
 import numpy as np
+from numpy.random import Generator
 from numpy.typing import NDArray
 
-from ._validation import ParameterError, ensure_positive
+from .validation import ParameterError, ensure_positive
 
-_CovParams = dict[str, float | tuple[float, float]]
+_CovParams = dict[str, float]
 
 
 def set_covariate_params(
@@ -30,37 +31,45 @@ def set_covariate_params(
     )
 
 
+def _get_float(params: _CovParams, key: str, default: float) -> float:
+    val = params.get(key, default)
+    if not isinstance(val, (int, float)):
+        raise ParameterError(f"covariate_params['{key}']", val, "must be a number")
+    return float(val)
+
+
 def generate_covariates(
     n: int,
     n_covariates: int,
     covariate_dist: Literal["normal", "uniform", "binary"],
     covariate_params: _CovParams,
+    rng: Generator,
 ) -> NDArray[np.float64]:
     """Generate covariate matrix according to the specified distribution."""
     if covariate_dist == "normal":
-        std = cast(float, covariate_params.get("std", 1.0))
+        std = _get_float(covariate_params, "std", 1.0)
         ensure_positive(std, "covariate_params['std']")
-        mean = cast(float, covariate_params.get("mean", 0.0))
-        return np.random.normal(mean, std, size=(n, n_covariates))
+        mean = _get_float(covariate_params, "mean", 0.0)
+        return rng.normal(mean, std, size=(n, n_covariates))
     if covariate_dist == "uniform":
-        low = cast(float, covariate_params.get("low", 0.0))
-        high = cast(float, covariate_params.get("high", 1.0))
+        low = _get_float(covariate_params, "low", 0.0)
+        high = _get_float(covariate_params, "high", 1.0)
         if high <= low:
             raise ParameterError(
                 "covariate_params['high']",
                 high,
                 "must be greater than 'low'",
             )
-        return np.random.uniform(low, high, size=(n, n_covariates))
+        return rng.uniform(low, high, size=(n, n_covariates))
     if covariate_dist == "binary":
-        p = cast(float, covariate_params.get("p", 0.5))
+        p = _get_float(covariate_params, "p", 0.5)
         if not 0 <= p <= 1:
             raise ParameterError(
                 "covariate_params['p']",
                 p,
                 "must be between 0 and 1",
             )
-        return np.random.binomial(1, p, size=(n, n_covariates)).astype(float)
+        return rng.binomial(1, p, size=(n, n_covariates)).astype(float)
     raise ParameterError(
         "covariate_dist",
         covariate_dist,