Repository: tenajima/nullpom (language: python)

Issue:
Minimum feature implemented.



Discussion / hints:

Fix patch:
diff --git a/.gitignore b/.gitignore
index 461151f..fd84cb5 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,11 +1,6 @@
 ### https://raw.github.com/github/gitignore/4a8e0a151becd5ccbb83e4aca6e6c195f3d506fd/Global/VisualStudioCode.gitignore
 
 .vscode/*
-!.vscode/settings.json
-!.vscode/tasks.json
-!.vscode/launch.json
-!.vscode/extensions.json
-
 
 ### https://raw.github.com/github/gitignore/4a8e0a151becd5ccbb83e4aca6e6c195f3d506fd/Python.gitignore
 
@@ -134,7 +129,8 @@ dmypy.json
 .LSOverride
 
 # Icon must end with two \r
-Icon
+Icon
+
 
 # Thumbnails
 ._*
diff --git a/nullpom/__init__.py b/nullpom/__init__.py
index b794fd4..f12f99a 100644
--- a/nullpom/__init__.py
+++ b/nullpom/__init__.py
@@ -1,1 +1,1 @@
-__version__ = '0.1.0'
+from .main import run_null_importance
\ No newline at end of file
diff --git a/nullpom/main.py b/nullpom/main.py
new file mode 100644
index 0000000..7bfcebb
--- /dev/null
+++ b/nullpom/main.py
@@ -0,0 +1,67 @@
+import lightgbm as lgb
+import numpy as np
+import pandas as pd
+
+
+def run_null_importance(params, n_runs=100, *, X_train, X_valid, y_train, y_valid):
+    experiment = Experiment(
+        params,
+        n_runs=100,
+        X_train=X_train,
+        X_valid=X_valid,
+        y_train=y_train,
+        y_valid=y_valid,
+    )
+    return experiment.execute()
+
+
+class Result:
+    def __init__(self, actual_importance, actual_model, null_importance):
+        self.actual_importance = actual_importance
+        self.actual_model = actual_model
+        self.null_importance = null_importance
+
+
+class Experiment:
+    def __init__(self, params, n_runs=100, *, X_train, X_valid, y_train, y_valid):
+        self.params = params
+        self.n_runs = n_runs
+        self.X_train = X_train
+        self.X_valid = X_valid
+        self.y_train = y_train
+        self.y_valid = y_valid
+
+    def check_params(self):
+        if "early_stopping_rounds" not in self.params.keys():
+            self.params["early_stopping_rounds"] = 100
+
+    def get_feature_importance(self, *, shuffle=False):
+        if shuffle:
+            y_train = np.random.permutation(self.y_train)
+            y_valid = np.random.permutation(self.y_valid)
+            dtrain = lgb.Dataset(self.X_train, y_train)
+            dvalid = lgb.Dataset(self.X_valid, y_valid)
+        else:
+            dtrain = lgb.Dataset(self.X_train, self.y_train)
+            dvalid = lgb.Dataset(self.X_valid, self.y_valid)
+
+        model = lgb.train(self.params, dtrain, valid_sets=[dtrain, dvalid])
+
+        importance = pd.DataFrame()
+        importance["feature"] = model.feature_name()
+        importance["importance"] = model.feature_importance("gain")
+        importance = importance.sort_values("importance", ascending=False).reset_index()
+        return importance, model
+
+    def execute(self):
+        self.check_params()
+
+        actual_importance, actual_model = self.get_feature_importance()
+
+        null_importance = pd.DataFrame()
+
+        for _ in range(self.n_runs):
+            tmp_importance, _ = self.get_feature_importance(shuffle=True)
+            null_importance = pd.concat([null_importance, tmp_importance])
+
+        return Result(actual_importance, actual_model, null_importance)
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..a1d083b
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,614 @@
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+python-versions = "*"
+
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+optional = false
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+
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diff --git a/pyproject.toml b/pyproject.toml
index ccc8602..6638814 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,7 +5,11 @@ description = "test"
 authors = ["tenajima <tenajima@gmail.com>"]
 
 [tool.poetry.dependencies]
-python = "^3.7"
+python = "^3.7.1"
+scikit-learn = "^0.24.1"
+pandas = "^1.2.3"
+black = "^20.8b1"
+lightgbm = "^3.1.1"
 
 [tool.poetry.dev-dependencies]
 pytest = "^5.2"


Test patch:
diff --git a/tests/test_nullpom.py b/tests/test_nullpom.py
index 5988533..4a6a638 100644
--- a/tests/test_nullpom.py
+++ b/tests/test_nullpom.py
@@ -1,5 +1,45 @@
-from nullpom import __version__
+import pandas as pd
+from nullpom.main import Experiment, run_null_importance
+from sklearn.datasets import load_breast_cancer
+from sklearn.model_selection import train_test_split
 
+cancer = load_breast_cancer()
+X = pd.DataFrame(cancer.data, columns=cancer.feature_names)
+y = cancer.target
+X_train, X_valid, y_train, y_valid = train_test_split(
+    X, y, random_state=42, test_size=0.3
+)
 
-def test_version():
-    assert __version__ == '0.1.0'
+
+class TestExperiment:
+    def test_init(self):
+        _ = Experiment(
+            {"objective": "binary"},
+            X_train=X_train,
+            X_valid=X_valid,
+            y_train=y_train,
+            y_valid=y_valid,
+        )
+        assert True
+
+    def test_execute(self):
+        experiment = Experiment(
+            {"objective": "binary"},
+            X_train=X_train,
+            X_valid=X_valid,
+            y_train=y_train,
+            y_valid=y_valid,
+        )
+        experiment.execute()
+        assert True
+
+
+def test_run_null_importance():
+    run_null_importance(
+        {"objective": "binary"},
+        X_train=X_train,
+        X_valid=X_valid,
+        y_train=y_train,
+        y_valid=y_valid,
+    )
+    assert True