【代码贡献】QSVR: build the show_res test grid from each column's own min/max

pyqpanda-algorithm/pyqpanda_alg/QSVR/QSVR.py

@@ -134,8 +134,8 @@ def get_res(self):
     def show_res(self):
         svr = SVR(kernel=self.k_kernel, gamma=0.1)
         svr.fit(self.x, self.y)
-        x0_test = np.linspace(min(self.x[:, 0]), max(self.x[:, 1]), 30)
-        x1_test = np.linspace(min(self.x[:, 0]), max(self.x[:, 1]), 30)
+        x0_test = np.linspace(min(self.x[:, 0]), max(self.x[:, 0]), 30)
+        x1_test = np.linspace(min(self.x[:, 1]), max(self.x[:, 1]), 30)
         X0_test, X1_test = np.meshgrid(x0_test, x1_test)
         X_test = np.c_[X0_test.ravel(), X1_test.ravel()]
         y_pred = svr.predict(X_test).reshape(X0_test.shape)

test/QAlgBase/Test_class_qsvr_Quantum_SVR.py

@@ -2,10 +2,43 @@
 import numpy as np
 import os
 from pyqpanda_alg.QSVR import Quantum_SVR
+from pyqpanda_alg.QSVR import QSVR as qsvr_module
 import warnings
 import os
 
 
+class _RecordingSVR:
+    def __init__(self):
+        self.seen = []
+
+    def fit(self, X, y):
+        return self
+
+    def predict(self, X):
+        X = np.asarray(X)
+        self.seen.append(X)
+        return np.zeros(len(X))
+
+
+class _FakeAxes:
+    def __getattr__(self, name):
+        return lambda *args, **kwargs: None
+
+
+class _FakeFigure:
+    def add_subplot(self, *args, **kwargs):
+        return _FakeAxes()
+
+
+def _grid_points(monkeypatch, qsvr):
+    svr = _RecordingSVR()
+    monkeypatch.setattr(qsvr_module, "SVR", lambda **kwargs: svr)
+    monkeypatch.setattr(qsvr_module.plt, "figure", lambda *args, **kwargs: _FakeFigure())
+    monkeypatch.setattr(qsvr_module.plt, "show", lambda *args, **kwargs: None)
+    qsvr.show_res()
+    return svr.seen[0]
+
+
 class Test_class_qsvr_Quantum_SVR:
 
     def setup_method(self):
@@ -38,6 +71,31 @@ def test_interface11_show_res_basic(self):
         except Exception as e:
             pytest.fail(f"show_res()方法执行失败: {e}")
 
+    def test_show_res_grid_matches_column_ranges(self, monkeypatch):
+        t = np.random.randn(60)
+        X = np.column_stack([t + 0.05 * np.random.randn(60), 20 * t + np.random.randn(60)])
+        qsvr = Quantum_SVR(X, np.sin(t))
+
+        points = _grid_points(monkeypatch, qsvr)
+
+        assert points.shape == (900, 2)
+        for col in (0, 1):
+            axis = np.unique(points[:, col])
+            assert len(axis) == 30
+            expected = np.linspace(qsvr.x[:, col].min(), qsvr.x[:, col].max(), 30)
+            assert np.allclose(axis, expected)
+
+    def test_show_res_grid_axes_are_independent(self, monkeypatch):
+        x = np.column_stack([np.linspace(0, 2, 40), np.linspace(10, 30, 40)])
+        qsvr = Quantum_SVR(x, np.zeros(40))
+        # bypass the scaler/PCA so the two columns keep exact, unmistakable ranges
+        qsvr.x = x
+
+        points = _grid_points(monkeypatch, qsvr)
+
+        assert np.allclose([points[:, 0].min(), points[:, 0].max()], [0.0, 2.0])
+        assert np.allclose([points[:, 1].min(), points[:, 1].max()], [10.0, 30.0])
+
 
 if __name__ == "__main__":
     # 运行测试