diff --git a/README.md b/README.md
index 16c0227..c022fb6 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1 @@
-1. 添加 A B C D 方法，对应不同的基
-2. 修改Levi部分和sk迭代部分，使用更通用的A B C D求解
-3. 添加正交基形式
-4. 加入多端口
-5. 引入QR，消除中间过程的残差求解，降低算法复杂度
-6. 使用最初始的表达式，获得无偏估计
\ No newline at end of file
+请将 examples.tar.gz解压到此处
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
index ec3563e..2ab07d1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "ovf"
-version = "0.1.5"
+version = "0.1.6"
 description = "A package for orthonormal basis and rational function fitting"
 authors = [
     {name = "M4yGem1ni", email = "M4yGem1ni@outlook.com"}
diff --git a/test/gvf_plot_poles.py b/test/gvf_plot_poles.py
index f934909..cdf33ec 100644
--- a/test/gvf_plot_poles.py
+++ b/test/gvf_plot_poles.py
@@ -1,7 +1,7 @@
 from ovf.core.GVFManager import GVFManager
 
-gvf = GVFManager.load("outputs/mtee_gvf.pkl")
-# gvf = GVFManager()
-# gvf.load_from_datasets("examples/data/capa.json",npoles_cplx=2,max_points=20)
-# gvf.save("outputs/capa_gvf.pkl")
+# gvf = GVFManager.load("outputs/mtee_gvf.pkl")
+gvf = GVFManager()
+gvf.load_from_datasets("examples/data/mtee.json",npoles_cplx=2,max_points=20)
+gvf.save("outputs/mtee_gvf.pkl")
 gvf.plot_poles("outputs/mtee_poles",degree=3,geometry_1="L1",geometry_2="L2")
\ No newline at end of file
diff --git a/test/test_save_and_reload_model.py b/test/test_save_and_reload_model.py
index 6e79ceb..5de2ee3 100644
--- a/test/test_save_and_reload_model.py
+++ b/test/test_save_and_reload_model.py
@@ -17,11 +17,11 @@ sampled_points = network.y.reshape(-1,ports,ports)
 H,freqs = auto_select_multple_ports(noised_sampled_points,full_freqences,max_points=20)
 
 def run_capa():
-    vf = VFManager(npoles_cplx=2,freqs=freqs,H=H,model=MultiPortOrthonormalBasis,iterations=K,verbose=False)
+    vf = VFManager(npoles_cplx=2,full_freqs=freqs,full_H=H,model=MultiPortOrthonormalBasis,iterations=K,verbose=False)
     vf.fit()
     vf.plot_metrics(show=False,save_path=f"outputs/{id}")
     model_responses = vf.get_model_responses(full_freqences)
-    vf.plot_model_responses(show=False,save_path=f"outputs/{id}")
+    vf.plot_model_responses(full_freqs=freqs,show=False,save_path=f"outputs/{id}")
     # vf.export(f"outputs/{id}")
     vf.write(f"outputs/{id}")
 
@@ -30,7 +30,7 @@ def load_model():
 
     vf.plot_metrics(show=False,save_path=f"outputs/3001")
     model_responses = vf.get_model_responses(full_freqences)
-    vf.plot_model_responses(show=False,save_path=f"outputs/3001")
+    vf.plot_model_responses(full_freqs=freqs,show=False,save_path=f"outputs/3001")
     # vf.export(f"outputs/{id}")
     vf.write(f"outputs/3001")
 
@@ -39,7 +39,7 @@ def load_model1():
 
     vf.plot_metrics(show=False,save_path=f"outputs/3002")
     model_responses = vf.get_model_responses(full_freqences)
-    vf.plot_model_responses(show=False,save_path=f"outputs/3002")
+    vf.plot_model_responses(full_freqs=freqs,show=False,save_path=f"outputs/3002")
     # vf.export(f"outputs/{id}")
     vf.write(f"outputs/3002")