Remove ModelInfo; add info to ModelFunction instead

1 files changed, 17 insertions, 23 deletions

diff --git a/test/test_ptamodel.py b/test/test_ptamodel.py
index e571dcc..9f5076c 100755
--- a/test/test_ptamodel.py
+++ b/test/test_ptamodel.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-from dfatool.functions import StaticInfo
+from dfatool.functions import StaticFunction
 from dfatool.loader import RawData, pta_trace_to_aggregate
 from dfatool.model import PTAModel
 from dfatool.utils import by_name_to_by_param
@@ -639,28 +639,26 @@ class TestFromFile(unittest.TestCase):
         )
 
         param_model, param_info = model.get_fitted()
-        self.assertIsInstance(param_info("POWERDOWN", "power"), StaticInfo)
+        self.assertIsInstance(param_info("POWERDOWN", "power"), StaticFunction)
         self.assertEqual(
-            param_info("RX", "power").function.model_function,
+            param_info("RX", "power").model_function,
             "0 + regression_arg(0) + regression_arg(1) * np.sqrt(parameter(datarate))",
         )
         self.assertAlmostEqual(
-            param_info("RX", "power").function.model_args[0], 48530.7, places=0
+            param_info("RX", "power").model_args[0], 48530.7, places=0
         )
-        self.assertAlmostEqual(
-            param_info("RX", "power").function.model_args[1], 117, places=0
-        )
-        self.assertIsInstance(param_info("STANDBY1", "power"), StaticInfo)
+        self.assertAlmostEqual(param_info("RX", "power").model_args[1], 117, places=0)
+        self.assertIsInstance(param_info("STANDBY1", "power"), StaticFunction)
         self.assertEqual(
-            param_info("TX", "power").function.model_function,
+            param_info("TX", "power").model_function,
             "0 + regression_arg(0) + regression_arg(1) * 1/(parameter(datarate)) + regression_arg(2) * parameter(txpower) + regression_arg(3) * 1/(parameter(datarate)) * parameter(txpower)",
         )
         self.assertEqual(
-            param_info("epilogue", "timeout").function.model_function,
+            param_info("epilogue", "timeout").model_function,
             "0 + regression_arg(0) + regression_arg(1) * 1/(parameter(datarate))",
         )
         self.assertEqual(
-            param_info("stopListening", "duration").function.model_function,
+            param_info("stopListening", "duration").model_function,
             "0 + regression_arg(0) + regression_arg(1) * 1/(parameter(datarate))",
         )
 
@@ -1823,22 +1821,18 @@ class TestFromFile(unittest.TestCase):
         """
 
         param_model, param_info = model.get_fitted()
-        self.assertIsInstance(param_info("IDLE", "power"), StaticInfo)
+        self.assertIsInstance(param_info("IDLE", "power"), StaticFunction)
         self.assertEqual(
-            param_info("RX", "power").function.model_function,
+            param_info("RX", "power").model_function,
             "0 + regression_arg(0) + regression_arg(1) * np.log(parameter(symbolrate) + 1)",
         )
-        self.assertIsInstance(param_info("SLEEP", "power"), StaticInfo)
-        self.assertIsInstance(param_info("SLEEP_EWOR", "power"), StaticInfo)
-        self.assertIsInstance(param_info("SYNTH_ON", "power"), StaticInfo)
-        self.assertIsInstance(param_info("XOFF", "power"), StaticInfo)
+        self.assertIsInstance(param_info("SLEEP", "power"), StaticFunction)
+        self.assertIsInstance(param_info("SLEEP_EWOR", "power"), StaticFunction)
+        self.assertIsInstance(param_info("SYNTH_ON", "power"), StaticFunction)
+        self.assertIsInstance(param_info("XOFF", "power"), StaticFunction)
 
-        self.assertAlmostEqual(
-            param_info("RX", "power").function.model_args[0], 84415, places=0
-        )
-        self.assertAlmostEqual(
-            param_info("RX", "power").function.model_args[1], 206, places=0
-        )
+        self.assertAlmostEqual(param_info("RX", "power").model_args[0], 84415, places=0)
+        self.assertAlmostEqual(param_info("RX", "power").model_args[1], 206, places=0)
 
 
 if __name__ == "__main__":