Add test case

src/adnap/evaluate.py

@@ -5,7 +5,7 @@
 from panda_model import Model
 
 from .optimize import coriolis_error, gravity_error, mass_error
-from .panda_param import PandaParametrized, sample, unflatten_params
+from .panda_param import PandaParameterized, sample, unflatten_params
 
 
 def run():
@@ -26,7 +26,7 @@ def run():
 
   params = np.load(args.file)
   m, c, I = unflatten_params(params)
-  r = PandaParametrized(m, c, I)
+  r = PandaParameterized(m, c, I)
   model = Model(libfranka)
 
   q_data, dq_data, __ = sample(args.n)

src/adnap/optimize.py

@@ -9,23 +9,23 @@
 import panda_model
 from scipy.optimize import least_squares
 
-from .panda_param import PandaParametrized, sample
+from .panda_param import PandaParameterized, sample
 
 
-def coriolis_error(model: panda_model.Model, opt_model: PandaParametrized,
+def coriolis_error(model: panda_model.Model, opt_model: PandaParameterized,
                    q_data: np.ndarray, dq_data: np.ndarray):
   return opt_model.coriolis(q_data, dq_data) @ dq_data - model.coriolis(
       q_data, dq_data, np.zeros((3, 3)), 0, np.zeros(3))
 
 
-def mass_error(model: panda_model.Model, opt_model: PandaParametrized,
+def mass_error(model: panda_model.Model, opt_model: PandaParameterized,
                q_data: np.ndarray):
   I_indices = np.tril_indices(7)
   return model.mass(q_data, np.zeros(
       (3, 3)), 0, np.zeros(3))[I_indices] - opt_model.inertia(q_data)[I_indices]
 
 
-def gravity_error(model: panda_model.Model, opt_model: PandaParametrized,
+def gravity_error(model: panda_model.Model, opt_model: PandaParameterized,
                   q_data: np.ndarray):
   return opt_model.gravload(q_data) - model.gravity(q_data, 0, np.zeros(3))
 
@@ -57,7 +57,7 @@ def residual(params):
     I = params[28:].reshape((7, 6))
 
     model = panda_model.Model(lib_path)
-    r = PandaParametrized(m, c, I)
+    r = PandaParameterized(m, c, I)
 
     mass_res = []
     coriolis_res = []

src/adnap/panda_param.py

@@ -53,7 +53,7 @@ def unflatten_params(params: np.ndarray):
   return m, c, I
 
 
-class PandaParametrized(DHRobot):
+class PandaParameterized(DHRobot):
   """
   DH version of the Panda robot parameterized in the
   dynamic physical parameters.
@@ -171,7 +171,7 @@ def __init__(self, m, c, I, **kwargs):
     self.addconfiguration("qz", self.qz)
 
 
-def create_sym_panda() -> PandaParametrized:
+def create_sym_panda() -> PandaParameterized:
   """
   Create symbolic version of parameterized Panda.
   """
@@ -182,4 +182,4 @@ def create_sym_panda() -> PandaParametrized:
     I.append(create_inertia_symbols(i + 1))
     c.append(create_com_symbols(i + 1))
 
-  return PandaParametrized(m, c, I, symbolic=True)
+  return PandaParameterized(m, c, I, symbolic=True)

tests/test_ParameterizedPanda.py

@@ -0,0 +1,12 @@
+import unittest
+import numpy as np
+from adnap import panda_param
+
+
+class testParameterizedPanda(unittest.TestCase):
+
+  def test_Panda(self):
+    params = np.zeros(70)
+    m, c, I = panda_param.unflatten_params(params)
+    panda_param.PandaParameterized(m, c, I)
+    panda_param.create_sym_panda()