"conflict possible"

crocoddyl/actuation.py

@@ -13,12 +13,12 @@ class ActuationModelDoublePendulum:
         self.actLink = actLink
 
     def calc(self, data, x, u):
-        S = np.zeros([self.nv,self.nu])
+        S = np.zeros([self.nv, self.nu])
         if self.actLink == 1:
             S[0] = 1
         else:
             S[1] = 1
-        data.a[:] = np.dot(S,u)
+        data.a[:] = np.dot(S, u)
         return data.a
 
     def calcDiff(self, data, x, u, recalc=True):
@@ -29,6 +29,7 @@ class ActuationModelDoublePendulum:
     def createData(self, pinocchioData):
         return ActuationDataDoublePendulum(self, pinocchioData)
 
+
 class ActuationDataDoublePendulum:
     def __init__(self, model, pinocchioData):
         self.pinocchio = pinocchioData
@@ -38,9 +39,9 @@ class ActuationDataDoublePendulum:
         self.Ax = self.A[:, :ndx]
         self.Au = self.A[:, ndx:]
         if model.actLink == 1:
-            self.Au[0,0] = 1
+            self.Au[0, 0] = 1
         else:
-            self.Au[1,0] = 1
+            self.Au[1, 0] = 1
 
 
 class ActuationModelUAM:
@@ -63,12 +64,11 @@ class ActuationModelUAM:
         self.cf = coefF
 
     def calc(self, data, x, u):
-        # data.a[2:] = u
         d, cf, cm = self.d, self.cf, self.cf
-        S = np.array(np.zeros([self.nv,self.nu]))
-        S[2:6,:4] = np.array([[1,1,1,1],[-d,d,d,-d],[-d,d,-d,d],[-cm/cf,-cm/cf,cm/cf,cm/cf]])
+        S = np.array(np.zeros([self.nv, self.nu]))
+        S[2:6, :4] = np.array([[1, 1, 1, 1], [-d, d, d, -d], [-d, d, -d, d], [-cm / cf, -cm / cf, cm / cf, cm / cf]])
         np.fill_diagonal(S[6:, 4:], 1)
-        data.a = np.dot(S,u)
+        data.a = np.dot(S, u)
         return data.a
 
     def calcDiff(self, data, x, u, recalc=True):
@@ -79,6 +79,7 @@ class ActuationModelUAM:
     def createData(self, pinocchioData):
         return ActuationDataUAM(self, pinocchioData)
 
+
 class ActuationDataUAM:
     def __init__(self, model, pinocchioData):
         self.pinocchio = pinocchioData
@@ -88,9 +89,9 @@ class ActuationDataUAM:
         self.A = np.zeros([nv, ndx + nu])  # result of calcDiff
         self.Ax = self.A[:, :ndx]
         self.Au = self.A[:, ndx:]
-        self.Au[2:6,:4] = np.array([[1,1,1,1],[-d,d,d,-d],[-d,d,-d,d],[-cm/cf,-cm/cf,cm/cf,cm/cf]])
+        self.Au[2:6, :4] = np.array([[1, 1, 1, 1], [-d, d, d, -d], [-d, d, -d, d], [-cm / cf, -cm / cf, cm / cf, cm / cf]])
         np.fill_diagonal(self.Au[6:, 4:], 1)
-        #np.fill_diagonal(self.Au[2:, :], 1)
+        # np.fill_diagonal(self.Au[2:, :], 1)
 # This is the matrix that, given a force vector representing the four motors, outputs the thrust and moment
 # [      0,      0,     0,     0]
 # [      0,      0,     0,     0]
@@ -105,6 +106,7 @@ class ActuationModelFreeFloating:
     This model transforms an actuation u into a joint torque tau.
     We implement here the simplest model: tau = S.T*u, where S is constant.
     '''
+
     def __init__(self, pinocchioModel):
         self.pinocchio = pinocchioModel
         if (pinocchioModel.joints[1].shortname() != 'JointModelFreeFlyer'):

crocoddyl/cost.py

@@ -15,6 +15,7 @@ class CostModelPinocchio:
     can be retrieved from Pinocchio data, through the calc and calcDiff
     functions, respectively.
     """
+
     def __init__(self, pinocchioModel, ncost, withResiduals=True, nu=None):
         self.ncost = ncost
         self.nq = pinocchioModel.nq
@@ -40,6 +41,7 @@ class CostDataPinocchio:
 
     It stores the data corresponting to the CostModelPinocchio class.
     """
+
     def __init__(self, model, pinocchioData):
         ncost, nv, ndx, nu = model.ncost, model.nv, model.ndx, model.nu
         self.pinocchio = pinocchioData
@@ -70,6 +72,7 @@ class CostDataPinocchio:
 class CostModelNumDiff(CostModelPinocchio):
     """ Abstract cost model that uses NumDiff for derivative computation.
     """
+
     def __init__(self, costModel, State, withGaussApprox=False, reevals=[]):
         '''
         reevals is a list of lambdas of (pinocchiomodel,pinocchiodata,x,u) to be

crocoddyl/differential_action.py

@@ -4,6 +4,7 @@ import pinocchio
 from .state import StatePinocchio, StateVector
 from .utils import EPS, a2m, m2a, randomOrthonormalMatrix
 
+
 class DifferentialActionModelAbstract:
     """ Abstract class for the differential action model.
 
@@ -13,6 +14,7 @@ class DifferentialActionModelAbstract:
     the dynamics, cost functions and their derivatives. These computations are
     mainly carry on inside calc() and calcDiff(), respectively.
     """
+
     def __init__(self, nq, nv, nu):
         self.nq = nq
         self.nv = nv

examples/notebooks/2DOFs.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -87,9 +87,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 20,
    "metadata": {
-    "scrolled": false
+    "scrolled": true
    },
    "outputs": [
     {
@@ -451,7 +451,7 @@
        " True)"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -463,16 +463,14 @@
     "ddp.callback.append(CallbackDDPLogger())\n",
     "\n",
     "us0 = np.zeros([T,1])\n",
-    "#us0 = ddp.us\n",
     "xs0 = [problem.initialState+0.1]*len(ddp.models())\n",
     "\n",
-    "ddp.solve(init_xs=xs0,init_us=us0,maxiter=150)\n",
-    "#ddp.solve(maxiter=150)"
+    "ddp.solve(init_xs=xs0,init_us=us0,maxiter=150)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -601,7 +599,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.16"
+   "version": "2.7.12"
   }
  },
  "nbformat": 4,

examples/notebooks/acrobot.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,18 +61,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "actModel = ActuationModelDoublePendulum(robot.model, actLink=2)\n",
-    "runningModel = IntegratedActionModelEuler(DifferentialActionModelUAM(robot.model, actModel, runningCostModel))\n",
-    "terminalModel = IntegratedActionModelEuler(DifferentialActionModelUAM(robot.model, actModel, terminalCostModel))"
+    "runningModel = IntegratedActionModelEuler(DifferentialActionModelActuated(robot.model, actModel, runningCostModel))\n",
+    "terminalModel = IntegratedActionModelEuler(DifferentialActionModelActuated(robot.model, actModel, terminalCostModel))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -87,7 +87,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 5,
    "metadata": {
     "scrolled": true
    },
@@ -440,7 +440,7 @@
        " True)"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -452,16 +452,14 @@
     "ddp.callback.append(CallbackDDPLogger())\n",
     "\n",
     "us0 = np.zeros([T,1])\n",
-    "#us0 = ddp.us\n",
     "xs0 = [problem.initialState+0.1]*len(ddp.models())\n",
     "\n",
-    "ddp.solve(init_xs=xs0,init_us=us0,maxiter=150)\n",
-    "#ddp.solve(maxiter=150)"
+    "ddp.solve(init_xs=xs0,init_us=us0,maxiter=150)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -469,8 +467,10 @@
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 13,
    "metadata": {},
+   "outputs": [],
    "source": [
     "import time \n",
     "dt = 0.01\n",
@@ -483,8 +483,10 @@
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 14,
    "metadata": {},
+   "outputs": [],
    "source": [
     "nle = np.zeros([2,1])\n",
     "for i in range(len(t)):\n",
@@ -593,7 +595,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.16"
+   "version": "2.7.12"
   }
  },
  "nbformat": 4,