Unifying numpy imports

modelon-community · Jan 24, 2024 · 3f8e9ea · 3f8e9ea
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diff --git a/doc/sphinx/source/tutorialCVodeDisc.py b/doc/sphinx/source/tutorialCVodeDisc.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python 
 # -*- coding: utf-8 -*-
 """
-Tutorial example showing how to use the explicit solver CVode for a discontinious problem. 
+Tutorial example showing how to use the explicit solver CVode for a discontinuous problem. 
 To run the example simply type,
 
     run tutorialCVodeDisc.py (in IPython)

diff --git a/examples/cvode_basic.py b/examples/cvode_basic.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -37,7 +37,7 @@ def run_example(with_plots=True):
     #Define the rhs
     def f(t,y):
         ydot = -y[0]
-        return N.array([ydot])
+        return np.array([ydot])
 
     #Define an Assimulo problem
     exp_mod = Explicit_Problem(f, y0=4, name = r'CVode Test Example: $\dot y = - y$')

diff --git a/examples/cvode_basic_backward.py b/examples/cvode_basic_backward.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -34,7 +34,7 @@ def run_example(with_plots=True):
     #Define the rhs
     def f(t,y):
         ydot = -y[0]
-        return N.array([ydot])
+        return np.array([ydot])
 
     #Define an Assimulo problem
     exp_mod = Explicit_Problem(f,t0=5, y0=0.02695, name = r'CVode Test Example (reverse time): $\dot y = - y$ ')

diff --git a/examples/cvode_stability.py b/examples/cvode_stability.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -54,9 +54,9 @@ def handle_result(self, solver, t, y):
     def f(t,y):
         yd_0 = y[1]
         yd_1 = my*((1.-y[0]**2)*y[1]-y[0])
-        yd_2 = N.sin(t*y[1])
+        yd_2 = np.sin(t*y[1])
 
-        return N.array([yd_0,yd_1, yd_2])
+        return np.array([yd_0,yd_1, yd_2])
 
     y0 = [2.0,-0.6, 0.1] #Initial conditions
 
@@ -89,7 +89,7 @@ def f(t,y):
 
     #Basic test
     x1 = y[:,0]
-    nose.tools.assert_less(N.abs(float(x1[-1]) - 1.8601438), 1e-1)
+    nose.tools.assert_less(np.abs(float(x1[-1]) - 1.8601438), 1e-1)
 
     return exp_mod, exp_sim
 

diff --git a/examples/cvode_with_disc.py b/examples/cvode_with_disc.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -50,7 +50,7 @@ def rhs(self,t,y,sw):
         yd_1 = 0.0
         yd_2 = 0.0
 
-        return N.array([yd_0,yd_1,yd_2])
+        return np.array([yd_0,yd_1,yd_2])
 
     #Sets a name to our function
     name = 'ODE with discontinuities and a function with consistency problem'
@@ -65,7 +65,7 @@ def state_events(self,t,y,sw):
         event_1 = -y[2] + 1.0
         event_2 = -t + 1.0
 
-        return N.array([event_0,event_1,event_2])
+        return np.array([event_0,event_1,event_2])
 
 
     #Responsible for handling the events.

diff --git a/examples/cvode_with_initial_sensitivity.py b/examples/cvode_with_initial_sensitivity.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -57,12 +57,12 @@ def f(t, y, p):
         yd_1 = k21*y1-(k02+k12)*y2
         yd_2 = k31*y1-k13*y3
 
-        return N.array([yd_0,yd_1,yd_2])
+        return np.array([yd_0,yd_1,yd_2])
 
     #The initial conditions
     y0 = [0.0,0.0,0.0]          #Initial conditions for y
     p0 = [0.0, 0.0, 0.0]  #Initial conditions for parameters
-    yS0 = N.array([[1,0,0],[0,1,0],[0,0,1.]])
+    yS0 = np.array([[1,0,0],[0,1,0],[0,0,1.]])
 
     #Create an Assimulo explicit problem
     exp_mod = Explicit_Problem(f, y0, p0=p0,name='Example: Computing Sensitivities')
@@ -93,25 +93,25 @@ def f(t, y, p):
         legend_text=r"$\mathrm{{d}}{}/\mathrm{{d}}{}$"
         P.figure(1)
         P.subplot(221)
-        P.plot(t, N.array(exp_sim.p_sol[0])[:,0],
-               t, N.array(exp_sim.p_sol[0])[:,1],
-               t, N.array(exp_sim.p_sol[0])[:,2])
+        P.plot(t, np.array(exp_sim.p_sol[0])[:,0],
+               t, np.array(exp_sim.p_sol[0])[:,1],
+               t, np.array(exp_sim.p_sol[0])[:,2])
         P.title(title_text.format('p_1'))
         P.legend((legend_text.format('y_1','p_1'),
                   legend_text.format('y_1','p_2'),
                   legend_text.format('y_1','p_3')))
         P.subplot(222)
-        P.plot(t, N.array(exp_sim.p_sol[1])[:,0],
-               t, N.array(exp_sim.p_sol[1])[:,1],
-               t, N.array(exp_sim.p_sol[1])[:,2])
+        P.plot(t, np.array(exp_sim.p_sol[1])[:,0],
+               t, np.array(exp_sim.p_sol[1])[:,1],
+               t, np.array(exp_sim.p_sol[1])[:,2])
         P.title(title_text.format('p_2'))
         P.legend((legend_text.format('y_2','p_1'),
                   legend_text.format('y_2','p_2'),
                   legend_text.format('y_2','p_3')))
         P.subplot(223)
-        P.plot(t, N.array(exp_sim.p_sol[2])[:,0],
-               t, N.array(exp_sim.p_sol[2])[:,1],
-               t, N.array(exp_sim.p_sol[2])[:,2])
+        P.plot(t, np.array(exp_sim.p_sol[2])[:,0],
+               t, np.array(exp_sim.p_sol[2])[:,1],
+               t, np.array(exp_sim.p_sol[2])[:,2])
         P.title(title_text.format('p_3'))
         P.legend((legend_text.format('y_3','p_1'),
                   legend_text.format('y_3','p_2'),

diff --git a/examples/cvode_with_jac.py b/examples/cvode_with_jac.py
@@ -15,12 +15,11 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
 
-
 def run_example(with_plots=True):
     r"""
     Example for demonstrating the use of a user supplied Jacobian
@@ -45,11 +44,11 @@ def run_example(with_plots=True):
     def f(t,y):
         yd_0 = y[1]
         yd_1 = -9.82
-        return N.array([yd_0,yd_1])
+        return np.array([yd_0,yd_1])
 
     #Defines the Jacobian
     def jac(t,y):
-        j = N.array([[0,1.],[0,0]])
+        j = np.array([[0,1.],[0,0]])
         return j
 
     #Defines an Assimulo explicit problem

diff --git a/examples/cvode_with_jac_sparse.py b/examples/cvode_with_jac_sparse.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import scipy.sparse as SP
 import nose
 from assimulo.solvers import CVode
@@ -50,7 +50,7 @@ def f(t,y):
         yd_0 = -0.04*y[0] + 1e4*y[1]*y[2]
         yd_2 = 3e7*y[1]*y[1]
         yd_1 = -yd_0 - yd_2
-        return N.array([yd_0,yd_1,yd_2])
+        return np.array([yd_0,yd_1,yd_2])
 
     #Defines the Jacobian
     def jac(t,y):

diff --git a/examples/cvode_with_jac_spgmr.py b/examples/cvode_with_jac_spgmr.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -48,12 +48,12 @@ def f(t,y):
         yd_0 = y[1]
         yd_1 = -9.82
 
-        return N.array([yd_0,yd_1])
+        return np.array([yd_0,yd_1])
 
     #Defines the Jacobian*vector product
     def jacv(t,y,fy,v):
-        j = N.array([[0,1.],[0,0]])
-        return N.dot(j,v)
+        j = np.array([[0,1.],[0,0]])
+        return np.dot(j,v)
 
     y0 = [1.0,0.0] #Initial conditions
 

diff --git a/examples/cvode_with_parameters.py b/examples/cvode_with_parameters.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -50,7 +50,7 @@ def f(t, y, p):
         yd_1 = p[0]*y[0]-p[1]*y[1]*y[2]-p[2]*y[1]**2 
         yd_2 = p[2]*y[1]**2
 
-        return N.array([yd_0,yd_1,yd_2])
+        return np.array([yd_0,yd_1,yd_2])
 
     #The initial conditions
     y0 = [1.0,0.0,0.0]          #Initial conditions for y
@@ -65,11 +65,11 @@ def f(t, y, p):
     #Create an Assimulo explicit solver (CVode)
     exp_sim = CVode(exp_mod)
 
-    #Sets the solver paramters
+    #Sets the solver parameters
     exp_sim.iter = 'Newton'
     exp_sim.discr = 'BDF'
     exp_sim.rtol = 1.e-4
-    exp_sim.atol = N.array([1.0e-8, 1.0e-14, 1.0e-6])
+    exp_sim.atol = np.array([1.0e-8, 1.0e-14, 1.0e-6])
     exp_sim.sensmethod = 'SIMULTANEOUS' #Defines the sensitivity method used
     exp_sim.suppress_sens = False       #Dont suppress the sensitivity variables in the error test.
     exp_sim.report_continuously = True

diff --git a/examples/cvode_with_parameters_fcn.py b/examples/cvode_with_parameters_fcn.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -50,19 +50,19 @@ def f(t, y, p):
         yd_1 = p[0]*y[0]-p[1]*y[1]*y[2]-p[2]*y[1]**2 
         yd_2 = p[2]*y[1]**2
 
-        return N.array([yd_0,yd_1,yd_2])
+        return np.array([yd_0,yd_1,yd_2])
 
     def jac(t,y, p):
-        J = N.array([[-p[0], p[1]*y[2], p[1]*y[1]],
+        J = np.array([[-p[0], p[1]*y[2], p[1]*y[1]],
                      [p[0], -p[1]*y[2]-2*p[2]*y[1], -p[1]*y[1]],
                      [0.0, 2*p[2]*y[1],0.0]])
         return J
 
     def fsens(t, y, s, p):
-        J = N.array([[-p[0], p[1]*y[2], p[1]*y[1]],
+        J = np.array([[-p[0], p[1]*y[2], p[1]*y[1]],
                      [p[0], -p[1]*y[2]-2*p[2]*y[1], -p[1]*y[1]],
                      [0.0, 2*p[2]*y[1],0.0]])
-        P = N.array([[-y[0],y[1]*y[2],0],
+        P = np.array([[-y[0],y[1]*y[2],0],
                      [y[0], -y[1]*y[2], -y[1]**2],
                      [0,0,y[1]**2]])
         return J.dot(s)+P
@@ -82,11 +82,11 @@ def fsens(t, y, s, p):
     #Create an Assimulo explicit solver (CVode)
     exp_sim = CVode(exp_mod)
 
-    #Sets the solver paramters
+    #Sets the solver parameters
     exp_sim.iter = 'Newton'
     exp_sim.discr = 'BDF'
     exp_sim.rtol = 1.e-4
-    exp_sim.atol = N.array([1.0e-8, 1.0e-14, 1.0e-6])
+    exp_sim.atol = np.array([1.0e-8, 1.0e-14, 1.0e-6])
     exp_sim.sensmethod = 'SIMULTANEOUS' #Defines the sensitivity method used
     exp_sim.suppress_sens = False       #Dont suppress the sensitivity variables in the error test.
     exp_sim.report_continuously = True

diff --git a/examples/cvode_with_parameters_modified.py b/examples/cvode_with_parameters_modified.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import CVode
 from assimulo.problem import Explicit_Problem
@@ -48,7 +48,7 @@ def f(t, y, p):
         yd_1 = p[0]*y[0]-p[1]*y[1]*y[2]-p3*y[1]**2
         yd_2 = p3*y[1]**2
 
-        return N.array([yd_0,yd_1,yd_2])
+        return np.array([yd_0,yd_1,yd_2])
 
     #The initial conditions
     y0 = [1.0,0.0,0.0]          #Initial conditions for y
@@ -63,11 +63,11 @@ def f(t, y, p):
     #Create an Assimulo explicit solver (CVode)
     exp_sim = CVode(exp_mod)
 
-    #Sets the paramters
+    #Sets the parameters
     exp_sim.iter = 'Newton'
     exp_sim.discr = 'BDF'
     exp_sim.rtol = 1.e-4
-    exp_sim.atol = N.array([1.0e-8, 1.0e-14, 1.0e-6])
+    exp_sim.atol = np.array([1.0e-8, 1.0e-14, 1.0e-6])
     exp_sim.sensmethod = 'SIMULTANEOUS' #Defines the sensitivity method used
     exp_sim.suppress_sens = False       #Dont suppress the sensitivity variables in the error test.
     exp_sim.report_continuously = True

diff --git a/examples/dasp3_basic.py b/examples/dasp3_basic.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 
 try:
@@ -56,22 +56,22 @@ def run_example(with_plots=True):
     #Define the slow rhs
     def dydt(t,y,z):
         eps=(1./3)*1.e-3
-        yp = N.array([-(.6*z[0]+.8*y[2])*y[0]+10.*y[1],
+        yp = np.array([-(.6*z[0]+.8*y[2])*y[0]+10.*y[1],
                       -10.*y[1]+ 1.6*z[0] *y[2],
                       -1.33*eps**2*y[2]*(y[0]+2.*z[0])])										 
         return yp
 
     #Define the fast rhs
     def dzdt(t,y,z):
         eps=(1./3)*1.e-3
-        zp = N.array([1.6*z[0]*y[2]-.6*z[0]*y[0]
+        zp = np.array([1.6*z[0]*y[2]-.6*z[0]*y[0]
                       -45.*(eps*z[0])**2+.8*y[2]*y[0]])
         return zp
 
     #The initial values
     y0 = [ 3.0, 0.216, 1.0]
     z0 = [1.35]
-    eps = N.array([.33333333e-3])
+    eps = np.array([.33333333e-3])
 
     #Define an Assimulo problem
     exp_mod = SingPerturbed_Problem(dydt, dzdt, 

diff --git a/examples/dopri5_basic.py b/examples/dopri5_basic.py
@@ -15,7 +15,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-import numpy as N
+import numpy as np
 import nose
 from assimulo.solvers import Dopri5
 from assimulo.problem import Explicit_Problem
@@ -35,7 +35,7 @@ def run_example(with_plots=True):
     #Defines the rhs
     def f(t,y):
         ydot = -y[0]
-        return N.array([ydot])
+        return np.array([ydot])
 
     #Define an Assimulo problem
     exp_mod = Explicit_Problem(f, 4.0,