Fix basic optimization example unknown arguments issues (#329)

ljvmiranda921 · Apr 25, 2019 · 90275e6 · 90275e6
1 parent a04b7e5
commit 90275e6
Show file tree

Hide file tree

Showing 4 changed files with 4 additions and 11 deletions.
diff --git a/docs/examples/basic_optimization.rst b/docs/examples/basic_optimization.rst
@@ -71,7 +71,7 @@ several variables at once.
     optimizer = ps.single.GlobalBestPSO(n_particles=10, dimensions=2, options=options)
     
     # Perform optimization
-    cost, pos = optimizer.optimize(fx.sphere, print_step=100, iters=1000, verbose=3)
+    cost, pos = optimizer.optimize(fx.sphere, iters=1000)
 
 
 .. parsed-literal::

diff --git a/docs/examples/inverse_kinematics.rst b/docs/examples/inverse_kinematics.rst
@@ -241,7 +241,7 @@ Braced with these preparations we can finally start using the algorithm:
                                         bounds=constraints)
 
     # Perform optimization
-    cost, joint_vars = optimizer.optimize(opt_func, print_step=100, iters=1000, verbose=3)
+    cost, joint_vars = optimizer.optimize(opt_func, iters=1000)
 
 
 .. parsed-literal::

diff --git a/examples/basic_optimization.ipynb b/examples/basic_optimization.ipynb
@@ -121,14 +121,7 @@
     "optimizer = ps.single.GlobalBestPSO(n_particles=10, dimensions=2, options=options)\n",
     "\n",
     "# Perform optimization\n",
-    "cost, pos = optimizer.optimize(fx.sphere, print_step=100, iters=1000, verbose=3)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can see that the optimizer was able to find a good minima as shown above. You can control the verbosity of the output using the `verbose` argument, and the number of steps to be printed out using the `print_step` argument."
+    "cost, pos = optimizer.optimize(fx.sphere, iters=1000)"
    ]
   },
   {

diff --git a/examples/inverse_kinematics.ipynb b/examples/inverse_kinematics.ipynb
@@ -322,7 +322,7 @@
     "                                    bounds=constraints)\n",
     "\n",
     "# Perform optimization\n",
-    "cost, joint_vars = optimizer.optimize(opt_func, print_step=100, iters=1000, verbose=3)"
+    "cost, joint_vars = optimizer.optimize(opt_func, iters=1000)"
    ]
   },
   {