changed examples generation to create good rho plots

xianglunkai · Mar 22, 2017 · 01f3e8f · 01f3e8f
1 parent 463afbb
commit 01f3e8f
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Showing 5 changed files with 18 additions and 16 deletions.
diff --git a/.gitignore b/.gitignore
@@ -199,6 +199,7 @@ out/
 # Data Files
 # -------------------------------------------------------------------
 interfaces/python/tests/qp_problems/results/
+interfaces/python/tests/qp_problems/results_bak
 interfaces/python/tests/qp_problems/figures/
 tests/**/*data.h
 interfaces/python/tests/codegen/**/*.so

diff --git a/interfaces/python/tests/qp_problems/qp_examples/lasso.py b/interfaces/python/tests/qp_problems/qp_examples/lasso.py
@@ -37,7 +37,7 @@ def create_dims(self, n_vec, m_vec):
                                       np.array([[n], [m]])))
         return dims_mat
 
-    def gen_problem(self, m, n, dens_lvl=0.5, version='dense'):
+    def gen_problem(self, m, n, dens_lvl=0.5, version='sparse'):
         """
         Lasso problem is defined as
                 minimize	|| Ax - b ||^2 + gamma * || x ||_1

diff --git a/interfaces/python/tests/qp_problems/qp_examples/qp_example.py b/interfaces/python/tests/qp_problems/qp_examples/qp_example.py
@@ -57,7 +57,7 @@ def perform_tests(self, **kwargs):
             for _ in range(self.nm_num_prob):  # Generate some random problems
 
                 # Get current seed
-                current_seed = np.random.randint(0, sys.maxsize)
+                current_seed = np.random.randint(0, 2**32 - 1)
                 np.random.seed(current_seed)
 
                 # generate problem and store statistics

diff --git a/interfaces/python/tests/qp_problems/qp_examples/svm.py b/interfaces/python/tests/qp_problems/qp_examples/svm.py
@@ -30,7 +30,7 @@ def create_dims(self, n_vec, m_vec):
                                       np.array([[n], [m]])))
         return dims_mat
 
-    def gen_problem(self, m, n, dens_lvl=1.0):
+    def gen_problem(self, m, n, dens_lvl=.8):
         """
         Support vector machine problem is defined as
                 minimize	|| x ||^2 + gamma * 1.T * max(0, diag(b) A x + 1)

diff --git a/interfaces/python/tests/qp_problems/run_qpexamples.py b/interfaces/python/tests/qp_problems/run_qpexamples.py
@@ -44,13 +44,13 @@
 
 
 
-dim_vecs_len = 10
+dim_vecs_len = 20
 # n_vec = np.array([20])
 # m_vec = np.array([30])
- n_max = 50
- m_max = 50
- n_vec = np.arange(10, n_max, int(n_max/dim_vecs_len))
- m_vec = np.arange(10, m_max, int(m_max/dim_vecs_len))
+n_max = 50
+m_max = 50
+n_vec = np.arange(10, n_max, int(n_max/dim_vecs_len))
+m_vec = np.arange(10, m_max, int(m_max/dim_vecs_len))
 
 
 
@@ -63,13 +63,14 @@
            'polish': False,
            'scaling_norm': 2,
            'scaling_iter': 3,
+           'early_terminate_interval': 1,
            'max_iter': 2500}
 
 # Test types
 # test_types = ['basis_pursuit', 'huber_fit', 'lasso', 'nonneg_l2', 'lp',
             #   'portfolio', 'svm']
 
-test_types = ['svm', 'lasso', 'portfolio']
+test_types = ['lasso', 'svm']
 
 def run_examples(test_type, n_vec, m_vec, rho_vec, sigma_vec,
                  alpha_vec, nm_num_prob, **kwargs):
@@ -112,13 +113,13 @@ def run_examples(test_type, n_vec, m_vec, rho_vec, sigma_vec,
 results_full = [x[1] for x in res]
 
 
-# # Execute problems in series
-# results = []
-# results_full = []
-# for i in range(len(test_types)):
-#     res, res_full = partial_tests(test_types[i])
-#     results.append(res)
-#     results_full.append(res_full)
+# Execute problems in series
+#  results = []
+#  results_full = []
+#  for i in range(len(test_types)):
+   #  res, res_full = partial_tests(test_types[i])
+   #  results.append(res)
+   #  results_full.append(res_full)
 
 cputime = time() - t
 print("total cputime = %.4f sec" % cputime)