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authorRémi Flamary <remi.flamary@gmail.com>2019-12-18 10:15:30 +0100
committerRémi Flamary <remi.flamary@gmail.com>2019-12-18 10:15:30 +0100
commit3cb03158c42dde141d6f33973ea6e3394b9dc3d4 (patch)
tree272412760f0e55b9a354b7c43ddc71a2a6320a69 /ot/lp/__init__.py
parenta4afee871d8e9d5db68228d1ed5bf4853eedc294 (diff)
cleanup variable name dense
Diffstat (limited to 'ot/lp/__init__.py')
-rw-r--r--ot/lp/__init__.py30
1 files changed, 14 insertions, 16 deletions
diff --git a/ot/lp/__init__.py b/ot/lp/__init__.py
index d476071..bb9829a 100644
--- a/ot/lp/__init__.py
+++ b/ot/lp/__init__.py
@@ -107,7 +107,6 @@ def emd(a, b, M, numItermax=100000, log=False, dense=True):
b = np.asarray(b, dtype=np.float64)
M = np.asarray(M, dtype=np.float64)
- sparse= not dense
# if empty array given then use uniform distributions
if len(a) == 0:
@@ -115,11 +114,11 @@ def emd(a, b, M, numItermax=100000, log=False, dense=True):
if len(b) == 0:
b = np.ones((M.shape[1],), dtype=np.float64) / M.shape[1]
- if sparse:
- Gv, iG, jG, cost, u, v, result_code = emd_c(a, b, M, numItermax,sparse)
- G = coo_matrix((Gv, (iG, jG)), shape=(a.shape[0], b.shape[0]))
+ if dense:
+ G, cost, u, v, result_code = emd_c(a, b, M, numItermax,dense)
else:
- G, cost, u, v, result_code = emd_c(a, b, M, numItermax,sparse)
+ Gv, iG, jG, cost, u, v, result_code = emd_c(a, b, M, numItermax,dense)
+ G = coo_matrix((Gv, (iG, jG)), shape=(a.shape[0], b.shape[0]))
result_code_string = check_result(result_code)
if log:
@@ -217,8 +216,6 @@ def emd2(a, b, M, processes=multiprocessing.cpu_count(),
b = np.asarray(b, dtype=np.float64)
M = np.asarray(M, dtype=np.float64)
- sparse=not dense
-
# problem with pikling Forks
if sys.platform.endswith('win32'):
processes=1
@@ -231,12 +228,11 @@ def emd2(a, b, M, processes=multiprocessing.cpu_count(),
if log or return_matrix:
def f(b):
-
- if sparse:
- Gv, iG, jG, cost, u, v, result_code = emd_c(a, b, M, numItermax,sparse)
- G = coo_matrix((Gv, (iG, jG)), shape=(a.shape[0], b.shape[0]))
+ if dense:
+ G, cost, u, v, result_code = emd_c(a, b, M, numItermax,dense)
else:
- G, cost, u, v, result_code = emd_c(a, b, M, numItermax,sparse)
+ Gv, iG, jG, cost, u, v, result_code = emd_c(a, b, M, numItermax,dense)
+ G = coo_matrix((Gv, (iG, jG)), shape=(a.shape[0], b.shape[0]))
result_code_string = check_result(result_code)
log = {}
@@ -249,11 +245,13 @@ def emd2(a, b, M, processes=multiprocessing.cpu_count(),
return [cost, log]
else:
def f(b):
- if sparse:
- Gv, iG, jG, cost, u, v, result_code = emd_c(a, b, M, numItermax,sparse)
- G = coo_matrix((Gv, (iG, jG)), shape=(a.shape[0], b.shape[0]))
+ if dense:
+ G, cost, u, v, result_code = emd_c(a, b, M, numItermax,dense)
else:
- G, cost, u, v, result_code = emd_c(a, b, M, numItermax,sparse)
+ Gv, iG, jG, cost, u, v, result_code = emd_c(a, b, M, numItermax,dense)
+ G = coo_matrix((Gv, (iG, jG)), shape=(a.shape[0], b.shape[0]))
+
+ result_code_string = check_result(result_code)
check_result(result_code)
return cost