import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit_transform for float64 : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 /opt/nec/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2) try: emb = tsne.fit_transform(mat) print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
desc = "Testing fit for DataFrame : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print ('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix([[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) mat = pd.DataFrame(mat) tsne = TSNE(n_components=2) try: tsne.fit(mat) print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing for accessing 'embedding_' attribute after calling fit() : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, method='exact') try: tsne.fit(mat) Y = tsne.embedding_ print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for n_iter>250 : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, n_iter=251) try: tsne.fit(mat) print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
from frovedis.mllib.manifold import TSNE desc = "Testing fit for early_exaggeration=0 : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print ('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix([[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, early_exaggeration=0) try: tsne.fit(mat) print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
#!/usr/bin/env python import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for metric='precomputed' with providing negative mat : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 /opt/nec/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix([[0, -4, 9, 16], [9, 0, 4, 9], [1, 4, 0, -9], [9, 16, 25, 0]], dtype=np.float64) tsne = TSNE(n_components=2, metric='precomputed') try: tsne.fit(mat) print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for metric='test' : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print ('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix([[0, 4, 9, 16], [9, 0, 4, 9], [1, 4, 0, 9], [25, 4, 9, 0]], dtype=np.float64) tsne = TSNE(n_components=2, metric='test') try: tsne.fit(mat) print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for method='barnes_hut': " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, method='barnes_hut') try: tsne.fit(mat) print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for init='pca': " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 /opt/nec/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, init='pca') try: tsne.fit(mat) print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing for setting 'n_iter_' attribute : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 /opt/nec/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, method='exact') try: tsne.n_iter_ = 500 print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
#dtype=np.int64) #mat = csr_matrix(mat) #mat = csc_matrix(mat) #mat = coo_matrix(mat) #mat = FrovedisRowmajorMatrix(mat) #mat = FrovedisColmajorMatrix(mat) #Should raise an error #mat = FrovedisCRSMatrix(mat) #mat = pd.DataFrame(mat) #mat = [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]] #mat = ((0, 0, 0, 0), (0, 1, 1, 1), (1, 0, 1, 0), (1, 1, 1, 0), (1, 1, 1, 1)) print("input matrix: ") print(mat) # for numpy matrix #print(mat.debug_print()) # for row major matrix tsne = TSNE().fit(mat) print("embeddings_: ") print(tsne.embedding_) #print(tsne.embedding_.debug_print()) #for row major matrix print("n_iter_: ") print(tsne.n_iter_) print("kl_divergence_: ") print(tsne.kl_divergence_) # releasing results from server #tsne.embedding_.release() #if mat is FrovedisRowmajorMatrix # sample numpy dense data (3x3) mat1 = np.matrix([[0, 0, 0, 0],
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for perplexity<0 : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 /opt/nec/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, perplexity=-1) try: tsne.fit(mat) print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing for setting 'embedding_' attribute : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) Y = np.matrix([[0, 0], [0, 1], [1, 0], [1, 1], [1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, method='exact') try: tsne.embedding_ = Y print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for metric='euclidean': " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, metric='euclidean') try: tsne.fit(mat) print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for learning_rate>0 : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, learning_rate=1.0) try: tsne.fit(mat) print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing fit for init='random': " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 /opt/nec/frovedis/ve/bin/frovedis_server")') quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, init='random') try: tsne.fit(mat) print(desc, "Passed") except: print(desc, "Failed") FrovedisServer.shut_down()
import sys import numpy as np from frovedis.exrpc.server import FrovedisServer from frovedis.mllib.manifold import TSNE desc = "Testing for setting 'kl_divergence_' attribute : " # initializing the frovedis server argvs = sys.argv argc = len(argvs) if (argc < 2): print('Please give frovedis_server calling command as the first argument\n\ (e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")' ) quit() FrovedisServer.initialize(argvs[1]) # sample numpy dense data (3x3) mat = np.matrix( [[0, 0, 0, 0], [0, 1, 1, 1], [1, 0, 1, 0], [1, 1, 1, 0], [1, 1, 1, 1]], dtype=np.float64) tsne = TSNE(n_components=2, method='exact') try: tsne.kl_divergence_ = 2.12 print(desc, "Failed") except: print(desc, "Passed") FrovedisServer.shut_down()