def test_simplex(self):
#--------------------------------------------------------
# embedded = False
#--------------------------------------------------------
print("--- Simplex embedded = False ---")
df = EDM.Simplex("", self.Files["block_3sp.csv"], None, "./", "",
"1 100", "101 195", 3, 1, 0, -1, 0, "x_t", "x_t",
False, False, True, False)
# cppEDM and devEDM outputs are rounded to os.precision( 4 );
dfv = EDM.ReadDataFrame("", self.Files["Smplx_E3_block_3sp_pyEDM.csv"])
S1 = dfv.get('Prediction_t(+1)')[1:95] # Skip row 0 Nan
S2 = round(df.get('Predictions'), 4)[1:95] # Skip row 0 Nan
self.assertTrue(S1.equals(S2))
def test_simplex2(self):
#--------------------------------------------------------
# embedded = True
#--------------------------------------------------------
print("--- Simplex embedded = True ---")
df = EDM.Simplex("", self.Files["block_3sp.csv"], None, "./", "",
"1 99", "100 198", 3, 1, 0, 1, 0, "x_t y_t z_t",
"x_t", True, False, True, False)
# This has been rounded to os.precision( 4 );
dfv = EDM.ReadDataFrame("",
self.Files["Smplx_embd_block_3sp_pyEDM.csv"])
S1 = dfv.get('Prediction_t(+1)')[1:98] # Skip row 0 Nan
S2 = round(df.get('Predictions'), 4)[1:98] # Skip row 0 Nan
self.assertTrue(S1.equals(S2))
def main():
'''EDM package examples.
df denotes a Pandas DataFrame.
S and M denote dictionaries of Pandas DataFrames'''
dataFiles = [ "TentMap_rEDM.csv",
"TentMapNoise_rEDM.csv",
"circle.csv",
"block_3sp.csv",
"sardine_anchovy_sst.csv" ]
# Create map of module dataFiles pathnames in Files
Files = {}
for file in dataFiles:
filename = "data/" + file
if pkg_resources.resource_exists( EDM.__name__, filename ):
Files[ file ] = \
pkg_resources.resource_filename( EDM.__name__, filename )
else :
raise Exception( "examples.py: Failed to find data file " + \
file + " in EDM package" )
# Note the path argument is empty "", file path is in Files{}
df = EDM.EmbedDimension( pathIn = "", dataFile = Files["TentMap_rEDM.csv"],
lib = "1 100", pred = "201 500", maxE = 10,
Tp = 1, tau = -1, exclusionRadius = 0,
columns = "TentMap", target = "TentMap",
validLib = [], numThreads = 4 )
df = EDM.PredictInterval( pathIn = "", dataFile = Files["TentMap_rEDM.csv"],
lib = "1 100", pred = "201 500", maxTp = 10,
E = 2, tau = -1, exclusionRadius = 0,
columns = "TentMap", target = "TentMap",
validLib = [], numThreads = 4 );
df = EDM.PredictNonlinear( pathIn = "",
dataFile = Files[ "TentMapNoise_rEDM.csv" ],
lib = "1 100", pred = "201 500", E = 2,
Tp = 1, knn = 0, tau = -1,
columns = "TentMap", target = "TentMap",
validLib = [], numThreads = 4 )
# Tent map simplex : specify multivariable columns embedded = True
S = EDM.Simplex( pathIn = "", dataFile = Files[ "block_3sp.csv" ],
lib = "1 99", pred = "100 198", E = 3, Tp = 1,
knn = 0, tau = -1, exclusionRadius = 0,
columns = "x_t y_t z_t", target = "x_t",
embedded = True, showPlot = True,
validLib = [], generateSteps = 0, parameterList = False )
# Tent map simplex : Embed column x_t to E=3, embedded = False
S = EDM.Simplex( pathIn = "", dataFile = Files[ "block_3sp.csv" ],
lib = "1 99", pred = "100 198", E = 3, Tp = 1,
knn = 0, tau = -1, exclusionRadius = 0,
columns = "x_t y_t z_t", target = "x_t",
embedded = False, showPlot = True,
validLib = [], generateSteps = 0, parameterList = False )
M = EDM.Multiview( pathIn = "", dataFile = Files[ "block_3sp.csv" ],
lib = "1 100", pred = "101 198",
D = 0, E = 3, Tp = 1, knn = 0, tau = -1,
multiview = 0, exclusionRadius = 0,
columns = "x_t y_t z_t", target = "x_t",
trainLib = True, excludeTarget = False,
numThreads = 4, showPlot = True )
# S-map circle : specify multivariable columns embedded = True
S = EDM.SMap( pathIn = "", dataFile = Files[ "circle.csv" ],
lib = "1 100", pred = "101 198",
E = 2, Tp = 1, knn = 0, tau = -1,
theta = 4, exclusionRadius = 0,
columns = "x y", target = "x",
solver = None, embedded = True,
validLib = [], generateSteps = 0, parameterList = False )
CM = EDM.CCM( pathIn = "", dataFile = Files[ "sardine_anchovy_sst.csv" ],
E = 3, Tp = 0, knn = 0, tau = -1, exclusionRadius = 0,
columns = "anchovy", target = "np_sst",
libSizes = "10 70 10", sample = 100, random = True,
replacement = False, seed = 0, includeData = False,
parameterList = False, verbose = False, showPlot = True )