From 55fe3159f3429fe66db33ae0b0682a7283b75459 Mon Sep 17 00:00:00 2001 From: Calvin Date: Wed, 3 Apr 2013 15:12:27 -0400 Subject: use proper namespaces so that our docs don't bleed pointers --- feast.py | 106 +++++++++++++++++++++++++++++++-------------------------------- 1 file changed, 53 insertions(+), 53 deletions(-) diff --git a/feast.py b/feast.py index 767d664..34d81a3 100644 --- a/feast.py +++ b/feast.py @@ -19,10 +19,10 @@ __email__ = "mutantturkey@gmail.com" __status__ = "Release" import numpy as np -from ctypes import * +import ctypes as c try: - libFSToolbox = CDLL("libFSToolbox.so"); + libFSToolbox = c.CDLL("libFSToolbox.so"); except: raise Exception("Error: could not load libFSToolbox.so") @@ -59,19 +59,19 @@ def BetaGamma(data, labels, n_select, beta=1.0, gamma=1.0): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) - c_beta = c_double(beta) - c_gamma = c_double(gamma) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) + c_beta = c.c_double(beta) + c_gamma = c.c_double(gamma) - libFSToolbox.BetaGamma.restype = POINTER(c_double * n_select) + libFSToolbox.BetaGamma.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.BetaGamma(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)), + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)), c_beta, c_gamma ) @@ -143,17 +143,17 @@ def CMIM(data, labels, n_select): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) - libFSToolbox.CMIM.restype = POINTER(c_double * n_select) + libFSToolbox.CMIM.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.CMIM(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)) + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)) ) @@ -196,17 +196,17 @@ def CondMI(data, labels, n_select): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) - libFSToolbox.CondMI.restype = POINTER(c_double * n_select) + libFSToolbox.CondMI.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.CondMI(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)) + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)) ) @@ -274,17 +274,17 @@ def DISR(data, labels, n_select): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) - libFSToolbox.DISR.restype = POINTER(c_double * n_select) + libFSToolbox.DISR.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.DISR(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)) + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)) ) @@ -328,17 +328,17 @@ def ICAP(data, labels, n_select): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) - libFSToolbox.ICAP.restype = POINTER(c_double * n_select) + libFSToolbox.ICAP.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.ICAP(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)) + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)) ) @@ -383,17 +383,17 @@ def JMI(data, labels, n_select): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) - libFSToolbox.JMI.restype = POINTER(c_double * n_select) + libFSToolbox.JMI.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.JMI(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)) + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)) ) @@ -486,17 +486,17 @@ def mRMR(data, labels, n_select): output = np.zeros(n_select) # cast as C types - c_n_observations = c_int(n_observations) - c_n_select = c_int(n_select) - c_n_features = c_int(n_features) + c_n_observations = c.c_int(n_observations) + c_n_select = c.c_int(n_select) + c_n_features = c.c_int(n_features) - libFSToolbox.mRMR_D.restype = POINTER(c_double * n_select) + libFSToolbox.mRMR_D.restype = c.POINTER(c.c_double * n_select) features = libFSToolbox.mRMR_D(c_n_select, c_n_observations, c_n_features, - data.ctypes.data_as(POINTER(c_double)), - labels.ctypes.data_as(POINTER(c_double)), - output.ctypes.data_as(POINTER(c_double)) + data.ctypes.data_as(c.POINTER(c.c_double)), + labels.ctypes.data_as(c.POINTER(c.c_double)), + output.ctypes.data_as(c.POINTER(c.c_double)) ) -- cgit v1.2.3