def add_indep(x, varnames, dtype=None):
'''
construct array with independent columns
x is either iterable (list, tuple) or instance of ndarray or a subclass of it.
If x is an ndarray, then each column is assumed to represent a variable with
observations in rows.
'''
#TODO: this needs tests for subclasses
if isinstance(x, np.ndarray) and x.ndim == 2:
x = x.T
nvars_orig = len(x)
nobs = len(x[0])
#print 'nobs, nvars_orig', nobs, nvars_orig
if not dtype:
dtype = np.asarray(x[0]).dtype
xout = np.zeros((nobs, nvars_orig), dtype=dtype)
count = 0
rank_old = 0
varnames_new = []
varnames_dropped = []
keepindx = []
for (xi, ni) in zip(x, varnames):
#print xi.shape, xout.shape
xout[:,count] = xi
rank_new = smrank(xout)
#print rank_new
if rank_new > rank_old:
varnames_new.append(ni)
rank_old = rank_new
count += 1
else:
varnames_dropped.append(ni)
return xout[:,:count], varnames_new
def add_indep(x, varnames, dtype=None):
'''
construct array with independent columns
x is either iterable (list, tuple) or instance of ndarray or a subclass of it.
If x is an ndarray, then each column is assumed to represent a variable with
observations in rows.
'''
#TODO: this needs tests for subclasses
if isinstance(x, np.ndarray) and x.ndim == 2:
x = x.T
nvars_orig = len(x)
nobs = len(x[0])
#print 'nobs, nvars_orig', nobs, nvars_orig
if not dtype:
dtype = np.asarray(x[0]).dtype
xout = np.zeros((nobs, nvars_orig), dtype=dtype)
count = 0
rank_old = 0
varnames_new = []
varnames_dropped = []
keepindx = []
for (xi, ni) in zip(x, varnames):
#print xi.shape, xout.shape
xout[:, count] = xi
rank_new = smrank(xout)
#print rank_new
if rank_new > rank_old:
varnames_new.append(ni)
rank_old = rank_new
count += 1
else:
varnames_dropped.append(ni)
return xout[:, :count], varnames_new
def check_rank(self, J):
rank = smrank(J)
if rank < np.size(J, axis=1):
raise ValueError("Rank condition not met: "
"solution may not be unique.")
def check_rank(self, J):
rank = smrank(J)
if rank < np.size(J, axis=1):
raise ValueError("Rank condition not met: "
"solution may not be unique.")