def do_concat (shape1, shape2, iaxis, count=[0]):
from pygeode.axis import XAxis, YAxis, ZAxis, TAxis
from pygeode.var import Var
from pygeode.concat import concat
from var_test import varTest
import numpy as np
# Increment test counter (and generate a unique test name)
count[0] += 1
testname = "concattest%05d"%(count[0])
# Create some test data
np.random.seed(count[0])
array1 = np.random.randn(*shape1)
array2 = np.random.randn(*shape2)
# Get the # of dimensions, and assign a unique axis class for each dim
assert array1.ndim == array2.ndim
ndim = array1.ndim
axis_classes = (XAxis, YAxis, ZAxis, TAxis)[:ndim]
# Construct the first var
axes = [cls(n) for cls,n in zip(axis_classes,array1.shape)]
var1 = Var(axes = axes, values = array1, name = "myvar", atts={'a':1, 'b':2, 'c':3})
# The second var should have the same axes, except for the concatenation one
n1 = array1.shape[iaxis]
n2 = array2.shape[iaxis]
axes[iaxis] = axis_classes[iaxis](np.arange(n1, n1+n2))
var2 = Var(axes = axes, values = array2, name = "myvar", atts={'a':1, 'b':3, 'd':4})
# Try concatenating
var = concat(var1,var2)
# The expected result
expected = np.concatenate ( (array1, array2), iaxis)
# Test this
test = varTest(testname=testname, var=var, values=expected)
# Store this test
globals()[testname] = test
def do_concat (shape1, shape2, iaxis, count=[0]):
from pygeode.axis import XAxis, YAxis, ZAxis, TAxis
from pygeode.var import Var
from pygeode.concat import concat
from var_test import varTest
import numpy as np
# Increment test counter (and generate a unique test name)
count[0] += 1
testname = "concattest%05d"%(count[0])
# Create some test data
np.random.seed(count[0])
array1 = np.random.randn(*shape1)
array2 = np.random.randn(*shape2)
# Get the # of dimensions, and assign a unique axis class for each dim
assert array1.ndim == array2.ndim
ndim = array1.ndim
axis_classes = (XAxis, YAxis, ZAxis, TAxis)[:ndim]
# Construct the first var
axes = [cls(n) for cls,n in zip(axis_classes,array1.shape)]
var1 = Var(axes = axes, values = array1, name = "myvar", atts={'a':1, 'b':2, 'c':3})
# The second var should have the same axes, except for the concatenation one
n1 = array1.shape[iaxis]
n2 = array2.shape[iaxis]
axes[iaxis] = axis_classes[iaxis](np.arange(n1, n1+n2))
var2 = Var(axes = axes, values = array2, name = "myvar", atts={'a':1, 'b':3, 'd':4})
# Try concatenating
var = concat(var1,var2)
# The expected result
expected = np.concatenate ( (array1, array2), iaxis)
# Test this
test = varTest(testname=testname, var=var, values=expected)
# Store this test
globals()[testname] = test
def concat(*datasets):
# {{{
from pygeode.concat import concat
from pygeode.tools import common_dict, islist
# Did we get passed a list of datasets already?
# (need to break out of the outer list)
if len(datasets) == 1 and islist(datasets[0]): datasets = list(datasets[0])
# If we only have one dataset, then return it
if len(datasets) == 1: return datasets[0]
# Collect a list of variable names (in the order they're found in the datasets)
# and, a corresponding dictionary mapping the names to vars
varnames = []
vardict = {}
for dataset in datasets:
for v in dataset.vars:
if v.name not in vardict:
vardict[v.name] = []
varnames.append(v.name)
vardict[v.name].append(v)
# Merge the var segments together
# If only one segment, just use the variable itself
vars = [vardict[n] for n in varnames]
vars = [concat(v) if len(v) > 1 else v[0] for v in vars]
d = Dataset(vars)
# Keep any common global attributes
# Collect all attributes found in the datasets
atts = common_dict(*[x.atts for x in datasets])
if len(atts) > 0:
d.atts = atts
return d
def concat(*datasets):
from pygeode.concat import concat
from pygeode.tools import common_dict, islist
# Did we get passed a list of datasets already?
# (need to break out of the outer list)
if len(datasets) == 1 and islist(datasets[0]): datasets = list(datasets[0])
# If we only have one dataset, then return it
if len(datasets) == 1: return datasets[0]
# Collect a list of variable names (in the order they're found in the datasets)
# and, a corresponding dictionary mapping the names to vars
varnames = []
vardict = {}
for dataset in datasets:
for v in dataset.vars:
if v.name not in vardict:
vardict[v.name] = []
varnames.append(v.name)
vardict[v.name].append(v)
# Merge the var segments together
# If only one segment, just use the variable itself
vars = [vardict[n] for n in varnames]
vars = [concat(v) if len(v)>1 else v[0] for v in vars]
d = Dataset(vars)
# Keep any common global attributes
# Collect all attributes found in the datasets
atts = common_dict(*[x.atts for x in datasets])
if len(atts) > 0:
d.atts = atts
return d