def load_topology_realisations(path, **args):
"""
Loads all model topology realisations and returns them as an array of NoddyTopology objects
**Arguments**:
- *path* = The root directory that models should be loaded from. All models with the same base_name
as this class will be loaded (including subdirectoriess)
**Optional Arguments**:
- *load_attributes* = True if nodes and edges in the topology network should be
attributed with properties such as volume
and surface area and lithology colour. Default is True.
- *verbose* = True if this function should write debug information to the print buffer. Default is True.
**Returns**:
- a list of NoddyTopology objects
"""
vb = args.get('verbose', True)
attr = args.get('load_attributes', True)
if vb:
print "Loading models in %s" % path
# array of topology objects
from pynoddy.output import NoddyTopology
topologies = []
for root, dirnames, filenames in os.walk(path): # walk the directory
for f in filenames:
if '.g23' in f: # find all topology files
base = os.path.join(root, f.split('.')[0])
if vb:
print 'Loading %s' % base
# load & store topology
topologies.append(NoddyTopology(base,
load_attributes=attr))
return topologies
def test_resolution(self, numTrials, **kwds):
'''Tests the sensitivity of a model to block size by generating models of different
resolutions and comparing them.
**Arguments**:
- *numTrials* = the number of different model resolutions to test
**Optional Keywords**:
- *cleanup* = True if this function should delete any models it creates. Otherwise models of different resolutions
are left in the same directory as the .his file they derive from. Default is True.
- *verbose* = If true, this function sends information to the print buffer. Otherwise it runs silently. Default is False.
**Returns**:
- The function returns a list containing the cumulative number of model topologies
observed, starting from the highest resolution (smallest block size) to the lowest block
size (largest block size)
'''
#get args
outFile = kwds.get("output", "")
cleanup = kwds.get("cleanup", True)
verbose = kwds.get("verbose", False)
#import pynoddy bindings
import pynoddy
#store null volume threshold and then set to zero
old_threshold = pynoddy.null_volume_threshold
pynoddy.null_volume_threshold = 0
#place to keep topologies
self.topo_list = []
self.res_list = []
self.nUnique = 0 #number of unique topologies
self.count = [] #number of differen topologies observed at each step
self.size = [] #number of edges (relationships) observed at each step
#run test
step = (self.maxSize -
self.minSize) / numTrials #step change between resolutions
for res in range(self.minSize, self.maxSize, step):
if verbose:
print(("Computing model with %d block size" % res))
#change cube size
self.change_cube_size(res)
self.change_cube_size(res)
print("Cube size: %d:" % self.get_cube_size())
#store cube size
self.res_list.append(res)
#save history file
basename = self.path + "_cube_size_%d" % res
self.write_history(basename + ".his")
#run saved history file
if verbose:
print(("Running resolution %d... " % res))
print((pynoddy.compute_model(basename + ".his",
basename + "_0001",
sim_type="TOPOLOGY")))
print("Complete.\n")
else:
pynoddy.compute_model(basename + ".his",
basename + "_0001",
sim_type="TOPOLOGY")
#calculate topology
if verbose:
print('Computing model topologies...')
print((pynoddy.compute_topology(basename)))
print('Finished.\n')
else:
pynoddy.compute_topology(basename, 1)
#load and store topology output
topo = NoddyTopology(basename + "_0001")
#cull small nodes
#topo.filter_node_volumes(self.min_node_volume)
#see if this is on the list
if topo.is_unique(self.topo_list):
self.nUnique += 1 #increment unique topologies
#store cumulative sequence
self.count.append(self.nUnique)
#add to list of observed topologies
self.topo_list.append(topo)
#append number of edges to edges list
self.size.append(topo.graph.number_of_edges())
#cleanup
if cleanup:
import os, glob
#remove noddy files
for f in glob.glob(basename + "*"):
os.remove(f)
print("Complete. A total of %d topologies were observed" %
self.nUnique)
print("The size of the network at each step was:")
print(self.size)
print("The cumulative observation sequence was:")
print(self.count)
#restore
pynoddy.null_volume_threshold = old_threshold
return self.count
