mirror of
https://github.com/wassname/simpeg.git
synced 2026-07-01 10:02:16 +08:00
Removed (now broken) database stuff.
This commit is contained in:
rowanc1
+1
-1
@@ -4,7 +4,7 @@ import Utils, numpy as np
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class BaseData(object):
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"""Data holds the observed data, and the standard deviations."""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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std = None #: Estimated Standard Deviations
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dobs = None #: Observed data
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+1
-1
@@ -7,7 +7,7 @@ class BaseInversion(object):
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"""BaseInversion(objFunc, opt, **kwargs)
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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name = 'BaseInversion'
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@@ -26,7 +26,7 @@ class LogicallyOrthogonalMesh(BaseMesh, DiffOperators, InnerProducts, LomView):
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M.plotGrid(showIt=True)
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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_meshType = 'LOM'
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@@ -33,7 +33,7 @@ class TensorMesh(BaseMesh, TensorView, DiffOperators, InnerProducts):
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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_meshType = 'TENSOR'
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+1
-1
@@ -7,7 +7,7 @@ class BaseModel(object):
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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counter = None #: A SimPEG.Utils.Counter object
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mesh = None #: A SimPEG Mesh
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@@ -3,7 +3,7 @@ import Utils, Parameters, numpy as np, scipy.sparse as sp
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class BaseObjFunction(object):
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"""BaseObjFunction(data, reg, **kwargs)"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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beta = Parameters.ParameterProperty('beta', default=1, doc='Regularization trade-off parameter')
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@@ -82,7 +82,7 @@ class Minimize(object):
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Minimize is a general class for derivative based optimization.
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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name = "General Optimization Algorithm" #: The name of the optimization algorithm
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+1
-1
@@ -34,7 +34,7 @@ class BaseProblem(object):
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to (locally) find how model parameters change the data, and optimize!
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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counter = None #: A SimPEG.Utils.Counter object
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@@ -10,7 +10,7 @@ class BaseRegularization(object):
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"""
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__metaclass__ = Utils.Save.Savable
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__metaclass__ = Utils.SimPEGMetaClass
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modelPair = Model.BaseModel #: Some regularizations only work on specific models
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@@ -1,352 +0,0 @@
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import numpy as np
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import time
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import re
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try:
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import h5py
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except Exception, e:
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print 'Warning: SimPEG.Utils.Save needs h5py to be installed.'
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SAVEABLES = {}
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def natural_keys(text):
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'''
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alist.sort(key=natural_keys) sorts in human order
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http://nedbatchelder.com/blog/200712/human_sorting.html
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(See Toothy's implementation in the comments)
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'''
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atoi = lambda text: int(text) if text.isdigit() else text
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return [ atoi(c) for c in re.split('(\d+)', text) ]
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def preIteration(group):
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group.attrs['complete'] = False
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group.attrs['time'] = time.time()
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def postIteration(group):
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group.attrs['time'] = time.time() - group.attrs['time']
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group.attrs['date'] = time.ctime()
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group.attrs['complete'] = True
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class SimPEGTable:
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"""
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This is a wrapper class on the HDF5 file.
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"""
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def __init__(self, name, mode='a'):
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if '.hdf5' not in name:
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name += '.hdf5'
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self.f = h5py.File(name, mode)
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self.root = hdf5Group(self,self.f)
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self.inversions = hdf5InversionGroup(self,self.root.addGroup('inversions',soft=True))
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def show(self): self.root.show()
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def saveInversion(self, invObj):
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# Create a new inversion anytime this is run.
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def _startup_hdf5_inv(invObj, m0):
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node = self.inversions.addGroup('%d'%self.inversions.numChildren)
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saveSavable(invObj,node.addGroup('rebuild'))
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results = node.addGroup('results')
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preIteration(results)
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invObj._invNode = results
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self.f.flush()
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invObj.hook(_startup_hdf5_inv, overwrite=True)
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# At the start of every iteration we will create a inversion iteration node.
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def _doStartIteration_hdf5_inv(invObj):
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invObj._invNodeIt = invObj._invNode.addGroup('%d'%(invObj.iter+1))
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preIteration(invObj._invNodeIt)
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invObj.hook(_doStartIteration_hdf5_inv, overwrite=True)
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def _doEndIteration_hdf5_inv(invObj):
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invObj.save(invObj._invNodeIt)
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postIteration(invObj._invNodeIt)
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self.f.flush()
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invObj.hook(_doEndIteration_hdf5_inv, overwrite=True)
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# Delete all iterates that did not finish.
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def _finish_hdf5_inv(invObj):
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postIteration(invObj._invNode)
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for it in invObj._invNode:
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if not it.attrs['complete']:
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del self.f[it.path]
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del invObj._invNode
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self.f.flush()
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invObj.hook(_finish_hdf5_inv, overwrite=True)
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def _doStartIteration_hdf5_opt(optObj):
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optObj._optNodeIt = optObj.parent._invNode.addGroup('%d.%d'%(optObj.parent.iter, optObj.iter))
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preIteration(optObj._optNodeIt)
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invObj.opt.hook(_doStartIteration_hdf5_opt, overwrite=True)
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def _doEndIteration_hdf5_opt(optObj, xt):
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optObj.save(optObj._optNodeIt)
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postIteration(optObj._optNodeIt)
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self.f.flush()
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invObj.opt.hook(_doEndIteration_hdf5_opt, overwrite=True)
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class hdf5Group(object):
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"""Has some low level support for wrapping the native HDF5-Group class"""
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def __init__(self, T, groupNode):
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self.T = T
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# check if you are inputing a hdf5Group rather than a raw node, and act accordingly
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if issubclass(groupNode.__class__, hdf5Group):
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self.node = groupNode.node
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else:
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self.node = groupNode
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self.childClass = hdf5Group
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self.parentClass = hdf5Group
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@property
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def children(self):
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"""Children names in a list
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Use obj[name] to return the actual node.
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"""
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myChildren = [c for c in self.node]
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myChildren.sort(key=natural_keys)
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return myChildren
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@property
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def numChildren(self):
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"""Returns the len(children)"""
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return len(self.children)
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@property
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def parent(self):
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"""Returns parent node"""
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return self.parentClass(self.T, self.node.parent)
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@property
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def name(self):
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return self.path.split('/')[-1]
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@property
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def path(self):
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"""Returns the root path of the group"""
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return self.node.name
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@property
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def attrs(self):
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"""Returns a list of attributes in the group"""
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return self.node.attrs
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def addGroup(self, name, soft=False):
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"""Adds a child group to the current node."""
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if name in self.children and soft:
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return self[name]
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assert name not in self.children, 'Already a child called: '+self.path+'/'+name
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return self.childClass(self.T, self.node.create_group(name))
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def setArray(self, name, data):
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a = self.node.create_dataset(name, data.shape)
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a[...] = data
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return a
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def __getitem__(self, val):
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if type(val) is int:
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val = self.children[val]
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child = self.node[val]
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if type(child) is h5py.Group:
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child = self.childClass(self.T, child)
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return child
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def __contains__(self, key):
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return key in self.children
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def show(self, pad='', maxDepth=1, depth=0):
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"""
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Recursively show the structure of the database.
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For example::
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<hdf5InversionGroup group "/inversions" (1 member)>
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- <hdf5Inversion group "/inversions/0" (4 members)>
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- <hdf5InversionIteration group "/inversions/0/0.0" (3 members)>
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- <hdf5InversionIteration group "/inversions/0/0.1" (3 members)>
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- <hdf5InversionIteration group "/inversions/0/0.2" (3 members)>
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- <hdf5InversionIteration group "/inversions/0/0.3" (3 members)>
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"""
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s = self.__str__()
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pad += ' '*4
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if maxDepth <= 0: print s
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if depth >= maxDepth: return s
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for c in self.children:
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if issubclass(self[c].__class__, hdf5Group):
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s += '\n%s- %s' % (pad, self[c].show(pad=pad,depth=depth+1,maxDepth=maxDepth))
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else:
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s += '\n%s- %s' % (pad, self[c].__str__())
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if depth is 0:
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print s
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else:
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return s
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def __str__(self):
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return '<%s "%s" (%d member%s, attrs=[%s])>' % (self.__class__.__name__, self.path, self.numChildren, '' if self.numChildren == 1 else 's',', '.join([a for a in self.attrs]))
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class hdf5InversionGroup(hdf5Group):
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def __init__(self, T, groupNode):
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hdf5Group.__init__(self, T, groupNode)
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self.childClass = hdf5Inversion
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class hdf5Inversion(hdf5Group):
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def __init__(self, T, groupNode):
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hdf5Group.__init__(self, T, groupNode)
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self.parentClass = hdf5InversionGroup
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self.childClass = hdf5InversionResults
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def rebuild(self):
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return loadSavable(self['rebuild'])
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@property
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def results(self): return self['results']
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class hdf5InversionResults(hdf5Group):
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def __init__(self, T, groupNode):
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hdf5Group.__init__(self, T, groupNode)
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self.parentClass = hdf5Inversion
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self.childClass = hdf5InversionIteration
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class hdf5InversionIteration(hdf5Group):
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def __init__(self, T, groupNode):
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hdf5Group.__init__(self, T, groupNode)
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self.parentClass = hdf5InversionResults
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class Savable(type):
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def __new__(cls, name, bases, attrs):
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__init__ = attrs['__init__']
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def init_wrapper(self, *args, **kwargs):
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self._args_init = args
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self._kwargs_init = kwargs
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return __init__(self, *args,**kwargs)
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attrs['__init__'] = init_wrapper
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newClass = super(Savable, cls).__new__(cls, name, bases, attrs)
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SAVEABLES[name] = newClass
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return newClass
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def saveSavable(obj, group, debug=False):
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"""
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This creates softlinks if _savable exists in children object.
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The first object is always created.
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"""
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assert type(obj.__class__) is Savable, 'Can only save objects that are Savable objects.'
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def doSave(grp, name, val):
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if debug: print name, val
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if type(val.__class__) is Savable:
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link = getattr(val,'_savable',None)
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if link is not None:
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group.node[name] = h5py.SoftLink(link.path)
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if debug: 'Created a softlink path to %s' % link.path
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else:
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subgrp = grp.addGroup(name)
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saveSavable(val, subgrp, debug=debug)
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elif type(val) in [list, tuple]:
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# Split up, and save each element
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for i, v in enumerate(val):
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doSave(grp, name + '[%d]'%i, v)
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elif type(val) is np.ndarray:
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grp.setArray(name, val)
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elif val is None:
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grp.attrs[name] = 'None'
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else:
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# just try saving it as an attr
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try:
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grp.attrs[name] = val
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except Exception, e:
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print 'Warning: Could not save %s, problems may arise in loading.' % name
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group.attrs['__class__'] = obj.__class__.__name__
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for arg in obj._kwargs_init:
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doSave(group, '_kwarg_'+arg, obj._kwargs_init[arg])
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for i, arg in enumerate(obj._args_init):
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doSave(group, '_arg%d'%i, arg)
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obj._savable = group
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def loadSavable(node, pointers=None):
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"""
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pointers allow things that point to the same node in the h5py file to
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be returned as the same object, if they have already been created.
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"""
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if pointers is None: pointers = []
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for pointer in pointers:
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if pointer._savable.node == node.node: return pointer
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args = ([a for a in node.attrs if '_arg' in a] + [a for a in node.children if '_arg' in a])
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kwargs = ([a for a in node.attrs if '_kwarg' in a] + [a for a in node.children if '_kwarg' in a])
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args.sort(key=natural_keys)
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kwargs.sort(key=natural_keys)
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def get(node,key):
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if key in node.children: return node[key]
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elif key in node.attrs: return node.attrs[key]
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ARGS = []
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for name in args:
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val = get(node, name)
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if val.__class__ is h5py.Dataset: val = val[:]
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if val is 'None': val = None
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if '[' in name: # We are reloading a list
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ind = int(name[4:name.index('[')])
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if len(ARGS) is ind: # Create the list
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ARGS.append([val])
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else:
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ARGS[ind].append(val)
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elif issubclass(val.__class__,hdf5Group):
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ARGS.append(loadSavable(val,pointers=pointers))
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else:
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ind = int(name[4:])
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ARGS.append(val)
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KWARGS = {}
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for name in kwargs:
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val = get(node, name)
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if val.__class__ is h5py.Dataset: val = val[:]
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if val is 'None': val = None
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if '[' in name: # We are reloading a list
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key = name[7:name.index('[')]
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if key not in KWARGS: # Create the list
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KWARGS[key] = [val]
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else:
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KWARGS[key].append(val)
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elif issubclass(val.__class__,hdf5Group):
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key = name[7:]
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KWARGS[key] = loadSavable(val,pointers=pointers)
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else:
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key = name[7:]
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KWARGS[key] = val
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cls = get(node, '__class__')
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if cls in SAVEABLES:
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try:
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out = SAVEABLES[cls](*ARGS, **KWARGS)
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out._savable = node
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pointers.append(out) # Because this is recursive.
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return out
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except Exception, e:
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print 'Warning: %s Class could not be initiated.' % cls
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print 'ARGS: ', ARGS
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print 'KWARGS: ', KWARGS
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return (cls, ARGS, KWARGS, node)
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else:
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print 'Warning: %s Class not found in SimPEG.Utils.Save.SAVABLES' % cls
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return (cls, ARGS, KWARGS, node)
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@@ -4,7 +4,6 @@ from meshutils import exampleLomGird, meshTensors
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from lomutils import volTetra, faceInfo, inv2X2BlockDiagonal, inv3X3BlockDiagonal, indexCube
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from interputils import interpmat
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from ipythonutils import easyAnimate as animate
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import Save
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import ModelBuilder
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import types
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@@ -12,6 +11,12 @@ import time
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import numpy as np
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from functools import wraps
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class SimPEGMetaClass(type):
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def __new__(cls, name, bases, attrs):
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return super(SimPEGMetaClass, cls).__new__(cls, name, bases, attrs)
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def hook(obj, method, name=None, overwrite=False, silent=False):
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"""
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This dynamically binds a method to the instance of the class.
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