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Minimal changes in the doc
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Michel Ferrero
parent
eb8060c290
commit
217f933634
9
doc/_templates/sideb_appli.html
vendored
9
doc/_templates/sideb_appli.html
vendored
@ -1,9 +0,0 @@
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<p>
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<a href="http://ipht.cea.fr"> <img style="width: 80px; margin: 10px 5px 0 0" src='_static/logo_cea.png' alt="CEA"/> </a>
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<a href="http://www.cpht.polytechnique.fr"> <img style="width: 80px; margin: 10px 5px 0 5px" src='_static/logo_x.png' alt="Ecole Polytechnique"/> </a>
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<br>
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<a href="http://www.cnrs.fr"> <img style="width: 80px; margin: 10px 0 0 5px" src='_static/logo_cnrs.png' alt="CNRS"/> </a>
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<img style="width: 80px; margin: 10px 0 0 5px" src='_static/logo_erc.jpg' alt="ERC"/>
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</p>
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@ -4,11 +4,16 @@
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Changelog
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=========
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This document describes the main changes in TRIQS 1.0 that might
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have consequences for your scripts and archives.
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This document describes the main changes in TRIQS.
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From TRIQS 0.x to TRIQS 1.0
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---------------------------
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There have been changes from versions 0.x to 1.0 that will most likely have
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consequences for your scripts and archives.
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Python classes
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--------------
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~~~~~~~~~~~~~~
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The number of python classes in the old 0.x releases was increasing with no
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clear naming convention. In TRIQS 1.0 we have unified the naming of the classes
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@ -17,9 +22,17 @@ following the `PEP naming conventions
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* Package and module names: lowercase with underscores
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* Class names: CapWords
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* Function names: lowercase with underscores
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* Function and method arguments: lowercase with underscores
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Archives
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--------
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~~~~~~~~
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We provide :download:`an update script <scripts/update_archive.py>` which should
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help you upgrade your archive. The usage is very simple::
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$ python update_archive.py old_archive new_archive
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where ``old_archive`` is your old archive to be upgraded and ``new_archive`` is
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the name of the new archive. If you encounter problems please post an
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issue with a copy of your archive.
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@ -10,5 +10,6 @@ Table of contents
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documentation
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applications
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issues
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changelog
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about
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@ -80,4 +80,3 @@ Further reading
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installation/install_options
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installation/python
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installation/clang
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installation/changelog
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222
doc/scripts/update_archive.py
Normal file
222
doc/scripts/update_archive.py
Normal file
@ -0,0 +1,222 @@
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import h5py
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import sys
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import numpy
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if len(sys.argv) < 3:
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print "Usage: python update_archive.py old_archive new_archive"
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sys.exit()
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print """
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This script is an attempt to update your archive to TRIQS 1.0.
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Please keep a copy of your old archive as this script is
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** not guaranteed ** to work for your archive.
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If you encounter any problem please report it on github!
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"""
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# The dictionary of modifications to make
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modifications = {
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'GF': {'SSS': 'BlockGf', '__Name': 'name', '__Note': 'note', '__BlockIndicesList': 'indices'},
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'GFBloc_ImFreq': {'SSS': 'GfImFreq'},
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'GFBloc_ReFreq': {'SSS': 'GfReFreq'},
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'GFBloc_ImTime': {'SSS': 'GfImTime'},
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'GFBloc_ReTime': {'SSS': 'GfReTime'},
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'GFBloc_ImLegendre': {'SSS': 'GfLegendre'},
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'MeshGF': {'SSS': 'MeshGf'},
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'TailGF': {'SSS': 'TailGf'},
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'DOS': {'Name': 'name'},
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'BlockGf': {'__Name': 'name', '__Note': 'note', '__BlockIndicesList': 'indices'}
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}
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def sanitize_imfreq(origin, dest):
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dest.create_dataset(name="data", data=origin["Data"].value.transpose((2,0,1,3)))
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dest["data"].attrs.create('__complex__', "1")
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dest.create_group(name="indices")
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exec("indL = %s"%origin["IndicesL"].value)
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exec("indR = %s"%origin["IndicesR"].value)
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indL = [ str(i) for i in indL ]
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indR = [ str(i) for i in indR ]
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dest["indices"].create_dataset(name="left", data=indL)
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dest["indices"].create_dataset(name="right", data=indR)
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dest.create_group(name="singularity")
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dest["singularity"].create_dataset(name="data", data=origin["Tail"]["array"].value.transpose((2,0,1,3)))
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dest["singularity"]["data"].attrs.create('__complex__', "1")
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dest["singularity"].create_dataset(name="omin", data=origin["Tail"]["OrderMinMIN"].value)
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mask = numpy.zeros( dest["singularity"]["data"].shape[0:2], numpy.integer )
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mask.fill(origin["Tail"]["OrderMax"].value)
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dest["singularity"].create_dataset(name="mask", data=mask)
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dest.create_group(name="mesh")
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beta = origin["Mesh"]["Beta"].value
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pi = numpy.arccos(-1)
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size = numpy.uint(len(origin["Mesh"]["array"].value))
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dest["mesh"].create_dataset(name="kind", data=2)
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dest["mesh"].create_dataset(name="min", data=pi/beta)
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dest["mesh"].create_dataset(name="max", data=(2*size+1)*pi/beta)
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dest["mesh"].create_dataset(name="size", data=size)
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dest["mesh"].create_group(name="domain")
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dest["mesh"]["domain"].create_dataset(name="beta", data=beta)
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dest["mesh"]["domain"].create_dataset(name="statistic", data={"Fermion":"F", "Boson":"B"}[origin["Mesh"]["Statistic"].value] )
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return ['Data', 'IndicesL', 'IndicesR', 'Mesh', 'Name', 'Note', 'Tail']
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def sanitize_imtime(origin, dest):
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dest.create_dataset(name="data", data=origin["Data"].value.transpose((2,0,1)))
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dest.create_group(name="indices")
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exec("indL = %s"%origin["IndicesL"].value)
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exec("indR = %s"%origin["IndicesR"].value)
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indL = [ str(i) for i in indL ]
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indR = [ str(i) for i in indR ]
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dest["indices"].create_dataset(name="left", data=indL)
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dest["indices"].create_dataset(name="right", data=indR)
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dest.create_group(name="singularity")
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dest["singularity"].create_dataset(name="data", data=origin["Tail"]["array"].value.transpose((2,0,1,3)))
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dest["singularity"]["data"].attrs.create('__complex__', "1")
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dest["singularity"].create_dataset(name="omin", data=origin["Tail"]["OrderMinMIN"].value)
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mask = numpy.zeros( dest["singularity"]["data"].shape[0:2], numpy.integer )
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mask.fill(origin["Tail"]["OrderMax"].value)
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dest["singularity"].create_dataset(name="mask", data=mask)
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dest.create_group(name="mesh")
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beta = origin["Mesh"]["Beta"].value
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size = numpy.uint(len(origin["Mesh"]["array"].value))
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min_t = origin["Mesh"]["array"].value[0]
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if min_t > 1e-10:
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kind = 0
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assert(abs(min_t - 0.5*beta/size) < 1e-10)
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else:
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kind = 2
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dest["mesh"].create_dataset(name="kind", data=kind)
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dest["mesh"].create_dataset(name="min", data=0.0)
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dest["mesh"].create_dataset(name="max", data=beta)
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dest["mesh"].create_dataset(name="size", data=size)
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dest["mesh"].create_group(name="domain")
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dest["mesh"]["domain"].create_dataset(name="beta", data=beta)
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dest["mesh"]["domain"].create_dataset(name="statistic", data={"Fermion":"F", "Boson":"B"}[origin["Mesh"]["Statistic"].value] )
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return ['Data', 'IndicesL', 'IndicesR', 'Mesh', 'Name', 'Note', 'Tail']
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def sanitize_legendre(origin, dest):
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dest.create_dataset(name="data", data=origin["Data"].value.transpose((2,0,1,3)))
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dest.create_group(name="indices")
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exec("indL = %s"%origin["IndicesL"].value)
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exec("indR = %s"%origin["IndicesR"].value)
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indL = [ str(i) for i in indL ]
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indR = [ str(i) for i in indR ]
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dest["indices"].create_dataset(name="left", data=indL)
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dest["indices"].create_dataset(name="right", data=indR)
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dest.create_group(name="mesh")
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beta = origin["Mesh"]["Beta"].value
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size = numpy.uint(len(origin["Mesh"]["array"].value))
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dest["mesh"].create_group(name="domain")
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dest["mesh"]["domain"].create_dataset(name="beta", data=beta)
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dest["mesh"]["domain"].create_dataset(name="n_max", data=size)
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dest["mesh"]["domain"].create_dataset(name="statistic", data={"Fermion":"F", "Boson":"B"}[origin["Mesh"]["Statistic"].value] )
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return ['Data', 'IndicesL', 'IndicesR', 'Mesh', 'Name', 'Note', 'Tail']
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def sanitize_refreq(origin, dest):
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dest.create_dataset(name="data", data=origin["Data"].value.transpose((2,0,1,3)))
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dest["data"].attrs.create('__complex__', "1")
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dest.create_group(name="indices")
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exec("indL = %s"%origin["IndicesL"].value)
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exec("indR = %s"%origin["IndicesR"].value)
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indL = [ str(i) for i in indL ]
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indR = [ str(i) for i in indR ]
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dest["indices"].create_dataset(name="left", data=indL)
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dest["indices"].create_dataset(name="right", data=indR)
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dest.create_group(name="singularity")
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dest["singularity"].create_dataset(name="data", data=origin["Tail"]["array"].value.transpose((2,0,1,3)))
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dest["singularity"]["data"].attrs.create('__complex__', "1")
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dest["singularity"].create_dataset(name="omin", data=origin["Tail"]["OrderMinMIN"].value)
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mask = numpy.zeros( dest["singularity"]["data"].shape[0:2], numpy.integer )
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mask.fill(origin["Tail"]["OrderMax"].value)
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dest["singularity"].create_dataset(name="mask", data=mask)
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dest.create_group(name="mesh")
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size = numpy.uint(len(origin["Mesh"]["array"].value))
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min_w = origin["Mesh"]["array"].value[0]
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max_w = origin["Mesh"]["array"].value[-1]
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dest["mesh"].create_dataset(name="kind", data=1)
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dest["mesh"].create_dataset(name="min", data=min_w)
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dest["mesh"].create_dataset(name="max", data=max_w)
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dest["mesh"].create_dataset(name="size", data=size)
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return ['Data', 'IndicesL', 'IndicesR', 'Mesh', 'Name', 'Note', 'Tail']
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def copy_and_correct(origin, dest):
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scheme = None
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exclude = []
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# copy attributes in destination archive
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for at in origin.attrs.keys():
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# figure if the group is a TRIQS scheme
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if at == 'TRIQS_HDF5_data_scheme':
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scheme = origin.attrs['TRIQS_HDF5_data_scheme']
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try:
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new_name = modifications[scheme]['SSS']
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except:
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new_name = scheme
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dest.attrs.create('TRIQS_HDF5_data_scheme', new_name)
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else:
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dest.attrs.create(at, origin.attrs[at])
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# some special cases here
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if scheme == "GFBloc_ImFreq" or scheme == "GfImFreq": exclude = sanitize_imfreq(origin, dest)
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if scheme == "GFBloc_ImTime" or scheme == "GfImTime": exclude = sanitize_imtime(origin, dest)
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if scheme == "GFBloc_ReFreq" or scheme == "GfReFreq": exclude = sanitize_refreq(origin, dest)
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if scheme == "GFBloc_ImLegendre" or scheme == "GfLegendre": exclude = sanitize_legendre(origin, dest)
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# copy the rest
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for key in [ o for o in origin if o not in exclude ]:
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# key is a dataset
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if hasattr(origin[key],'value'):
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# check if dataset needs renaming
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try:
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new_key = modifications[scheme][key]
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except:
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new_key = key
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# create dataset and copy data as well as attributes in destination archive
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dest.create_dataset(name=new_key, data=origin[key].value)
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for at in origin[key].attrs.keys():
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dest[key].attrs.create(at, origin[key].attrs[at])
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# key is a group
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else:
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dest.create_group(name=key)
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copy_and_correct(origin[key], dest[key])
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# Let's do it
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A = h5py.File(sys.argv[1],'r')
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B = h5py.File(sys.argv[2],'w')
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print "Starting update..."
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copy_and_correct(A,B)
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print "Update done and written in", sys.argv[2]
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@ -1,6 +1,44 @@
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.. _versions:
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Version compatibility
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=====================
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As the TRIQS library and applications based on it might live separate lives, it
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is important to define a clear version compatibility scheme.
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TRIQS version numbering
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-----------------------
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The TRIQS library has three-digit *release* numbers (e.g. 1.0.5) and two-digit
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*version* numbers (e.g. 1.0). The first two digits of the release number always
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correspond to the version number.
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New releases within the same version correspond to bug fixes and improvements
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that do not change the API of the library. In other words, applications based
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on the TRIQS library do not need to be changed between such releases of the
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TRIQS library. Instead, a modification of the version number, say from 1.0 to
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1.1, indicates deeper modifications of the library with possible breaks of the
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API. In that case, the source codes of the applications might need to be
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modified.
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TRIQS applications version numbering
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------------------------------------
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In order to easily identify which versions of an application are compatible
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with given versions of TRIQS, the applications follow a similar version
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numbering: three-digit release numbers and two-digit version numbers. The
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compatibility rule is then simply that *an application is compatible with the
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TRIQS library if it has the same version number*.
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How to figure the version of the installed TRIQS library
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--------------------------------------------------------
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In order to figure the version of an installed TRIQS library, you can
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either:
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* Read the content of the ``version.hpp`` file which is in the
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``path_to_install_directory/include/triqs/`` diretory.
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* Run ``pytriqs`` and type the following commands::
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from pytriqs.version import *
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show_version()
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