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Commit ad44ca0a authored by Martin Reinecke's avatar Martin Reinecke
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docs/howtogenerate.txt deleted 100644 → 0
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Two step creation of webpages:
sphinx-apidoc -l -e -d 3 -o sphinx/source/mod/ nifty/ nifty/plotting/ nifty/spaces/power_space/power_indices.py nifty/spaces/power_space/power_index_factory.py nifty/config/ nifty/basic_arithmetics.py nifty/nifty_meta.py nifty/random.py nifty/version.py nifty/field_types/ nifty/operators/fft_operator/transformations/rg_transforms.py
creates all .rst files neccesary for ModuleIndex excluding helper modules
sphinx-build -b html sphinx/source/ sphinx/build/
generates html filel amd build directory
docs/source/_static/style.css deleted 100644 → 0
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/* override table width restrictions */
.wy-nav-content {
max-width: none;
}
docs/source/_templates/layout.html deleted 100644 → 0
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{% extends "!layout.html" %}
{% block extrahead %}
<link href="{{ pathto("_static/style.css", True) }}" rel="stylesheet" type="text/css">
{% endblock %}
docs/source/conf.py deleted 100644 → 0
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# -*- coding: utf-8 -*-
#
# NIFTY documentation build configuration file, created by
# sphinx-quickstart on Tue May 16 10:22:50 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
from nifty import *
import sys
import os
import sphinx_rtd_theme
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#sys.path.insert(0, os.path.abspath('.'))
napoleon_google_docstring = False
napoleon_numpy_docstring = True
napoleon_use_ivar = True
napoleon_use_param = False
napoleon_use_keyword = False
autodoc_member_order='groupwise'
#autosummary_generate = True
numpydoc_show_inherited_class_members=False
numpydoc_class_members_toctree=False
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
'sphinx.ext.autodoc',
'numpydoc',
'sphinx.ext.autosummary',
'sphinx.ext.napoleon',
'sphinx.ext.coverage',
'sphinx.ext.todo',
'sphinx.ext.mathjax',
'sphinx.ext.viewcode'
]
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix(es) of source filenames.
# You can specify multiple suffix as a list of string:
# source_suffix = ['.rst', '.md']
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = u'NIFTY'
copyright = u'2013-2017, Max-Planck-Society'
author = u'Theo Steininger'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = u'3.0'
# The full version, including alpha/beta/rc tags.
release = u'3.0.4'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = []
# The reST default role (used for this markup: `text`) to use for all
# documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# If true, keep warnings as "system message" paragraphs in the built documents.
#keep_warnings = False
# If true, `todo` and `todoList` produce output, else they produce nothing.
todo_include_todos = True
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = "sphinx_rtd_theme"
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
html_theme_options = {
'collapse_navigation': False,
'display_version': False,
'navigation_depth': 3,
}
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = []
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
html_logo = 'nifty_logo_white.png'
# The name of an image file (relative to this directory) to use as a favicon of
# the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied
# directly to the root of the documentation.
#html_extra_path = []
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
html_domain_indices = False
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
#html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
#html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Language to be used for generating the HTML full-text search index.
# Sphinx supports the following languages:
# 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja'
# 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr'
#html_search_language = 'en'
# A dictionary with options for the search language support, empty by default.
# Now only 'ja' uses this config value
#html_search_options = {'type': 'default'}
# The name of a javascript file (relative to the configuration directory) that
# implements a search results scorer. If empty, the default will be used.
#html_search_scorer = 'scorer.js'
# Output file base name for HTML help builder.
htmlhelp_basename = 'NIFTYdoc'
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#'preamble': '',
# Latex figure (float) alignment
#'figure_align': 'htbp',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(master_doc, 'NIFTY.tex', u'NIFTY Documentation',
u'NIFTY', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
#latex_logo = None
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
#latex_use_parts = False
# If true, show page references after internal links.
#latex_show_pagerefs = False
# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output ---------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
(master_doc, 'nifty', u'NIFTY Documentation',
[author], 1)
]
# If true, show URL addresses after external links.
#man_show_urls = False
# -- Options for Texinfo output -------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
(master_doc, 'NIFTY', u'NIFTY Documentation',
author, 'NIFTY', 'One line description of project.',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
#texinfo_appendices = []
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# If true, do not generate a @detailmenu in the "Top" node's menu.
#texinfo_no_detailmenu = False
# Example configuration for intersphinx: refer to the Python standard library.
#intersphinx_mapping = {'https://docs.python.org/': None}
\ No newline at end of file
docs/source/field.rst deleted 100644 → 0
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.. currentmodule:: nifty
The ``Field`` class -- Basic class to define fields over spaces
...............................................................
The discrete representation of a continuous field over multiple spaces.
In NIFTY, Fields are used to store data arrays and carry all the needed metainformation (i.e. the domain) for operators to be able to work on them. In addition Field has methods to work with power-spectra.
.. autoclass:: Field
:show-inheritance:
:members:
docs/source/gallery.rst deleted 100644 → 0
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Image Gallery
-------------
Transformations & Projections
.............................
.. currentmodule:: nifty
The "Faraday Map" [1]_ in spherical representation on a :py:class:`hp_space` and a :py:class:`gl_space`, their quadrupole projections, the uncertainty of the map, and the angular power spectrum.
+----------------------------+----------------------------+
| .. image:: images/f_00.png | .. image:: images/f_01.png |
| :width: 90 % | :width: 90 % |
+----------------------------+----------------------------+
| .. image:: images/f_02.png | .. image:: images/f_03.png |
| :width: 90 % | :width: 90 % |
+----------------------------+----------------------------+
| .. image:: images/f_04.png | .. image:: images/f_05.png |
| :width: 90 % | :width: 70 % |
+----------------------------+----------------------------+
Gaussian random fields
......................
Statistically homogeneous and isotropic Gaussian random fields drawn from different power spectra.
+----------------------------+----------------------------+
| .. image:: images/t_03.png | .. image:: images/t_04.png |
| :width: 60 % | :width: 70 % |
+----------------------------+----------------------------+
| .. image:: images/t_05.png | .. image:: images/t_06.png |
| :width: 60 % | :width: 70 % |
+----------------------------+----------------------------+
Wiener filtering I
..................
Wiener filter reconstruction of Gaussian random signal.
+--------------------------------+--------------------------------+--------------------------------+
| original signal | noisy data | reconstruction |
+================================+================================+================================+
| .. image:: images/rg1_s.png | .. image:: images/rg1_d.png | .. image:: images/rg1_m.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+--------------------------------+--------------------------------+--------------------------------+
| .. image:: images/rg2_s_pm.png | .. image:: images/rg2_d_pm.png | .. image:: images/rg2_m_pm.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+--------------------------------+--------------------------------+--------------------------------+
| .. image:: images/hp_s.png | .. image:: images/hp_d.png | .. image:: images/hp_m.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+--------------------------------+--------------------------------+--------------------------------+
Image reconstruction
....................
Image reconstruction of the classic "Moon Surface" image. The original image "Moon Surface" was taken from the `USC-SIPI image database <http://sipi.usc.edu/database/>`_.
+-----------------------------------+-----------------------------------+-----------------------------------+
| .. image:: images/moon_s.png | .. image:: images/moon_d.png | .. image:: images/moon_m.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+-----------------------------------+-----------------------------------+-----------------------------------+
| .. image:: images/moon_kernel.png | .. image:: images/moon_mask.png | .. image:: images/moon_sigma.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+-----------------------------------+-----------------------------------+-----------------------------------+
Wiener filtering II
...................
Wiener filter reconstruction results for the full and partially blinded data. Shown are the original signal (orange), the reconstruction (green), and :math:`1\sigma`-confidence interval (gray).
+--------------------------------------+--------------------------------------+
| noisy data | reconstruction results |
+======================================+======================================+
| .. image:: images/rg1_d.png | .. image:: images/rg1_m_err_.png |
| :width: 90 % | :width: 90 % |
+--------------------------------------+--------------------------------------+
| .. image:: images/rg1_d_gap.png | .. image:: images/rg1_m_gap_err_.png |
| :width: 90 % | :width: 90 % |
+--------------------------------------+--------------------------------------+
D\ :sup:`3`\ PO -- Denoising, Deconvolving, and Decomposing Photon Observations
...............................................................................
Application of the D\ :sup:`3`\ PO algorithm [2]_ showing the raw photon count data and the denoised, deconvolved, and decomposed reconstruction of the diffuse photon flux.
+--------------------------------------+--------------------------------------+
| .. image:: images/D3PO_data.png | .. image:: images/D3PO_diffuse.png |
| :width: 95 % | :width: 95 % |
+--------------------------------------+--------------------------------------+
RESOLVE -- Aperature synthesis imaging in radio astronomy
.........................................................
Signal inference on simulated single-frequency data: reconstruction by CLEAN (using uniform weighting) and by RESOLVE [3]_ (using IFT & NIFTY).
+-------------------------------------+-------------------------------------+-------------------------------------+
| .. image:: images/radio_signal.png | .. image:: images/radio_CLEAN.png | .. image:: images/radio_RESOLVE.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+-------------------------------------+-------------------------------------+-------------------------------------+
D\ :sup:`3`\ PO -- light
........................
Inference of the mock distribution of some species across Australia exploiting geospatial correlations in a (strongly) simplified scenario [4]_.
+--------------------------------+--------------------------------+--------------------------------+
| .. image:: images/au_data.png | .. image:: images/au_map.png | .. image:: images/au_error.png |
| :width: 90 % | :width: 90 % | :width: 90 % |
+--------------------------------+--------------------------------+--------------------------------+
NIFTY meets Lensing
...................
Signal reconstruction for a simulated image that has undergone strong gravitational lensing. Without *a priori* knowledge of the signal covariance :math:`S`, a common approach rescaling the `Laplace-Operator <http://de.wikipedia.org/wiki/Laplace-Operator>`_ and IFT's `"critical" filter <./demo_excaliwir.html#critical-wiener-filtering>`_ are compared.
+--------------------------------+--------------------------------+--------------------------------+--------------------------------+
| .. image:: images/lens_s0.png | .. image:: images/lens_d0.png | .. image:: images/lens_m1.png | .. image:: images/lens_m2.png |
| :width: 80 % | :width: 80 % | :width: 80 % | :width: 80 % |
| | | | |
| | | .. math:: | .. math:: |
| | | S(x,y) &= | S(x,y) &= |
| | | \lambda \: \Delta^{-1} | S(|x-y|) |
| | | \\ \equiv | \\ \equiv |
| | | S(k,l) &= \delta(k-l) | S(k,l) &= \delta(k-l) |
| | | \: \lambda \: k^{-2} | \: P(k) |
+--------------------------------+--------------------------------+--------------------------------+--------------------------------+
.. [1] N. Oppermann et. al., "An improved map of the Galactic Faraday sky", Astronomy & Astrophysics, vol. 542, id. A93, p. 14, see also the `project homepage <http://www.mpa-garching.mpg.de/ift/faraday/>`_
.. [2] M. Selig et. al., "Denoising, Deconvolving, and Decomposing Photon Observations", submitted to Astronomy & Astrophysics, 2013; `arXiv:1311.1888 <http://www.arxiv.org/abs/1311.1888>`_
.. [3] H. Junklewitz et. al., "RESOLVE: A new algorithm for aperture synthesis imaging of extended emission in radio astronomy", submitted to Astronomy & Astrophysics, 2013; `arXiv:1311.5282 <http://www.arxiv.org/abs/1311.5282>`_
.. [4] M. Selig, "The NIFTY way of Bayesian signal inference", submitted proceeding of the 33rd MaxEnt, 2013
docs/source/ift.rst deleted 100644 → 0
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IFT -- Information Field Theory
===============================
Theoretical Background
----------------------
`Information Field Theory <http://www.mpa-garching.mpg.de/ift/>`_ [1]_ (IFT) is information theory, the logic of reasoning under uncertainty, applied to fields. A field can be any quantity defined over some space, e.g. the air temperature over Europe, the magnetic field strength in the Milky Way, or the matter density in the Universe. IFT describes how data and knowledge can be used to infer field properties. Mathematically it is a statistical field theory and exploits many of the tools developed for such. Practically, it is a framework for signal processing and image reconstruction.
IFT is fully Bayesian. How else can infinitely many field degrees of freedom be constrained by finite data?
It can be used without the knowledge of Feynman diagrams. There is a full toolbox of methods. It reproduces many known well working algorithms. This should be reassuring. And, there were certainly previous works in a similar spirit. Anyhow, in many cases IFT provides novel rigorous ways to extract information from data.
.. tip:: An *in-a-nutshell introduction to information field theory* can be found in [2]_.
.. [1] T. Ensslin et al., "Information field theory for cosmological perturbation reconstruction and nonlinear signal analysis", PhysRevD.80.105005, 09/2009; `arXiv:0806.3474 <http://www.arxiv.org/abs/0806.3474>`_
.. [2] T. Ensslin, "Information field theory", accepted for the proceedings of MaxEnt 2012 -- the 32nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; `arXiv:1301.2556 <http://arxiv.org/abs/1301.2556>`_
Discretized continuum
---------------------
The representation of fields that are mathematically defined on a continuous space in a finite computer environment is a common necessity. The goal hereby is to preserve the continuum limit in the calculus in order to ensure a resolution independent discretization.
+-----------------------------+-----------------------------+
| .. image:: images/42vs6.png | .. image:: images/42vs9.png |
| :width: 100 % | :width: 100 % |
+-----------------------------+-----------------------------+
Any partition of the continuous position space :math:`\Omega` (with volume :math:`V`) into a set of :math:`Q` disjoint, proper subsets :math:`\Omega_q` (with volumes :math:`V_q`) defines a pixelization,
.. math::
\Omega &\quad=\quad \dot{\bigcup_q} \; \Omega_q \qquad \mathrm{with} \qquad q \in \{1,\dots,Q\} \subset \mathbb{N}
, \\
V &\quad=\quad \int_\Omega \mathrm{d}x \quad=\quad \sum_{q=1}^Q \int_{\Omega_q} \mathrm{d}x \quad=\quad \sum_{q=1}^Q V_q
.
Here the number :math:`Q` characterizes the resolution of the pixelization and the continuum limit is described by :math:`Q \rightarrow \infty` and :math:`V_q \rightarrow 0` for all :math:`q \in \{1,\dots,Q\}` simultaneously. Moreover, the above equation defines a discretization of continuous integrals, :math:`\int_\Omega \mathrm{d}x \mapsto \sum_q V_q`.
Any valid discretization scheme for a field :math:`{s}` can be described by a mapping,
.. math::
s(x \in \Omega_q) \quad\mapsto\quad s_q \quad=\quad \int_{\Omega_q} \mathrm{d}x \; w_q(x) \; s(x)
,
if the weighting function :math:`w_q(x)` is chosen appropriately. In order for the discretized version of the field to converge to the actual field in the continuum limit, the weighting functions need to be normalized in each subset; i.e., :math:`\forall q: \int_{\Omega_q} \mathrm{d}x \; w_q(x) = 1`. Choosing such a weighting function that is constant with respect to :math:`x` yields
.. math::
s_q = \frac{\int_{\Omega_q} \mathrm{d}x \; s(x)}{\int_{\Omega_q} \mathrm{d}x} = \left< s(x) \right>_{\Omega_q}
,
which corresponds to a discretization of the field by spatial averaging. Another common and equally valid choice is :math:`w_q(x) = \delta(x-x_q)`, which distinguishes some position :math:`x_q \in \Omega_q`, and evaluates the continuous field at this position,
.. math::
s_q \quad=\quad \int_{\Omega_q} \mathrm{d}x \; \delta(x-x_q) \; s(x) \quad=\quad s(x_q)
.
In practice, one often makes use of the spatially averaged pixel position, :math:`x_q = \left< x \right>_{\Omega_q}`. If the resolution is high enough to resolve all features of the signal field :math:`{s}`, both of these discretization schemes approximate each other, :math:`\left< s(x) \right>_{\Omega_q} \approx s(\left< x \right>_{\Omega_q})`, since they approximate the continuum limit by construction. (The approximation of :math:`\left< s(x) \right>_{\Omega_q} \approx s(x_q \in \Omega_q)` marks a resolution threshold beyond which further refinement of the discretization reveals no new features; i.e., no new information content of the field :math:`{s}`.)
All operations involving position integrals can be normalized in accordance with the above definitions. For example, the scalar product between two fields :math:`{s}` and :math:`{u}` is defined as
.. math::
{s}^\dagger {u} \quad=\quad \int_\Omega \mathrm{d}x \; s^*(x) \; u(x) \quad\approx\quad \sum_{q=1}^Q V_q^{\phantom{*}} \; s_q^* \; u_q^{\phantom{*}}
,
where :math:`\dagger` denotes adjunction and :math:`*` complex conjugation. Since the above approximation becomes an equality in the continuum limit, the scalar product is independent of the pixelization scheme and resolution, if the latter is sufficiently high.
The above line of argumentation analogously applies to the discretization of operators. For a linear operator :math:`{A}` acting on some field :math:`{s}` as :math:`{A} {s} = \int_\Omega \mathrm{d}y \; A(x,y) \; s(y)`, a matrix representation discretized with constant weighting functions is given by
.. math::
A(x \in \Omega_p, y \in \Omega_q) \quad\mapsto\quad A_{pq} \quad=\quad \frac{\iint_{\Omega_p \Omega_q} \mathrm{d}x \, \mathrm{d}y \; A(x,y)}{\iint_{\Omega_p \Omega_q} \mathrm{d}x \, \mathrm{d}y} \quad=\quad \big< \big< A(x,y) \big>_{\Omega_p} \big>_{\Omega_q}
.
The proper discretization of spaces, fields, and operators, as well as the normalization of position integrals, is essential for the conservation of the continuum limit. Their consistent implementation in NIFTY allows a pixelization independent coding of algorithms.
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