├── .gitignore ├── .readthedocs.yml ├── .travis.yml ├── AUTHORS.rst ├── CHANGES.md ├── LICENSE.txt ├── README.md ├── docs ├── 01_Introduction.rst ├── 02_Installation.rst ├── 03_Theory.rst ├── Makefile ├── _static │ └── logo │ │ ├── Multiply_multicolour.png │ │ └── Multiply_multicolour_white_background.png ├── _templates │ └── layout.html ├── annex_technical.rst ├── authors.rst ├── changes.rst ├── conf.py ├── environment.yml ├── index.rst └── references.bib ├── multiply_forward_operators ├── S1Observations.py ├── __init__.py ├── optical_forward_model.py ├── sar_forward_model.py └── version.py ├── recipe ├── bld.bat ├── build.sh └── meta.yaml ├── setup.py └── tests ├── .gitignore ├── data ├── prosail5.txt └── prosailD.txt ├── test_optical.py └── test_sar.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | env/ 12 | build/ 13 | develop-eggs/ 14 | dist/ 15 | downloads/ 16 | eggs/ 17 | .eggs/ 18 | lib/ 19 | lib64/ 20 | parts/ 21 | sdist/ 22 | var/ 23 | wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | 49 | # Translations 50 | *.mo 51 | *.pot 52 | 53 | # Django stuff: 54 | *.log 55 | local_settings.py 56 | 57 | # Flask stuff: 58 | instance/ 59 | .webassets-cache 60 | 61 | # Scrapy stuff: 62 | .scrapy 63 | 64 | # Sphinx documentation 65 | docs/_build/ 66 | 67 | # PyBuilder 68 | target/ 69 | 70 | # PyCharm 71 | .idea/ 72 | *.iml 73 | 74 | # Jupyter Notebook 75 | .ipynb_checkpoints 76 | 77 | # pyenv 78 | .python-version 79 | 80 | # celery beat schedule file 81 | celerybeat-schedule 82 | 83 | # SageMath parsed files 84 | *.sage.py 85 | 86 | # dotenv 87 | .env 88 | 89 | # virtualenv 90 | .venv 91 | venv/ 92 | ENV/ 93 | 94 | # Spyder project settings 95 | .spyderproject 96 | .spyproject 97 | 98 | # Rope project settings 99 | .ropeproject 100 | 101 | # mkdocs documentation 102 | /site 103 | 104 | # mypy 105 | .mypy_cache/ 106 | 107 | # SublimeText settings 108 | .sublime/ 109 | -------------------------------------------------------------------------------- /.readthedocs.yml: -------------------------------------------------------------------------------- 1 | build: 2 | image: latest 3 | conda: 4 | file: docs/environment.yml 5 | python: 6 | version: 3.6 7 | setup_py_install: true 8 | -------------------------------------------------------------------------------- /.travis.yml: -------------------------------------------------------------------------------- 1 | language: python 2 | python: 3 | - "2.7" 4 | - "3.6" 5 | install: 6 | - sudo apt-get update 7 | - echo $TRAVIS_PYTHON_VERSION 8 | - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then 9 | wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh; 10 | else 11 | wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh; 12 | fi 13 | - bash miniconda.sh -b -p $HOME/miniconda 14 | - export PATH="$HOME/miniconda/bin:$PATH" 15 | - hash -r 16 | - conda config --set always_yes yes --set changeps1 no 17 | - conda update -q conda 18 | # This next line is needed to deal with GDAL on 3.6 19 | - conda config --add channels conda-forge 20 | - conda info -a 21 | - conda create -q -n test python=$TRAVIS_PYTHON_VERSION numpy scipy pytest pytest-cov coverage sphinx nose 22 | - source activate test 23 | - pip install -U codecov 24 | # Install prosail 25 | - pip install https://github.com/jgomezdans/prosail/zipball/master 26 | - python setup.py install 27 | 28 | script: 29 | - pytest 30 | 31 | after_success: 32 | - coveralls 33 | -------------------------------------------------------------------------------- /AUTHORS.rst: -------------------------------------------------------------------------------- 1 | Developer 2 | ========== 3 | * Thomas weiß <"weiss.thomas@lmu.de"> 4 | * José Gómez-Dans <"j.gomez-dans@ucl.ac.uk"> 5 | -------------------------------------------------------------------------------- /CHANGES.md: -------------------------------------------------------------------------------- 1 | Change log forward-operator 2 | ===================================== 3 | 4 | version 0.4 5 | ------------- 6 | 7 | 8 | -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Forward Operators 2 | 3 | This repository contains optical and microwave forward operator codes which are used within the MULTIPLY Platform. 4 | 5 | In a first step the optical and microwave forward operators will be used within the MULTIPLY platform to retrieve biophysical parameters separately for each domain. In a second step the retrieval schemes of the optical and microwave forward operators will be brought together to accomplish a joint retrieval of specific biophysical parameters. 6 | 7 | ## Optical Forward Operator 8 | The widely used PROSPECT & SAIL (PROSAIL) model was chosen as a RT-model for the optical domain of the MULTIPLY platform. 9 | 10 | The python code for the optical forward operator is implemented in "optical_forward_model.py" 11 | 12 | ## Microwave Forward Operator 13 | The Water Cloud Model (WCM), as a semi empirical RT-model, was chosen for the first implementation of a RT-model for the microwave domain of the MULTIPLY platform. WCMs can be used to estimate the backscatter of vegetated surfaces accounting separately for vegetation and underlying surface contributions. An advantage of WCMs compared to other RT-models is their low parametrization effort. 14 | 15 | The python code for the microwave forward operator is implemented in "sar_forward_model.py" 16 | 17 | # References 18 | 19 | ATTEMA, E. P. W. & ULABY, F. T. 1978. Vegetation modeled as a water cloud. Radio Science, 13, 357- 364. 20 | 21 | DABROWSKA-ZIELINSKA, K., INOUE, Y., KOWALIK, W. & GRUSZCZYNSKA, M. 2007. Inferring the effect 22 | of plant and soil variables on C- and L-band SAR backscatter over agricultural fields, based on model analysis. Advances in Space Research, 39, 139-148. 23 | 24 | 25 | -------------------------------------------------------------------------------- /docs/01_Introduction.rst: -------------------------------------------------------------------------------- 1 | Introduction 2 | ============ 3 | Scope 4 | ----- 5 | This is the documentation of the optical and microwave forward operators that can be used within the MULTIPLY platform. 6 | 7 | To be continued... 8 | 9 | 10 | 11 | Structure of this documentation 12 | ------------------------------- 13 | .. code:: 14 | 15 | Need to be done !!! 16 | 17 | This documentation gives a detailed 18 | 19 | The documentation is organised in ... main sections. 20 | - Section 21 | - Section 22 | - Section 23 | 24 | -------------------------------------------------------------------------------- /docs/02_Installation.rst: -------------------------------------------------------------------------------- 1 | Installation 2 | ============= 3 | 4 | The standard python way 5 | ------------------------ 6 | You can download the source code from the `project website `_. Unpack the file you obtained and then run:: 7 | 8 | python setup.py install 9 | 10 | Using conda 11 | -------------- 12 | not yet implemented 13 | 14 | Using pip 15 | ------------- 16 | not yet implemented 17 | 18 | From code repository for developing 19 | ------------------------------------ 20 | to be continued 21 | 22 | Installation from the recent stable code repository can be done by:: 23 | 24 | to be continued 25 | -------------------------------------------------------------------------------- /docs/03_Theory.rst: -------------------------------------------------------------------------------- 1 | Theory 2 | ================ 3 | 4 | .. code:: 5 | 6 | Need to be done !!! 7 | 8 | 9 | Overview 10 | -------- 11 | 12 | 13 | .. rubric:: References 14 | .. bibliography:: references.bib 15 | :style: unsrt 16 | -------------------------------------------------------------------------------- /docs/Makefile: -------------------------------------------------------------------------------- 1 | # Makefile for Sphinx documentation 2 | # 3 | 4 | # You can set these variables from the command line. 5 | SPHINXOPTS = 6 | SPHINXBUILD = sphinx-build 7 | PAPER = 8 | BUILDDIR = _build 9 | 10 | # User-friendly check for sphinx-build 11 | ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $?), 1) 12 | $(error The '$(SPHINXBUILD)' command was not found. 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The pseudo-XML files are in $(BUILDDIR)/pseudoxml." 178 | -------------------------------------------------------------------------------- /docs/_static/logo/Multiply_multicolour.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/multiply-org/forward-operators/6250bbce04ece6b76961e6a683126591c151c905/docs/_static/logo/Multiply_multicolour.png -------------------------------------------------------------------------------- /docs/_static/logo/Multiply_multicolour_white_background.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/multiply-org/forward-operators/6250bbce04ece6b76961e6a683126591c151c905/docs/_static/logo/Multiply_multicolour_white_background.png -------------------------------------------------------------------------------- /docs/_templates/layout.html: -------------------------------------------------------------------------------- 1 | {% extends "!layout.html" %} 2 | 3 | {% block menu %} 4 | {{ super() }} 5 | Index 6 | Python module index 7 | {% endblock %} 8 | -------------------------------------------------------------------------------- /docs/annex_technical.rst: -------------------------------------------------------------------------------- 1 | Technical documentation 2 | ======================= 3 | 4 | The Optical Forward Model 5 | ------------------------- 6 | .. automodule:: multiply_forward_operators.optical_forward_model 7 | :members: 8 | :undoc-members: 9 | :show-inheritance: 10 | 11 | The Microwave Forward Model 12 | --------------------------------- 13 | .. automodule:: multiply_forward_operators.sar_forward_model 14 | :members: 15 | :noindex: 16 | :undoc-members: 17 | :show-inheritance: 18 | -------------------------------------------------------------------------------- /docs/authors.rst: -------------------------------------------------------------------------------- 1 | .. _authors: 2 | .. include:: ../AUTHORS.rst 3 | -------------------------------------------------------------------------------- /docs/changes.rst: -------------------------------------------------------------------------------- 1 | .. _changes: 2 | .. include:: ../CHANGES.md 3 | -------------------------------------------------------------------------------- /docs/conf.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # 3 | # This file is execfile()d with the current directory set to its containing dir. 4 | # 5 | # Note that not all possible configuration values are present in this 6 | # autogenerated file. 7 | # 8 | # All configuration values have a default; values that are commented out 9 | # serve to show the default. 10 | 11 | import sys 12 | import os 13 | 14 | # If extensions (or modules to document with autodoc) are in another directory, 15 | # add these directories to sys.path here. If the directory is relative to the 16 | # documentation root, use os.path.abspath to make it absolute, like shown here. 17 | # sys.path.insert(0, os.path.abspath('.')) 18 | sys.path.insert(0, os.path.abspath('../..')) 19 | sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir))) 20 | sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__)))) 21 | sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "multiply_forward_operator"))) 22 | 23 | # -- Hack for ReadTheDocs ------------------------------------------------------ 24 | # This hack is necessary since RTD does not issue `sphinx-apidoc` before running 25 | # `sphinx-build -b html . _build/html`. See Issue: 26 | # https://github.com/rtfd/readthedocs.org/issues/1139 27 | # DON'T FORGET: Check the box "Install your project inside a virtualenv using 28 | # setup.py install" in the RTD Advanced Settings. 29 | 30 | on_rtd = os.environ.get('READTHEDOCS', None) == 'True' 31 | if on_rtd: 32 | import inspect 33 | from sphinx import apidoc 34 | 35 | __location__ = os.path.join(os.getcwd(), os.path.dirname( 36 | inspect.getfile(inspect.currentframe()))) 37 | 38 | output_dir = os.path.join(__location__, "../docs/api") 39 | module_dir = os.path.join(__location__, "../multiply_forward_operators") 40 | cmd_line_template = "sphinx-apidoc -f -o {outputdir} {moduledir}" 41 | cmd_line = cmd_line_template.format(outputdir=output_dir, moduledir=module_dir) 42 | apidoc.main(cmd_line.split(" ")) 43 | 44 | # -- General configuration ----------------------------------------------------- 45 | 46 | # If your documentation needs a minimal Sphinx version, state it here. 47 | # needs_sphinx = '1.0' 48 | 49 | # Add any Sphinx extension module names here, as strings. They can be extensions 50 | # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. 51 | extensions = ['sphinx.ext.autodoc', 'sphinx.ext.intersphinx', 'sphinx.ext.todo', 52 | 'sphinx.ext.autosummary', 'sphinx.ext.viewcode', 'sphinx.ext.coverage', 53 | 'sphinx.ext.doctest', 'sphinx.ext.ifconfig', 'sphinx.ext.mathjax', 54 | 'sphinx.ext.napoleon', 'sphinxcontrib.bibtex'] 55 | 56 | # Add any paths that contain templates here, relative to this directory. 57 | templates_path = ['_templates'] 58 | 59 | # The suffix of source filenames. 60 | source_suffix = '.rst' 61 | 62 | # The encoding of source files. 63 | # source_encoding = 'utf-8-sig' 64 | 65 | # The master toctree document. 66 | master_doc = 'index' 67 | 68 | # General information about the project. 69 | project = u'MULTIPLY Forward Operator' 70 | copyright = u'2018, Thomas Weiß' 71 | 72 | # The version info for the project you're documenting, acts as replacement for 73 | # |version| and |release|, also used in various other places throughout the 74 | # built documents. 75 | # 76 | # The short X.Y version. 77 | try: 78 | from multiply_forward_operators import __version__ as version 79 | except ImportError: 80 | version = 'unknown' 81 | 82 | # The full version, including alpha/beta/rc tags. 83 | # release = __version__ # Is set by calling `setup.py docs` 84 | release = version 85 | 86 | # The language for content autogenerated by Sphinx. Refer to documentation 87 | # for a list of supported languages. 88 | language = None 89 | 90 | # There are two options for replacing |today|: either, you set today to some 91 | # non-false value, then it is used: 92 | # today = '' 93 | # Else, today_fmt is used as the format for a strftime call. 94 | # today_fmt = '%B %d, %Y' 95 | 96 | # List of patterns, relative to source directory, that match files and 97 | # directories to ignore when looking for source files. 98 | exclude_patterns = ['_build'] 99 | 100 | # The reST default role (used for this markup: `text`) to use for all documents. 101 | # default_role = None 102 | 103 | # If true, '()' will be appended to :func: etc. cross-reference text. 104 | # add_function_parentheses = True 105 | 106 | # If true, the current module name will be prepended to all description 107 | # unit titles (such as .. function::). 108 | # add_module_names = True 109 | 110 | # If true, sectionauthor and moduleauthor directives will be shown in the 111 | # output. They are ignored by default. 112 | # show_authors = False 113 | 114 | # The name of the Pygments (syntax highlighting) style to use. 115 | pygments_style = 'sphinx' 116 | 117 | # A list of ignored prefixes for module index sorting. 118 | # modindex_common_prefix = [] 119 | 120 | # If true, keep warnings as "system message" paragraphs in the built documents. 121 | # keep_warnings = False 122 | 123 | 124 | # -- Options for HTML output --------------------------------------------------- 125 | 126 | # The theme to use for HTML and HTML Help pages. See the documentation for 127 | # a list of builtin themes. 128 | html_theme = 'sphinx_rtd_theme' 129 | 130 | # Theme options are theme-specific and customize the look and feel of a theme 131 | # further. For a list of options available for each theme, see the 132 | # documentation. 133 | # html_theme_options = {} 134 | 135 | # Add any paths that contain custom themes here, relative to this directory. 136 | # html_theme_path = [] 137 | 138 | # The name for this set of Sphinx documents. If None, it defaults to 139 | # " v documentation". 140 | try: 141 | from multiply_forward_operators import __version__ as version 142 | except ImportError: 143 | pass 144 | else: 145 | release = version 146 | 147 | # A shorter title for the navigation bar. Default is the same as html_title. 148 | # html_short_title = None 149 | 150 | # The name of an image file (relative to this directory) to place at the top 151 | # of the sidebar. 152 | # html_logo = "" 153 | 154 | # The name of an image file (within the static path) to use as favicon of the 155 | # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 156 | # pixels large. 157 | # html_favicon = None 158 | 159 | # Add any paths that contain custom static files (such as style sheets) here, 160 | # relative to this directory. They are copied after the builtin static files, 161 | # so a file named "default.css" will overwrite the builtin "default.css". 162 | html_static_path = ['_static'] 163 | 164 | # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, 165 | # using the given strftime format. 166 | # html_last_updated_fmt = '%b %d, %Y' 167 | 168 | # If true, SmartyPants will be used to convert quotes and dashes to 169 | # typographically correct entities. 170 | # html_use_smartypants = True 171 | 172 | # Custom sidebar templates, maps document names to template names. 173 | # html_sidebars = {} 174 | 175 | # Additional templates that should be rendered to pages, maps page names to 176 | # template names. 177 | # html_additional_pages = {} 178 | 179 | # If false, no module index is generated. 180 | # html_domain_indices = True 181 | 182 | # If false, no index is generated. 183 | # html_use_index = True 184 | 185 | # If true, the index is split into individual pages for each letter. 186 | # html_split_index = False 187 | 188 | # If true, links to the reST sources are added to the pages. 189 | # html_show_sourcelink = True 190 | 191 | # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. 192 | # html_show_sphinx = True 193 | 194 | # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. 195 | # html_show_copyright = True 196 | 197 | # If true, an OpenSearch description file will be output, and all pages will 198 | # contain a tag referring to it. The value of this option must be the 199 | # base URL from which the finished HTML is served. 200 | # html_use_opensearch = '' 201 | 202 | # This is the file name suffix for HTML files (e.g. ".xhtml"). 203 | # html_file_suffix = None 204 | 205 | # Output file base name for HTML help builder. 206 | htmlhelp_basename = 'multiply_forward_operators_doc' 207 | 208 | 209 | html_logo = '_static/logo/Multiply_multicolour_white_background.png' 210 | 211 | # -- Options for LaTeX output -------------------------------------------------- 212 | 213 | latex_elements = { 'classoptions': ',openany,oneside' 214 | # The paper size ('letterpaper' or 'a4paper'). 215 | # 'papersize': 'letterpaper', 216 | 217 | # The font size ('10pt', '11pt' or '12pt'). 218 | # 'pointsize': '10pt', 219 | 220 | # Additional stuff for the LaTeX preamble. 221 | # 'preamble': '', 222 | } 223 | 224 | # Grouping the document tree into LaTeX files. List of tuples 225 | # (source start file, target name, title, author, documentclass [howto/manual]). 226 | latex_documents = [ 227 | ('index', 'user_guide.tex', u'MULTIPLY Forward Operator Documentation', 228 | u'Thomas Weiß', 'manual'), 229 | ] 230 | 231 | # The name of an image file (relative to this directory) to place at the top of 232 | # the title page. 233 | latex_logo = '_static/logo/Multiply_multicolour_white_background.png' 234 | 235 | # For "manual" documents, if this is true, then toplevel headings are parts, 236 | # not chapters. 237 | # latex_use_parts = False 238 | 239 | # If true, show page references after internal links. 240 | # latex_show_pagerefs = False 241 | 242 | # If true, show URL addresses after external links. 243 | # latex_show_urls = False 244 | 245 | # Documents to append as an appendix to all manuals. 246 | # latex_appendices = [] 247 | 248 | # If false, no module index is generated. 249 | # latex_domain_indices = True 250 | 251 | # -- External mapping ------------------------------------------------------------ 252 | python_version = '.'.join(map(str, sys.version_info[0:2])) 253 | intersphinx_mapping = { 254 | 'sphinx': ('http://sphinx.pocoo.org', None), 255 | 'python': ('http://docs.python.org/' + python_version, None), 256 | 'matplotlib': ('http://matplotlib.sourceforge.net', None), 257 | 'numpy': ('http://docs.scipy.org/doc/numpy', None), 258 | 'sklearn': ('http://scikit-learn.org/stable', None), 259 | 'pandas': ('http://pandas.pydata.org/pandas-docs/stable', None), 260 | 'scipy': ('http://docs.scipy.org/doc/scipy/reference/', None), 261 | } 262 | 263 | 264 | # add numbered figures 265 | numfig = True 266 | 267 | -------------------------------------------------------------------------------- /docs/environment.yml: -------------------------------------------------------------------------------- 1 | channels: 2 | - conda-forge 3 | - defaults 4 | 5 | dependencies: 6 | - python=3.6* 7 | - pip 8 | - pip: 9 | - git+https://github.com/jgomezdans/prosail 10 | - very-good-setuptools-git-version 11 | - xarray 12 | - sphinxcontrib-bibtex 13 | 14 | -------------------------------------------------------------------------------- /docs/index.rst: -------------------------------------------------------------------------------- 1 | MULTIPLY forward operator 2 | ========================= 3 | 4 | .. toctree:: 5 | :maxdepth: 2 6 | :caption: Documentation 7 | 8 | 01_Introduction 9 | 02_Installation 10 | 03_Theory 11 | annex_technical 12 | 13 | .. toctree:: 14 | :maxdepth: 2 15 | :caption: Anything else 16 | 17 | Authors 18 | Change log 19 | -------------------------------------------------------------------------------- /docs/references.bib: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/multiply-org/forward-operators/6250bbce04ece6b76961e6a683126591c151c905/docs/references.bib -------------------------------------------------------------------------------- /multiply_forward_operators/S1Observations.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | """ 3 | 4 | """ 5 | import datetime 6 | import glob 7 | import os 8 | from collections import namedtuple 9 | import gdal 10 | import numpy as np 11 | import osr 12 | import scipy.sparse as sp 13 | from netCDF4 import Dataset 14 | from dateutil import parser 15 | 16 | 17 | WRONG_VALUE = -999.0 # TODO tentative missing value 18 | 19 | SARdata = namedtuple('SARdata','observations uncertainty mask metadata emulator') 20 | 21 | def reproject_image(source_img, target_img, dstSRSs=None): 22 | """Reprojects/Warps an image to fit exactly another image. 23 | Additionally, you can set the destination SRS if you want 24 | to or if it isn't defined in the source image.""" 25 | g = gdal.Open(target_img) 26 | geo_t = g.GetGeoTransform() 27 | x_size, y_size = g.RasterXSize, g.RasterYSize 28 | xmin = min(geo_t[0], geo_t[0] + x_size * geo_t[1]) 29 | xmax = max(geo_t[0], geo_t[0] + x_size * geo_t[1]) 30 | ymin = min(geo_t[3], geo_t[3] + y_size * geo_t[5]) 31 | ymax = max(geo_t[3], geo_t[3] + y_size * geo_t[5]) 32 | xRes, yRes = abs(geo_t[1]), abs(geo_t[5]) 33 | if dstSRSs is None: 34 | dstSRS = osr.SpatialReference() 35 | raster_wkt = g.GetProjection() 36 | dstSRS.ImportFromWkt(raster_wkt) 37 | else: 38 | dstSRS = dstSRSs 39 | 40 | g = gdal.Warp('', source_img, format='MEM', 41 | outputBounds=[xmin, ymin, xmax, ymax], xRes=xRes, yRes=yRes, 42 | dstSRS=dstSRS) 43 | if g is None: 44 | raise ValueError("Something failed with GDAL!") 45 | return g 46 | 47 | class S1Observations(object): 48 | """ 49 | """ 50 | 51 | def __init__(self, data_folder, state_mask, emulators={'vv':'SOmething', 'vh':'Other'}): 52 | 53 | """ 54 | File sorting ??? Are sorted observation_dates needed for KafKa? 55 | """ 56 | 57 | # 1. Find the files 58 | files = glob.glob(os.path.join(data_folder, '*.nc')) 59 | files.sort() 60 | self.state_mask = state_mask 61 | self.dates = [] 62 | self.date_data = {} 63 | 64 | for fich in files: 65 | fname = os.path.basename(fich) 66 | # TODO Maybe filter files by metadata 67 | # (e.g. select ascending/descending passes) 68 | data = Dataset(fich) 69 | attrs = data.ncattrs() 70 | 71 | # Search for date in attribute name and takes first variable that matches 72 | for i, s in enumerate(attrs): 73 | if 'date' in s.lower(): 74 | date = getattr(data, s) 75 | break 76 | 77 | this_date = parser.parse(date) 78 | 79 | self.dates.append(this_date) 80 | self.date_data[this_date] = fich 81 | # self.observation_dates = sorted(self.observation_dates.items()) 82 | 83 | # 2. Store the emulator(s) 84 | self.emulators = emulators 85 | self.bands_per_observation = {} 86 | for the_date in self.dates: 87 | self.bands_per_observation[the_date] = 2 # 2 bands 88 | 89 | def _calculate_uncertainty(self, backscatter): 90 | """ 91 | Calculation of the uncertainty of Sentinel-1 input data 92 | Radiometric uncertainty of Sentinel-1 Sensors are within 1 and 0.5 dB 93 | Calculate Equivalent Number of Looks (ENL) of input dataset leads to 94 | uncertainty of scene caused by speckle-filtering/multi-looking 95 | Input 96 | ------ 97 | backscatter (backscatter values) 98 | Output 99 | ------ 100 | unc (uncertainty in dB) 101 | """ 102 | 103 | # first approximation of uncertainty (1 dB) 104 | unc = backscatter*0.05 105 | 106 | 107 | # need to find a good way to calculate ENL 108 | # self.ENL = (backscatter.mean()**2) / (backscatter.std()**2) 109 | 110 | return unc 111 | 112 | 113 | def _get_mask (self, this_file): 114 | """ 115 | Mask for selection of pixels 116 | 117 | Get a True/False array with the selected/unselected pixels 118 | 119 | 120 | Input 121 | ------ 122 | this_file ????? 123 | 124 | Output 125 | ------ 126 | 127 | """ 128 | 129 | mask = np.ones_like(this_file, dtype=np.bool) 130 | mask[this_file == WRONG_VALUE] = False 131 | return mask 132 | 133 | def _get_metadata(self, this_file): 134 | """ 135 | get all relevant data information from netcdf4 global attributes 136 | 137 | 138 | Input 139 | ------ 140 | timestep 141 | 142 | Output 143 | ------ 144 | freq 145 | later maybe only for S1 data 146 | - satellite 147 | - relativorbit 148 | - orbitdirection 149 | """ 150 | dset = Dataset(this_file, 'r', format="NETCDF4") 151 | freq = getattr(dset, 'frequency') 152 | 153 | return freq 154 | 155 | def _get_variable_name(self, this_file, search_string): 156 | """ 157 | search for part of search string in variable names of netCDF4 files and return complete string 158 | 159 | Input 160 | ------- 161 | this_file (path and name of netCDF4 file) 162 | search_string (identification string that needs to be part of the variable name within the netCDF4 file) 163 | 164 | Output 165 | ------- 166 | variable_name (complete name of variable within netCDF4 file) 167 | 168 | """ 169 | dset = Dataset(this_file, 'r', format="NETCDF4") 170 | 171 | for i, s in enumerate(dset.variables): 172 | if search_string in s.lower(): 173 | variable_name = s 174 | break 175 | 176 | assert 'variable_name' in locals(), 'ERROR: search string "'+ search_string + '" can not be found in band names of netCDF4-file' 177 | 178 | return variable_name 179 | 180 | 181 | 182 | def get_band_data(self, timestep, band): 183 | """ 184 | get all relevant S1 data information for one timestep to get processing done 185 | 186 | 187 | Input 188 | ------ 189 | timestep 190 | band 191 | 192 | Output 193 | ------ 194 | sardata (namedtuple with information on observations, uncertainty, mask, metadata, emulator/used model) 195 | 196 | """ 197 | 198 | if band == 0: 199 | polarisation = 'vv' 200 | elif band == 1: 201 | polarisation = 'vh' 202 | elif band == 2: 203 | polarisation = 'hh' 204 | 205 | this_file = self.date_data[timestep] 206 | 207 | variable_name = self._get_variable_name(this_file, polarisation) 208 | 209 | fname = 'NETCDF:"{:s}":{:s}'.format(this_file, variable_name) 210 | obs_ptr = reproject_image(fname, self.state_mask) 211 | observations = obs_ptr.ReadAsArray() 212 | uncertainty = self._calculate_uncertainty(observations) 213 | mask = self._get_mask(observations) 214 | R_mat = np.zeros_like(observations) 215 | R_mat = uncertainty 216 | R_mat[np.logical_not(mask)] = 0. 217 | N = mask.ravel().shape[0] 218 | R_mat_sp = sp.lil_matrix((N, N)) 219 | R_mat_sp.setdiag(1./(R_mat.ravel())**2) 220 | R_mat_sp = R_mat_sp.tocsr() 221 | 222 | emulator = self.emulators[polarisation] 223 | 224 | variable_name = self._get_variable_name(this_file, 'theta') 225 | fname = 'NETCDF:"{:s}":{:s}'.format(this_file, variable_name) 226 | obs_ptr = reproject_image(fname, self.state_mask) 227 | frequency = self._get_metadata(this_file) 228 | 229 | metadata = {'incidence_angle': obs_ptr.ReadAsArray(), 'frequency': float(frequency)} 230 | 231 | sardata = SARdata(observations, R_mat_sp, mask, metadata, emulator) 232 | return sardata 233 | 234 | if __name__ == "__main__": 235 | data_folder = "/home/tweiss/LRZ Sync+Share/Tonio" 236 | sentinel1 = S1Observations(data_folder,'NETCDF:"/home/tweiss/LRZ Sync+Share/Tonio/S1A_IW_SLC__1SDV_20170101T165853_20170101T165920_014641_017CE5_63E5_GC_RC_No_Su_Co_speckle.nc":theta') 237 | -------------------------------------------------------------------------------- /multiply_forward_operators/__init__.py: -------------------------------------------------------------------------------- 1 | from .version import __version__ 2 | from .optical_forward_model import optical_forward_operator 3 | from .sar_forward_model import sar_observation_operator 4 | -------------------------------------------------------------------------------- /multiply_forward_operators/optical_forward_model.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | """Optical observation operator. 3 | Just a thin wrapper around PROSPECT+SAIL bindings. 4 | """ 5 | try: 6 | from prosail import run_prosail 7 | except ImportError: 8 | raise ImportError("You need the PROSAIL Python bindings from " 9 | "http://github.com/jgomezdans/prosail/!") 10 | 11 | __author__ = "J Gomez-Dans" 12 | __copyright__ = "Copyright 2017 J Gomez-Dans" 13 | __version__ = "1.0 (09.03.2017)" 14 | __license__ = "GPLv3" 15 | __email__ = "j.gomez-dans@ucl.ac.uk" 16 | 17 | 18 | def optical_forward_operator(x, sza, vza, raa, version="PROSAIL_D", 19 | hspot=0.01): 20 | """A generic wrapper to the PROSPECT+SAIL operators. Uses either PROSPECT D 21 | or PROSPECT 5. The state vector is given as a 1D vector, with parameters 22 | in order: 23 | 1. N (leaf layers) 24 | 2. Ant (if using PROSPECT-D, Anthocyanins, ug/cm2) 25 | 3. Cab (leaf chlorophyll conc, ug/cm2) 26 | 4. Car (leaf carotenoids conc, ug/cm2) 27 | 5. Cbrown (senescent pigment-like concentration, -) 28 | 6. Cw (equivalent leaf water thickness, cm) 29 | 7. Cm (dry matter, g/cm2) 30 | 8. LAI (leaf area index, m2/m2) 31 | 9. ALA (average leaf angle, deg) 32 | 10. rsoil (dry soil scalar) 33 | 11. psoil (wet soil scalar) 34 | 35 | Additionally, one needs to pass the different view/illumination angles, and 36 | optionally the value of the hotspot parameter. The function returns the 37 | top of canopy reflectance between 400 and 2500 nm every 1 nm. 38 | """ 39 | if not version.upper() in ["PROSAIL_D", "PROSAIL_5"]: 40 | raise ValueError("Can only deal with SAIL + PROSPECT D or 5!") 41 | 42 | if version.upper() == "PROSAIL_D": 43 | # Using prospect D 44 | n, ant, cab, car, cbrown, cw, cm, lai, ala, rsoil, psoil = x 45 | rho_canopy = run_prosail(n, cab, car, cbrown, cw, cm, lai, ala, hspot, 46 | sza, vza, raa, ant=ant, prospect_version="D", 47 | rsoil=rsoil, psoil=psoil) 48 | 49 | elif version.upper() == "PROSAIL_5": 50 | n, cab, car, cbrown, cw, cm, lai, ala, rsoil, psoil = x 51 | rho_canopy = run_prosail(n, cab, car, cbrown, cw, cm, lai, ala, hspot, 52 | sza, vza, raa, prospect_version="5", 53 | rsoil=rsoil, psoil=psoil) 54 | return rho_canopy 55 | -------------------------------------------------------------------------------- /multiply_forward_operators/sar_forward_model.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | """ 3 | 4 | """ 5 | 6 | import numpy as np 7 | import pdb 8 | 9 | def sar_observation_operator(x, polarisation): 10 | 11 | """ 12 | For the sar_observation_operator a simple Water Cloud Model (WCM) is used 13 | We assume that the WCM is given by 14 | 15 | ----------------------------------------------------- 16 | tau = exp(-2*B*V/cos(theta)) 17 | sigma_veg = A*V**E*cos(theta)*(1-tau) 18 | sigma_soil = 10**((C+D*SM)/10) 19 | sigma_0 = sigma_veg + tau*sigma_soil 20 | 21 | A, B, C, D, E are parameters determined by fitting of the model 22 | V is a vegetation descriptor e.g. LAI, LWAI, VWM 23 | SM is the soil moisture [m^3/m^3] 24 | sigma_veg is the volume component of the backscatter [m^3/m^3] 25 | sigma_soil is the surface component of the backscatter [m^3/m^3] 26 | tau is the two way attenuation through the canopy (unitless) 27 | sigma_0 is the total backscatter in [m^3/m^3] 28 | ---------------------------------------------------- 29 | 30 | Input 31 | ----- 32 | polarisation: considered polarisation as string 33 | x: 2D array where every row is the set of parameters for one pixel 34 | 35 | Output 36 | ------ 37 | sigma_0: predicted backscatter for each individual parameter set 38 | grad: gradient for each individual parameter set and each parameter determined by 2D input array x. The gradient should thus have the same size and shape as x 39 | sigma_veg: predicted volume component of sigma_0 40 | sigma_surf: predicted surface component of sigma_0 41 | tau: predicted two-way attenuation through the canopy 42 | """ 43 | 44 | # x 2D array where every row is the set of parameters for one pixel 45 | x = np.atleast_2d(x) 46 | 47 | # conversion of incidence angle to radiant 48 | # the incidence angle itself should probably implemented in x) 49 | theta = np.deg2rad(23.) 50 | 51 | # Simpler definition of cosine of theta 52 | mu = np.cos(theta) 53 | 54 | # the model parameters (A, B, C, D, E) for different polarisations 55 | parameters = {'VV': [0.0846, 0.0615, -14.8465, 15.907, 0.], 'VH': [0.0795, 0.1464, -14.8332, 15.907, 0.]} 56 | 57 | # Select model parameters 58 | try: 59 | A, B, C, D, E = parameters[polarisation] 60 | except KeyError: 61 | raise ValueError('Only VV and VH polarisations available!') 62 | 63 | # Calculate Model 64 | tau = np.exp(-2 * B / mu * x[0, :]) 65 | sigma_veg = A * (x[0, :] ** E) * mu * (1 - tau) 66 | sigma_surf = 10 ** ((C + D * x[1, :]) / 10.) 67 | 68 | sigma_0 = sigma_veg + tau * sigma_surf 69 | 70 | # Calculate Gradient (grad has same dimension as x) 71 | grad = x*0 72 | n_elems = x.shape[1] 73 | for i in range(n_elems): 74 | tau_value = np.exp(-2 * B / mu * x[0, i]) 75 | grad[0, i] = A * E * mu * (x[0, i] ** (E - 1)) * (1 - tau_value) + \ 76 | 2 * A * B * (x[0, i] ** E) * tau_value - (\ 77 | (2 ** (1/10. * (C + D * x[1, i]) + 1)) * \ 78 | (5 ** (1/10. * (C + D * x[1, i])) * B * tau_value) \ 79 | ) / mu 80 | grad[1, i] = D * np.log(10) * tau_value * 10 ** (1/10. * (C + D * x[1, i]) - 1) 81 | 82 | 83 | # returned values are linear scaled not dB!!! 84 | # return sigma_0, grad, sigma_veg, sigma_surf, tau 85 | return sigma_0, grad 86 | 87 | 88 | 89 | # # Calculate Gradient without conversion of sigma_soil from dB to linear 90 | # grad = x*0 91 | # n_elems = x.shape[0] 92 | # for i in range(n_elems): 93 | # tau = np.exp(-2 * B / mu * x[i, 0]) 94 | # grad[i, 0] = 2 * A * B * x[i, 0] * tau - \ 95 | # A * mu * tau + \ 96 | # A * mu - \ 97 | # 2 * B * C * tau / mu - \ 98 | # 2 * B * D * x[i, 1] * tau / mu 99 | # grad[i, 1] = D * tau 100 | 101 | 102 | -------------------------------------------------------------------------------- /multiply_forward_operators/version.py: -------------------------------------------------------------------------------- 1 | import very_good_setuptools_git_version 2 | 3 | __version__= very_good_setuptools_git_version.get_tag() 4 | -------------------------------------------------------------------------------- /recipe/bld.bat: -------------------------------------------------------------------------------- 1 | "%PYTHON%" setup.py install 2 | if errorlevel 1 exit 1 -------------------------------------------------------------------------------- /recipe/build.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | $PYTHON setup.py install --single-version-externally-managed --record=record.txt -------------------------------------------------------------------------------- /recipe/meta.yaml: -------------------------------------------------------------------------------- 1 | about: 2 | summary: "MULTIPLY forward operators package" 3 | home: https://github.com/multiply-org/forward_operators 4 | 5 | package: 6 | name: multiply_forward_operators 7 | version: "0.1" 8 | 9 | source: 10 | git_url: "https://github.com/multiply-org/forward_operators.git" 11 | 12 | build: 13 | number: 0 14 | 15 | requirements: 16 | build: 17 | - python 18 | - setuptools 19 | - numpy 20 | - scipy 21 | 22 | run: 23 | - python 24 | - numpy 25 | - scipy 26 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | from setuptools import setup 4 | 5 | try: 6 | from multiply_forward_operators import __version__ as version 7 | except ImportError: 8 | version = 'unknown' 9 | 10 | setup(name='multiply-forward-operators', 11 | version=version, 12 | description='MULTIPLY Forward Operators', 13 | author='MULTIPLY Team', 14 | packages=['multiply_forward_operators'] 15 | ) 16 | -------------------------------------------------------------------------------- /tests/.gitignore: -------------------------------------------------------------------------------- 1 | *.png 2 | *.tif 3 | # Byte-compiled / optimized / DLL files 4 | __pycache__/ 5 | *.py[cod] 6 | *$py.class 7 | 8 | # C extensions 9 | *.so 10 | 11 | # Distribution / packaging 12 | .Python 13 | env/ 14 | build/ 15 | develop-eggs/ 16 | dist/ 17 | downloads/ 18 | eggs/ 19 | .eggs/ 20 | lib/ 21 | lib64/ 22 | parts/ 23 | sdist/ 24 | var/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .coverage 43 | .coverage.* 44 | .cache 45 | nosetests.xml 46 | coverage.xml 47 | *,cover 48 | .hypothesis/ 49 | 50 | # Translations 51 | *.mo 52 | *.pot 53 | 54 | # Django stuff: 55 | *.log 56 | local_settings.py 57 | 58 | # Flask stuff: 59 | instance/ 60 | .webassets-cache 61 | 62 | # Scrapy stuff: 63 | .scrapy 64 | 65 | # Sphinx documentation 66 | docs/_build/ 67 | 68 | # PyBuilder 69 | target/ 70 | 71 | # IPython Notebook 72 | .ipynb_checkpoints 73 | 74 | # pyenv 75 | .python-version 76 | 77 | # celery beat schedule file 78 | celerybeat-schedule 79 | 80 | # dotenv 81 | .env 82 | 83 | # virtualenv 84 | venv/ 85 | ENV/ 86 | 87 | # Spyder project settings 88 | .spyderproject 89 | 90 | # Rope project settings 91 | .ropeproject 92 | 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0.59766479 0.59758558 0.59751020 0.59743872 0.59737122 0.59730775 0.59724839 0.59719320 0.59714222 0.59709550 0.59705310 0.59701505 0.59698139 0.59695215 0.59692736 0.59690705 0.59689123 0.59687992 0.59687313 0.59687086 4 | 0.60709861 0.60709438 0.60708171 0.60706061 0.60703112 0.60699330 0.60694722 0.60689296 0.60683061 0.60676028 0.60668211 0.60659622 0.60650277 0.60640192 0.60629385 0.60617874 0.60605678 0.60592818 0.60579315 0.60565193 0.60550473 0.60535180 0.60519337 0.60502972 0.60486108 0.60468771 0.60450989 0.60432789 0.60414197 0.60395243 0.60375954 0.60356358 0.60336485 0.60316362 0.60296018 0.60275481 0.60254778 0.60233937 0.60212987 0.60191953 0.60170863 0.60149744 0.60128621 0.60107521 0.60086468 0.60065488 0.60044605 0.60023843 0.60003225 0.59982775 0.59962514 0.59942465 0.59922650 0.59903088 0.59883800 0.59864806 0.59846126 0.59827776 0.59809776 0.59792142 0.59774892 0.59758042 0.59741609 0.59725608 0.59710055 0.59694964 0.59680351 0.59666228 0.59652610 0.59639508 0.59626934 0.59614901 0.59603419 0.59592498 0.59582149 0.59572381 0.59563202 0.59554620 0.59546644 0.59539280 0.59532535 0.59526414 0.59520923 0.59516067 0.59511850 0.59508275 0.59505346 0.59503066 0.59501435 0.59500456 0.59500130 5 | 0.60938866 0.60938268 0.60936476 0.60933492 0.60929324 0.60923980 0.60917470 0.60909809 0.60901012 0.60891096 0.60880082 0.60867992 0.60854849 0.60840680 0.60825511 0.60809372 0.60792294 0.60774308 0.60755447 0.60735747 0.60715246 0.60693980 0.60671989 0.60649311 0.60625986 0.60602054 0.60577555 0.60552530 0.60527018 0.60501061 0.60474698 0.60447970 0.60420916 0.60393577 0.60365991 0.60338198 0.60310234 0.60282139 0.60253948 0.60225699 0.60197428 0.60169168 0.60140956 0.60112824 0.60084805 0.60056931 0.60029235 0.60001746 0.59974493 0.59947507 0.59920815 0.59894444 0.59868421 0.59842772 0.59817521 0.59792692 0.59768309 0.59744393 0.59720968 0.59698053 0.59675668 0.59653833 0.59632566 0.59611885 0.59591807 0.59572348 0.59553524 0.59535348 0.59517835 0.59500999 0.59484852 0.59469408 0.59454680 0.59440679 0.59427418 0.59414906 0.59403155 0.59392173 0.59381970 0.59372552 0.59363929 0.59356107 0.59349091 0.59342888 0.59337502 0.59332937 0.59329198 0.59326286 0.59324205 0.59322956 0.59322539 6 | 0.61176305 0.61175511 0.61173132 0.61169174 0.61163646 0.61156561 0.61147935 0.61137790 0.61126149 0.61113039 0.61098489 0.61082533 0.61065206 0.61046547 0.61026597 0.61005401 0.60983006 0.60959460 0.60934814 0.60909118 0.60882426 0.60854790 0.60826265 0.60796904 0.60766763 0.60735896 0.60704358 0.60672203 0.60639486 0.60606261 0.60572581 0.60538499 0.60504066 0.60469334 0.60434353 0.60399172 0.60363840 0.60328405 0.60292912 0.60257406 0.60221932 0.60186533 0.60151251 0.60116125 0.60081196 0.60046502 0.60012080 0.59977967 0.59944196 0.59910802 0.59877818 0.59845275 0.59813204 0.59781634 0.59750593 0.59720109 0.59690207 0.59660915 0.59632254 0.59604250 0.59576924 0.59550298 0.59524391 0.59499225 0.59474817 0.59451185 0.59428346 0.59406316 0.59385110 0.59364743 0.59345229 0.59326578 0.59308805 0.59291919 0.59275932 0.59260855 0.59246699 0.59233475 0.59221192 0.59209858 0.59199484 0.59190074 0.59181637 0.59174179 0.59167704 0.59162217 0.59157723 0.59154224 0.59151723 0.59150222 0.59149722 7 | 0.61422330 0.61421317 0.61418281 0.61413231 0.61406180 0.61397148 0.61386160 0.61373244 0.61358436 0.61341775 0.61323304 0.61303072 0.61281131 0.61257540 0.61232358 0.61205650 0.61177479 0.61147915 0.61117025 0.61084880 0.61051551 0.61017110 0.60981628 0.60945178 0.60907832 0.60869661 0.60830737 0.60791129 0.60750908 0.60710140 0.60668894 0.60627234 0.60585225 0.60542929 0.60500408 0.60457722 0.60414929 0.60372084 0.60329242 0.60286457 0.60243780 0.60201260 0.60158946 0.60116885 0.60075120 0.60033696 0.59992654 0.59952035 0.59911878 0.59872219 0.59833095 0.59794542 0.59756591 0.59719275 0.59682625 0.59646671 0.59611441 0.59576961 0.59543259 0.59510359 0.59478285 0.59447060 0.59416705 0.59387242 0.59358689 0.59331066 0.59304391 0.59278680 0.59253949 0.59230214 0.59207488 0.59185784 0.59165115 0.59145493 0.59126928 0.59109429 0.59093007 0.59077669 0.59063427 0.59050290 0.59038266 0.59027363 0.59017589 0.59008949 0.59001451 0.58995097 0.58989893 0.58985842 0.58982947 0.58981209 0.58980629 8 | 0.61677621 0.61676361 0.61672584 0.61666302 0.61657536 0.61646313 0.61632669 0.61616646 0.61598293 0.61577667 0.61554831 0.61529856 0.61502816 0.61473792 0.61442865 0.61410123 0.61375654 0.61339548 0.61301897 0.61262795 0.61222334 0.61180608 0.61137710 0.61093734 0.61048770 0.61002908 0.60956237 0.60908845 0.60860816 0.60812233 0.60763176 0.60713726 0.60663956 0.60613942 0.60563755 0.60513464 0.60463135 0.60412833 0.60362620 0.60312554 0.60262694 0.60213095 0.60163810 0.60114889 0.60066382 0.60018335 0.59970795 0.59923803 0.59877402 0.59831631 0.59786529 0.59742132 0.59698475 0.59655593 0.59613516 0.59572277 0.59531905 0.59492427 0.59453872 0.59416264 0.59379629 0.59343990 0.59309369 0.59275788 0.59243267 0.59211826 0.59181481 0.59152252 0.59124153 0.59097201 0.59071409 0.59046791 0.59023360 0.59001127 0.58980104 0.58960299 0.58941721 0.58924380 0.58908282 0.58893436 0.58879851 0.58867534 0.58856494 0.58846738 0.58838270 0.58831096 0.58825221 0.58820647 0.58817378 0.58815416 0.58814762 9 | 0.61944074 0.61942531 0.61937909 0.61930224 0.61919505 0.61905791 0.61889133 0.61869590 0.61847233 0.61822143 0.61794409 0.61764129 0.61731403 0.61696341 0.61659053 0.61619655 0.61578264 0.61534999 0.61489980 0.61443327 0.61395160 0.61345598 0.61294758 0.61242755 0.61189703 0.61135712 0.61080889 0.61025338 0.60969161 0.60912455 0.60855317 0.60797837 0.60740104 0.60682204 0.60624217 0.60566221 0.60508291 0.60450497 0.60392908 0.60335589 0.60278600 0.60222001 0.60165848 0.60110195 0.60055092 0.60000587 0.59946726 0.59893555 0.59841113 0.59789441 0.59738578 0.59688560 0.59639423 0.59591201 0.59543928 0.59497634 0.59452350 0.59408103 0.59364922 0.59322831 0.59281857 0.59242022 0.59203349 0.59165860 0.59129575 0.59094513 0.59060692 0.59028130 0.58996844 0.58966847 0.58938156 0.58910783 0.58884740 0.58860040 0.58836693 0.58814708 0.58794096 0.58774863 0.58757017 0.58740564 0.58725510 0.58711865 0.58699635 0.58688828 0.58679450 0.58671505 0.58664999 0.58659935 0.58656315 0.58654143 0.58653419 10 | 0.62224526 0.62222657 0.62217058 0.62207754 0.62194784 0.62178205 0.62158086 0.62134512 0.62107584 0.62077413 0.62044123 0.62007843 0.61968712 0.61926873 0.61882474 0.61835666 0.61786604 0.61735440 0.61682328 0.61627421 0.61570869 0.61512819 0.61453417 0.61392803 0.61331116 0.61268491 0.61205055 0.61140934 0.61076246 0.61011103 0.60945616 0.60879887 0.60814014 0.60748091 0.60682206 0.60616444 0.60550885 0.60485604 0.60420672 0.60356158 0.60292126 0.60228636 0.60165747 0.60103512 0.60041983 0.59981210 0.59921238 0.59862111 0.59803872 0.59746558 0.59690209 0.59634858 0.59580540 0.59527287 0.59475127 0.59424091 0.59374204 0.59325495 0.59277990 0.59231714 0.59186692 0.59142947 0.59100501 0.59059376 0.59019591 0.58981165 0.58944117 0.58908463 0.58874219 0.58841401 0.58810022 0.58780097 0.58751636 0.58724652 0.58699155 0.58675155 0.58652659 0.58631677 0.58612214 0.58594278 0.58577872 0.58563003 0.58549678 0.58537904 0.58527687 0.58519033 0.58511946 0.58506430 0.58502488 0.58500122 0.58499333 11 | 0.62518393 0.62516146 0.62509418 0.62498242 0.62482675 0.62462795 0.62438700 0.62410510 0.62378364 0.62342414 0.62302825 0.62259773 0.62213442 0.62164021 0.62111704 0.62056689 0.61999170 0.61939346 0.61877407 0.61813547 0.61747954 0.61680809 0.61612291 0.61542568 0.61471804 0.61400155 0.61327768 0.61254785 0.61181338 0.61107554 0.61033552 0.60959444 0.60885336 0.60811329 0.60737514 0.60663981 0.60590813 0.60518087 0.60445875 0.60374248 0.60303270 0.60233001 0.60163498 0.60094816 0.60027005 0.59960113 0.59894186 0.59829265 0.59765391 0.59702601 0.59640933 0.59580420 0.59521093 0.59462984 0.59406121 0.59350531 0.59296240 0.59243273 0.59191651 0.59141397 0.59092531 0.59045075 0.58999049 0.58954475 0.58911373 0.58869759 0.58829653 0.58791070 0.58754026 0.58718536 0.58684614 0.58652272 0.58621523 0.58592377 0.58564846 0.58538938 0.58514661 0.58492023 0.58471031 0.58451690 0.58434006 0.58417982 0.58403623 0.58390936 0.58379928 0.58370605 0.58362969 0.58357027 0.58352780 0.58350232 0.58349382 12 | 0.62826570 0.62823883 0.62815839 0.62802485 0.62783901 0.62760195 0.62731507 0.62698002 0.62659869 0.62617314 0.62570559 0.62519839 0.62465397 0.62407480 0.62346341 0.62282232 0.62215401 0.62146100 0.62074572 0.62001051 0.61925767 0.61848935 0.61770764 0.61691451 0.61611184 0.61530137 0.61448477 0.61366359 0.61283929 0.61201322 0.61118666 0.61036079 0.60953672 0.60871547 0.60789800 0.60708520 0.60627789 0.60547687 0.60468283 0.60389647 0.60311840 0.60234920 0.60158944 0.60083963 0.60010024 0.59937173 0.59865453 0.59794904 0.59725563 0.59657466 0.59590647 0.59525137 0.59460967 0.59398165 0.59336758 0.59276770 0.59218227 0.59161151 0.59105562 0.59051483 0.58998930 0.58947923 0.58898478 0.58850611 0.58804340 0.58759683 0.58716657 0.58675278 0.58635561 0.58597520 0.58561170 0.58526522 0.58493588 0.58462379 0.58432905 0.58405175 0.58379197 0.58354978 0.58332525 0.58311843 0.58292937 0.58275810 0.58260466 0.58246909 0.58235147 0.58225185 0.58217027 0.58210678 0.58206141 0.58203418 0.58202510 13 | 0.63150460 0.63147256 0.63137665 0.63121755 0.63099637 0.63071464 0.63037429 0.62997762 0.62952716 0.62902572 0.62847628 0.62788192 0.62724585 0.62657128 0.62586147 0.62511965 0.62434899 0.62355255 0.62273330 0.62189406 0.62103752 0.62016621 0.61928252 0.61838868 0.61748680 0.61657879 0.61566647 0.61475150 0.61383543 0.61291966 0.61200552 0.61109421 0.61018684 0.60928443 0.60838793 0.60749820 0.60661605 0.60574222 0.60487738 0.60402217 0.60317718 0.60234295 0.60152000 0.60070879 0.59990976 0.59912334 0.59834990 0.59758982 0.59684344 0.59611108 0.59539305 0.59468964 0.59400111 0.59332774 0.59266976 0.59202741 0.59140091 0.59079047 0.59019628 0.58961853 0.58905740 0.58851305 0.58798564 0.58747531 0.58698220 0.58650644 0.58604817 0.58560755 0.58518473 0.58477985 0.58439304 0.58402442 0.58367410 0.58334220 0.58302880 0.58273401 0.58245788 0.58220051 0.58196194 0.58174223 0.58154142 0.58135955 0.58119665 0.58105273 0.58092787 0.58082212 0.58073553 0.58066814 0.58061998 0.58059107 0.58058144 14 | 0.63492450 0.63488629 0.63477201 0.63458259 0.63431959 0.63398517 0.63358201 0.63311325 0.63258235 0.63199308 0.63134942 0.63065545 0.62991535 0.62913332 0.62831352 0.62745997 0.62657658 0.62566708 0.62473498 0.62378362 0.62281610 0.62183531 0.62084394 0.61984444 0.61883909 0.61782996 0.61681895 0.61580780 0.61479811 0.61379131 0.61278872 0.61179153 0.61080084 0.60981761 0.60884274 0.60787704 0.60692125 0.60597605 0.60504204 0.60411979 0.60320980 0.60231256 0.60142849 0.60055801 0.59970149 0.59885929 0.59803177 0.59721924 0.59642199 0.59564032 0.59487450 0.59412478 0.59339140 0.59267459 0.59197458 0.59129156 0.59062575 0.58997733 0.58934648 0.58873336 0.58813815 0.58756098 0.58700201 0.58646136 0.58593917 0.58543555 0.58495060 0.58448444 0.58403719 0.58360899 0.58319998 0.58281026 0.58243996 0.58208917 0.58175800 0.58144652 0.58115481 0.58088295 0.58063100 0.58039899 0.58018698 0.57999500 0.57982307 0.57967120 0.57953944 0.57942785 0.57933648 0.57926537 0.57921455 0.57918405 0.57917389 15 | 0.63855836 0.63851275 0.63837635 0.63815052 0.63783745 0.63744020 0.63696247 0.63640856 0.63578321 0.63509149 0.63433869 0.63353022 0.63267154 0.63176800 0.63082479 0.62984689 0.62883904 0.62780566 0.62675089 0.62567855 0.62459216 0.62349493 0.62238982 0.62127949 0.62016636 0.61905261 0.61794020 0.61683086 0.61572617 0.61462752 0.61353618 0.61245325 0.61137973 0.61031653 0.60926442 0.60822414 0.60719633 0.60618156 0.60518036 0.60419321 0.60322052 0.60226270 0.60132010 0.60039305 0.59948185 0.59858678 0.59770810 0.59684605 0.59600086 0.59517274 0.59436193 0.59356865 0.59279311 0.59203549 0.59129600 0.59057482 0.58987212 0.58918807 0.58852283 0.58787655 0.58724937 0.58664144 0.58605289 0.58548383 0.58493438 0.58440465 0.58389474 0.58340473 0.58293470 0.58248478 0.58205506 0.58164569 0.58125675 0.58088836 0.58054061 0.58021358 0.57990735 0.57962199 0.57935755 0.57911409 0.57889164 0.57869023 0.57850988 0.57835061 0.57821243 0.57809541 0.57799959 0.57792501 0.57787172 0.57783974 0.57782908 16 | 0.64242107 0.64236644 0.64220320 0.64193326 0.64155979 0.64108704 0.64052021 0.63986521 0.63912852 0.63831698 0.63743764 0.63649762 0.63550389 0.63446320 0.63338198 0.63226627 0.63112172 0.62995349 0.62876635 0.62756461 0.62635220 0.62513260 0.62390894 0.62268399 0.62146020 0.62023973 0.61902449 0.61781613 0.61661613 0.61542578 0.61424618 0.61307834 0.61192310 0.61078123 0.60965338 0.60854015 0.60744205 0.60635953 0.60529302 0.60424286 0.60320940 0.60219291 0.60119369 0.60021196 0.59924796 0.59830189 0.59737395 0.59646432 0.59557316 0.59470064 0.59384690 0.59301209 0.59219634 0.59139982 0.59062270 0.58986512 0.58912724 0.58840920 0.58771115 0.58703323 0.58637555 0.58573825 0.58512144 0.58452524 0.58394974 0.58339506 0.58286127 0.58234846 0.58185670 0.58138607 0.58093664 0.58050852 0.58010182 0.57971665 0.57935309 0.57901124 0.57869115 0.57839291 0.57811656 0.57786216 0.57762974 0.57741933 0.57723095 0.57706461 0.57692031 0.57679810 0.57669804 0.57662016 0.57656451 0.57653111 0.57651998 17 | 0.64653994 0.64647422 0.64627799 0.64595403 0.64550686 0.64494254 0.64426833 0.64349245 0.64262375 0.64167149 0.64064502 0.63955354 0.63840593 0.63721058 0.63597533 0.63470741 0.63341341 0.63209931 0.63077042 0.62943146 0.62808658 0.62673943 0.62539316 0.62405052 0.62271388 0.62138527 0.62006644 0.61875888 0.61746388 0.61618251 0.61491570 0.61366424 0.61242880 0.61120996 0.61000819 0.60882393 0.60765752 0.60650929 0.60537949 0.60426838 0.60317616 0.60210302 0.60104912 0.60001463 0.59899968 0.59800442 0.59702895 0.59607341 0.59513790 0.59422253 0.59332741 0.59245263 0.59159828 0.59076445 0.58995125 0.58915876 0.58838713 0.58763647 0.58690692 0.58619859 0.58551159 0.58484605 0.58420206 0.58357973 0.58297916 0.58240043 0.58184363 0.58130883 0.58079611 0.58030553 0.57983713 0.57939099 0.57896720 0.57856588 0.57818711 0.57783097 0.57749754 0.57718688 0.57689906 0.57663411 0.57639208 0.57617299 0.57597686 0.57580370 0.57565350 0.57552630 0.57542215 0.57534109 0.57528317 0.57524840 0.57523681 18 | 0.65095028 0.65087072 0.65063341 0.65024240 0.64970426 0.64902764 0.64822282 0.64730126 0.64627514 0.64515691 0.64395885 0.64269279 0.64136988 0.64000044 0.63859389 0.63715870 0.63570238 0.63423153 0.63275188 0.63126837 0.62978524 0.62830609 0.62683395 0.62537140 0.62392056 0.62248321 0.62106082 0.61965461 0.61826556 0.61689449 0.61554205 0.61420878 0.61289509 0.61160135 0.61032781 0.60907470 0.60784221 0.60663046 0.60543958 0.60426967 0.60312080 0.60199305 0.60088648 0.59980115 0.59873711 0.59769443 0.59667314 0.59567332 0.59469501 0.59373827 0.59280316 0.59188974 0.59099805 0.59012817 0.58928014 0.58845403 0.58764989 0.58686780 0.58610787 0.58537020 0.58465490 0.58396207 0.58329180 0.58264420 0.58201936 0.58141735 0.58083825 0.58028214 0.57974909 0.57923914 0.57875235 0.57828876 0.57784843 0.57743147 0.57703795 0.57666797 0.57632160 0.57599891 0.57569995 0.57542478 0.57517342 0.57494591 0.57474226 0.57456247 0.57440655 0.57427450 0.57416638 0.57408223 0.57402210 0.57398601 0.57397398 19 | 0.65569943 0.65560231 0.65531301 0.65483756 0.65418556 0.65336956 0.65240424 0.65130570 0.65009066 0.64877577 0.64737710 0.64590968 0.64438735 0.64282256 0.64122633 0.63960825 0.63797655 0.63633827 0.63469930 0.63306456 0.63143813 0.62982334 0.62822290 0.62663900 0.62507339 0.62352745 0.62200225 0.62049863 0.61901720 0.61755842 0.61612260 0.61470997 0.61332065 0.61195471 0.61061217 0.60929301 0.60799720 0.60672467 0.60547539 0.60424928 0.60304631 0.60186641 0.60070954 0.59957566 0.59846474 0.59737675 0.59631167 0.59526951 0.59425025 0.59325391 0.59228050 0.59133004 0.59040254 0.58949805 0.58861658 0.58775818 0.58692288 0.58611071 0.58532170 0.58455594 0.58381352 0.58309454 0.58239907 0.58172723 0.58107908 0.58045470 0.57985418 0.57927758 0.57872497 0.57819639 0.57769190 0.57721153 0.57675532 0.57632332 0.57591564 0.57553236 0.57517356 0.57483929 0.57452963 0.57424462 0.57398429 0.57374867 0.57353778 0.57335163 0.57319019 0.57305348 0.57294155 0.57285443 0.57279217 0.57275481 0.57274235 20 | 0.66084800 0.66072821 0.66037195 0.65978834 0.65899172 0.65800050 0.65683588 0.65552057 0.65407748 0.65252882 0.65089534 0.64919596 0.64744745 0.64566438 0.64385918 0.64204230 0.64022239 0.63840653 0.63660044 0.63480873 0.63303500 0.63128206 0.62955206 0.62784661 0.62616685 0.62451362 0.62288744 0.62128864 0.61971737 0.61817363 0.61665737 0.61516843 0.61370661 0.61227169 0.61086341 0.60948152 0.60812574 0.60679583 0.60549154 0.60421261 0.60295885 0.60173002 0.60052598 0.59934657 0.59819168 0.59706120 0.59595506 0.59487317 0.59381549 0.59278198 0.59177261 0.59078735 0.58982622 0.58888919 0.58797629 0.58708751 0.58622289 0.58538243 0.58456615 0.58377407 0.58300625 0.58226275 0.58154366 0.58084907 0.58017906 0.57953371 0.57891309 0.57831726 0.57774628 0.57720022 0.57667910 0.57618298 0.57571187 0.57526581 0.57484486 0.57444912 0.57407867 0.57373357 0.57341388 0.57311964 0.57285091 0.57260770 0.57239003 0.57219790 0.57203131 0.57189024 0.57177472 0.57168483 0.57162058 0.57158203 0.57156917 21 | 0.66645768 0.66630802 0.66586389 0.66513937 0.66415628 0.66294213 0.66152783 0.65994547 0.65822640 0.65639999 0.65449271 0.65252768 0.65052460 0.64849991 0.64646701 0.64443671 0.64241756 0.64041619 0.63843768 0.63648579 0.63456326 0.63267203 0.63081336 0.62898802 0.62719639 0.62543856 0.62371439 0.62202360 0.62036579 0.61874047 0.61714713 0.61558521 0.61405415 0.61255341 0.61108245 0.60964076 0.60822784 0.60684323 0.60548652 0.60415730 0.60285521 0.60157993 0.60033114 0.59910858 0.59791201 0.59674122 0.59559607 0.59447643 0.59338220 0.59231329 0.59126965 0.59025121 0.58925795 0.58828984 0.58734687 0.58642902 0.58553631 0.58466872 0.58382628 0.58300899 0.58221686 0.58144990 0.58070820 0.57999184 0.57930088 0.57863541 0.57799550 0.57738122 0.57679262 0.57622975 0.57569267 0.57518140 0.57469597 0.57423641 0.57380274 0.57339504 0.57301341 0.57265790 0.57232857 0.57202549 0.57174868 0.57149818 0.57127399 0.57107612 0.57090457 0.57075931 0.57064036 0.57054780 0.57048164 0.57044194 0.57042870 22 | 0.67261220 0.67242225 0.67186019 0.67094835 0.66972077 0.66821927 0.66648932 0.66457634 0.66252299 0.66036748 0.65814264 0.65587581 0.65358917 0.65130029 0.64902275 0.64676686 0.64454018 0.64234816 0.64019451 0.63808167 0.63601106 0.63398333 0.63199860 0.63005657 0.62815665 0.62629805 0.62447986 0.62270110 0.62096075 0.61925778 0.61759118 0.61595997 0.61436323 0.61280007 0.61126965 0.60977122 0.60830404 0.60686748 0.60546092 0.60408381 0.60273566 0.60141603 0.60012450 0.59886072 0.59762436 0.59641513 0.59523278 0.59407709 0.59294792 0.59184513 0.59076864 0.58971836 0.58869424 0.58769623 0.58672431 0.58577844 0.58485862 0.58396484 0.58309710 0.58225541 0.58143976 0.58065017 0.57988663 0.57914922 0.57843801 0.57775308 0.57709450 0.57646234 0.57585665 0.57527750 0.57472492 0.57419895 0.57369962 0.57322695 0.57278095 0.57236166 0.57196918 0.57160357 0.57126491 0.57095323 0.57066858 0.57041100 0.57018048 0.56997705 0.56980067 0.56965134 0.56952907 0.56943391 0.56936590 0.56932509 0.56931148 23 | 0.67942065 0.67917481 0.67845022 0.67728361 0.67572953 0.67385273 0.67172060 0.66939732 0.66694001 0.66439699 0.66180743 0.65920210 0.65660436 0.65403146 0.65149573 0.64900564 0.64656671 0.64418223 0.64185388 0.63958213 0.63736661 0.63520638 0.63310008 0.63104616 0.62904288 0.62708849 0.62518119 0.62331925 0.62150099 0.61972480 0.61798918 0.61629271 0.61463408 0.61301206 0.61142556 0.60987353 0.60835504 0.60686926 0.60541541 0.60399280 0.60260082 0.60123889 0.59990653 0.59860329 0.59732878 0.59608264 0.59486459 0.59367433 0.59251163 0.59137630 0.59026821 0.58918726 0.58813337 0.58710648 0.58610654 0.58513354 0.58418744 0.58326824 0.58237592 0.58151050 0.58067196 0.57986031 0.57907554 0.57831767 0.57758676 0.57688289 0.57620612 0.57555654 0.57493419 0.57433914 0.57377144 0.57323112 0.57271821 0.57223272 0.57177467 0.57134408 0.57094101 0.57056554 0.57021775 0.56989768 0.56960537 0.56934086 0.56910416 0.56889528 0.56871419 0.56856089 0.56843536 0.56833766 0.56826785 0.56822594 0.56821197 24 | 0.68702718 0.68670107 0.68574540 0.68422303 0.68222430 0.67985129 0.67720428 0.67437270 0.67143081 0.66843701 0.66543526 0.66245728 0.65952510 0.65665331 0.65385094 0.65112300 0.64847163 0.64589700 0.64339794 0.64097241 0.63861783 0.63633133 0.63410992 0.63195058 0.62985035 0.62780639 0.62581600 0.62387665 0.62198597 0.62014177 0.61834201 0.61658487 0.61486865 0.61319182 0.61155298 0.60995088 0.60838438 0.60685246 0.60535419 0.60388875 0.60245541 0.60105352 0.59968250 0.59834182 0.59703105 0.59574978 0.59449765 0.59327437 0.59207965 0.59091327 0.58977502 0.58866475 0.58758236 0.58652779 0.58550099 0.58450192 0.58353056 0.58258689 0.58167090 0.58078259 0.57992196 0.57908901 0.57828374 0.57750615 0.57675625 0.57603410 0.57533978 0.57467337 0.57403494 0.57342453 0.57284220 0.57228800 0.57176194 0.57126406 0.57079435 0.57035283 0.56993952 0.56955453 0.56919791 0.56886972 0.56857001 0.56829881 0.56805612 0.56784197 0.56765632 0.56749917 0.56737050 0.56727035 0.56719878 0.56715582 0.56714150 25 | 0.69562411 0.69517780 0.69388086 0.69184681 0.68923057 0.68619561 0.68288994 0.67943439 0.67592037 0.67241308 0.66895659 0.66557904 0.66229711 0.65911948 0.65604940 0.65308658 0.65022841 0.64747093 0.64480944 0.64223888 0.63975411 0.63735012 0.63502210 0.63276551 0.63057611 0.62844997 0.62638347 0.62437332 0.62241648 0.62051019 0.61865195 0.61683950 0.61507077 0.61334390 0.61165724 0.61000929 0.60839874 0.60682440 0.60528523 0.60378028 0.60230872 0.60086982 0.59946292 0.59808746 0.59674294 0.59542890 0.59414497 0.59289081 0.59166612 0.59047064 0.58930416 0.58816648 0.58705745 0.58597697 0.58492499 0.58390148 0.58290641 0.58193976 0.58100153 0.58009171 0.57921030 0.57835732 0.57753275 0.57673661 0.57596887 0.57522957 0.57451878 0.57383657 0.57318302 0.57255818 0.57196212 0.57139487 0.57085647 0.57034694 0.56986628 0.56941450 0.56899161 0.56859767 0.56823278 0.56789698 0.56759032 0.56731284 0.56706455 0.56684545 0.56665553 0.56649477 0.56636315 0.56626071 0.56618750 0.56614355 0.56612890 26 | 0.70547342 0.70483704 0.70301226 0.70021772 0.69672936 0.69280999 0.68867138 0.68446628 0.68029602 0.67622314 0.67228307 0.66849325 0.66485968 0.66138126 0.65805278 0.65486673 0.65181454 0.64888734 0.64607635 0.64337320 0.64077003 0.63825958 0.63583521 0.63349084 0.63122099 0.62902068 0.62688542 0.62481119 0.62279433 0.62083158 0.61892001 0.61705698 0.61524013 0.61346734 0.61173671 0.61004655 0.60839534 0.60678173 0.60520457 0.60366280 0.60215553 0.60068195 0.59924136 0.59783313 0.59645673 0.59511168 0.59379758 0.59251407 0.59126083 0.59003760 0.58884415 0.58768027 0.58654580 0.58544057 0.58436452 0.58331761 0.58229981 0.58131111 0.58035152 0.57942102 0.57851964 0.57764736 0.57680421 0.57599018 0.57520527 0.57444947 0.57372283 0.57302541 0.57235730 0.57171857 0.57110927 0.57052945 0.56997914 0.56945837 0.56896716 0.56850548 0.56807335 0.56767082 0.56729795 0.56695482 0.56664147 0.56635793 0.56610424 0.56588038 0.56568634 0.56552211 0.56538764 0.56528299 0.56520819 0.56516330 0.56514834 27 | 0.71694988 0.71599025 0.71330055 0.70933709 0.70460706 0.69952230 0.69436172 0.68929250 0.68440469 0.67974016 0.67531247 0.67111936 0.66715025 0.66339061 0.65982447 0.65643583 0.65320943 0.65013104 0.64718769 0.64436763 0.64166034 0.63905638 0.63654736 0.63412580 0.63178505 0.62951919 0.62732295 0.62519165 0.62312113 0.62110767 0.61914795 0.61723905 0.61537833 0.61356347 0.61179239 0.61006323 0.60837435 0.60672430 0.60511177 0.60353561 0.60199486 0.60048866 0.59901625 0.59757700 0.59617034 0.59479577 0.59345287 0.59214127 0.59086066 0.58961076 0.58839134 0.58720219 0.58604315 0.58491405 0.58381478 0.58274527 0.58170549 0.58069545 0.57971515 0.57876460 0.57784381 0.57695279 0.57609156 0.57526012 0.57445848 0.57368663 0.57294458 0.57223238 0.57155011 0.57089784 0.57027565 0.56968358 0.56912167 0.56858996 0.56808844 0.56761713 0.56717600 0.56676508 0.56638445 0.56603418 0.56571431 0.56542488 0.56516591 0.56493741 0.56473936 0.56457174 0.56443451 0.56432770 0.56425136 0.56420554 0.56419027 28 | 0.73060828 0.72903909 0.72482781 0.71902213 0.71255309 0.70600167 0.69966475 0.69366984 0.68805586 0.68281883 0.67793570 0.67337624 0.66910892 0.66510356 0.66133247 0.65777083 0.65439665 0.65119060 0.64813573 0.64521722 0.64242212 0.63973911 0.63715826 0.63467088 0.63226935 0.62994695 0.62769777 0.62551660 0.62339884 0.62134042 0.61933773 0.61738759 0.61548718 0.61363400 0.61182584 0.61006072 0.60833693 0.60665291 0.60500732 0.60339894 0.60182673 0.60028975 0.59878723 0.59731850 0.59588299 0.59448019 0.59310968 0.59177108 0.59046409 0.58918843 0.58794388 0.58673023 0.58554732 0.58439501 0.58327317 0.58218169 0.58112053 0.58008970 0.57908921 0.57811908 0.57717932 0.57626997 0.57539105 0.57454256 0.57372452 0.57293693 0.57217978 0.57145310 0.57075696 0.57009144 0.56945661 0.56885252 0.56827923 0.56773677 0.56722514 0.56674436 0.56629440 0.56587526 0.56548701 0.56512973 0.56480346 0.56450824 0.56424411 0.56401105 0.56380906 0.56363811 0.56349817 0.56338924 0.56331139 0.56326467 0.56324909 29 | 0.74730590 0.74438895 0.73728542 0.72862247 0.71990315 0.71170086 0.70416867 0.69730066 0.69103809 0.68530989 0.68004748 0.67518961 0.67068326 0.66648318 0.66255091 0.65885377 0.65536403 0.65205804 0.64891559 0.64591936 0.64305449 0.64030815 0.63766926 0.63512818 0.63267655 0.63030707 0.62801335 0.62578979 0.62363146 0.62153405 0.61949375 0.61750720 0.61557144 0.61368386 0.61184216 0.61004431 0.60828850 0.60657318 0.60489693 0.60325854 0.60165692 0.60009114 0.59856035 0.59706385 0.59560107 0.59417151 0.59277474 0.59141042 0.59007823 0.58877791 0.58750925 0.58627205 0.58506618 0.58389148 0.58274786 0.58163521 0.58055344 0.57950255 0.57848256 0.57749351 0.57653541 0.57560832 0.57471225 0.57384723 0.57301329 0.57221043 0.57143865 0.57069795 0.56998837 0.56931000 0.56866292 0.56804720 0.56746287 0.56690998 0.56638855 0.56589858 0.56544005 0.56501295 0.56461733 0.56425325 0.56392078 0.56361996 0.56335081 0.56311334 0.56290753 0.56273336 0.56259078 0.56247981 0.56240049 0.56235289 0.56233702 30 | 0.76844774 0.76161842 0.74895356 0.73655371 0.72553800 0.71588948 0.70740598 0.69988503 0.69315706 0.68708601 0.68156362 0.67650344 0.67183594 0.66750470 0.66346351 0.65967426 0.65610522 0.65272985 0.64952580 0.64647411 0.64355867 0.64076569 0.63808332 0.63550134 0.63301090 0.63060433 0.62827495 0.62601694 0.62382518 0.62169521 0.61962311 0.61760543 0.61563913 0.61372156 0.61185036 0.61002348 0.60823910 0.60649563 0.60479168 0.60312601 0.60149756 0.59990537 0.59834863 0.59682660 0.59533869 0.59388439 0.59246330 0.59107508 0.58971943 0.58839612 0.58710494 0.58584573 0.58461834 0.58342267 0.58225860 0.58112607 0.58002499 0.57895531 0.57791704 0.57691024 0.57593494 0.57499119 0.57407903 0.57319849 0.57234962 0.57153241 0.57074689 0.56999304 0.56927088 0.56858048 0.56792193 0.56729530 0.56670064 0.56613799 0.56560738 0.56510881 0.56464226 0.56420773 0.56380521 0.56343479 0.56309653 0.56279048 0.56251665 0.56227505 0.56206568 0.56188850 0.56174347 0.56163059 0.56154991 0.56150148 0.56148534 31 | 0.79654836 0.77316564 0.75499281 0.74034665 0.72820425 0.71790836 0.70901690 0.70122097 0.69429768 0.68808179 0.68244797 0.67729922 0.67255923 0.66816701 0.66407327 0.66023767 0.65662695 0.65321342 0.64997386 0.64688873 0.64394144 0.64111784 0.63840581 0.63579494 0.63327621 0.63084181 0.62848495 0.62619971 0.62398094 0.62182412 0.61972533 0.61768109 0.61568837 0.61374450 0.61184716 0.60999429 0.60818410 0.60641501 0.60468564 0.60299479 0.60134142 0.59972459 0.59814352 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0.59794271 0.59637391 0.59483981 0.59333992 0.59187381 0.59044118 0.58904179 0.58767545 0.58634201 0.58504135 0.58377338 0.58253804 0.58133525 0.58016499 0.57902720 0.57792187 0.57684894 0.57580844 0.57480044 0.57382501 0.57288222 0.57197213 0.57109478 0.57025022 0.56943848 0.56865955 0.56791343 0.56720014 0.56651975 0.56587235 0.56525801 0.56467677 0.56412867 0.56361372 0.56313191 0.56268321 0.56226760 0.56188513 0.56153586 0.56121985 0.56093713 0.56068770 0.56047156 0.56028867 0.56013897 0.56002246 0.55993919 0.55988920 0.55987254 33 | 0.75332422 0.75008190 0.74230651 0.73299320 0.72375094 0.71514452 0.70729813 0.70018061 0.69371457 0.68781570 0.68240609 0.67741783 0.67279311 0.66848320 0.66444706 0.66065019 0.65706344 0.65366218 0.65042547 0.64733550 0.64437700 0.64153690 0.63880392 0.63616831 0.63362161 0.63115650 0.62876655 0.62644617 0.62419048 0.62199517 0.61985650 0.61777117 0.61573634 0.61374950 0.61180848 0.60991136 0.60805648 0.60624241 0.60446786 0.60273177 0.60103317 0.59937125 0.59774531 0.59615475 0.59459903 0.59307772 0.59159043 0.59013683 0.58871671 0.58732991 0.58597631 0.58465583 0.58336840 0.58211398 0.58089254 0.57970407 0.57854854 0.57742594 0.57633626 0.57527948 0.57425567 0.57326490 0.57230726 0.57138283 0.57049167 0.56963383 0.56880934 0.56801821 0.56726046 0.56653607 0.56584509 0.56518761 0.56456372 0.56397346 0.56341687 0.56289396 0.56240473 0.56194916 0.56152720 0.56113888 0.56078428 0.56046345 0.56017641 0.55992319 0.55970376 0.55951809 0.55936614 0.55924787 0.55916334 0.55911260 0.55909568 34 | 0.73900316 0.73716784 0.73231013 0.72574707 0.71857619 0.71143116 0.70460684 0.69821228 0.69226658 0.68674901 0.68162343 0.67684969 0.67238880 0.66820500 0.66426641 0.66054510 0.65701673 0.65366023 0.65045737 0.64739239 0.64445162 0.64162325 0.63889699 0.63626390 0.63371617 0.63124698 0.62885037 0.62652113 0.62425466 0.62204694 0.61989446 0.61779410 0.61574315 0.61373926 0.61178039 0.60986474 0.60799078 0.60615715 0.60436269 0.60260640 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0.60250162 0.60076426 0.59906321 0.59739791 0.59576790 0.59417278 0.59261221 0.59108593 0.58959369 0.58813533 0.58671067 0.58531968 0.58396233 0.58263863 0.58134861 0.58009229 0.57886972 0.57768092 0.57652594 0.57540479 0.57431751 0.57326409 0.57224460 0.57125916 0.57030786 0.56939080 0.56850805 0.56765966 0.56684568 0.56606611 0.56532095 0.56461019 0.56393390 0.56329217 0.56268506 0.56211262 0.56157487 0.56107181 0.56060341 0.56016963 0.55977044 0.55940592 0.55907611 0.55878106 0.55852078 0.55829524 0.55810443 0.55794828 0.55782675 0.55773989 0.55768775 0.55767036 36 | 0.71818317 0.71736212 0.71503186 0.71152614 0.70724288 0.70253405 0.69766051 0.69279387 0.68803676 0.68344461 0.67904274 0.67483828 0.67082784 0.66700236 0.66335000 0.65985796 0.65651345 0.65330423 0.65021894 0.64724718 0.64437953 0.64160753 0.63892360 0.63632099 0.63379369 0.63133636 0.62894427 0.62661324 0.62433954 0.62211992 0.61995148 0.61783169 0.61575830 0.61372937 0.61174316 0.60979820 0.60789324 0.60602718 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0.60597272 0.60412994 0.60232371 0.60055347 0.59881878 0.59711925 0.59545459 0.59382457 0.59222898 0.59066770 0.58914061 0.58764763 0.58618870 0.58476380 0.58337292 0.58201615 0.58069359 0.57940533 0.57815148 0.57693213 0.57574736 0.57459725 0.57348187 0.57240125 0.57135544 0.57034450 0.56936856 0.56842775 0.56752215 0.56665185 0.56581690 0.56501734 0.56425316 0.56352435 0.56283091 0.56217293 0.56155048 0.56096361 0.56041235 0.55989671 0.55941666 0.55897215 0.55856312 0.55818962 0.55785170 0.55754940 0.55728273 0.55705168 0.55685622 0.55669629 0.55657181 0.55648285 0.55642944 0.55641164 38 | 0.70382718 0.70336208 0.70200960 0.69988584 0.69714976 0.69396971 0.69049874 0.68686206 0.68315456 0.67944389 0.67577571 0.67217907 0.66867117 0.66526092 0.66195170 0.65874327 0.65563310 0.65261734 0.64969144 0.64685052 0.64408971 0.64140422 0.63878956 0.63624148 0.63375608 0.63132979 0.62895937 0.62664189 0.62437472 0.62215552 0.61998220 0.61785292 0.61576606 0.61372019 0.61171407 0.60974662 0.60781691 0.60592415 0.60406769 0.60224703 0.60046175 0.59871149 0.59699601 0.59531509 0.59366858 0.59205637 0.59047840 0.58893462 0.58742503 0.58594961 0.58450838 0.58310137 0.58172865 0.58039037 0.57908666 0.57781766 0.57658349 0.57538427 0.57422009 0.57309105 0.57199721 0.57093861 0.56991531 0.56892742 0.56797508 0.56705840 0.56617746 0.56533234 0.56452307 0.56374966 0.56301210 0.56231037 0.56164452 0.56101465 0.56042080 0.55986301 0.55934129 0.55885560 0.55840591 0.55799214 0.55761431 0.55727248 0.55696668 0.55669694 0.55646323 0.55626553 0.55610377 0.55597789 0.55588790 0.55583389 0.55581588 39 | 0.69823540 0.69786584 0.69678407 0.69506462 0.69281353 0.69014927 0.68718638 0.68402526 0.68074768 0.67741661 0.67407830 0.67076530 0.66749952 0.66429499 0.66115998 0.65809871 0.65511260 0.65220119 0.64936281 0.64659505 0.64389508 0.64125988 0.63868640 0.63617165 0.63371280 0.63130716 0.62895226 0.62664583 0.62438582 0.62217039 0.61999786 0.61786679 0.61577587 0.61372398 0.61171014 0.60973349 0.60779331 0.60588898 0.60401999 0.60218597 0.60038662 0.59862174 0.59689116 0.59519479 0.59353256 0.59190445 0.59031047 0.58875066 0.58722505 0.58573372 0.58427672 0.58285413 0.58146602 0.58011255 0.57879390 0.57751024 0.57626173 0.57504850 0.57387070 0.57272842 0.57162176 0.57055078 0.56951553 0.56851609 0.56755261 0.56662521 0.56573400 0.56487905 0.56406040 0.56327808 0.56253208 0.56182235 0.56114894 0.56051193 0.55991137 0.55934730 0.55881972 0.55832862 0.55787395 0.55745563 0.55707365 0.55672807 0.55641892 0.55614623 0.55590998 0.55571014 0.55554663 0.55541939 0.55532844 0.55527384 0.55525564 40 | 0.69343453 0.69313292 0.69224587 0.69082331 0.68893832 0.68667581 0.68412185 0.68135596 0.67844663 0.67544980 0.67240929 0.66935812 0.66632039 0.66331309 0.66034778 0.65743196 0.65457010 0.65176450 0.64901594 0.64632412 0.64368807 0.64110635 0.63857728 0.63609905 0.63366983 0.63128782 0.62895130 0.62665866 0.62440840 0.62219919 0.62002980 0.61789915 0.61580629 0.61375039 0.61173073 0.60974671 0.60779780 0.60588359 0.60400372 0.60215793 0.60034606 0.59856804 0.59682382 0.59511339 0.59343680 0.59179412 0.59018543 0.58861083 0.58707044 0.58556438 0.58409278 0.58265575 0.58125340 0.57988588 0.57855341 0.57725618 0.57599438 0.57476820 0.57357778 0.57242325 0.57130474 0.57022231 0.56917604 0.56816598 0.56719225 0.56625501 0.56535437 0.56449040 0.56366316 0.56287268 0.56211895 0.56140194 0.56072164 0.56007813 0.55947147 0.55890169 0.55836882 0.55787281 0.55741364 0.55699121 0.55660548 0.55625652 0.55594436 0.55566902 0.55543048 0.55522870 0.55506363 0.55493517 0.55484335 0.55478823 0.55476985 41 | 0.68928831 0.68903661 0.68829372 0.68709430 0.68549020 0.68354348 0.68131938 0.67888073 0.67628413 0.67357803 0.67080230 0.66798865 0.66516158 0.66233951 0.65953597 0.65676065 0.65402029 0.65131932 0.64866048 0.64604529 0.64347435 0.64094763 0.63846469 0.63602481 0.63362709 0.63127056 0.62895423 0.62667712 0.62443831 0.62223692 0.62007219 0.61794340 0.61584996 0.61379133 0.61176707 0.60977681 0.60782025 0.60589717 0.60400739 0.60215078 0.60032732 0.59853703 0.59677998 0.59505630 0.59336612 0.59170958 0.59008687 0.58849816 0.58694364 0.58542349 0.58393789 0.58248700 0.58107100 0.57969003 0.57834431 0.57703407 0.57575954 0.57452093 0.57331841 0.57215215 0.57102227 0.56992889 0.56887206 0.56785184 0.56686834 0.56592171 0.56501206 0.56413950 0.56330408 0.56250583 0.56174475 0.56102082 0.56033399 0.55968432 0.55907188 0.55849672 0.55795883 0.55745819 0.55699476 0.55656845 0.55617920 0.55582706 0.55551206 0.55523422 0.55499353 0.55478995 0.55462340 0.55449380 0.55440116 0.55434556 0.55432702 42 | 0.68569162 0.68547754 0.68484396 0.68381569 0.68243046 0.68073449 0.67877783 0.67661024 0.67427826 0.67182328 0.66928072 0.66668003 0.66404496 0.66139429 0.65874252 0.65610069 0.65347705 0.65087764 0.64830675 0.64576732 0.64326131 0.64078989 0.63835371 0.63595302 0.63358779 0.63125781 0.62896278 0.62670233 0.62447605 0.62228357 0.62012452 0.61799860 0.61590551 0.61384504 0.61181701 0.60982131 0.60785784 0.60592658 0.60402754 0.60216076 0.60032632 0.59852434 0.59675504 0.59501863 0.59331535 0.59164545 0.59000917 0.58840679 0.58683855 0.58530470 0.58380548 0.58234112 0.58091181 0.57951776 0.57815916 0.57683627 0.57554936 0.57429866 0.57308438 0.57190670 0.57076577 0.56966171 0.56859463 0.56756456 0.56657159 0.56561585 0.56469749 0.56381661 0.56297327 0.56216751 0.56139934 0.56066872 0.55997560 0.55932000 0.55870201 0.55812165 0.55757894 0.55707385 0.55660634 0.55617631 0.55578369 0.55542850 0.55511079 0.55483056 0.55458782 0.55438250 0.55421454 0.55408386 0.55399044 0.55393437 0.55391567 43 | 0.68256216 0.68237705 0.68182805 0.68093337 0.67972112 0.67822633 0.67648786 0.67454539 0.67243717 0.67019831 0.66785987 0.66544859 0.66298686 0.66049305 0.65798195 0.65546530 0.65295228 0.65045005 0.64796403 0.64549833 0.64305598 0.64063917 0.63824949 0.63588804 0.63355557 0.63125258 0.62897938 0.62673618 0.62452307 0.62234014 0.62018743 0.61806499 0.61597287 0.61391114 0.61187991 0.60987928 0.60790940 0.60597043 0.60406257 0.60218601 0.60034098 0.59852772 0.59674653 0.59499774 0.59328169 0.59159873 0.58994919 0.58833341 0.58675171 0.58520441 0.58369181 0.58221419 0.58077180 0.57936488 0.57799364 0.57665834 0.57535927 0.57409669 0.57287086 0.57168196 0.57053018 0.56941565 0.56833849 0.56729877 0.56629652 0.56533189 0.56440501 0.56351599 0.56266491 0.56185182 0.56107672 0.56033957 0.55964033 0.55897897 0.55835558 0.55777017 0.55722278 0.55671338 0.55624190 0.55580827 0.55541238 0.55505425 0.55473391 0.55445138 0.55420664 0.55399965 0.55383034 0.55369860 0.55360443 0.55354790 0.55352906 44 | 0.67983636 0.67967398 0.67919156 0.67840282 0.67732907 0.67599736 0.67443821 0.67268354 0.67076483 0.66871184 0.66655160 0.66430803 0.66200186 0.65965060 0.65726885 0.65486855 0.65245941 0.65004926 0.64764437 0.64524969 0.64286912 0.64050569 0.63816177 0.63583922 0.63353946 0.63126361 0.62901257 0.62678705 0.62458764 0.62241484 0.62026908 0.61815076 0.61606025 0.61399792 0.61196412 0.60995920 0.60798353 0.60603746 0.60412136 0.60223560 0.60038054 0.59855657 0.59676405 0.59500343 0.59327516 0.59157966 0.58991736 0.58828868 0.58669402 0.58513376 0.58360825 0.58211782 0.58066280 0.57924345 0.57786002 0.57651277 0.57520199 0.57392799 0.57269103 0.57149134 0.57032913 0.56920454 0.56811771 0.56706871 0.56605760 0.56508446 0.56414944 0.56325266 0.56239421 0.56157413 0.56079243 0.56004909 0.55934404 0.55867723 0.55804872 0.55745856 0.55690675 0.55639327 0.55591806 0.55548104 0.55508209 0.55472119 0.55439838 0.55411369 0.55386709 0.55365854 0.55348795 0.55335524 0.55326037 0.55320342 0.55318443 45 | 0.67746527 0.67732102 0.67689187 0.67618833 0.67522691 0.67402878 0.67261822 0.67102113 0.66926355 0.66737068 0.66536601 0.66327077 0.66110387 0.65888174 0.65661844 0.65432582 0.65201377 0.64969050 0.64736282 0.64503631 0.64271552 0.64040416 0.63810526 0.63582128 0.63355425 0.63130586 0.62907750 0.62687036 0.62468546 0.62252371 0.62038590 0.61827276 0.61618497 0.61412316 0.61208794 0.61007991 0.60809961 0.60614762 0.60422446 0.60233067 0.60046677 0.59863326 0.59683062 0.59505937 0.59332005 0.59161319 0.58993931 0.58829890 0.58669242 0.58512033 0.58358304 0.58208093 0.58061438 0.57918369 0.57778917 0.57643105 0.57510965 0.57382529 0.57257825 0.57136881 0.57019717 0.56906351 0.56796798 0.56691066 0.56589161 0.56491089 0.56396863 0.56306496 0.56219997 0.56137372 0.56058621 0.55983741 0.55912727 0.55845571 0.55782276 0.55722846 0.55667282 0.55615582 0.55567740 0.55523747 0.55483589 0.55447263 0.55414773 0.55386120 0.55361302 0.55340314 0.55323148 0.55309793 0.55300247 0.55294516 0.55292605 46 | 0.67540326 0.67527365 0.67488764 0.67425343 0.67338399 0.67229616 0.67100949 0.66954517 0.66792488 0.66617001 0.66430092 0.66233644 0.66029363 0.65818774 0.65603212 0.65383828 0.65161609 0.64937390 0.64711882 0.64485685 0.64259304 0.64033163 0.63807617 0.63582965 0.63359461 0.63137320 0.62916729 0.62697849 0.62480821 0.62265772 0.62052817 0.61842059 0.61633594 0.61427513 0.61223900 0.61022836 0.60824399 0.60628662 0.60435697 0.60245571 0.60058352 0.59874103 0.59692884 0.59514755 0.59339778 0.59168016 0.58999528 0.58834371 0.58672599 0.58514263 0.58359412 0.58208090 0.58060337 0.57916189 0.57775680 0.57638838 0.57505692 0.57376275 0.57250619 0.57128752 0.57010699 0.56896478 0.56786105 0.56679590 0.56576941 0.56478160 0.56383259 0.56292250 0.56205144 0.56121945 0.56042656 0.55967273 0.55895790 0.55828197 0.55764494 0.55704686 0.55648773 0.55596753 0.55548619 0.55504361 0.55463966 0.55427427 0.55394748 0.55365929 0.55340969 0.55319861 0.55302599 0.55289170 0.55279571 0.55273808 0.55271887 47 | 0.67361419 0.67349656 0.67314586 0.67256863 0.67177520 0.67077916 0.66959641 0.66824444 0.66674145 0.66510564 0.66335468 0.66150525 0.65957270 0.65757103 0.65551278 0.65340902 0.65126939 0.64910225 0.64691484 0.64471341 0.64250337 0.64028934 0.63807530 0.63586467 0.63366041 0.63146509 0.62928098 0.62711006 0.62495411 0.62281474 0.62069339 0.61859140 0.61651000 0.61445033 0.61241348 0.61040048 0.60841227 0.60644979 0.60451392 0.60260549 0.60072531 0.59887415 0.59705272 0.59526173 0.59350185 0.59177381 0.59007827 0.58841588 0.58678727 0.58519300 0.58363362 0.58210961 0.58062144 0.57916952 0.57775420 0.57637582 0.57503465 0.57373104 0.57246531 0.57123778 0.57004869 0.56889828 0.56778669 0.56671406 0.56568045 0.56468589 0.56373046 0.56281428 0.56193746 0.56110005 0.56030207 0.55954350 0.55882425 0.55814423 0.55750340 0.55690179 0.55633941 0.55581622 0.55533217 0.55488714 0.55448100 0.55411365 0.55378512 0.55349541 0.55324450 0.55303234 0.55285883 0.55272386 0.55262738 0.55256947 0.55255016 48 | 0.67206844 0.67196068 0.67163917 0.67110918 0.67037906 0.66945990 0.66836479 0.66710830 0.66570581 0.66417285 0.66252484 0.66077652 0.65894170 0.65703317 0.65506262 0.65304056 0.65097635 0.64887822 0.64675342 0.64460833 0.64244857 0.64027906 0.63810410 0.63592746 0.63375246 0.63158202 0.62941875 0.62726497 0.62512278 0.62299409 0.62088064 0.61878402 0.61670572 0.61464712 0.61260952 0.61059415 0.60860216 0.60663464 0.60469264 0.60277715 0.60088910 0.59902939 0.59719887 0.59539832 0.59362853 0.59189024 0.59018424 0.58851124 0.58687193 0.58526695 0.58369690 0.58216232 0.58066372 0.57920155 0.57777622 0.57638809 0.57503746 0.57372463 0.57244998 0.57121382 0.57001643 0.56885805 0.56773884 0.56665895 0.56561846 0.56461740 0.56365579 0.56273376 0.56185142 0.56100882 0.56020598 0.55944288 0.55871943 0.55803553 0.55739109 0.55678614 0.55622069 0.55569470 0.55520810 0.55476078 0.55435259 0.55398341 0.55365326 0.55336213 0.55311001 0.55289683 0.55272250 0.55258691 0.55248998 0.55243180 0.55241240 49 | 0.67074512 0.67064559 0.67034842 0.66985791 0.66918093 0.66832661 0.66730585 0.66613088 0.66481478 0.66337094 0.66181279 0.66015339 0.65840518 0.65657980 0.65468811 0.65274004 0.65074455 0.64870970 0.64664266 0.64454984 0.64243698 0.64030919 0.63817102 0.63602652 0.63387929 0.63173255 0.62958921 0.62745190 0.62532298 0.62320463 0.62109887 0.61900752 0.61693232 0.61487486 0.61283665 0.61081910 0.60882356 0.60685127 0.60490344 0.60298121 0.60108563 0.59921774 0.59737849 0.59556879 0.59378949 0.59204140 0.59032538 0.58864222 0.58699267 0.58537743 0.58379717 0.58225248 0.58074392 0.57927197 0.57783710 0.57643968 0.57508006 0.57375852 0.57247543 0.57123112 0.57002591 0.56886003 0.56773367 0.56664699 0.56560006 0.56459294 0.56362561 0.56269818 0.56181075 0.56096338 0.56015608 0.55938884 0.55866156 0.55797415 0.55732646 0.55671852 0.55615031 0.55562182 0.55513295 0.55468359 0.55427360 0.55390282 0.55357124 0.55327888 0.55302570 0.55281164 0.55263660 0.55250046 0.55240315 0.55234473 0.55232525 50 | 0.66963109 0.66953847 0.66926179 0.66880459 0.66817258 0.66737336 0.66641611 0.66531118 0.66406978 0.66270351 0.66122411 0.65964319 0.65797197 0.65622106 0.65440048 0.65251956 0.65058688 0.64861023 0.64659667 0.64455257 0.64248368 0.64039526 0.63829203 0.63617824 0.63405773 0.63193398 0.62981014 0.62768908 0.62557343 0.62346562 0.62136788 0.61928228 0.61721075 0.61515510 0.61311703 0.61109813 0.60909990 0.60712378 0.60517109 0.60324311 0.60134105 0.59946604 0.59761915 0.59580138 0.59401370 0.59225697 0.59053209 0.58883993 0.58718132 0.58555701 0.58396772 0.58241410 0.58089675 0.57941620 0.57797295 0.57656740 0.57519993 0.57387084 0.57258046 0.57132915 0.57011723 0.56894495 0.56781253 0.56672011 0.56566779 0.56465561 0.56368357 0.56275171 0.56186014 0.56100891 0.56019805 0.55942752 0.55869724 0.55800709 0.55735691 0.55674668 0.55617640 0.55564603 0.55515549 0.55470465 0.55429335 0.55392142 0.55358884 0.55329560 0.55304169 0.55282702 0.55265150 0.55251499 0.55241741 0.55235883 0.55233930 51 | 0.66870222 0.66861544 0.66835608 0.66792711 0.66733330 0.66658106 0.66567821 0.66463355 0.66345678 0.66215801 0.66074754 0.65923574 0.65763273 0.65594821 0.65419140 0.65237106 0.65049535 0.64857178 0.64660724 0.64460801 0.64257985 0.64052804 0.63845744 0.63637245 0.63427710 0.63217508 0.63006973 0.62796416 0.62586121 0.62376353 0.62167355 0.61959356 0.61752567 0.61547190 0.61343411 0.61141406 0.60941342 0.60743376 0.60547657 0.60354325 0.60163512 0.59975344 0.59789938 0.59607405 0.59427849 0.59251366 0.59078050 0.58907993 0.58741283 0.58578005 0.58418233 0.58262038 0.58109485 0.57960631 0.57815529 0.57674223 0.57536753 0.57403150 0.57273447 0.57147678 0.57025877 0.56908072 0.56794284 0.56684528 0.56578816 0.56477151 0.56379533 0.56285961 0.56196446 0.56110992 0.56029601 0.55952270 0.55878989 0.55809747 0.55744525 0.55683317 0.55626123 0.55572937 0.55523751 0.55478551 0.55437321 0.55400042 0.55366709 0.55337321 0.55311875 0.55290364 0.55272777 0.55259100 0.55249324 0.55243455 0.55241498 52 | 0.66794091 0.66785909 0.66761443 0.66720947 0.66664825 0.66593622 0.66508006 0.66408739 0.66296659 0.66172658 0.66037643 0.65892543 0.65738274 0.65575723 0.65405743 0.65229151 0.65046722 0.64859178 0.64667187 0.64471369 0.64272293 0.64070487 0.63866444 0.63660616 0.63453420 0.63245240 0.63036432 0.62827321 0.62618214 0.62409391 0.62201117 0.61993638 0.61787186 0.61581975 0.61378212 0.61176087 0.60975783 0.60777470 0.60581312 0.60387459 0.60196058 0.60007243 0.59821144 0.59637880 0.59457564 0.59280301 0.59106189 0.58935325 0.58767804 0.58603715 0.58443139 0.58286151 0.58132820 0.57983207 0.57837369 0.57695353 0.57557201 0.57422948 0.57292623 0.57166262 0.57043897 0.56925558 0.56811267 0.56701042 0.56594892 0.56492823 0.56394833 0.56300918 0.56211085 0.56125340 0.56043684 0.55966113 0.55892617 0.55823183 0.55757792 0.55696432 0.55639103 0.55585798 0.55536507 0.55491218 0.55449912 0.55412569 0.55379181 0.55349746 0.55324261 0.55302719 0.55285108 0.55271413 0.55261625 0.55255748 0.55253789 53 | 0.66733252 0.66725492 0.66702281 0.66663835 0.66610500 0.66542744 0.66461147 0.66366368 0.66259142 0.66140256 0.66010518 0.65870760 0.65721814 0.65564497 0.65399595 0.65227873 0.65050065 0.64866862 0.64678913 0.64486823 0.64291156 0.64092436 0.63891157 0.63687781 0.63482734 0.63276415 0.63069193 0.62861411 0.62653390 0.62445429 0.62237810 0.62030794 0.61824629 0.61619549 0.61415771 0.61213505 0.61012944 0.60814273 0.60617669 0.60423294 0.60231306 0.60041850 0.59855065 0.59671080 0.59490017 0.59311989 0.59137100 0.58965450 0.58797140 0.58632264 0.58470908 0.58313153 0.58159071 0.58008727 0.57862182 0.57719485 0.57580682 0.57445808 0.57314896 0.57187974 0.57065079 0.56946241 0.56831482 0.56720820 0.56614267 0.56511826 0.56413497 0.56319273 0.56229157 0.56143154 0.56061265 0.55983485 0.55909805 0.55840208 0.55774676 0.55713192 0.55655753 0.55602354 0.55552983 0.55507626 0.55466264 0.55428875 0.55395448 0.55365982 0.55340472 0.55318910 0.55301284 0.55287578 0.55277782 0.55271902 0.55269941 54 | 0.66687038 0.66679640 0.66657503 0.66620815 0.66569875 0.66505089 0.66426961 0.66336071 0.66233065 0.66118643 0.65993531 0.65858473 0.65714233 0.65561560 0.65401187 0.65233825 0.65060170 0.64880885 0.64696596 0.64507895 0.64315337 0.64119442 0.63920701 0.63719580 0.63516516 0.63311916 0.63106162 0.62899610 0.62692597 0.62485435 0.62278420 0.62071832 0.61865931 0.61660965 0.61457168 0.61254760 0.61053951 0.60854937 0.60657906 0.60463034 0.60270487 0.60080422 0.59892987 0.59708320 0.59526551 0.59347800 0.59172179 0.58999793 0.58830745 0.58665134 0.58503052 0.58344584 0.58189807 0.58038789 0.57891593 0.57748273 0.57608876 0.57473441 0.57341999 0.57214578 0.57091213 0.56971935 0.56856767 0.56745727 0.56638828 0.56536073 0.56437461 0.56342984 0.56252640 0.56166433 0.56084363 0.56006425 0.55932607 0.55862895 0.55797267 0.55735702 0.55678196 0.55624740 0.55575325 0.55529934 0.55488547 0.55451141 0.55417702 0.55388227 0.55362711 0.55341146 0.55323519 0.55309814 0.55300018 0.55294138 0.55292177 55 | 0.66655545 0.66648459 0.66627249 0.66592080 0.66543214 0.66481003 0.66405894 0.66318398 0.66219086 0.66108588 0.65987556 0.65856665 0.65716613 0.65568092 0.65411787 0.65248362 0.65078474 0.64902758 0.64721821 0.64536239 0.64346556 0.64153288 0.63956922 0.63757925 0.63556739 0.63353779 0.63149438 0.62944083 0.62738062 0.62531702 0.62325311 0.62119182 0.61913589 0.61708794 0.61505042 0.61302568 0.61101593 0.60902325 0.60704963 0.60509694 0.60316695 0.60126131 0.59938159 0.59752926 0.59570571 0.59391220 0.59214992 0.59041998 0.58872341 0.58706127 0.58543452 0.58384404 0.58229064 0.58077505 0.57929792 0.57785981 0.57646122 0.57510256 0.57378415 0.57250627 0.57126921 0.57007330 0.56891879 0.56780586 0.56673462 0.56570511 0.56471732 0.56377116 0.56286655 0.56200351 0.56118204 0.56040207 0.55966350 0.55896614 0.55830977 0.55769416 0.55711921 0.55658485 0.55609095 0.55563734 0.55522382 0.55485013 0.55451610 0.55422169 0.55396686 0.55375150 0.55357548 0.55343864 0.55334084 0.55328212 0.55326254 56 | 0.66636804 0.66629987 0.66609578 0.66575721 0.66528648 0.66468669 0.66396181 0.66311639 0.66215554 0.66108491 0.65991046 0.65863830 0.65727484 0.65582652 0.65429972 0.65270070 0.65103566 0.64931068 0.64753162 0.64570410 0.64383345 0.64192476 0.63998287 0.63801242 0.63601787 0.63400344 0.63197313 0.62993071 0.62787975 0.62582365 0.62376561 0.62170866 0.61965568 0.61760940 0.61557240 0.61354714 0.61153594 0.60954101 0.60756442 0.60560815 0.60367406 0.60176391 0.59987934 0.59802192 0.59619307 0.59439417 0.59262646 0.59089109 0.58918914 0.58752167 0.58588970 0.58429416 0.58273589 0.58121564 0.57973410 0.57829185 0.57688941 0.57552721 0.57420558 0.57292479 0.57168512 0.57048687 0.56933030 0.56821558 0.56714284 0.56611212 0.56512338 0.56417654 0.56327146 0.56240815 0.56158657 0.56080667 0.56006831 0.55937131 0.55871544 0.55810041 0.55752609 0.55699241 0.55649922 0.55604634 0.55563355 0.55526060 0.55492726 0.55463349 0.55437922 0.55416437 0.55398878 0.55385228 0.55375473 0.55369617 0.55367664 57 | 0.66629576 0.66622991 0.66603273 0.66570550 0.66525028 0.66466983 0.66396769 0.66314797 0.66221525 0.66117466 0.66003165 0.65879181 0.65746104 0.65604534 0.65455071 0.65298306 0.65134823 0.64965205 0.64790020 0.64609813 0.64425109 0.64236408 0.64044191 0.63848917 0.63651035 0.63450970 0.63249129 0.63045897 0.62841641 0.62636709 0.62431433 0.62226126 0.62021087 0.61816600 0.61612935 0.61410348 0.61209081 0.61009366 0.60811420 0.60615451 0.60421653 0.60230211 0.60041298 0.59855077 0.59671700 0.59491308 0.59314033 0.59139997 0.58969310 0.58802080 0.58638413 0.58478405 0.58322143 0.58169708 0.58021168 0.57876586 0.57736015 0.57599498 0.57467072 0.57338763 0.57214594 0.57094595 0.56978792 0.56867203 0.56759838 0.56656702 0.56557791 0.56463095 0.56372598 0.56286294 0.56204181 0.56126249 0.56052486 0.55982870 0.55917378 0.55855979 0.55798654 0.55745394 0.55696184 0.55651004 0.55609832 0.55572639 0.55539401 0.55510112 0.55484764 0.55463347 0.55445845 0.55432242 0.55422521 0.55416684 0.55414738 58 | 0.66632844 0.66626460 0.66607338 0.66575593 0.66531412 0.66475041 0.66406799 0.66327060 0.66236237 0.66134798 0.66023245 0.65902095 0.65771891 0.65633195 0.65486573 0.65332584 0.65171783 0.65004728 0.64831966 0.64654031 0.64471435 0.64284674 0.64094222 0.63900536 0.63704062 0.63505229 0.63304450 0.63102117 0.62898603 0.62694266 0.62489446 0.62284467 0.62079638 0.61875252 0.61671590 0.61468917 0.61267488 0.61067540 0.60869303 0.60672992 0.60478811 0.60286953 0.60097598 0.59910916 0.59727067 0.59546198 0.59368446 0.59193940 0.59022794 0.58855117 0.58691018 0.58530595 0.58373941 0.58221137 0.58072257 0.57927362 0.57786510 0.57649744 0.57517101 0.57388610 0.57264291 0.57144169 0.57028271 0.56916614 0.56809210 0.56706060 0.56607162 0.56512503 0.56422066 0.56335838 0.56253815 0.56175988 0.56102341 0.56032854 0.55967498 0.55906242 0.55849062 0.55795947 0.55746879 0.55701840 0.55660803 0.55623740 0.55590622 0.55561442 0.55536191 0.55514859 0.55497428 0.55483881 0.55474201 0.55468389 0.55466451 59 | 0.66646530 0.66640319 0.66621713 0.66590817 0.66547799 0.66492881 0.66426354 0.66348560 0.66259875 0.66160729 0.66051585 0.65932926 0.65805253 0.65669095 0.65524988 0.65373463 0.65215050 0.65050281 0.64879687 0.64703787 0.64523084 0.64338067 0.64149206 0.63956954 0.63761754 0.63564038 0.63364221 0.63162701 0.62959860 0.62756062 0.62551655 0.62346972 0.62142331 0.61938035 0.61734374 0.61531621 0.61330041 0.61129881 0.60931379 0.60734758 0.60540230 0.60347996 0.60158244 0.59971151 0.59786882 0.59605592 0.59427423 0.59252508 0.59080967 0.58912912 0.58748450 0.58587685 0.58430712 0.58277614 0.58128468 0.57983337 0.57842280 0.57705342 0.57572561 0.57443966 0.57319575 0.57199410 0.57083495 0.56971849 0.56864481 0.56761394 0.56662583 0.56568035 0.56477730 0.56391649 0.56309786 0.56232131 0.56158665 0.56089367 0.56024208 0.55963152 0.55906172 0.55853252 0.55804375 0.55759520 0.55718660 0.55681764 0.55648802 0.55619761 0.55594634 0.55573408 0.55556067 0.55542591 0.55532962 0.55527180 0.55525253 60 | 0.66671473 0.66665414 0.66647260 0.66617107 0.66575109 0.66521468 0.66456450 0.66380369 0.66293574 0.66196458 0.66089454 0.65973013 0.65847603 0.65713721 0.65571876 0.65422578 0.65266330 0.65103644 0.64935033 0.64761004 0.64582052 0.64398655 0.64211282 0.64020383 0.63826395 0.63629752 0.63430871 0.63230156 0.63027994 0.62824755 0.62620795 0.62416454 0.62212060 0.62007922 0.61804339 0.61601594 0.61399959 0.61199690 0.61001032 0.60804217 0.60609465 0.60416983 0.60226966 0.60039597 0.59855049 0.59673480 0.59495040 0.59319865 0.59148080 0.58979799 0.58815130 0.58654179 0.58497044 0.58343810 0.58194556 0.58049348 0.57908243 0.57771290 0.57638526 0.57509981 0.57385672 0.57265616 0.57149836 0.57038348 0.56931163 0.56828281 0.56729696 0.56635394 0.56545353 0.56459549 0.56377972 0.56300608 0.56227440 0.56158443 0.56093585 0.56032831 0.55976146 0.55923512 0.55874910 0.55830317 0.55789706 0.55753042 0.55720293 0.55691445 0.55666487 0.55645407 0.55628187 0.55614807 0.55605246 0.55599506 0.55597592 61 | 0.66705555 0.66699628 0.66681868 0.66652361 0.66611252 0.66558726 0.66495026 0.66420445 0.66335305 0.66239972 0.66134850 0.66020364 0.65896954 0.65765089 0.65625254 0.65477936 0.65323622 0.65162800 0.64995969 0.64823624 0.64646250 0.64464321 0.64278297 0.64088629 0.63895751 0.63700092 0.63502075 0.63302106 0.63100577 0.62897864 0.62694330 0.62490322 0.62286173 0.62082204 0.61878718 0.61676008 0.61474352 0.61274015 0.61075249 0.60878294 0.60683376 0.60490709 0.60300496 0.60112924 0.59928172 0.59746405 0.59567776 0.59392426 0.59220485 0.59052069 0.58887288 0.58726248 0.58569048 0.58415777 0.58266514 0.58121328 0.57980277 0.57843410 0.57710764 0.57582370 0.57458244 0.57338399 0.57222854 0.57111625 0.57004720 0.56902140 0.56803877 0.56709914 0.56620229 0.56534792 0.56453587 0.56376600 0.56303811 0.56235192 0.56170711 0.56110330 0.56054007 0.56001723 0.55953456 0.55909182 0.55868870 0.55832486 0.55799993 0.55771374 0.55746618 0.55725712 0.55708637 0.55695370 0.55685891 0.55680200 0.55678303 62 | 0.66747553 0.66741740 0.66724322 0.66695377 0.66655039 0.66603482 0.66540928 0.66467653 0.66383958 0.66290182 0.66186706 0.66073934 0.65952281 0.65822190 0.65684124 0.65538554 0.65385950 0.65226782 0.65061531 0.64890683 0.64714714 0.64534093 0.64349275 0.64160707 0.63968824 0.63774050 0.63576809 0.63377512 0.63176553 0.62974316 0.62771167 0.62567462 0.62363540 0.62159727 0.61956335 0.61753664 0.61552000 0.61351614 0.61152765 0.60955701 0.60760653 0.60567843 0.60377479 0.60189754 0.60004853 0.59822945 0.59644188 0.59468727 0.59296696 0.59128215 0.58963395 0.58802340 0.58645152 0.58491923 0.58342732 0.58197649 0.58056734 0.57920035 0.57787591 0.57659430 0.57535571 0.57416022 0.57300797 0.57189911 0.57083370 0.56981174 0.56883313 0.56789769 0.56700517 0.56615524 0.56534767 0.56458230 0.56385889 0.56317717 0.56253678 0.56193731 0.56137831 0.56085953 0.56038074 0.55994166 0.55954199 0.55918136 0.55885937 0.55857581 0.55833056 0.55812348 0.55795437 0.55782300 0.55772915 0.55767280 0.55765401 63 | 0.66796459 0.66790745 0.66773622 0.66745162 0.66705492 0.66654773 0.66593212 0.66521068 0.66438627 0.66346203 0.66244160 0.66132880 0.66012759 0.65884216 0.65747698 0.65603659 0.65452552 0.65294835 0.65130973 0.64961440 0.64786707 0.64607236 0.64423479 0.64235879 0.64044871 0.63850877 0.63654318 0.63455610 0.63255151 0.63053328 0.62850515 0.62647071 0.62443343 0.62239663 0.62036351 0.61833711 0.61632037 0.61431608 0.61232689 0.61035532 0.60840379 0.60647453 0.60456970 0.60269130 0.60084121 0.59902116 0.59723279 0.59547759 0.59375693 0.59207204 0.59042405 0.58881400 0.58724290 0.58571170 0.58422120 0.58277211 0.58136502 0.58000045 0.57867875 0.57740023 0.57616505 0.57497328 0.57382499 0.57272032 0.57165931 0.57064194 0.56966809 0.56873757 0.56785010 0.56700531 0.56620291 0.56544271 0.56472445 0.56404782 0.56341245 0.56281790 0.56226368 0.56174948 0.56127506 0.56084011 0.56044431 0.56008727 0.55976857 0.55948795 0.55924529 0.55904043 0.55887315 0.55874323 0.55865041 0.55859468 0.55857610 64 | 0.66852393 0.66846766 0.66829898 0.66801860 0.66762770 0.66712779 0.66652082 0.66580924 0.66499575 0.66408334 0.66307543 0.66197569 0.66078792 0.65951611 0.65816455 0.65673763 0.65523980 0.65367548 0.65204918 0.65036555 0.64862922 0.64684477 0.64501669 0.64314939 0.64124719 0.63931430 0.63735493 0.63537324 0.63337325 0.63135889 0.62933393 0.62730202 0.62526669 0.62323132 0.62119916 0.61917334 0.61715684 0.61515251 0.61316307 0.61119111 0.60923908 0.60730931 0.60540397 0.60352513 0.60167471 0.59985451 0.59806618 0.59631126 0.59459114 0.59290709 0.59126027 0.58965170 0.58808239 0.58655330 0.58506524 0.58361893 0.58221498 0.58085387 0.57953598 0.57826160 0.57703089 0.57584391 0.57470065 0.57360122 0.57254565 0.57153390 0.57056583 0.56964122 0.56875976 0.56792108 0.56712479 0.56637065 0.56565841 0.56498771 0.56435817 0.56376930 0.56322060 0.56271167 0.56224226 0.56181205 0.56142067 0.56106773 0.56075277 0.56047550 0.56023578 0.56003344 0.55986825 0.55973996 0.55964832 0.55959330 0.55957496 65 | 0.66916589 0.66911037 0.66894397 0.66866732 0.66828157 0.66778815 0.66718888 0.66648609 0.66568237 0.66478055 0.66378389 0.66269592 0.66152030 0.66026085 0.65892169 0.65750712 0.65602144 0.65446900 0.65285417 0.65118150 0.64945557 0.64768090 0.64586196 0.64400313 0.64210872 0.64018295 0.63822999 0.63625400 0.63425906 0.63224912 0.63022800 0.62819941 0.62616691 0.62413394 0.62210382 0.62007972 0.61806469 0.61606164 0.61407333 0.61210242 0.61015142 0.60822268 0.60631845 0.60444084 0.60259180 0.60077317 0.59898666 0.59723381 0.59551606 0.59383471 0.59219092 0.59058573 0.58902012 0.58749506 0.58601136 0.58456975 0.58317083 0.58181510 0.58050292 0.57923456 0.57801018 0.57682982 0.57569344 0.57460105 0.57355270 0.57254830 0.57158770 0.57067066 0.56979684 0.56896582 0.56817717 0.56743058 0.56672576 0.56606236 0.56543993 0.56485798 0.56431596 0.56381341 0.56335003 0.56292550 0.56253943 0.56219138 0.56188089 0.56160761 0.56137139 0.56117203 0.56100932 0.56088297 0.56079273 0.56073855 0.56072048 66 | 0.66986431 0.66980946 0.66964505 0.66937167 0.66899043 0.66850269 0.66791017 0.66721511 0.66641999 0.66552750 0.66454076 0.66346319 0.66229833 0.66104986 0.65972175 0.65831818 0.65684339 0.65530162 0.65369714 0.65203440 0.65031792 0.64855219 0.64674164 0.64489065 0.64300352 0.64108445 0.63913761 0.63716715 0.63517717 0.63317167 0.63115451 0.62912943 0.62710006 0.62506989 0.62304227 0.62102044 0.61900749 0.61700639 0.61501998 0.61305093 0.61110181 0.60917504 0.60727289 0.60539752 0.60355092 0.60173498 0.59995141 0.59820181 0.59648764 0.59481021 0.59317071 0.59157018 0.59000958 0.58848986 0.58701186 0.58557629 0.58418376 0.58283475 0.58152963 0.58026865 0.57905194 0.57787954 0.57675136 0.57566735 0.57462752 0.57363177 0.57267991 0.57177167 0.57090669 0.57008452 0.56930465 0.56856673 0.56787042 0.56721534 0.56660101 0.56602692 0.56549247 0.56499714 0.56454060 0.56412249 0.56374239 0.56339986 0.56309440 0.56282561 0.56259332 0.56239733 0.56223739 0.56211322 0.56202455 0.56197130 0.56195355 67 | 0.67060394 0.67054967 0.67038699 0.67011645 0.66973913 0.66925633 0.66866969 0.66798135 0.66719371 0.66630938 0.66533132 0.66426285 0.66310742 0.66186859 0.66055020 0.65915635 0.65769116 0.65615884 0.65456357 0.65290968 0.65120166 0.64944396 0.64764098 0.64579710 0.64391659 0.64200369 0.64006253 0.63809727 0.63611202 0.63411080 0.63209754 0.63007600 0.62804986 0.62602266 0.62399781 0.62197858 0.61996813 0.61796947 0.61598548 0.61401890 0.61207232 0.61014822 0.60824892 0.60637659 0.60453329 0.60272092 0.60094123 0.59919585 0.59748625 0.59581377 0.59417961 0.59258483 0.59103036 0.58951713 0.58804597 0.58661761 0.58523265 0.58389155 0.58259467 0.58134224 0.58013440 0.57897114 0.57785235 0.57677791 0.57574777 0.57476181 0.57381983 0.57292151 0.57206646 0.57125421 0.57048418 0.56975593 0.56906912 0.56842330 0.56781799 0.56725262 0.56672656 0.56623923 0.56579025 0.56537924 0.56500575 0.56466931 0.56436938 0.56410554 0.56387759 0.56368530 0.56352842 0.56340665 0.56331969 0.56326749 0.56325008 68 | 0.67137172 0.67131795 0.67115675 0.67088866 0.67051472 0.67003618 0.66945461 0.66877208 0.66799091 0.66711363 0.66614308 0.66508250 0.66393525 0.66270481 0.66139489 0.66000950 0.65855271 0.65702865 0.65544146 0.65379537 0.65209481 0.65034421 0.64854796 0.64671041 0.64483586 0.64292852 0.64099255 0.63903207 0.63705122 0.63505406 0.63304454 0.63102647 0.62900357 0.62697943 0.62495750 0.62294110 0.62093344 0.61893758 0.61695644 0.61499280 0.61304931 0.61112847 0.60923266 0.60736408 0.60552482 0.60371680 0.60194182 0.60020151 0.59849738 0.59683078 0.59520292 0.59361487 0.59206755 0.59056185 0.58909861 0.58767854 0.58630223 0.58497014 0.58368261 0.58243986 0.58124200 0.58008899 0.57898071 0.57791696 0.57689763 0.57592257 0.57499155 0.57410422 0.57326015 0.57245883 0.57169964 0.57098206 0.57030568 0.56967004 0.56907461 0.56851879 0.56800193 0.56752335 0.56708264 0.56667938 0.56631310 0.56598330 0.56568942 0.56543098 0.56520775 0.56501949 0.56486594 0.56474679 0.56466171 0.56461063 0.56459360 69 | 0.67216775 0.67211441 0.67195451 0.67168856 0.67131756 0.67084274 0.67026560 0.66958814 0.66881264 0.66794154 0.66697759 0.66592395 0.66478392 0.66356090 0.66225849 0.66088062 0.65943132 0.65791467 0.65633475 0.65469573 0.65300196 0.65125787 0.64946783 0.64763619 0.64576725 0.64386522 0.64193428 0.63997852 0.63800210 0.63600911 0.63400352 0.63198920 0.62996990 0.62794926 0.62593076 0.62391779 0.62191359 0.61992125 0.61794375 0.61598392 0.61404443 0.61212784 0.61023653 0.60837277 0.60653867 0.60473617 0.60296710 0.60123311 0.59953573 0.59787631 0.59625609 0.59467612 0.59313734 0.59164059 0.59018670 0.58877636 0.58741015 0.58608853 0.58481181 0.58358020 0.58239376 0.58125247 0.58015614 0.57910451 0.57809741 0.57713466 0.57621597 0.57534098 0.57450921 0.57372011 0.57297302 0.57226732 0.57160256 0.57097823 0.57039377 0.56984855 0.56934185 0.56887296 0.56844139 0.56804669 0.56768838 0.56736591 0.56707869 0.56682620 0.56660817 0.56642435 0.56627447 0.56615819 0.56607517 0.56602533 0.56600871 70 | 0.67300527 0.67295234 0.67279362 0.67252962 0.67216132 0.67168991 0.67111684 0.67044406 0.66967379 0.66880843 0.66785063 0.66680347 0.66567021 0.66445421 0.66315895 0.66178830 0.66034624 0.65883680 0.65726405 0.65563209 0.65394520 0.65220779 0.65042423 0.64859888 0.64673601 0.64483988 0.64291464 0.64096442 0.63899333 0.63700550 0.63500495 0.63299558 0.63098117 0.62896540 0.62695181 0.62494381 0.62294468 0.62095757 0.61898549 0.61703129 0.61509770 0.61318730 0.61130252 0.60944564 0.60761880 0.60582397 0.60406299 0.60233753 0.60064914 0.59899918 0.59738888 0.59581931 0.59429139 0.59280594 0.59136374 0.58996547 0.58861171 0.58730289 0.58603930 0.58482113 0.58364841 0.58252107 0.58143892 0.58040163 0.57940894 0.57846062 0.57755635 0.57669573 0.57587825 0.57510329 0.57437016 0.57367816 0.57302675 0.57241540 0.57184350 0.57131038 0.57081528 0.57035743 0.56993626 0.56955130 0.56920202 0.56888786 0.56860818 0.56836243 0.56815029 0.56797150 0.56782576 0.56771272 0.56763204 0.56758360 0.56756745 71 | 0.67385093 0.67379835 0.67364069 0.67337843 0.67301253 0.67254417 0.67197475 0.67130616 0.67054059 0.66968040 0.66872815 0.66768687 0.66655978 0.66535017 0.66406149 0.66269749 0.66126214 0.65975944 0.65819343 0.65656817 0.65488788 0.65315693 0.65137972 0.64956059 0.64770382 0.64581368 0.64389435 0.64194994 0.63998457 0.63800238 0.63600741 0.63400361 0.63199481 0.62998471 0.62797688 0.62597480 0.62398176 0.62200096 0.62003544 0.61808809 0.61616168 0.61425881 0.61238194 0.61053337 0.60871527 0.60692964 0.60517832 0.60346301 0.60178525 0.60014641 0.59854774 0.59699029 0.59547499 0.59400261 0.59257389 0.59118950 0.58985000 0.58855578 0.58730714 0.58610420 0.58494699 0.58383540 0.58276918 0.58174799 0.58077144 0.57983926 0.57895110 0.57810650 0.57730490 0.57654565 0.57582800 0.57515117 0.57451455 0.57391755 0.57335952 0.57283974 0.57235743 0.57191174 0.57150202 0.57112777 0.57078843 0.57048340 0.57021201 0.56997365 0.56976797 0.56959469 0.56945350 0.56934402 0.56926589 0.56921899 0.56920335 72 | 0.67468418 0.67463191 0.67447519 0.67421446 0.67385069 0.67338503 0.67281884 0.67215397 0.67139258 0.67053699 0.66958971 0.66855370 0.66743214 0.66622831 0.66494559 0.66358766 0.66215846 0.66066197 0.65910222 0.65748323 0.65580916 0.65408438 0.65231327 0.65050018 0.64864942 0.64676525 0.64485187 0.64291342 0.64095399 0.63897774 0.63698874 0.63499098 0.63298831 0.63098449 0.62898312 0.62698770 0.62500159 0.62302799 0.62106999 0.61913052 0.61721237 0.61531817 0.61345040 0.61161141 0.60980335 0.60802826 0.60628800 0.60458426 0.60291860 0.60129239 0.59970687 0.59816311 0.59666200 0.59520431 0.59379072 0.59242187 0.59109828 0.58982035 0.58858831 0.58740229 0.58626226 0.58516807 0.58411945 0.58311598 0.58215722 0.58124280 0.58037232 0.57954529 0.57876109 0.57801903 0.57731831 0.57665807 0.57603758 0.57545624 0.57491333 0.57440810 0.57393969 0.57350723 0.57310997 0.57274737 0.57241883 0.57212371 0.57186132 0.57163098 0.57143232 0.57126503 0.57112877 0.57102315 0.57094780 0.57090256 0.57088747 73 | 0.67548697 0.67543497 0.67527907 0.67501969 0.67465778 0.67419449 0.67363115 0.67296955 0.67221184 0.67136032 0.67041745 0.66938612 0.66826951 0.66707085 0.66579350 0.66444107 0.66301747 0.66152666 0.65997266 0.65835950 0.65669128 0.65497233 0.65320705 0.65139979 0.64955489 0.64767661 0.64576918 0.64383675 0.64188342 0.63991334 0.63793062 0.63593927 0.63394320 0.63194617 0.62995186 0.62796378 0.62598532 0.62401973 0.62207013 0.62013947 0.61823057 0.61634609 0.61448855 0.61266028 0.61086349 0.60910021 0.60737231 0.60568150 0.60402933 0.60241718 0.60084629 0.59931770 0.59783232 0.59639088 0.59499399 0.59364228 0.59233623 0.59107620 0.58986241 0.58869493 0.58757371 0.58649855 0.58546914 0.58448502 0.58354565 0.58265058 0.58179935 0.58099142 0.58022613 0.57950273 0.57882036 0.57817809 0.57757511 0.57701072 0.57648418 0.57599467 0.57554131 0.57512314 0.57473935 0.57438933 0.57407245 0.57378803 0.57353534 0.57331367 0.57312258 0.57296174 0.57283080 0.57272935 0.57265698 0.57261353 0.57259905 74 | 0.67625631 0.67620456 0.67604939 0.67579123 0.67543100 0.67496985 0.67440909 0.67375047 0.67299612 0.67214832 0.67120949 0.67018249 0.66907044 0.66787660 0.66660429 0.66525705 0.66383876 0.66235339 0.66080495 0.65919747 0.65753502 0.65582189 0.65406248 0.65226118 0.65042231 0.64855019 0.64664904 0.64472305 0.64277634 0.64081302 0.63883723 0.63685304 0.63486438 0.63287506 0.63088876 0.62890906 0.62693937 0.62498298 0.62304303 0.62112250 0.61922424 0.61735094 0.61550511 0.61368913 0.61190521 0.61015540 0.60844156 0.60676543 0.60512854 0.60353227 0.60197785 0.60046633 0.59899857 0.59757531 0.59619710 0.59486450 0.59357797 0.59233783 0.59114427 0.58999733 0.58889690 0.58784275 0.58683450 0.58587166 0.58495361 0.58407978 0.58324967 0.58246267 0.58171808 0.58101508 0.58035276 0.57973011 0.57914621 0.57860031 0.57809161 0.57761923 0.57718223 0.57677961 0.57641046 0.57607411 0.57576990 0.57549711 0.57525496 0.57504269 0.57485981 0.57470598 0.57458080 0.57448387 0.57441474 0.57437324 0.57435941 75 | 0.67700489 0.67695339 0.67679895 0.67654199 0.67618343 0.67572440 0.67516621 0.67451056 0.67375957 0.67291552 0.67198080 0.67095821 0.66985086 0.66866201 0.66739495 0.66605318 0.66464056 0.66316104 0.66161865 0.66001741 0.65836138 0.65665480 0.65490209 0.65310765 0.65127583 0.64941095 0.64751727 0.64559901 0.64366029 0.64170521 0.63973794 0.63776257 0.63578307 0.63380328 0.63182693 0.62985761 0.62789877 0.62595373 0.62402566 0.62211756 0.62023230 0.61837258 0.61654096 0.61473981 0.61297135 0.61123763 0.60954053 0.60788178 0.60626291 0.60468531 0.60315016 0.60165851 0.60021121 0.59880896 0.59745229 0.59614167 0.59487751 0.59366012 0.59248963 0.59136603 0.59028918 0.58925879 0.58827444 0.58733556 0.58644148 0.58559150 0.58478507 0.58402150 0.58330003 0.58261979 0.58197980 0.58137899 0.58081632 0.58029095 0.57980203 0.57934864 0.57892977 0.57854435 0.57819140 0.57787017 0.57757995 0.57731998 0.57708947 0.57688757 0.57671375 0.57656764 0.57644882 0.57635687 0.57629131 0.57625196 0.57623883 76 | 0.67769275 0.67764148 0.67748774 0.67723192 0.67687494 0.67641794 0.67586221 0.67520941 0.67446166 0.67362123 0.67269051 0.67167222 0.67056949 0.66938555 0.66812372 0.66678743 0.66538052 0.66390695 0.66237075 0.66077595 0.65912662 0.65742694 0.65568134 0.65389424 0.65207002 0.65021302 0.64832753 0.64641778 0.64448793 0.64254207 0.64058437 0.63861895 0.63664982 0.63468085 0.63271581 0.63075832 0.62881185 0.62687975 0.62496521 0.62307127 0.62120080 0.61935654 0.61754103 0.61575668 0.61400571 0.61229016 0.61061194 0.60897274 0.60737411 0.60581740 0.60430380 0.60283433 0.60140983 0.60003095 0.59869819 0.59741193 0.59617256 0.59498031 0.59383529 0.59273742 0.59168653 0.59068227 0.58972415 0.58881155 0.58794373 0.58711988 0.58633933 0.58560137 0.58490515 0.58424974 0.58363409 0.58305706 0.58251750 0.58201449 0.58154709 0.58111433 0.58071515 0.58034842 0.58001305 0.57970822 0.57943319 0.57918714 0.57896923 0.57877858 0.57861458 0.57847683 0.57836491 0.57827834 0.57821666 0.57817963 0.57816728 77 | 0.67829498 0.67824392 0.67809084 0.67783610 0.67748062 0.67702554 0.67647214 0.67582206 0.67507741 0.67424046 0.67331358 0.67229946 0.67120122 0.67002209 0.66876539 0.66743455 0.66603333 0.66456574 0.66303580 0.66144756 0.65980511 0.65811259 0.65637441 0.65459502 0.65277884 0.65093023 0.64905352 0.64715294 0.64523269 0.64329689 0.64134967 0.63939519 0.63743749 0.63548048 0.63352796 0.63158358 0.62965085 0.62773313 0.62583363 0.62395542 0.62210140 0.62027429 0.61847668 0.61671096 0.61497937 0.61328395 0.61162658 0.61000898 0.60843267 0.60689899 0.60540911 0.60396402 0.60256452 0.60121126 0.59990469 0.59864511 0.59743283 0.59626805 0.59515081 0.59408100 0.59305838 0.59208254 0.59115293 0.59026888 0.58942955 0.58863404 0.58788158 0.58717136 0.58650248 0.58587393 0.58528461 0.58473329 0.58421871 0.58373984 0.58329568 0.58288520 0.58250726 0.58216068 0.58184427 0.58155713 0.58129847 0.58106741 0.58086308 0.58068454 0.58053112 0.58040239 0.58029788 0.58021712 0.58015960 0.58012507 0.58011356 78 | 0.67879022 0.67873938 0.67858691 0.67833318 0.67797912 0.67752587 0.67697468 0.67632719 0.67558550 0.67475187 0.67382869 0.67281861 0.67172472 0.67055029 0.66929864 0.66797318 0.66657764 0.66511603 0.66359240 0.66201082 0.66037539 0.65869024 0.65695976 0.65518843 0.65338069 0.65154094 0.64967353 0.64778274 0.64587278 0.64394780 0.64201191 0.64006930 0.63812403 0.63618007 0.63424123 0.63231120 0.63039350 0.62849154 0.62660855 0.62474760 0.62291161 0.62110333 0.61932534 0.61758005 0.61586968 0.61419629 0.61256175 0.61096776 0.60941583 0.60790728 0.60644326 0.60502473 0.60365248 0.60232708 0.60104896 0.59981836 0.59863550 0.59750051 0.59641339 0.59537398 0.59438196 0.59343687 0.59253809 0.59168486 0.59087630 0.59011138 0.58938921 0.58870891 0.58806950 0.58746990 0.58690892 0.58638526 0.58589757 0.58544468 0.58502552 0.58463899 0.58428388 0.58395895 0.58366291 0.58339478 0.58315370 0.58293875 0.58274900 0.58258346 0.58244140 0.58232234 0.58222580 0.58215126 0.58209821 0.58206637 0.58205575 79 | 0.67917461 0.67912396 0.67897210 0.67871938 0.67836672 0.67791526 0.67736628 0.67672136 0.67598261 0.67515231 0.67423285 0.67322684 0.67213738 0.67096774 0.66972126 0.66840135 0.66701170 0.66555633 0.66403932 0.66246477 0.66083679 0.65915951 0.65743729 0.65567464 0.65387605 0.65204594 0.65018869 0.64830862 0.64640997 0.64449691 0.64257355 0.64064407 0.63871260 0.63678312 0.63485947 0.63294537 0.63104439 0.62915993 0.62729526 0.62545347 0.62363748 0.62185007 0.62009380 0.61837110 0.61668419 0.61503512 0.61342576 0.61185778 0.61033267 0.60885174 0.60741611 0.60602671 0.60468427 0.60338936 0.60214233 0.60094339 0.59979262 0.59869013 0.59763582 0.59662949 0.59567075 0.59475906 0.59389375 0.59307397 0.59229876 0.59156700 0.59087764 0.59022973 0.58962221 0.58905391 0.58852356 0.58802979 0.58757114 0.58714629 0.58675412 0.58639343 0.58606295 0.58576136 0.58548729 0.58523964 0.58501750 0.58481990 0.58464586 0.58449432 0.58436449 0.58425584 0.58416788 0.58410005 0.58405181 0.58402286 0.58401320 80 | 0.67946408 0.67941366 0.67926246 0.67901082 0.67865968 0.67821018 0.67766360 0.67702150 0.67628598 0.67545935 0.67454400 0.67354251 0.67245798 0.67129369 0.67005300 0.66873934 0.66735635 0.66590808 0.66439861 0.66283208 0.66121263 0.65954441 0.65783173 0.65607914 0.65429114 0.65247221 0.65062677 0.64875914 0.64687363 0.64497440 0.64306559 0.64115138 0.63923591 0.63732320 0.63541713 0.63352144 0.63163972 0.62977540 0.62793177 0.62611193 0.62431881 0.62255519 0.62082366 0.61912662 0.61746629 0.61584472 0.61426375 0.61272505 0.61123008 0.60978012 0.60837626 0.60701939 0.60571021 0.60444923 0.60323676 0.60207293 0.60095775 0.59989121 0.59887318 0.59790336 0.59698131 0.59610641 0.59527789 0.59449486 0.59375624 0.59306083 0.59240744 0.59179499 0.59122235 0.59068826 0.59019137 0.58973022 0.58930324 0.58890898 0.58854621 0.58821367 0.58791000 0.58763380 0.58738363 0.58715826 0.58695671 0.58677798 0.58662099 0.58648467 0.58636812 0.58627079 0.58619213 0.58613159 0.58608857 0.58606275 0.58605415 81 | 0.67961863 0.67956844 0.67941792 0.67916742 0.67881786 0.67837039 0.67782631 0.67718715 0.67645502 0.67563223 0.67472120 0.67372449 0.67264517 0.67148656 0.67025204 0.66894507 0.66756925 0.66612861 0.66462730 0.66306948 0.66145931 0.65980096 0.65809873 0.65635717 0.65458083 0.65277423 0.65094180 0.64908793 0.64721694 0.64533304 0.64344037 0.64154309 0.63964537 0.63775128 0.63586471 0.63398944 0.63212909 0.63028710 0.62846676 0.62667121 0.62490338 0.62316605 0.62146180 0.61979305 0.61816201 0.61657069 0.61502094 0.61351439 0.61205249 0.61063647 0.60926740 0.60794611 0.60667326 0.60544931 0.60427452 0.60314896 0.60207254 0.60104513 0.60006654 0.59913641 0.59825420 0.59741921 0.59663061 0.59588739 0.59518840 0.59453234 0.59391786 0.59334377 0.59280884 0.59231173 0.59185098 0.59142503 0.59103224 0.59067099 0.59033995 0.59003775 0.58976298 0.58951416 0.58928973 0.58908837 0.58890902 0.58875059 0.58861198 0.58849203 0.58838978 0.58830463 0.58823600 0.58818329 0.58814590 0.58812346 0.58811597 82 | 0.67961551 0.67956555 0.67941573 0.67916639 0.67881845 0.67837309 0.67783158 0.67719546 0.67646684 0.67564804 0.67474149 0.67374977 0.67267591 0.67152327 0.67029524 0.66899532 0.66762710 0.66619459 0.66470197 0.66315345 0.66155322 0.65990549 0.65821453 0.65648490 0.65472118 0.65292794 0.65110966 0.64927076 0.64741558 0.64554838 0.64367333 0.64179455 0.63991626 0.63804252 0.63617729 0.63432437 0.63248738 0.63066980 0.62887494 0.62710593 0.62536573 0.62365711 0.62198265 0.62034476 0.61874564 0.61718729 0.61567153 0.61419997 0.61277403 0.61139490 0.61006359 0.60878092 0.60754748 0.60636368 0.60522971 0.60414557 0.60311109 0.60212602 0.60119008 0.60030283 0.59946365 0.59867176 0.59792622 0.59722594 0.59656967 0.59595601 0.59538346 0.59485069 0.59435637 0.59389905 0.59347719 0.59308912 0.59273309 0.59240734 0.59211040 0.59184083 0.59159712 0.59137770 0.59118094 0.59100536 0.59084984 0.59071323 0.59059435 0.59049199 0.59040509 0.59033301 0.59027514 0.59023085 0.59019948 0.59018067 0.59017440 83 | 0.67943668 0.67938696 0.67923786 0.67898971 0.67864344 0.67820022 0.67766137 0.67702838 0.67630338 0.67548870 0.67458681 0.67360028 0.67253212 0.67138570 0.67016448 0.66887197 0.66751176 0.66608784 0.66460444 0.66306579 0.66147615 0.65983974 0.65816085 0.65644401 0.65469386 0.65291500 0.65111197 0.64928921 0.64745113 0.64560199 0.64374601 0.64188730 0.64003006 0.63817843 0.63633636 0.63450769 0.63269608 0.63090501 0.62913781 0.62739762 0.62568741 0.62400994 0.62236780 0.62076338 0.61919886 0.61767624 0.61619730 0.61476363 0.61337659 0.61203737 0.61074691 0.60950598 0.60831511 0.60717465 0.60608474 0.60504530 0.60405605 0.60311664 0.60222668 0.60138564 0.60059281 0.59984732 0.59914814 0.59849406 0.59788374 0.59731567 0.59678822 0.59629987 0.59584919 0.59543463 0.59505454 0.59470714 0.59439058 0.59410295 0.59384263 0.59360808 0.59339771 0.59320984 0.59304276 0.59289486 0.59276490 0.59265168 0.59255397 0.59247047 0.59240004 0.59234199 0.59229565 0.59226038 0.59223549 0.59222056 0.59221559 84 | 0.67908277 0.67903330 0.67888496 0.67863806 0.67829355 0.67785260 0.67731654 0.67668687 0.67596570 0.67515540 0.67425845 0.67327743 0.67221534 0.67107559 0.66986166 0.66857708 0.66722548 0.66581081 0.66433735 0.66280938 0.66123118 0.65960705 0.65794126 0.65623833 0.65450294 0.65273975 0.65095333 0.64914819 0.64732874 0.64549932 0.64366415 0.64182737 0.63999315 0.63816566 0.63634891 0.63454673 0.63276283 0.63100070 0.62926368 0.62755493 0.62587741 0.62423389 0.62262695 0.62105897 0.61953210 0.61804834 0.61660942 0.61521690 0.61387211 0.61257618 0.61133002 0.61013433 0.60898958 0.60789606 0.60685382 0.60586271 0.60492238 0.60403233 0.60319205 0.60240092 0.60165813 0.60096272 0.60031354 0.59970928 0.59914849 0.59862954 0.59815068 0.59771019 0.59730651 0.59693799 0.59660286 0.59629923 0.59602513 0.59577851 0.59555758 0.59536070 0.59518617 0.59503223 0.59489705 0.59477889 0.59467641 0.59458834 0.59451336 0.59445013 0.59439740 0.59435442 0.59432048 0.59429490 0.59427696 0.59426621 0.59426262 85 | 0.67857603 0.67852684 0.67837935 0.67813385 0.67779129 0.67735288 0.67681994 0.67619397 0.67547709 0.67467168 0.67378026 0.67280542 0.67175015 0.67061786 0.66941209 0.66813642 0.66679449 0.66539023 0.66392794 0.66241196 0.66084662 0.65923626 0.65758519 0.65589789 0.65417909 0.65243348 0.65066570 0.64888029 0.64708172 0.64527434 0.64346243 0.64165013 0.63984161 0.63804104 0.63625247 0.63447977 0.63272665 0.63099664 0.62929308 0.62761914 0.62597778 0.62437177 0.62280367 0.62127585 0.61979045 0.61834941 0.61695447 0.61560712 0.61430866 0.61306017 0.61186249 0.61071627 0.60962191 0.60857962 0.60758938 0.60665095 0.60576390 0.60492758 0.60414135 0.60340449 0.60271608 0.60207505 0.60148014 0.60092993 0.60042284 0.59995712 0.59953088 0.59914223 0.59878944 0.59847074 0.59818424 0.59792794 0.59769974 0.59749744 0.59731907 0.59716288 0.59702706 0.59690975 0.59680901 0.59672296 0.59665015 0.59658922 0.59653878 0.59649740 0.59646377 0.59643704 0.59641648 0.59640135 0.59639091 0.59638466 0.59638258 86 | -------------------------------------------------------------------------------- /tests/test_optical.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | import os 3 | import sys 4 | 5 | from distutils import dir_util 6 | 7 | import numpy as np 8 | 9 | from pytest import fixture 10 | 11 | myPath = os.path.dirname(os.path.abspath(__file__)) 12 | sys.path.insert(0, myPath + '/../') 13 | 14 | from multiply_forward_operators import optical_forward_operator 15 | 16 | 17 | @fixture 18 | def datadir(tmpdir, request): 19 | ''' 20 | Fixture responsible for locating the test data directory and copying it 21 | into a temporary directory. 22 | Taken from http://www.camillescott.org/2016/07/15/travis-pytest-scipyconf/ 23 | ''' 24 | filename = request.module.__file__ 25 | test_dir = os.path.dirname(filename) 26 | data_dir = os.path.join(test_dir, 'data') 27 | dir_util.copy_tree(data_dir, str(tmpdir)) 28 | 29 | def getter(filename, as_str=True): 30 | filepath = tmpdir.join(filename) 31 | if as_str: 32 | return str(filepath) 33 | return filepath 34 | 35 | return getter 36 | 37 | 38 | def test_prosaild(datadir): 39 | n = 2.1 40 | cab = 40 41 | car = 10. 42 | cbrown = 0.1 43 | ant = 12. 44 | cw = 0.001 45 | cm = 0.001 46 | lai = 4. 47 | ala = 45. 48 | rsoil = 0.1 49 | psoil = 0.1 50 | sza = 30. 51 | hspot = 0.1 52 | r_fwd = np.zeros((85, 91)) 53 | x = n, ant, cab, car, cbrown, cw, cm, lai, ala, rsoil, psoil 54 | for i, vza in enumerate(np.arange(0, 85, 1)): 55 | for j, raa in enumerate(np.arange(0, 182, 2)): 56 | r = optical_forward_operator(x, sza, vza, raa, version="PROSAIL_D", 57 | hspot=hspot) 58 | r_fwd[i, j] = r[465] 59 | 60 | fname = datadir("prosailD.txt") 61 | r_save = np.loadtxt(fname) 62 | assert np.allclose(r_fwd, r_save) 63 | 64 | 65 | def test_prosail5(datadir): 66 | n = 2.1 67 | cab = 40 68 | car = 10. 69 | cbrown = 0.1 70 | cw = 0.001 71 | cm = 0.001 72 | lai = 4. 73 | ala = 45. 74 | rsoil = 0.1 75 | psoil = 0.1 76 | sza = 30. 77 | hspot = 0.1 78 | r_fwd = np.zeros((85, 91)) 79 | x = n, cab, car, cbrown, cw, cm, lai, ala, rsoil, psoil 80 | for i, vza in enumerate(np.arange(0, 85, 1)): 81 | for j, raa in enumerate(np.arange(0, 182, 2)): 82 | r = optical_forward_operator(x, sza, vza, raa, version="PROSAIL_5", 83 | hspot=hspot) 84 | r_fwd[i, j] = r[465] 85 | fname = datadir("prosail5.txt") 86 | r_save = np.loadtxt(fname) 87 | assert np.allclose(r_fwd, r_save) 88 | -------------------------------------------------------------------------------- /tests/test_sar.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | import os 3 | import sys 4 | 5 | import numpy as np 6 | 7 | import pytest 8 | from scipy.optimize import approx_fprime 9 | 10 | 11 | myPath = os.path.dirname(os.path.abspath(__file__)) 12 | sys.path.insert(0, myPath + '/../') 13 | 14 | from multiply_forward_operators import sar_observation_operator 15 | 16 | 17 | def test_water_cloud_bs_vv(): 18 | x = np.atleast_2d(np.array([0.5, 2.])) 19 | polarisation = "VV" 20 | sigma, dsigma = sar_observation_operator(x, polarisation) 21 | assert(np.allclose(sigma, 1.975, atol=1.e-3)) 22 | 23 | 24 | def test_water_cloud_bs_vh(): 25 | x = np.atleast_2d(np.array([0.5, 1.1])) 26 | polarisation = "VH" 27 | sigma, dsigma = sar_observation_operator(x, polarisation) 28 | assert(np.allclose(sigma, 1.087, atol=1.e-3)) 29 | 30 | 31 | def test_water_cloud_bs_hh(): 32 | x = np.array([0.5, 1.1]) 33 | polarisation = "HH" 34 | with pytest.raises(ValueError): 35 | sigma, dsigma = sar_observation_operator(x, polarisation) 36 | 37 | 38 | def test_water_cloud_gradient_vv(): 39 | x = np.atleast_2d(np.array([0.5, 2.])) 40 | polarisation = "VV" 41 | sigma, dsigma = sar_observation_operator(x, polarisation) 42 | 43 | def backscatter_gradient(t): 44 | return sar_observation_operator(t, polarisation)[0] 45 | 46 | finite_difference_gradient_approx = approx_fprime(x.squeeze(), 47 | backscatter_gradient, 48 | 1e-6) 49 | assert(np.allclose(dsigma.squeeze(), 50 | finite_difference_gradient_approx, atol=1e-2)) 51 | 52 | 53 | def test_water_cloud_gradient_vh(): 54 | x = np.atleast_2d(np.array([0.5, 2.])) 55 | polarisation = "VH" 56 | sigma, dsigma = sar_observation_operator(x, polarisation) 57 | 58 | def backscatter_gradient(t): 59 | return sar_observation_operator(t, polarisation)[0] 60 | 61 | finite_difference_gradient_approx = approx_fprime(x.squeeze(), 62 | backscatter_gradient, 63 | 1e-6) 64 | assert(np.allclose(dsigma.squeeze(), 65 | finite_difference_gradient_approx, atol=1e-2)) 66 | 67 | 68 | def test_water_cloud_bs_vv_array(): 69 | x = np.array([[0.5, 2.], [0.5, 2.], [0.5, 2.]]) 70 | polarisation = "VV" 71 | sigma, dsigma = sar_observation_operator(x, polarisation) 72 | assert(np.allclose(sigma, np.array([1.975, 1.975, 1.975]), atol=1.e-3)) 73 | 74 | 75 | def test_water_cloud_bs_vh_array(): 76 | x = np.array([[0.5, 1.1], [0.5, 1.1], [0.5, 1.1]]) 77 | polarisation = "VH" 78 | sigma, dsigma = sar_observation_operator(x, polarisation) 79 | assert(np.allclose(sigma, np.array([1.087, 1.087, 1.087]), atol=1.e-3)) 80 | --------------------------------------------------------------------------------