cabal-version: 1.12
name:           trainmodel
version:        0.1.0.0
description:    Please see the README on GitHub at <https://github.com/quickdudley/trainmodel#readme>
homepage:       https://github.com/quickdudley/trainmodel#readme
bug-reports:    https://github.com/quickdudley/trainmodel/issues
author:         Jeremy List
maintainer:     quick.dudley@gmail.com
copyright:      BSD3
license:        BSD3
license-file:   LICENSE
build-type:     Simple
extra-source-files:
    README.md
    ChangeLog.md
source-repository head
  type: git
  location: https://github.com/quickdudley/trainmodel
executable trainmodel
  main-is: Main.hs
  other-modules:
      Paths_trainmodel
  hs-source-dirs:
      app
  ghc-options: -threaded -rtsopts -with-rtsopts=-N
  build-depends:
      base >=4.7 && <5
  default-language: Haskell2010

# This file was autogenerated by Stack.
# You should not edit this file by hand.
# For more information, please see the documentation at:
#   https://docs.haskellstack.org/en/stable/lock_files
packages: []
snapshots:
- completed:
    size: 563103
    url: https://raw.githubusercontent.com/commercialhaskell/stackage-snapshots/master/lts/17/4.yaml
    sha256: f11e2153044f5f71ea7b1c9398f4721f517c9bd37642ed769647b896564021f3
  original:
    url: https://raw.githubusercontent.com/commercialhaskell/stackage-snapshots/master/lts/17/4.yaml

# This file was automatically generated by 'stack init'
#
# Some commonly used options have been documented as comments in this file.
# For advanced use and comprehensive documentation of the format, please see:
# https://docs.haskellstack.org/en/stable/yaml_configuration/
# Resolver to choose a 'specific' stackage snapshot or a compiler version.
# A snapshot resolver dictates the compiler version and the set of packages
# to be used for project dependencies. For example:
#
# resolver: lts-3.5
# resolver: nightly-2015-09-21
# resolver: ghc-7.10.2
#
# The location of a snapshot can be provided as a file or url. Stack assumes
# a snapshot provided as a file might change, whereas a url resource does not.
#
# resolver: ./custom-snapshot.yaml
# resolver: https://example.com/snapshots/2018-01-01.yaml
resolver:
  url: https://raw.githubusercontent.com/commercialhaskell/stackage-snapshots/master/lts/17/4.yaml
# User packages to be built.
# Various formats can be used as shown in the example below.
#
# packages:
# - some-directory
# - https://example.com/foo/bar/baz-0.0.2.tar.gz
#   subdirs:
#   - auto-update
#   - wai
packages:
- .
# Dependency packages to be pulled from upstream that are not in the resolver.
# These entries can reference officially published versions as well as
# forks / in-progress versions pinned to a git hash. For example:
#
# extra-deps:
# - acme-missiles-0.3
# - git: https://github.com/commercialhaskell/stack.git
#   commit: e7b331f14bcffb8367cd58fbfc8b40ec7642100a
#
# extra-deps: []
# Override default flag values for local packages and extra-deps
# flags: {}
# Extra package databases containing global packages
# extra-package-dbs: []
# Control whether we use the GHC we find on the path
# system-ghc: true
#
# Require a specific version of stack, using version ranges
# require-stack-version: -any # Default
# require-stack-version: ">=2.5"
#
# Override the architecture used by stack, especially useful on Windows
# arch: i386
# arch: x86_64
#
# Extra directories used by stack for building
# extra-include-dirs: [/path/to/dir]
# extra-lib-dirs: [/path/to/dir]
#
# Allow a newer minor version of GHC than the snapshot specifies
# compiler-check: newer-minor

module Main where
main :: IO ()
main = return ()

import Distribution.Simple
main = defaultMain

# trainmodel

Copyright Jeremy List (c) 2021
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above
      copyright notice, this list of conditions and the following
      disclaimer in the documentation and/or other materials provided
      with the distribution.
    * Neither the name of Jeremy List nor the names of other
      contributors may be used to endorse or promote products derived
      from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

# Changelog for trainmodel
## Unreleased changes

.stack-work/
*~

import base64
import json
import struct
import tensorflow as tf
class SimResult:
    def __init__(self, stream):
        def check(item):
            if type(item) == dict:
                return {k: check(v) for k, v in item.items()}
            elif type(item) == list:
                return list(map(check, item))
            elif type(item) == str and item.startswith('buffer:'):
                return base64.b64decode(item[len('buffer:'):])
            else:
                return item
        self.raw = check(json.load(stream))
        def vertex(obj):
            return [obj['x'], obj['y'], obj['z']]
        self.vertices = tf.convert_to_tensor(list(map(vertex, self.raw['model']['bodies']['world']['grid']['vertices'])), dtype=tf.float32)
        crust = tf.convert_to_tensor(list(map(lambda x: x[0], struct.iter_unpack('f', self.raw['model']['bodies']['world']['lithosphere']['total_crust']))))
        crust = tf.reshape(crust, (8, self.vertices.shape[0]))
        self.crust_layers = {SimResult.crust_columns()[i]: crust[i] for i in range(0,8)}
        self.total_crust = tf.transpose(crust)
    def seed(self):
        return self.raw['seed']
    def total_crust_mass(self):
        return tf.math.reduce_sum(self.total_crust, axis=1)
    def crust_columns():
        return ['sediment','sedimentary','metamorphic','felsic_plutonic','felsic_volcanic','mafic_volcanic','mafic_plutonic','age']