Feature/eden

autofit/__init__.py

@@ -1,61 +1,63 @@
-from autoconf import conf
-from autofit.mapper.model import path_instances_of_class
-from autofit.mapper.prior_model.attribute_pair import (
-    cast_collection,
-    AttributeNameValue,
-    PriorNameValue,
-    InstanceNameValue,
-)
-
-dir(conf)
+from . import conf
 from . import exc
-from autofit.optimize.non_linear.samples import AbstractSamples, MCMCSamples, NestedSamplerSamples
-from .aggregator import Aggregator, PhaseOutput
-from .mapper import *
+from .aggregator import Aggregator
+from .aggregator import PhaseOutput
 from .mapper import link
+from .mapper import prior
 from .mapper.model import AbstractModel
 from .mapper.model import ModelInstance
 from .mapper.model import ModelInstance as Instance
+from .mapper.model import path_instances_of_class
 from .mapper.model_mapper import ModelMapper
 from .mapper.model_mapper import ModelMapper as Mapper
 from .mapper.model_object import ModelObject
-from .mapper.prior_model import *
+from .mapper.prior import AbstractPromise
+from .mapper.prior import GaussianPrior
+from .mapper.prior import LogUniformPrior
+from .mapper.prior import Prior
+from .mapper.prior import UniformPrior
+from .mapper.prior import last
+from .mapper.prior.deferred import DeferredArgument
+from .mapper.prior.deferred import DeferredInstance
 from .mapper.prior_model.abstract import AbstractPriorModel
 from .mapper.prior_model.annotation import AnnotationPriorModel
+from .mapper.prior_model.attribute_pair import AttributeNameValue
+from .mapper.prior_model.attribute_pair import InstanceNameValue
+from .mapper.prior_model.attribute_pair import PriorNameValue
+from .mapper.prior_model.attribute_pair import cast_collection
 from .mapper.prior_model.collection import CollectionPriorModel
 from .mapper.prior_model.collection import CollectionPriorModel as Collection
-from autofit.mapper.prior.deferred import DeferredArgument
-from autofit.mapper.prior.deferred import DeferredInstance
-from .mapper.prior_model.dimension_type import DimensionType, map_types
+from .mapper.prior_model.dimension_type import DimensionType
+from .mapper.prior_model.dimension_type import map_types
 from .mapper.prior_model.prior_model import PriorModel
 from .mapper.prior_model.prior_model import PriorModel as Model
 from .mapper.prior_model.util import PriorModelNameValue
 from .optimize.grid_search import GridSearch as OptimizerGridSearch
-from .optimize import *
-from .optimize.non_linear.downhill_simplex import DownhillSimplex
-from .optimize.non_linear.nested_sampling.dynesty import DynestyStatic, DynestyDynamic
 from .optimize.grid_search import GridSearchResult
-from .optimize.non_linear.nested_sampling.multi_nest import MultiNest
+from .optimize.non_linear.downhill_simplex import DownhillSimplex
+from .optimize.non_linear.emcee import Emcee
 from .optimize.non_linear.mock_nlo import MockNLO
+from .optimize.non_linear.nested_sampling.dynesty import DynestyDynamic
+from .optimize.non_linear.nested_sampling.dynesty import DynestyStatic
+from .optimize.non_linear.nested_sampling.multi_nest import MultiNest
 from .optimize.non_linear.non_linear import Analysis
 from .optimize.non_linear.non_linear import NonLinearOptimizer
-from .optimize.non_linear.emcee import Emcee
-from autofit.optimize.non_linear.paths import Paths
-from autofit.optimize.non_linear.paths import make_path
-from autofit.optimize.non_linear.paths import convert_paths
 from .optimize.non_linear.non_linear import Result
-from .text import formatter, samples_text
-from .tools import *
+from .optimize.non_linear.paths import Paths
+from .optimize.non_linear.paths import convert_paths
+from .optimize.non_linear.paths import make_path
+from .optimize.non_linear.samples import AbstractSamples
+from .optimize.non_linear.samples import MCMCSamples
+from .optimize.non_linear.samples import NestedSamplerSamples
+from .text import formatter
+from .text import samples_text
 from .tools import path_util
 from .tools.phase import AbstractPhase
-from .tools.phase import Phase
 from .tools.phase import Dataset
+from .tools.phase import Phase
 from .tools.phase import as_grid_search
 from .tools.phase_property import PhaseProperty
 from .tools.pipeline import Pipeline
 from .tools.pipeline import ResultsCollection
-from autofit.mapper.prior import AbstractPromise
-from autofit.mapper.prior import last
-from .mapper.prior import *
 
 __version__ = '0.58.0'

autofit/conf.py

@@ -0,0 +1 @@
+from autoconf.conf import *

autofit/exc.py

@@ -36,3 +36,7 @@ class DeferredInstanceException(Exception):
     """
 
     pass
+
+
+class AggregatorException(Exception):
+    pass

autofit/mapper/prior/prior.py

@@ -7,7 +7,7 @@
 import numpy as np
 from scipy.special import erfcinv
 
-from autoconf import conf
+from autofit import conf
 from autofit import exc
 from autofit.mapper.model_object import ModelObject
 from autofit.mapper.prior.arithmetic import ArithmeticMixin

autofit/mapper/prior_model/abstract.py

@@ -10,14 +10,14 @@
 import autofit.mapper.model
 import autofit.mapper.model_mapper
 import autofit.mapper.prior_model.collection
-from autofit import cast_collection, PriorNameValue, InstanceNameValue
 from autofit import exc
 from autofit.mapper.model import AbstractModel
 from autofit.mapper.prior.deferred import DeferredArgument
 from autofit.mapper.prior.prior import GaussianPrior
 from autofit.mapper.prior.prior import TuplePrior, Prior, WidthModifier, Limits
 from autofit.mapper.prior_model import dimension_type as dim
 from autofit.mapper.prior_model.attribute_pair import DeferredNameValue
+from autofit.mapper.prior_model.attribute_pair import cast_collection, PriorNameValue, InstanceNameValue
 from autofit.mapper.prior_model.recursion import DynamicRecursionCache
 from autofit.mapper.prior_model.util import PriorModelNameValue
 from autofit.text.formatter import TextFormatter
@@ -429,7 +429,7 @@ def instance_from_prior_medians(self):
 
     def log_priors_from_vector(
             self,
-            vector : [float],
+            vector: [float],
     ):
         """
         Compute the log priors of every parameter in a vector, using the Prior of every parameter.
@@ -449,13 +449,12 @@ def log_priors_from_vector(
         """
         return list(
             map(
-                lambda prior_tuple, value : prior_tuple.prior.log_prior_from_value(value=value),
+                lambda prior_tuple, value: prior_tuple.prior.log_prior_from_value(value=value),
                 self.prior_tuples_ordered_by_id,
                 vector,
             )
         )
 
-
     def random_instance(self):
         """
         Creates a random instance of the model.

autofit/mapper/prior_model/util.py

@@ -1,4 +1,4 @@
-from autofit import AttributeNameValue
+from autofit.mapper.prior_model.attribute_pair import AttributeNameValue
 
 
 class PriorModelNameValue(AttributeNameValue):

autofit/optimize/non_linear/mock_nlo.py

@@ -1,7 +1,7 @@
 import math
 
 import autofit as af
-from autofit import AbstractSamples
+from autofit.optimize.non_linear.samples import AbstractSamples
 from autofit.optimize.non_linear.non_linear import NonLinearOptimizer
 from autofit.optimize.non_linear.non_linear import Analysis
 

autofit/tools/edenise.py

@@ -0,0 +1,164 @@
+import re
+import shutil
+from os import walk
+from uuid import uuid1
+
+
+class Line:
+    def __init__(self, string):
+        if "*" in string:
+            print("Please ensure no imports in the __init__ contain a *")
+            exit(1)
+        if "," in string:
+            print("Comma separated imports not allowed")
+            exit(1)
+        self.string = string.replace("\n", "")
+        self.id = str(uuid1())
+
+    def __str__(self):
+        return f"{self.source} -> {self.import_target}"
+
+    def __repr__(self):
+        return f"<{self.__class__.__name__} {self}>"
+
+    def __len__(self):
+        return len(self.source)
+
+    def __lt__(self, other):
+        return len(self) < len(other)
+
+    def __gt__(self, other):
+        return len(self) > len(other)
+
+    def __eq__(self, other):
+        return self._target == other._target
+
+    @property
+    def is_import(self):
+        return self.string.startswith("from")
+
+    @property
+    def source(self):
+        match = re.match("from .* as (.+)", self.string)
+        if match is not None:
+            return match.group(1)
+        return re.match("from .* import (.+)", self.string).group(1)
+
+    @property
+    def target(self):
+        return self._target.split(".")[-1]
+
+    @property
+    def import_target(self):
+        target = ".".join(
+            self._target.split(".")[:-1]
+        )
+        if len(target) > 0:
+            return f".{target}"
+        return target
+
+    def __hash__(self):
+        return hash(self._target)
+
+    @property
+    def _target(self):
+        return self.string.replace(
+            f" as {self.source}",
+            ""
+        ).replace(
+            "from ",
+            ""
+        ).replace(
+            " import ",
+            "."
+        ).lstrip(
+            "."
+        )
+
+
+class Converter:
+    def __init__(self, name, prefix, lines):
+        self.name = name
+        self.prefix = prefix
+        self.lines = sorted(
+            filter(
+                lambda line: line.is_import,
+                lines
+            ),
+            reverse=True
+        )
+
+    @classmethod
+    def from_prefix_and_source_directory(
+            cls,
+            name,
+            prefix,
+            source_directory
+    ):
+        source_directory = source_directory
+        with open(
+                f"{source_directory}/__init__.py"
+        ) as f:
+            lines = map(Line, f.readlines())
+        return Converter(name, prefix, lines)
+
+    def convert(self, string):
+        matched_lines = set()
+        string = string.replace(f"import {self.name} as {self.prefix}", "")
+        for line in self.lines:
+            source = f"{self.prefix}.{line.source}"
+            if source in string:
+                matched_lines.add(
+                    line
+                )
+                string = string.replace(
+                    source,
+                    line.id
+                )
+        for line in self.lines:
+            string = string.replace(
+                line.id,
+                line.target
+            )
+
+        import_string = "\n".join(
+            f"from {self.name}{line.import_target} import {line.target}"
+            for line in matched_lines
+        )
+        return f"{import_string}\n{string}"
+
+
+def edenise(
+        root_directory,
+        name,
+        prefix
+):
+    target_directory = f"{root_directory}/../{name}_eden"
+
+    print(f"Creating {target_directory}...")
+    shutil.copytree(
+        root_directory,
+        target_directory,
+        symlinks=True
+    )
+
+    converter = Converter.from_prefix_and_source_directory(
+        name=name,
+        prefix=prefix,
+        source_directory=f"{root_directory}/{name}"
+    )
+
+    for root, _, files in walk(f"{target_directory}/test_{name}"):
+        for file in files:
+            if file.endswith(".py"):
+                with open(f"{root}/{file}", "r+") as f:
+                    string = f.read()
+                    f.seek(0)
+                    f.write(
+                        converter.convert(
+                            string
+                        )
+                    )
+                    f.truncate()
+
+    open(f"{target_directory}/{name}/__init__.py", "w+").close()

eden.ini

@@ -0,0 +1,3 @@
+[eden]
+name = autofit
+prefix = af

scripts/edenise.py

@@ -0,0 +1,31 @@
+#!/usr/bin/env python
+
+from configparser import ConfigParser
+from sys import argv
+
+from autofit.tools import edenise
+
+
+def main(
+        root_directory
+):
+    try:
+        config = ConfigParser()
+        config.read(
+            f"{root_directory}/eden.ini"
+        )
+
+        edenise.edenise(
+            root_directory,
+            config.get("eden", "name"),
+            config.get("eden", "prefix")
+        )
+    except ValueError:
+        print("Usage: ./edenise.py root_directory")
+        exit(1)
+
+
+if __name__ == "__main__":
+    main(
+        argv[1]
+    )

test_autofit/conftest.py

@@ -3,7 +3,7 @@
 import pytest
 
 import autofit as af
-from autoconf import conf
+from autofit import conf
 import shutil
 
 directory = path.dirname(path.realpath(__file__))