From 39bb89a82ea9473a5917d04f2e2597b8a986b410 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Miguel=20Gonz=C3=A1lez=20Duque?= Date: Fri, 2 Aug 2024 13:54:32 +0200 Subject: [PATCH] Update documentation --- ...il.abstract_observer.AbstractObserver.html | 11 +-- _sources/contributing/a_new_problem.md | 62 +++++------- .../the_basics/defining_an_observer.ipynb | 56 +++++------ .../using_poli/the_basics/intro_to_poli.ipynb | 90 +++++------------- contributing/a_new_problem.html | 62 +++++------- genindex.html | 6 +- objects.inv | Bin 12466 -> 12433 bytes searchindex.js | 2 +- .../the_basics/defining_a_problem_solver.html | 2 +- .../the_basics/defining_an_observer.html | 42 +++----- using_poli/the_basics/intro_to_poli.html | 41 +++----- 11 files changed, 134 insertions(+), 240 deletions(-) diff --git a/_autosummary/poli.core.util.abstract_observer.AbstractObserver.html b/_autosummary/poli.core.util.abstract_observer.AbstractObserver.html index f4bf4373..e041bfd9 100644 --- a/_autosummary/poli.core.util.abstract_observer.AbstractObserver.html +++ b/_autosummary/poli.core.util.abstract_observer.AbstractObserver.html @@ -743,12 +743,9 @@

poli.core.util.abstract_observer.AbstractObserver
-
-initialize_observer(problem_setup_info: ProblemSetupInformation, caller_info: object,
-
-

x0: np.ndarray, y0: np.ndarray, seed: int) -> object:

-
-

Initializes the observer with the necessary information to monitor +

+initialize_observer(problem_setup_info: ProblemSetupInformation, caller_info: object, seed: int) → object:#
+

Initializes the observer with the necessary information to monitor the optimization process.

@@ -777,7 +774,7 @@

poli.core.util.abstract_observer.AbstractObserver

finish()

Finish the observer.

-

initialize_observer(problem_setup_info, ...)

+

initialize_observer(problem_setup_info, ...)

Initialize the observer.

observe(x, y[, context])

diff --git a/_sources/contributing/a_new_problem.md b/_sources/contributing/a_new_problem.md index 3ec4679f..9119baf9 100644 --- a/_sources/contributing/a_new_problem.md +++ b/_sources/contributing/a_new_problem.md @@ -2,7 +2,7 @@ This tutorial covers how black boxes and problems are structured in the repository, and what it takes to add a new one. -If you want to implement your own black box and problem, we recommend copy-pasting an existing folder (e.g. `sa_tdc`), and modifying it to suit your needs. We provide a checklist at the end of this tutorial for the things you need to pay attention to. +If you want to implement your own black box and problem, we recommend copy-pasting an existing folder (e.g. `dockstring`), and modifying it to suit your needs. We provide a checklist at the end of this tutorial for the things you need to pay attention to. ## The structure of a problem @@ -15,7 +15,7 @@ poli/objective_repository │   ├── information.py # A BlackBoxInformation containing a desc. of the black box │   ├── isolated_function.py # The logic of your black box, as complex as you want. │   ├── environment.yml # The conda env where isolated_function.py runs -│   └── register.py # Boilerplate for registration and importing. +│   └── register.py # Boilerplate. the problem factory and black box interface. ``` You can also have as many other files as you want. Think of the folder `.../problem_name` as a small project as of itself: you can use any internal code you write here, since it'll be carried with `poli` at installation time. @@ -68,7 +68,7 @@ my_problem_information = BlackBoxInformation( Think of `isolated_function.py` as the entry-route to all the complex, dependency-heavy logic of your black box. -We expect you to implement a subclass of an `AbstractIsolatedFunction`. These are dynamically instanced in isolated environments, such as the one you provide in `environment.yml. +We expect you to implement a subclass of an `AbstractIsolatedFunction`. These are dynamically instanced in isolated environments, such as the one you provide in `environment.yml`. The average structure of this file would be as follows: @@ -118,7 +118,7 @@ The average `register.py` has the following structure ```python # my_problem_name/register.py -# This one needs to run on a conda env. with minimal dependencies (numpy) +# This one NEEDS TO run on a conda env. with minimal dependencies (numpy) from typing import Tuple, List import numpy as np @@ -142,33 +142,38 @@ class MyBlackBox(AbstractBlackBox): batch_size: int = None, parallelize: bool = False, num_workers: int = None, - evaluation_budget: int = float("inf") + evaluation_budget: int = float("inf"), + force_isolation: bool = False, ): super().__init__( batch_size=batch_size, parallelize=parallelize, num_workers=num_workers, evaluation_budget=evaluation_budget, + force_isolation=force_isolation, ) #... your manipulation of args and kwargs. # Importing the isolated logic if we can: - try: - from poli.objective_repository.my_problem.isolated_function import - MyIsolatedLogic - - self.inner_function = MyIsolatedLogic(...) - except ImportError: - # If we weren't able to import it, we can still - # create it in an isolated process: - self.inner_function = instance_function_as_isolated_process( - name="problem_name__isolated" # The same name in `isolated_function.py`. - ) + _ = get_inner_function( + isolated_function_name="your_problem__isolated", # <-- modify this + class_name="MyIsolatedLogic", # <-- modify this + module_to_import="poli.objective_repository.your_problem.isolated_function", # <-- modify this + force_isolation=force_isolation, + **other_kwargs_that_go_into_MyIsolatedLogic # <-- modify this + ) # Boilerplate for the black box call: def _black_box(self, x: np.ndarray, context: dict = None) -> np.ndarray: - return self.inner_function(x, context) + inner_function = get_inner_function( + isolated_function_name="your_problem__isolated", # <-- modify this + class_name="MyIsolatedLogic", # <-- modify this + module_to_import="poli.objective_repository.your_problem.isolated_function", # <-- modify this + force_isolation=force_isolation, + **other_kwargs_that_go_into_MyIsolatedLogic # <-- modify this + ) + return inner_function(x, context) # A static method that gives you access to the information. @staticmethod @@ -209,24 +214,9 @@ class MyProblemFactory(AbstractProblemFactory): x0 = ... return Problem(f, x0) - - -if __name__ == "__main__": - from poli.core.registry import register_problem - - # Once we have created a simple conda enviroment - # (see the environment.yml file in this folder), - # we can register our problem s.t. it uses - # said conda environment. - my_problem_factory = MyProblemFactory() - register_problem( - my_problem_factory, - conda_environment_name="your_env", # This is the env specified - # by your environment.yml - ) ``` -That is, **the script creates and registers** your problem factory. +That is, **the script provides an access to your isolated logic**. Now users can create a new problem factory or black box without having to worry about having the right dependencies. :::{warning} It is important that name of your problem should be the name of the folder it's contained in, **exactly**. (We advice using `camel_case`). @@ -319,7 +309,7 @@ If you 1. have put your new problem is inside `poli/objective_repository`, 2. have an `information.py` that describes your black box, 3. have an `isolated_function.py` that implements the complex logic of your black box and registers it, -4. have a `register.py` that creates and register your problem factory, +4. have a `register.py` that creates your problem factory and black box, 5. have an `environment.yml` that describes the environment you use, 6. have imported your black box and factory in `objective_repository/__init__.py`, @@ -335,10 +325,6 @@ problem = objective_factory.create( ..., your_arg_1=..., # <-- Keywords you (maybe) needed your_arg_2=..., # <-- at your_factory.create(...) - your_kwarg=..., # <-- - # For now, only certain types are - # supported: str, int, bool, float, - # None, and lists thereof. ) ``` diff --git a/_sources/using_poli/the_basics/defining_an_observer.ipynb b/_sources/using_poli/the_basics/defining_an_observer.ipynb index 49db7fd1..03f6c6a7 100644 --- a/_sources/using_poli/the_basics/defining_an_observer.ipynb +++ b/_sources/using_poli/the_basics/defining_an_observer.ipynb @@ -34,7 +34,7 @@ "metadata": {}, "source": [ "All observers inherit from an `AbstractObserver` (which you can find on `poli/core/util/abstract_observer.py`). The abstract methods you need to overwrite are:\n", - "- `initialize_observer(problem_info: ProblemSetupInformation, caller_info: object, x0: np.ndarray, y0: np.ndarray, seed: int) -> object`, which gets called as part of the set-up of the objective function (when `objective_factory.create` is called).\n", + "- `initialize_observer(problem_setup_info: BlackBoxInformation, caller_info: object, seed: int) -> object`, which gets called as part of the set-up of the objective function (when `objective_factory.create` is called).\n", "- `observe(x: np.ndarray, y: np.ndarray, context: object) -> None`, which gets called every time your optimization algorithms query the objective function.\n", "- `finish()`, which gets called either by the user, or by the object deletion at the end of the script." ] @@ -72,8 +72,6 @@ " self,\n", " problem_setup_info: ProblemSetupInformation,\n", " caller_info: object,\n", - " x0: np.ndarray,\n", - " y0: np.ndarray,\n", " seed: int\n", " ) -> object:\n", " ...\n", @@ -101,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -111,7 +109,7 @@ "\n", "import numpy as np\n", "\n", - "from poli.core.problem_setup_information import ProblemSetupInformation\n", + "from poli.core.black_box_information import BlackBoxInformation\n", "from poli.core.util.abstract_observer import AbstractObserver\n", "\n", "THIS_DIR = Path().resolve()\n", @@ -131,10 +129,8 @@ " \n", " def initialize_observer(\n", " self,\n", - " problem_setup_info: ProblemSetupInformation,\n", + " problem_setup_info: BlackBoxInformation,\n", " caller_info: object,\n", - " x0: np.ndarray,\n", - " y0: np.ndarray,\n", " seed: int\n", " ) -> object:\n", "\n", @@ -147,8 +143,6 @@ " metadata[\"caller_info\"] = caller_info\n", "\n", " # Saving the initial evaluations and seed\n", - " metadata[\"x0\"] = x0.tolist()\n", - " metadata[\"y0\"] = y0.tolist()\n", " metadata[\"seed\"] = seed\n", "\n", " # Saving the metadata\n", @@ -183,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -224,7 +218,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": { "tags": [ "hide-cell" @@ -260,8 +254,6 @@ " self,\n", " problem_setup_info: ProblemSetupInformation,\n", " caller_info: object,\n", - " x0: np.ndarray,\n", - " y0: np.ndarray,\n", " seed: int\n", " ) -> object:\n", "\n", @@ -274,8 +266,6 @@ " metadata[\"caller_info\"] = caller_info\n", "\n", " # Saving the initial evaluations and seed\n", - " metadata[\"x0\"] = x0.tolist()\n", - " metadata[\"y0\"] = y0.tolist()\n", " metadata[\"seed\"] = seed\n", "\n", " # Saving the metadata\n", @@ -304,22 +294,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 13, "metadata": { "tags": [ "hide-output" ] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "poli 🧪: Creating the objective aloha from the repository.\n", - "poli 🧪: initializing the observer.\n" - ] - } - ], + "outputs": [], "source": [ "from poli import objective_factory\n", "\n", @@ -331,7 +312,17 @@ " name=\"aloha\",\n", " observer=observer,\n", ")\n", - "f, x0 = problem.black_box, problem.x0" + "f, x0 = problem.black_box, problem.x0\n", + "\n", + "# We initialize the observer\n", + "observer.initialize_observer(\n", + " problem_setup_info=f.info,\n", + " caller_info={},\n", + " seed=None,\n", + ")\n", + "\n", + "# We set the observer to track f.\n", + "f.set_observer(observer)" ] }, { @@ -343,14 +334,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'name': 'aloha', 'max_sequence_length': 5, 'aligned': True, 'fixed_length': True, 'deterministic': True, 'discrete': True, 'fidelity': None, 'alphabet': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'], 'log_transform_recommended': False, 'padding_token': '', 'caller_info': None, 'x0': [['A', 'L', 'O', 'O', 'F']], 'y0': [[3]], 'seed': None}\n" + "{'name': 'aloha', 'max_sequence_length': 5, 'aligned': True, 'fixed_length': True, 'deterministic': True, 'discrete': True, 'fidelity': None, 'alphabet': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'], 'log_transform_recommended': False, 'padding_token': '', 'caller_info': {}, 'seed': None}\n" ] } ], @@ -368,7 +359,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -396,14 +387,13 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[['A', 'L', 'O', 'O', 'F']]\t[[3]]\n", "[['M', 'I', 'G', 'U', 'E']]\t[[0]]\n", "[['F', 'L', 'E', 'A', 'S']]\t[[1]]\n", "[['A', 'L', 'O', 'H', 'A']]\t[[5]]\n", diff --git a/_sources/using_poli/the_basics/intro_to_poli.ipynb b/_sources/using_poli/the_basics/intro_to_poli.ipynb index b19b8c63..18da4de0 100644 --- a/_sources/using_poli/the_basics/intro_to_poli.ipynb +++ b/_sources/using_poli/the_basics/intro_to_poli.ipynb @@ -14,11 +14,11 @@ "```{contents}\n", "```\n", "\n", - "`poli` is a library for creating and calling black box optimization functions, with a special focus on *discrete* sequence optimization. It stands for *Protein Objectives Library*, since some of the work done on drug design is done through representing proteins and small molecules as discrete sequences.\n", + "`poli` is a library for creating and calling black box objective functions, with a special focus on *discrete* sequence optimization. It stands for *Protein Objectives Library*, since some of the work done on drug design and protein engineering is done through representing proteins and small molecules as discrete sequences.\n", "\n", "We also build `poli-baselines` on top, allowing you to define black box optimization algorithms for discrete sequences.\n", "\n", - "These next chapters detail a basic example of how to use `poli` and `poli-baselines`. If you want to start coding now, continue to [the next chapter](./registering_an_objective_function.md)!\n", + "These next chapters detail a basic example of how to use `poli` and `poli-baselines`.\n", "\n", "The rest of this intro details the usual development loops we assume you'll follow when using `poli` and `poli-baselines`:" ] @@ -64,7 +64,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "['aloha', 'dockstring', 'drd3_docking', 'foldx_rfp_lambo', 'foldx_sasa', 'foldx_stability', 'foldx_stability_and_sasa', 'gfp_cbas', 'gfp_select', 'penalized_logp_lambo', 'rasp', 'rdkit_logp', 'rdkit_qed', 'rfp_foldx_stability_and_sasa', 'sa_tdc', 'super_mario_bros', 'white_noise', 'toy_continuous_problem']\n" + "['albuterol_similarity', 'aloha', 'amlodipine_mpo', 'celecoxib_rediscovery', 'deco_hop', 'dockstring', 'dockstring__isolated', 'drd2_docking', 'drd3_docking', 'ehrlich', 'fexofenadine_mpo', 'foldx_rfp_lambo', 'foldx_rfp_lambo__isolated', 'foldx_sasa', 'foldx_sasa__isolated', 'foldx_stability', 'foldx_stability__isolated', 'foldx_stability_and_sasa', 'foldx_stability_and_sasa__isolated', 'gfp_cbas', 'gfp_cbas__isolated', 'gfp_select', 'gfp_select__isolated', 'gsk3_beta', 'isomer_c7h8n2o2', 'isomer_c9h10n2o2pf2cl', 'jnk3', 'median_1', 'median_2', 'mestranol_similarity', 'osimetrinib_mpo', 'penalized_logp_lambo', 'penalized_logp_lambo__isolated', 'perindopril_mpo', 'ranolazine_mpo', 'rasp', 'rasp__isolated', 'rdkit_logp', 'rdkit_qed', 'rfp_foldx_stability_and_sasa', 'rmf_landscape', 'rmf_landscape__isolated', 'rosetta_energy', 'sa_tdc', 'sa_tdc__isolated', 'scaffold_hop', 'sitagliptin_mpo', 'super_mario_bros', 'super_mario_bros__isolated', 'thiothixene_rediscovery', 'toy_continuous_problem', 'troglitazone_rediscovery', 'valsartan_smarts', 'white_noise', 'zaleplon_mpo']\n" ] } ], @@ -86,7 +86,7 @@ "source": [ ":::{note}\n", "\n", - "Some objective functions have more requirements, like installing external dependencies. Check [the page on all objective functions](../objective_repository/all_objectives.md) and click on the objective function you are interested in to get a detailed set of instructions on how to install and run it.\n", + "Most black box functions run out-of-the-box, but some have more requirements, like installing external dependencies. Check [the page on all objective functions](../objective_repository/all_objectives.md) and click on the objective function you are interested in to get a detailed set of instructions on how to install and run it.\n", "\n", ":::\n", "\n", @@ -95,17 +95,9 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "poli 🧪: Creating the objective white_noise from the repository.\n" - ] - } - ], + "outputs": [], "source": [ "# One way to create a white noise problem/black box\n", "from poli import objective_factory\n", @@ -144,23 +136,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/sjt972/anaconda3/envs/poli-docs2/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ "x0: [['1' '2' '3']]\n", - "y0: [[-1.2003119]]\n" + "y0: [[1.6068791]]\n" ] } ], @@ -183,61 +167,35 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Solvers implement a `next_candidate()` method, based on their history:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([['1', '2', '3']], dtype=' Contents

Adding a new black box to the repository#

This tutorial covers how black boxes and problems are structured in the repository, and what it takes to add a new one.

-

If you want to implement your own black box and problem, we recommend copy-pasting an existing folder (e.g. sa_tdc), and modifying it to suit your needs. We provide a checklist at the end of this tutorial for the things you need to pay attention to.

+

If you want to implement your own black box and problem, we recommend copy-pasting an existing folder (e.g. dockstring), and modifying it to suit your needs. We provide a checklist at the end of this tutorial for the things you need to pay attention to.

The structure of a problem#

If you take a look at the source code of poli, you will find a folder called objective_repository. This is where all the objective functions in the repository live. The structure of a generic problem goes as follows

@@ -753,7 +753,7 @@

The structure of a problem   ├── information.py # A BlackBoxInformation containing a desc. of the black box │   ├── isolated_function.py # The logic of your black box, as complex as you want. │   ├── environment.yml # The conda env where isolated_function.py runs -│   └── register.py # Boilerplate for registration and importing. +│   └── register.py # Boilerplate. the problem factory and black box interface.

You can also have as many other files as you want. Think of the folder .../problem_name as a small project as of itself: you can use any internal code you write here, since it’ll be carried with poli at installation time.

@@ -802,7 +802,7 @@

Specifying your problem information in

A generic isolated_function.py#

Think of isolated_function.py as the entry-route to all the complex, dependency-heavy logic of your black box.

-

We expect you to implement a subclass of an AbstractIsolatedFunction. These are dynamically instanced in isolated environments, such as the one you provide in `environment.yml.

+

We expect you to implement a subclass of an AbstractIsolatedFunction. These are dynamically instanced in isolated environments, such as the one you provide in environment.yml.

The average structure of this file would be as follows:

# my_problem_name/isolated_function.py,
 # able to run inside the conda env you specify in environment.yml
@@ -846,7 +846,7 @@ 
A generic isola
 
A generic register.py#

 
The average register.py has the following structure

 
# my_problem_name/register.py
-# This one needs to run on a conda env. with minimal dependencies (numpy)
+# This one NEEDS TO run on a conda env. with minimal dependencies (numpy)
 from typing import Tuple, List
 
 import numpy as np
@@ -870,33 +870,38 @@ 
A generic regis
         batch_size: int = None,
         parallelize: bool = False,
         num_workers: int = None,
-        evaluation_budget: int = float("inf")
+        evaluation_budget: int = float("inf"),
+        force_isolation: bool = False,
     ):
         super().__init__(
             batch_size=batch_size,
             parallelize=parallelize,
             num_workers=num_workers,
             evaluation_budget=evaluation_budget,
+            force_isolation=force_isolation,
         )
 
         #... your manipulation of args and kwargs.
 
         # Importing the isolated logic if we can:
-        try:
-            from poli.objective_repository.my_problem.isolated_function import
-            MyIsolatedLogic
-
-            self.inner_function = MyIsolatedLogic(...)
-        except ImportError:
-            # If we weren't able to import it, we can still
-            # create it in an isolated process:
-            self.inner_function = instance_function_as_isolated_process(
-                name="problem_name__isolated"  # The same name in `isolated_function.py`.
-            )
+        _ = get_inner_function(
+            isolated_function_name="your_problem__isolated",  # <-- modify this
+            class_name="MyIsolatedLogic",  # <-- modify this
+            module_to_import="poli.objective_repository.your_problem.isolated_function",  # <-- modify this
+            force_isolation=force_isolation,
+            **other_kwargs_that_go_into_MyIsolatedLogic  # <-- modify this
+        )
 
     # Boilerplate for the black box call:
     def _black_box(self, x: np.ndarray, context: dict = None) -> np.ndarray:
-        return self.inner_function(x, context)
+        inner_function = get_inner_function(
+            isolated_function_name="your_problem__isolated",  # <-- modify this
+            class_name="MyIsolatedLogic",  # <-- modify this
+            module_to_import="poli.objective_repository.your_problem.isolated_function",  # <-- modify this
+            force_isolation=force_isolation,
+            **other_kwargs_that_go_into_MyIsolatedLogic  # <-- modify this
+        )
+        return inner_function(x, context)
 
     # A static method that gives you access to the information.
     @staticmethod
@@ -937,24 +942,9 @@ 
A generic regis
         x0 = ...
 
         return Problem(f, x0)
-
-
-if __name__ == "__main__":
-    from poli.core.registry import register_problem
-
-    # Once we have created a simple conda enviroment
-    # (see the environment.yml file in this folder),
-    # we can register our problem s.t. it uses
-    # said conda environment.
-    my_problem_factory = MyProblemFactory()
-    register_problem(
-        my_problem_factory,                   
-        conda_environment_name="your_env",    # This is the env specified
-                                              # by your environment.yml
-    )
 

 

-
That is, the script creates and registers your problem factory.

+
That is, the script provides an access to your isolated logic. Now users can create a new problem factory or black box without having to worry about having the right dependencies.

 

 
Warning

 
It is important that name of your problem should be the name of the folder it’s contained in, exactly. (We advice using camel_case).

@@ -1038,7 +1028,7 @@ 
Testing your installationpoli/objective_repository,

 
  • have an information.py that describes your black box,
    • 
 
  • have an isolated_function.py that implements the complex logic of your black box and registers it,
    • 
-
  • have a register.py that creates and register your problem factory,
    • 
+
  • have a register.py that creates your problem factory and black box,
    • 
 
  • have an environment.yml that describes the environment you use,
    • 
 
  • have imported your black box and factory in objective_repository/__init__.py,
    • 
 
@@ -1051,10 +1041,6 @@ 
    Testing your installation...,
     your_arg_1=...,      # <-- Keywords you (maybe) needed
     your_arg_2=...,       # <-- at your_factory.create(...)
-    your_kwarg=...,       # <--
-                            # For now, only certain types are
-                            # supported: str, int, bool, float,
-                            # None, and lists thereof.
 )
    diff --git a/genindex.html b/genindex.html index b8685097..9c058f2c 100644 --- a/genindex.html +++ b/genindex.html @@ -1109,8 +1109,12 @@

    I

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394, 407, 418, 435, 439, 441], "far": [390, 435], "support": [367, 389, 391, 392, 435, 439], "two": [65, 83, 391, 394, 428, 436, 439, 440, 441, 451], "drd3": [138, 141, 142, 143, 392, 397], "synthet": [275, 277, 278, 279, 280, 388, 392, 397], "access": [58, 81, 138, 158, 163, 164, 172, 176, 177, 268, 277, 278, 279, 280, 388, 389, 392, 394, 397, 404, 420, 421, 425, 428], "see": [51, 52, 82, 117, 138, 271, 306, 324, 327, 336, 389, 390, 391, 394, 395, 407, 434, 438, 439, 441], "document": [246, 391, 392, 394, 411, 412, 424, 432, 434, 439], "our": [389, 390, 394, 397, 402, 408, 409, 434, 435, 436, 439, 440, 441, 444, 446, 448, 451], "more": [82, 163, 170, 176, 327, 328, 391, 394, 411, 412, 424, 432, 434, 438], "refer": [13, 14, 15, 25, 80, 115, 122, 125, 128, 132, 133, 134, 137, 138, 141, 146, 149, 150, 220, 223, 226, 229, 232, 235, 238, 241, 242, 244, 245, 250, 253, 274, 277, 278, 283, 286, 304, 331, 334, 341, 392, 395, 396, 398, 399, 400, 401, 402, 403, 406, 407, 408, 409, 410, 411, 412, 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409, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 425, 427, 429, 430, 432, 448], "org": [13, 14, 15, 45, 80, 115, 122, 125, 128, 132, 133, 134, 137, 141, 146, 149, 150, 220, 223, 226, 229, 232, 235, 238, 241, 242, 244, 245, 250, 253, 256, 257, 271, 274, 277, 278, 283, 286, 304, 306, 327, 328, 331, 334, 341, 388, 394, 395, 396, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 422, 423, 424, 425, 427, 428, 429, 430, 432, 445, 448], "1038": [13, 14, 15, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "s41589": [13, 14, 15, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "022": [13, 14, 15, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "01131": [13, 14, 15, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "2": [13, 14, 15, 45, 80, 83, 115, 122, 125, 128, 137, 141, 149, 162, 169, 175, 182, 183, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 270, 271, 274, 277, 278, 283, 286, 304, 306, 322, 325, 328, 331, 334, 341, 388, 389, 391, 392, 394, 395, 396, 397, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 438, 442, 443, 444, 445, 448, 450, 452, 454, 456], "oracle_nam": [14, 142], "str": [14, 23, 26, 48, 49, 50, 51, 52, 55, 58, 59, 61, 64, 65, 74, 77, 81, 83, 84, 85, 87, 88, 89, 109, 111, 133, 142, 163, 170, 176, 211, 292, 293, 325, 389, 394, 405, 431, 436, 441, 445, 452], "from_smil": [142, 261, 266], "true": [48, 49, 50, 51, 52, 58, 81, 83, 84, 89, 109, 111, 142, 188, 205, 210, 246, 261, 266, 322, 389, 394, 408, 409, 431, 434, 436, 440, 441], "kwargs_for_oracl": 14, "repres": [26, 65, 83, 88, 142, 204, 438], "It": [64, 65, 138, 389, 390, 391, 394, 402, 404, 435, 438, 442], "name": [11, 14, 15, 23, 55, 58, 59, 77, 87, 88, 89, 109, 111, 133, 142, 325, 328, 389, 390, 391, 394, 395, 407, 431, 434, 436, 438, 440, 441, 443, 445, 452], "comput": [25, 61, 81, 83, 85, 118, 133, 138, 162, 163, 169, 170, 172, 175, 176, 242, 244, 245, 258, 261, 266, 268, 270, 306, 388, 391, 392, 393, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 439, 442, 443, 445, 448, 450, 452, 454, 456], "dock": [132, 133, 134, 137, 138, 141, 142, 143, 388, 392, 397, 402, 439], "score": [132, 133, 134, 163, 170, 176, 388, 392, 395, 397, 402, 403, 404, 408, 409, 418, 422, 439], "an": [6, 13, 14, 15, 21, 25, 39, 42, 45, 48, 49, 50, 51, 52, 54, 55, 58, 65, 76, 77, 80, 85, 109, 111, 162, 169, 175, 182, 183, 220, 229, 270, 294, 325, 389, 391, 392, 393, 394, 402, 405, 407, 408, 409, 410, 413, 425, 426, 428, 430, 434, 439, 442, 443, 444, 445, 446, 448, 451, 452, 454, 456], "process": [6, 39, 54, 55, 64, 65, 76, 77, 109, 111, 118, 133, 163, 169, 170, 176, 200, 261, 266, 388, 389, 394, 396, 399, 400, 401, 403, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 425, 427, 428, 429, 430, 432, 434, 438, 439, 440, 441, 442, 443, 444, 452, 454, 456], "multipl": [118, 133, 261, 266], "infin": [14, 109, 118, 133, 142, 163, 170, 176, 261, 266, 279], "molecul": [14, 47, 48, 49, 50, 115, 132, 133, 134, 137, 142, 220, 229, 238, 246, 261, 266, 267, 279, 304, 331, 388, 391, 394, 402, 403, 404, 410, 413, 414, 415, 422, 438], "ar": [6, 21, 39, 80, 83, 85, 110, 138, 146, 188, 246, 261, 266, 267, 324, 374, 389, 390, 391, 393, 395, 397, 405, 407, 408, 409, 420, 421, 425, 426, 428, 434, 435, 436, 438, 439, 440, 441, 444, 448], "smile": [14, 49, 50, 51, 52, 115, 128, 133, 142, 238, 246, 260, 261, 265, 266, 279, 392, 396, 399, 400, 401, 403, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 420, 421, 423, 424, 427, 429, 430, 432], "format": [64, 82, 85, 184], "represent": [14, 47, 50, 133, 142, 256, 257, 261, 266, 279, 388, 395, 439], "dict": [14, 64, 109, 111, 118, 133, 389, 441], "addit": [55, 64, 74, 109, 111, 146, 395, 405], "keyword": [14, 55, 64, 109, 111, 389, 408, 409, 440], "argument": [14, 39, 55, 64, 109, 111, 408, 409, 440], "custom": [16, 440], "packag": [16, 18, 51, 52, 57, 434, 438, 439, 441, 443], "rais": [17, 20, 48, 49, 51, 52, 58, 59, 65, 80, 83, 84, 390, 393, 405, 435, 440], "when": [15, 17, 64, 109, 111, 115, 122, 125, 128, 137, 146, 149, 223, 226, 229, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 389, 395, 405, 411, 412, 424, 432, 436, 438, 439, 440], "exhaust": 17, "multi_object": 19, "version": [19, 55, 81, 138, 242, 265, 267, 390, 391, 392, 393, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 435, 436, 442, 443, 445, 448, 450, 451, 452, 454, 456], "mean": [19, 85, 186, 246, 389, 390, 418, 428, 446], "simpli": [19, 390, 391, 407, 435, 436, 438], "concaten": [19, 20, 261, 266], "result": [19, 20, 81, 261, 266, 394, 436, 439], "individu": [19, 20, 82, 293, 394, 436, 439], "objective_funct": [20, 451], "list": [20, 26, 48, 49, 50, 51, 52, 74, 81, 82, 83, 84, 85, 87, 88, 163, 170, 176, 182, 196, 205, 291, 293, 325, 328, 389, 392, 394, 405, 408, 409, 436, 438, 441, 445, 452], "multi": [20, 220, 229, 388, 399, 406, 410, 413, 417, 419, 424, 432, 451], "requir": [20, 26, 39, 57, 58, 138, 389, 390, 392, 394, 395, 425, 434, 435, 436, 438, 439, 440], "valueerror": [20, 59, 84], "e": [6, 21, 22, 58, 79, 85, 111, 118, 138, 146, 182, 183, 187, 256, 257, 261, 266, 267, 322, 337, 388, 389, 390, 391, 392, 394, 395, 397, 402, 405, 407, 408, 409, 431, 434, 435, 436, 440, 441, 442, 448, 452, 454], "g": [6, 21, 22, 79, 85, 182, 183, 267, 274, 389, 390, 391, 392, 394, 397, 405, 408, 409, 431, 434, 435, 436, 440, 441, 454], "alphabet": [11, 22, 26, 118, 133, 389, 390, 405, 407, 431, 434, 435, 436, 438, 441, 445, 451, 452, 453, 455], "sequenc": [11, 22, 80, 117, 118, 119, 146, 150, 182, 183, 184, 185, 189, 190, 191, 242, 244, 245, 388, 389, 390, 392, 394, 395, 396, 398, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 434, 435, 438, 441, 442, 443, 445, 448, 450, 452, 454, 456], "length": [11, 22, 45, 83, 84, 193, 389, 394, 405, 441, 445, 452], "max_sequence_length": [389, 431, 436, 441], "align": [11, 388, 389, 392, 431, 436, 441], "log_transform_recommend": [389, 431, 436], "s": [11, 21, 23, 26, 51, 52, 79, 80, 111, 138, 146, 163, 170, 176, 179, 256, 257, 260, 261, 265, 266, 267, 306, 320, 388, 391, 392, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 434, 435, 436, 438, 439, 440, 442, 443, 444, 445, 450, 451, 452, 454, 456], "longest": 11, "have": [6, 11, 45, 138, 146, 163, 170, 176, 306, 367, 389, 390, 391, 393, 394, 395, 402, 404, 405, 407, 408, 409, 418, 425, 426, 434, 435, 438, 439, 440, 441, 442, 443, 445, 448, 452, 454], "been": [306, 393], "charact": 11, "mai": [256, 257, 388, 395, 438, 443, 445, 450, 452], "appear": [391, 394], "recommend": [115, 122, 125, 128, 137, 138, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 389, 391, 392, 404, 407, 425, 446], "algorithm": [21, 39, 146, 324, 374, 388, 390, 394, 405, 428, 435, 436, 438, 440, 441, 444, 451], "log": [55, 208, 242, 258, 260, 261, 389, 390, 392, 397, 441, 448], "transform": [47, 289, 294, 295, 389], "target": [118, 133], "foldx": [25, 26, 82, 85, 162, 163, 164, 165, 169, 170, 172, 175, 176, 177, 256, 257, 268, 270, 391, 392, 394, 397, 434, 439, 441], "simul": [25, 26, 80, 81, 162, 169, 175, 270, 306, 389, 391, 425], "free": [25, 162, 169, 175, 270, 389, 390, 393, 394], "energi": [25, 81, 162, 169, 175, 270, 393, 409], "between": [25, 83, 85, 118, 162, 169, 175, 265, 270, 405, 411, 412, 420, 424, 432], "wildtyp": [25, 26, 84, 85, 162, 163, 169, 170, 175, 176, 256, 257, 270, 392, 395, 397, 408, 409], "mutat": [25, 26, 81, 162, 169, 175, 184, 270, 388, 390, 392, 395, 397, 408, 409, 435, 438, 440, 451], "web": [25, 80, 162, 169, 175, 270, 407, 408, 409], "server": [25, 64, 65, 80, 162, 169, 175, 270, 407, 408, 409], "onlin": [25, 80, 162, 169, 175, 270, 407, 408, 409], "forc": [14, 25, 80, 142, 162, 169, 175, 270, 369, 407, 408, 409], "field": [25, 80, 162, 169, 175, 270, 407, 408, 409], "nucleic": [25, 80, 162, 169, 175, 270, 407, 408, 409], "acid": [25, 26, 79, 80, 162, 169, 175, 182, 183, 185, 190, 191, 270, 405, 407, 408, 409], "research": [25, 80, 162, 169, 175, 270, 388, 407, 408, 409], "schymkowitz": [25, 80, 162, 169, 175, 270, 394, 407, 408, 409], "j": 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306, 436], "id": [26, 82, 163, 170, 176, 291, 367, 388, 389, 394, 403, 410, 413, 436, 441, 443], "temporari": [26, 163, 170, 176], "folder": [26, 58, 117, 138, 163, 170, 176, 324, 336, 389, 390, 391, 393, 436, 439, 441], "eagerli": [26, 170], "repair": [26, 80, 81, 163, 170, 176, 434], "print": [26, 45, 58, 81, 87, 88, 89, 111, 163, 170, 176, 391, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 434, 436, 438, 440, 441, 451, 453, 455], "output": [26, 81, 87, 88, 89, 163, 170, 176, 389, 392, 394, 438, 439], "wildtype_residu": [26, 85], "residu": [26, 82, 84, 85, 87, 88, 394], "each": [26, 39, 45, 83, 85, 185, 190, 392, 394, 436, 439, 440, 446], "wildtype_amino_acid": 26, "wildtype_residue_str": [26, 85], "string": [14, 26, 47, 48, 49, 50, 51, 52, 64, 83, 84, 85, 87, 115, 133, 142, 183, 184, 193, 238, 260, 261, 265, 266, 279, 292, 293, 390, 392, 394, 398, 401, 403, 420, 421, 423, 425, 431, 435, 440, 441, 453, 455], "create_working_directori": 26, "work": [26, 45, 74, 81, 111, 138, 315, 319, 369, 381, 390, 391, 393, 394, 397, 402, 420, 421, 434, 435, 436, 438, 440, 442, 443, 444, 448, 454, 456], "directori": [26, 74, 81, 393, 394, 395, 407, 408, 409, 436], "regist": [15, 28, 110, 138, 391, 405, 438], "observer_nam": [55, 77, 109, 111, 433], "delet": 436, "run": [6, 15, 21, 54, 64, 72, 73, 74, 81, 109, 111, 138, 170, 389, 390, 391, 393, 394, 435, 436, 438, 440, 441], "script": [6, 15, 64, 72, 73, 74, 76, 80, 117, 138, 169, 260, 265, 306, 324, 336, 369, 389, 395, 404, 436, 440, 441], "take": [64, 293, 388, 389, 390, 398, 425, 428, 431, 434, 435, 438, 441, 442, 443, 444, 448, 454, 456], "pass": [14, 55, 64, 85, 89, 109, 390, 394, 407, 408, 409, 434, 441], "locat": [80, 320, 328, 394, 453, 455], "note": [58, 64, 65, 77, 81, 163, 170, 176, 425, 428, 448], "must": [39, 391, 398, 405, 426, 428, 431], "accept": [64, 389], "port": [64, 65, 77], "password": [64, 65, 77], "problem_nam": [389, 426, 434], "configur": 110, "dictionari": [64, 434], "problem_factori": [434, 451, 453, 455], "only_avail": [], "includ": [11, 21, 138, 391, 392, 395, 402, 404, 428, 436, 439, 440, 441, 444, 448], "can": [6, 45, 54, 64, 77, 89, 138, 146, 205, 256, 257, 261, 266, 389, 390, 391, 393, 394, 395, 396, 399, 400, 401, 403, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 420, 421, 423, 424, 425, 426, 427, 428, 429, 430, 432, 434, 435, 436, 438, 439, 440, 441, 442, 443, 445, 448, 450, 452, 454], "import": [39, 59, 80, 111, 244, 245, 389, 390, 391, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 434, 436, 438, 439, 440, 441, 442, 443, 444, 445, 446, 448, 450, 451, 452, 453, 454, 455, 456], "directli": [312, 394, 439], "problem_list": [], "repositori": [56, 57, 58, 59, 107, 132, 179, 306, 312, 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"poli.objective_repository.gfp_select.register.GFPBlackBox", "poli.objective_repository.gfp_select.register.GFPSelectionProblemFactory", "poli.objective_repository.gsk3_beta", "poli.objective_repository.gsk3_beta.information", "poli.objective_repository.gsk3_beta.register", "poli.objective_repository.isomer_c7h8n2o2", "poli.objective_repository.isomer_c7h8n2o2.information", "poli.objective_repository.isomer_c7h8n2o2.register", "poli.objective_repository.isomer_c9h10n2o2pf2cl", "poli.objective_repository.isomer_c9h10n2o2pf2cl.information", "poli.objective_repository.isomer_c9h10n2o2pf2cl.register", "poli.objective_repository.jnk3", "poli.objective_repository.jnk3.information", "poli.objective_repository.jnk3.register", "poli.objective_repository.median_1", "poli.objective_repository.median_1.information", "poli.objective_repository.median_1.register", "poli.objective_repository.median_2", "poli.objective_repository.median_2.information", "poli.objective_repository.median_2.register", "poli.objective_repository.mestranol_similarity", "poli.objective_repository.mestranol_similarity.information", "poli.objective_repository.mestranol_similarity.register", "poli.objective_repository.osimetrinib_mpo", "poli.objective_repository.osimetrinib_mpo.information", "poli.objective_repository.osimetrinib_mpo.register", "poli.objective_repository.penalized_logp_lambo", "poli.objective_repository.penalized_logp_lambo.information", "poli.objective_repository.penalized_logp_lambo.isolated_function", "poli.objective_repository.penalized_logp_lambo.register", "poli.objective_repository.penalized_logp_lambo.register.PenalizedLogPLamboBlackBox", "poli.objective_repository.penalized_logp_lambo.register.PenalizedLogPLamboProblemFactory", "poli.objective_repository.perindopril_mpo", "poli.objective_repository.perindopril_mpo.information", "poli.objective_repository.perindopril_mpo.register", "poli.objective_repository.ranolazine_mpo", "poli.objective_repository.ranolazine_mpo.information", "poli.objective_repository.ranolazine_mpo.register", "poli.objective_repository.rasp", "poli.objective_repository.rasp.information", "poli.objective_repository.rasp.isolated_function", "poli.objective_repository.rasp.register", "poli.objective_repository.rdkit_logp", "poli.objective_repository.rdkit_logp.information", "poli.objective_repository.rdkit_logp.register", "poli.objective_repository.rdkit_logp.register.LogPBlackBox", "poli.objective_repository.rdkit_logp.register.LogPProblemFactory", "poli.objective_repository.rdkit_qed", "poli.objective_repository.rdkit_qed.information", "poli.objective_repository.rdkit_qed.register", "poli.objective_repository.rdkit_qed.register.QEDBlackBox", "poli.objective_repository.rdkit_qed.register.QEDProblemFactory", "poli.objective_repository.rfp_foldx_stability_and_sasa", "poli.objective_repository.rfp_foldx_stability_and_sasa.information", "poli.objective_repository.rfp_foldx_stability_and_sasa.register", "poli.objective_repository.rmf_landscape", "poli.objective_repository.rmf_landscape.information", "poli.objective_repository.rmf_landscape.isolated_function", "poli.objective_repository.rmf_landscape.register", "poli.objective_repository.sa_tdc", "poli.objective_repository.sa_tdc.information", "poli.objective_repository.sa_tdc.isolated_function", "poli.objective_repository.sa_tdc.register", "poli.objective_repository.sa_tdc.register.SABlackBox", "poli.objective_repository.sa_tdc.register.SAProblemFactory", "poli.objective_repository.scaffold_hop", "poli.objective_repository.scaffold_hop.information", "poli.objective_repository.scaffold_hop.register", "poli.objective_repository.sitagliptin_mpo", "poli.objective_repository.sitagliptin_mpo.information", "poli.objective_repository.sitagliptin_mpo.register", "poli.objective_repository.super_mario_bros", "poli.objective_repository.super_mario_bros.information", "poli.objective_repository.super_mario_bros.level_utils", "poli.objective_repository.super_mario_bros.level_utils.add_padding_to_level", "poli.objective_repository.super_mario_bros.level_utils.clean_level", "poli.objective_repository.super_mario_bros.level_utils.level_to_array", "poli.objective_repository.super_mario_bros.level_utils.level_to_list", "poli.objective_repository.super_mario_bros.level_utils.levels_to_onehot", "poli.objective_repository.super_mario_bros.level_utils.onehot_to_levels", "poli.objective_repository.super_mario_bros.level_utils.tensor_to_sim_level", "poli.objective_repository.super_mario_bros.level_utils.vectorized", "poli.objective_repository.super_mario_bros.model", "poli.objective_repository.super_mario_bros.model.VAEMario", "poli.objective_repository.super_mario_bros.model.load_example_model", "poli.objective_repository.super_mario_bros.register", "poli.objective_repository.thiothixene_rediscovery", "poli.objective_repository.thiothixene_rediscovery.information", 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405, 407, 422, 425, 428, 434, 435, 436, 438, 439, 442, 446, 452], "all": [3, 13, 107, 109, 112, 117, 118, 119, 138, 196, 306, 337, 389, 390, 391, 394, 395, 398, 405, 434, 435, 438, 439], "should": [3, 64, 138, 146, 389, 391, 393, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 427, 428, 429, 430, 431, 432, 434, 435, 436, 439], "inherit": [3, 20, 115, 122, 125, 128, 149, 223, 226, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 390, 434, 435, 436], "info": [26, 142, 337, 390, 434, 435, 436, 438, 443, 449, 450], "problemsetupinform": [26, 39, 337, 407, 436], "batch_siz": [4, 5, 14, 20, 26, 109, 118, 133, 142, 163, 170, 176, 192, 210, 246, 261, 266, 279, 325, 337, 389, 405, 449], "option": [4, 5, 14, 20, 26, 48, 50, 51, 52, 55, 58, 61, 74, 81, 83, 84, 87, 88, 89, 101, 102, 109, 111, 118, 133, 142, 163, 170, 176, 210, 246, 261, 266, 279, 325, 328, 337, 390, 405], "int": [4, 5, 14, 20, 26, 39, 45, 65, 77, 83, 84, 101, 102, 109, 111, 118, 133, 142, 163, 170, 176, 197, 210, 246, 261, 266, 279, 290, 291, 294, 325, 328, 337, 389, 390, 405, 435, 436, 438, 443, 450], "none": [4, 5, 14, 20, 26, 39, 51, 52, 55, 58, 74, 81, 101, 102, 109, 111, 118, 133, 142, 163, 170, 176, 191, 193, 195, 210, 211, 246, 261, 266, 279, 325, 328, 337, 389, 390, 396, 398, 399, 400, 401, 402, 403, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 426, 427, 428, 429, 430, 431, 432, 436], "parallel": [4, 5, 14, 26, 109, 118, 133, 142, 163, 170, 176, 210, 246, 261, 266, 279, 325, 337, 389, 405], "bool": [4, 5, 14, 26, 48, 49, 50, 51, 52, 58, 81, 83, 84, 87, 88, 89, 109, 111, 118, 133, 142, 163, 170, 176, 188, 210, 246, 261, 266, 279, 322, 325, 337, 389, 405], "fals": [4, 5, 14, 26, 49, 50, 51, 52, 58, 81, 84, 87, 88, 89, 109, 111, 118, 133, 142, 163, 170, 176, 187, 188, 194, 210, 246, 261, 266, 279, 295, 325, 337, 389, 405, 425, 431, 436, 438], "num_work": [4, 5, 14, 26, 109, 118, 133, 142, 163, 170, 176, 210, 246, 261, 266, 279, 325, 337, 389, 405], "evaluation_budget": [4, 5, 14, 26, 109, 118, 133, 142, 163, 170, 176, 210, 246, 261, 266, 279, 325, 337, 389, 405], "inf": [4, 5, 13, 14, 26, 109, 115, 118, 122, 125, 128, 133, 142, 149, 163, 170, 176, 210, 223, 226, 232, 235, 238, 241, 246, 250, 253, 261, 266, 279, 283, 286, 304, 325, 331, 334, 337, 341, 389, 405, 431, 438], "base": [4, 8, 18, 39, 64, 138, 204, 388, 391, 392, 394, 397, 422, 440, 441, 443, 446, 449, 450, 452, 454], "optim": [4, 6, 13, 21, 39, 80, 125, 146, 150, 242, 244, 245, 304, 305, 306, 324, 327, 331, 374, 388, 393, 394, 397, 400, 403, 405, 407, 408, 409, 410, 411, 412, 413, 414, 415, 418, 427, 428, 429, 435, 436, 441, 443, 449, 450, 451], "problem": [4, 7, 8, 11, 13, 14, 22, 23, 26, 28, 42, 72, 73, 109, 117, 118, 119, 133, 134, 143, 164, 177, 260, 265, 267, 268, 280, 287, 306, 324, 325, 335, 336, 337, 374, 391, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 429, 430, 431, 432, 436, 438, 439, 441, 443, 449, 450, 451], "paramet": [4, 5, 8, 14, 20, 23, 26, 45, 48, 49, 50, 51, 52, 55, 58, 59, 61, 64, 65, 74, 77, 81, 82, 83, 84, 85, 87, 88, 89, 101, 102, 109, 111, 118, 119, 133, 134, 142, 163, 164, 170, 176, 177, 210, 261, 266, 267, 279, 280, 325, 337, 390, 405], "The": [4, 5, 11, 14, 20, 21, 23, 25, 26, 39, 45, 55, 58, 59, 61, 64, 65, 74, 77, 80, 81, 83, 84, 85, 87, 88, 89, 109, 110, 111, 116, 117, 118, 119, 133, 138, 142, 162, 163, 169, 170, 175, 176, 204, 210, 242, 261, 266, 267, 270, 271, 274, 279, 301, 320, 321, 324, 325, 336, 337, 388, 390, 392, 394, 395, 397, 402, 403, 405, 407, 408, 409, 410, 425, 434, 435, 439, 440, 441, 446, 449, 452, 454], "setup": [8, 21, 22, 26, 55, 77, 119, 134, 143, 164, 177, 267, 280, 337, 405, 407], "inform": [4, 8, 11, 21, 22, 26, 39, 55, 77, 109, 111, 119, 132, 133, 134, 143, 164, 177, 256, 257, 267, 280, 328, 337, 388, 394, 396, 399, 400, 401, 402, 403, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 427, 429, 430, 432, 434, 436, 438, 440, 441, 450, 454], "provid": [20, 55, 107, 115, 143, 170, 238, 389, 392, 393, 394, 403, 405, 425, 436, 438, 439, 440, 443, 450], "detail": [82, 146, 394, 405, 434, 438], "about": [109, 111, 389, 392, 393, 397, 434, 438], "batch": [4, 5, 14, 20, 26, 109, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325, 337, 405], "size": [4, 5, 14, 20, 26, 45, 109, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325, 337, 405, 441, 444, 449], "evalu": [4, 5, 6, 14, 19, 20, 21, 26, 109, 111, 118, 133, 142, 146, 163, 170, 176, 210, 261, 266, 267, 279, 325, 337, 390, 391, 405, 408, 409, 435, 436, 439], "default": [4, 5, 14, 20, 26, 53, 55, 58, 61, 81, 83, 84, 87, 88, 89, 109, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325, 337, 389, 390, 396, 399, 400, 401, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 419, 423, 424, 427, 429, 430, 432, 442, 448], "flag": [4, 5, 14, 26, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325], "indic": [4, 5, 14, 26, 118, 133, 142, 163, 170, 176, 182, 183, 210, 261, 266, 279, 325, 390, 435], "whether": [4, 5, 11, 14, 21, 26, 58, 87, 88, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325, 337, 369, 381, 389, 394, 405, 420, 421, 425, 434, 436], "number": [4, 5, 14, 21, 26, 45, 65, 77, 99, 100, 101, 102, 109, 111, 118, 133, 142, 163, 170, 176, 210, 246, 261, 266, 279, 301, 325, 337, 390, 396, 397, 399, 400, 401, 402, 403, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 425, 427, 429, 430, 432, 435, 438, 446], "worker": [4, 5, 14, 26, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325, 337], "us": [4, 5, 6, 9, 11, 14, 21, 26, 39, 40, 51, 52, 55, 58, 60, 64, 65, 79, 80, 81, 109, 111, 115, 117, 118, 122, 125, 128, 133, 137, 138, 141, 142, 149, 163, 169, 170, 172, 176, 186, 187, 188, 210, 220, 223, 226, 229, 232, 235, 238, 241, 242, 244, 245, 246, 250, 253, 256, 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184, 189, 261, 266, 271, 274, 325, 389, 394, 403, 405], "observ": [4, 6, 28, 37, 38, 39, 40, 53, 54, 55, 72, 73, 74, 76, 77, 109, 111, 187, 390, 392], "record": [4, 301], "dure": [4, 77, 389, 428], "abstractobserv": [4, 74, 436], "observer_info": 4, "given": [4, 20, 51, 52, 65, 74, 81, 84, 89, 132, 133, 134, 170, 184, 185, 186, 301, 390, 391, 395, 396, 399, 402, 405, 406, 411, 412, 416, 417, 419, 424, 425, 432, 435], "after": [4, 39, 138, 389, 390, 394, 404, 407, 434, 435], "initi": [4, 5, 14, 20, 21, 23, 26, 39, 55, 64, 77, 81, 109, 111, 118, 133, 142, 163, 170, 176, 210, 261, 266, 279, 325, 337, 390, 394, 405, 434, 435, 438, 449], "set_observ": [4, 433, 436], "set": [4, 39, 64, 89, 138, 186, 188, 194, 200, 261, 266, 389, 390, 402, 405, 422, 425, 435, 436, 438], "reset_evaluation_budget": 4, "reset": [4, 111], "budget": [4, 17, 21, 26, 111, 405, 438], "made": 4, "0": [4, 81, 83, 163, 170, 176, 206, 265, 271, 274, 295, 318, 390, 391, 394, 395, 396, 398, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 435, 436, 438, 440, 441, 442, 443, 444, 446, 448, 450, 452, 454], "__call__": [4, 5, 6, 389], "x": [4, 5, 6, 20, 39, 55, 111, 118, 133, 137, 138, 170, 188, 193, 194, 261, 266, 307, 308, 309, 310, 311, 312, 313, 314, 316, 317, 318, 321, 322, 325, 337, 388, 389, 390, 391, 396, 398, 399, 400, 401, 402, 403, 404, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 426, 427, 428, 429, 430, 431, 432, 434, 435, 436, 442, 450], "context": [4, 6, 20, 39, 55, 111, 118, 133, 170, 261, 266, 325, 337, 389, 436], "input": [4, 20, 42, 44, 109, 118, 133, 170, 261, 266, 274, 325, 337, 389, 391, 392, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 426, 427, 428, 429, 430, 431, 432, 435, 440, 441, 442, 446, 448, 449, 450, 452, 454], "_black_box": [4, 5, 6, 20, 118, 133, 170, 261, 266, 325, 337, 389], "method": [4, 5, 6, 8, 9, 14, 20, 23, 26, 39, 55, 64, 81, 85, 89, 109, 118, 119, 133, 134, 142, 143, 163, 164, 170, 171, 176, 177, 180, 186, 197, 198, 199, 204, 205, 210, 211, 217, 246, 247, 261, 262, 266, 267, 279, 280, 325, 326, 328, 337, 338, 389, 390, 394, 405, 407, 408, 409, 434, 435, 436, 438], "termin": [4, 77, 436], "__enter__": 4, "enter": 4, "manag": [4, 58, 111], "__exit__": 4, "exc_typ": 4, "exc_val": 4, "exc_tb": 4, "exit": 4, "__del__": 4, "destructor": 4, "__neg__": 4, "creat": [4, 8, 21, 26, 58, 64, 72, 73, 74, 107, 111, 119, 134, 143, 164, 177, 267, 280, 287, 367, 369, 389, 390, 391, 392, 393, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 429, 430, 431, 432, 434, 436, 439, 440, 441, 443, 446, 449, 450, 451, 452, 453], "new": [4, 14, 142, 392, 394, 435, 438], "neg": [4, 208, 402, 409], "origin": [4, 5, 81, 82, 85, 179, 321, 394, 440, 441, 446, 450, 452, 454], "one": [4, 191, 294, 388, 389, 390, 392, 394, 395, 397, 407, 434, 435, 439, 448], "__init__": [4, 5, 8, 9, 14, 20, 23, 26, 39, 55, 64, 81, 118, 119, 133, 134, 142, 143, 163, 164, 170, 171, 176, 177, 180, 197, 198, 199, 204, 205, 210, 211, 217, 246, 247, 261, 262, 266, 267, 279, 280, 325, 326, 328, 337, 338, 390, 435, 436], "execut": [4, 5, 14, 60, 64, 74, 138, 142, 163, 170, 176, 210, 279, 325, 393, 404], "we": [4, 5, 14, 19, 26, 79, 85, 109, 115, 122, 125, 128, 137, 138, 142, 149, 162, 163, 169, 170, 175, 176, 187, 210, 220, 223, 226, 229, 232, 235, 238, 241, 242, 244, 245, 250, 253, 260, 261, 265, 266, 270, 283, 286, 304, 306, 320, 322, 324, 325, 331, 334, 341, 374, 378, 389, 390, 391, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 434, 435, 436, 438, 439, 440, 441, 442, 443, 444, 446, 448, 449, 450, 452, 454], "f": [5, 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407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 436, 438, 439, 440, 441, 443, 446, 448, 450, 452, 454], "you": [5, 6, 14, 81, 89, 115, 122, 125, 128, 137, 138, 142, 149, 220, 223, 226, 229, 232, 241, 250, 253, 261, 266, 279, 283, 286, 304, 306, 331, 334, 341, 389, 390, 391, 392, 393, 394, 395, 396, 398, 399, 400, 401, 402, 403, 405, 406, 407, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 434, 435, 436, 438, 439, 440, 441, 443, 446, 448, 450, 452, 454], "construct": [5, 205, 405], "maxim": [5, 128, 146, 301, 306, 321, 322, 390, 405, 428], "minim": [5, 306, 389, 390, 397, 402, 435, 449], "latter": [5, 394], "onli": [5, 6, 111, 179, 187, 196, 315, 319, 320, 325, 390, 391, 394, 395, 402, 407, 408, 409, 428, 435], "differ": [5, 25, 83, 162, 169, 175, 270, 389, 390, 391, 394, 395, 435, 436, 439, 440, 441, 443, 446, 450, 452], "return": [5, 8, 26, 48, 49, 50, 51, 52, 59, 61, 65, 74, 81, 83, 84, 85, 87, 88, 89, 109, 110, 111, 119, 134, 164, 170, 177, 184, 185, 186, 189, 191, 206, 207, 246, 260, 261, 265, 266, 267, 280, 293, 335, 336, 337, 389, 390, 398, 402, 405, 407, 408, 409, 420, 421, 425, 431, 434, 435], "instead": [5, 306, 390, 408, 409, 435, 446], "same": [5, 84, 85, 242, 244, 245, 246, 389, 391, 395, 414, 415], "factori": [7, 8, 25, 64, 107, 109, 111, 112, 116, 117, 119, 129, 132, 134, 143, 152, 153, 162, 164, 165, 169, 175, 177, 260, 265, 267, 270, 280, 301, 324, 336, 389, 392, 405], "defin": [8, 82, 268, 306, 374, 390, 428, 438, 439, 443, 450], "interfac": [8, 80, 107, 389, 392, 410, 413, 430, 439, 443, 446, 450], "instanc": [8, 14, 20, 119, 134, 142, 164, 177, 267, 280, 325, 389, 390, 391, 434, 439, 449], "get_setup_inform": [8, 119, 134, 143, 164, 177, 267, 280, 389, 405], "specifi": [8, 14, 58, 59, 109, 119, 134, 142, 164, 177, 185, 190, 198, 204, 267, 279, 280, 324, 394, 420, 421, 440, 449], "metaclass": 9, 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188, 205, 210, 246, 261, 266, 322, 389, 394, 408, 409, 431, 434, 436, 438], "kwargs_for_oracl": 14, "repres": [26, 65, 83, 88, 142, 204, 438], "It": [64, 65, 138, 389, 390, 391, 394, 402, 404, 435, 438, 440], "name": [11, 14, 15, 23, 55, 58, 59, 77, 87, 88, 89, 109, 111, 133, 142, 325, 328, 389, 390, 391, 394, 395, 407, 431, 434, 436, 438, 441, 443, 450], "comput": [25, 61, 81, 83, 85, 118, 133, 138, 162, 163, 169, 170, 172, 175, 176, 242, 244, 245, 258, 261, 266, 268, 270, 306, 388, 391, 392, 393, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 439, 440, 441, 443, 446, 448, 450, 452, 454], "dock": [132, 133, 134, 137, 138, 141, 142, 143, 388, 392, 397, 402, 439], "score": [132, 133, 134, 163, 170, 176, 388, 392, 395, 397, 402, 403, 404, 408, 409, 418, 422, 439], "an": [6, 13, 14, 15, 21, 25, 39, 42, 45, 48, 49, 50, 51, 52, 54, 55, 58, 65, 76, 77, 80, 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128, 133, 142, 238, 246, 260, 261, 265, 266, 279, 392, 396, 399, 400, 401, 403, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 420, 421, 423, 424, 427, 429, 430, 432], "format": [64, 82, 85, 184], "represent": [14, 47, 50, 133, 142, 256, 257, 261, 266, 279, 388, 395, 439], "dict": [14, 64, 109, 111, 118, 133, 389], "addit": [55, 64, 74, 109, 111, 146, 395, 405], "keyword": [14, 55, 64, 109, 111, 389, 408, 409], "argument": [14, 39, 55, 64, 109, 111, 408, 409], "custom": 16, "packag": [16, 18, 51, 52, 57, 434, 438, 439, 441], "rais": [17, 20, 48, 49, 51, 52, 58, 59, 65, 80, 83, 84, 390, 393, 405, 435], "when": [15, 17, 64, 109, 111, 115, 122, 125, 128, 137, 146, 149, 223, 226, 229, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 389, 395, 405, 411, 412, 424, 432, 436, 438, 439], "exhaust": 17, "multi_object": 19, "version": [19, 55, 81, 138, 242, 265, 267, 390, 391, 392, 393, 394, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 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183, 267, 274, 389, 390, 391, 392, 394, 397, 405, 408, 409, 431, 434, 435, 436, 452], "alphabet": [11, 22, 26, 118, 133, 389, 390, 405, 407, 431, 434, 435, 436, 438, 443, 449, 450, 451, 453], "sequenc": [11, 22, 80, 117, 118, 119, 146, 150, 182, 183, 184, 185, 189, 190, 191, 242, 244, 245, 388, 389, 390, 392, 394, 395, 396, 398, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 434, 435, 438, 440, 441, 443, 446, 448, 450, 452, 454], "length": [11, 22, 45, 83, 84, 193, 389, 394, 405, 443, 450], "max_sequence_length": [389, 431, 436, 438], "align": [11, 388, 389, 392, 431, 436, 438], "log_transform_recommend": [389, 431, 436], "s": [11, 21, 23, 26, 51, 52, 79, 80, 111, 138, 146, 163, 170, 176, 179, 256, 257, 260, 261, 265, 266, 267, 306, 320, 388, 391, 392, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 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253, 260, 277, 278, 283, 286, 304, 318, 331, 334, 341, 388, 405, 436], "m": [79, 137, 193, 256, 257, 388, 394, 395, 396, 398, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 436, 440, 441, 443, 446, 448, 450, 452, 454], "p": [79, 388, 405, 436], "v": [79, 81, 405, 436], "measur": [80, 115, 187, 238, 394, 420, 421], "stabil": [80, 81, 165, 169, 170, 172, 175, 256, 257, 268, 270, 388, 391, 392, 394, 397, 408, 439], "sasa": [80, 81, 158, 162, 163, 164, 172, 175, 176, 177, 268, 270, 392, 397, 408, 409], "foldxinterfac": 80, "queri": [80, 146, 389, 390, 395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 435], "heavili": [6, 80, 394], "inspir": [80, 394], "wai": [21, 80, 390, 391, 394, 405, 435, 436, 438, 439], "lambo": [80, 138, 150, 242, 244, 245, 246, 392, 394, 397, 408, 409, 434], "automat": [80, 111, 388, 389, 393], "acceler": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "bayesian": [80, 150, 242, 244, 245, 374, 388, 390, 392, 407, 408, 409, 418, 435, 441, 443, 450], "biolog": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "design": [13, 80, 115, 122, 125, 128, 132, 133, 134, 137, 149, 150, 204, 220, 223, 226, 229, 232, 235, 238, 241, 242, 244, 245, 250, 253, 283, 286, 304, 331, 334, 341, 388, 389, 390, 392, 393, 396, 397, 399, 400, 401, 402, 403, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 423, 424, 427, 429, 430, 432, 434, 435, 438], "withdenois": 80, "autoencod": [80, 150, 204, 242, 244, 245, 388, 407, 408, 409, 418, 440, 441, 442, 446, 452, 454], "stanton": [80, 146, 150, 242, 244, 245, 388, 393, 394, 405, 407, 408, 409, 418, 434], "samuel": [80, 150, 242, 244, 245, 388, 405, 407, 408, 409, 418, 450], "weslei": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "maddox": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "nate": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "gruver": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "phillip": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "maffetton": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "emili": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "delanei": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "peyton": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "greensid": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "andrew": [80, 150, 242, 244, 245, 388, 405, 407, 408, 409, 418], "gordon": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "wilson": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "arxiv": [13, 80, 146, 150, 242, 244, 245, 388, 405, 407, 408, 409, 418, 443, 446], "juli": [80, 150, 242, 244, 245, 388, 407, 408, 409, 410, 413, 418], "ab": [13, 80, 146, 150, 242, 244, 245, 388, 405, 407, 408, 409, 418, 443, 446], "2203": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "12742": [80, 150, 242, 244, 245, 388, 407, 408, 409, 418], "samuelstanton": [80, 138, 407], "working_dir": [81, 394], "interact": [81, 394], "engin": [81, 306, 428, 438, 442], "softwar": [81, 393, 395, 396, 398, 399, 400, 401, 402, 403, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 428, 429, 430, 431, 432, 440, 441, 443, 446, 448, 450, 452, 454], "where": [81, 117, 118, 119, 205, 389, 390, 392, 394, 425, 435, 439, 440, 441, 443, 446, 450, 452], "store": [81, 390, 395, 434, 439], "pdb_file": 81, "remove_and_renam": 81, "ph": [81, 394, 408, 409], "remove_heteroatom": 81, "_repair_if_necessary_and_provide_path": 81, "_simulate_mut": 81, "_read_energi": 81, "_compute_sasa": 81, "solvent": [81, 158, 163, 164, 172, 176, 177, 268, 388, 392, 394, 397], "surfac": [81, 158, 163, 164, 172, 176, 177, 268, 392, 394, 397, 408], "area": [81, 158, 163, 164, 172, 176, 177, 268, 392, 394, 397, 408], "compute_st": 81, "structur": [81, 87, 88, 89, 138, 170, 390, 394, 404, 436], "compute_sasa": 81, "compute_stability_and_sasa": 81, "singl": [81, 85, 256, 257, 306, 388, 392, 395, 397, 418, 420, 421, 428, 434, 436, 442, 448], "copy_foldx_fil": 81, "copi": [81, 389, 390, 394, 435, 449], "write_mutations_to_fil": 81, "wildtype_resiud": 81, "output_dir": 81, "write": [81, 138, 369, 389, 391, 394, 404, 433, 436, 437, 445, 447], "stdout": 81, "previou": [81, 394, 436], "reli": [81, 367, 428, 446, 452], "rotabas": [81, 393, 394, 407, 408, 409], "longer": 81, "manipul": [82, 389, 391, 392], "accord": [82, 186, 394, 438], "certain": [82, 128, 146, 304, 331, 392, 394, 401, 402, 405, 423, 452], "first": [82, 83, 85, 389, 390, 392, 394, 397, 398, 434, 435], "letter": [82, 85, 117, 118, 119, 392, 394, 397, 398], "second": [82, 83, 85, 196, 392, 394, 397], "posit": [82, 83, 85, 185, 190, 390, 394, 395, 434, 435, 438], "third": [82, 85], "chain": [82, 85, 394], "fourth": [82, 85], "mutant": [82, 84, 85, 256, 257, 390, 394, 435], "foldxsuit": [82, 393, 394], "crg": [82, 393, 394], "eu": [82, 393, 394], "string_1": 83, "string_2": 83, "edit": [83, 256, 257, 395], "oper": [83, 393], "assertionerror": 83, "abc": 83, "abd": 83, "def": [83, 389, 390, 435, 436], "wildtype_pdb_fil": [84, 408, 409], "mutated_residue_str": [84, 85], "return_hamming_dist": 84, "find": [84, 117, 118, 119, 138, 389, 395, 402, 404, 436, 438, 440, 441, 443, 446, 450, 452], "closest": 84, "ham": 84, "distanc": [84, 85, 118, 395, 398], "along": 84, "best": [84, 390, 434, 435, 444, 449], "candid": [84, 390, 438], "found": [84, 391, 394, 434, 438], "bio": [85, 88, 89, 394], "individual_list": [85, 394], "levenshtein": 85, "track": [85, 388, 436], "written": 85, "line": [85, 392, 394], "ea1r": 85, "still": [85, 439], "need": [11, 85, 138, 389, 390, 393, 394, 404, 407, 408, 409, 434, 436], "dummi": 85, "itself": [85, 389, 391], "ecd": 85, "acd": 85, "would": [85, 389, 390, 394, 395, 436], "ea1a": 85, "load": [86, 110, 179, 187, 196, 394, 436], "them": [86, 138, 374, 389, 390, 391, 394, 395, 397, 404, 435, 438, 443, 450], "path_to_pdb": [87, 88, 89], "structure_nam": [87, 88, 89], "done": [89, 138, 394, 407, 418, 438], "quietli": 89, "some": [89, 200, 246, 374, 390, 391, 392, 394, 407, 428, 436, 438], "get_structur": [89, 394], "pdbparser": [89, 394], "numpi": [101, 271, 292, 389, 391, 392, 396, 398, 399, 400, 401, 402, 403, 404, 406, 407, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 426, 427, 428, 429, 430, 431, 432, 436, 439, 440, 441, 442, 443, 446, 448, 449, 450, 451, 452, 453, 454], "obj": [], "dynam": 389, "intern": [388, 389, 410, 413, 422, 426, 448], "constructor": [], "factory_kwarg": [], "processwrapp": [], "how": [138, 389, 390, 391, 392, 394, 397, 434, 435, 436, 438], "objective_nam": [], "loop": [367, 388, 440, 441, 442, 446, 452, 454], "process_wrapp": [], "observer_init_info": 109, "force_regist": [], "force_isol": [4, 14, 109, 111, 133, 142, 163, 170, 176, 210, 246, 279, 389, 405], "instantiant": 109, "associ": [109, 388, 434, 439, 440, 454], "caller": [109, 111, 436], "forward": [109, 111, 436], "logger": [109, 111], "ask": 390, "confirm": [], "By": [109, 261, 266, 325, 389, 390, 405, 408, 409, 442, 448], "onc": [109, 389, 390, 425, 438], "round": [109, 337], "down": 109, "give": [109, 290, 374, 389], "config": [110, 369], "configpars": 110, "just": [53, 111, 389, 407, 434, 436], "One": [111, 393, 438, 448], "aloha": [111, 391, 392, 397, 434, 435, 438, 449], "arrai": [111, 182, 183, 192, 193, 289, 292, 294, 389, 391, 392, 396, 398, 399, 400, 401, 402, 403, 404, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 434, 436, 438, 439, 450], "reshap": [111, 390, 418, 420, 425, 440, 441, 442, 446, 448, 452, 454], "simpl": [117, 118, 119, 132, 133, 134, 186, 260, 261, 265, 266, 390, 434, 435, 438], "goal": [117, 118, 119, 301], "o": [117, 118, 119, 388, 396, 398, 399, 400, 401, 402, 403, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 427, 429, 430, 432, 436, 439, 446], "among": [115, 117, 118, 119, 393, 394], "poli__bas": [117, 324, 336], "yml": [117, 138, 324, 336, 390, 407, 440, 441, 443, 446, 450, 452], "simultan": [14, 118, 133, 142, 261, 266, 279, 395], "map": [118, 133], "symbol": [118, 133], "main": [6, 118, 261, 266, 390, 391, 392, 393, 394, 435, 436], "api": [132, 133, 134, 391, 407], "assess": [132, 133, 134, 256, 257, 392, 397], "small": [132, 133, 134, 261, 389, 391, 402, 403, 404, 422, 436, 438], "protein": [132, 133, 134, 146, 162, 169, 170, 175, 256, 257, 270, 388, 391, 393, 395, 402, 404, 405, 438, 439], "easi": [132, 133, 134, 146, 388, 394, 402, 405, 438], "molecular": [13, 115, 122, 125, 128, 132, 133, 134, 137, 149, 162, 169, 175, 223, 226, 232, 235, 238, 241, 250, 253, 270, 283, 286, 304, 331, 334, 341, 388, 396, 399, 400, 401, 402, 403, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 427, 429, 430, 432], "better": 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134, 388, 402, 448], "bender": [132, 133, 134, 388, 402], "sergio": [132, 133, 134, 388, 402], "bacallado": [132, 133, 134, 388, 402], "journal": [132, 133, 134, 137, 220, 229, 388, 395, 396, 399, 400, 401, 402, 403, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 427, 429, 430, 432], "62": [132, 133, 134, 388, 402], "15": [132, 133, 134, 388, 402, 412, 449], "august": [132, 133, 134, 388, 402], "3486": [132, 133, 134, 388, 402], "3502": [132, 133, 134, 388, 402], "1021": [13, 115, 122, 125, 128, 132, 133, 134, 149, 223, 226, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 388, 396, 399, 400, 401, 402, 406, 411, 412, 414, 415, 416, 417, 419, 423, 424, 427, 429, 430, 432], "ac": [13, 115, 122, 125, 128, 132, 133, 134, 149, 223, 226, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 388, 396, 399, 400, 401, 402, 406, 411, 412, 414, 415, 416, 417, 419, 423, 424, 425, 427, 429, 430, 432], "jcim": [13, 115, 122, 125, 128, 132, 133, 134, 149, 223, 226, 232, 235, 238, 241, 250, 253, 283, 286, 304, 331, 334, 341, 388, 396, 399, 400, 401, 402, 406, 411, 412, 414, 415, 416, 417, 419, 423, 424, 427, 429, 430, 432], "1c01334": [132, 133, 134, 388, 402], "target_nam": [133, 402, 439], "string_represent": [14, 133, 142, 246, 261, 266, 279, 396, 399, 400, 401, 403, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 420, 421, 423, 424, 427, 429, 430, 432, 443, 450], "liter": [14, 133, 142, 210, 246, 261, 266, 279, 328], "There": [138, 411, 412, 424, 432, 434, 436], "sever": [138, 306, 315, 324, 394, 395, 414, 415], "prepare_receptor": 138, "rest": [138, 436, 438], "descript": [138, 436], "show": [138, 391, 394, 434], "center": [138, 404], "websit": [138, 404], "scripp": 138, "edu": [138, 220, 229], "uncompress": [138, 404], "add": [138, 187, 290, 389, 390, 407, 408, 409, 418, 435, 450], "export": [138, 404], "autodock_vina": [138, 404], "bin": [138, 404], "bashrc": [138, 404], "zshrc": [138, 404], "bash": 138, 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253, 283, 286, 304, 331, 334, 341, 388, 394, 396, 399, 400, 401, 403, 406, 407, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 427, 429, 430, 432, 442], "git": [138, 389, 390, 391, 392, 407], "clone": [138, 391, 395, 407, 426, 440, 441, 443, 446, 450, 452], "431b052": [138, 407], "cd": [138, 391, 407], "particular": [138, 246, 268, 407, 428, 434, 436, 439], "proxy_rfp": [138, 407], "proxyrfptask": [138, 407], "rfp": [138, 150, 152, 153, 268, 392, 397], "asset": [138, 407], "fpbase": [138, 407], "And": [138, 434], "now": [138, 389, 391, 394], "py": [6, 93, 138, 328, 390, 391, 394, 434, 435, 436, 438, 439], "query_exampl": 138, "ddr3": [], "et": [13, 14, 115, 122, 125, 128, 137, 141, 146, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 271, 274, 277, 278, 283, 286, 304, 331, 334, 341, 388, 392, 393, 394, 395, 396, 397, 399, 400, 401, 402, 403, 404, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 422, 423, 424, 425, 427, 429, 430, 432, 434, 440, 441, 442, 443, 446, 448, 449, 450, 452, 454], "al": [13, 14, 115, 122, 125, 128, 137, 141, 146, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 271, 274, 277, 278, 283, 286, 304, 306, 328, 331, 334, 341, 388, 392, 393, 394, 395, 396, 397, 399, 400, 401, 402, 403, 404, 405, 406, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 422, 423, 424, 425, 427, 428, 429, 430, 432, 434, 440, 441, 442, 443, 446, 448, 449, 450, 452, 454], "nat": [13, 14, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "biol": [13, 14, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "1036": [13, 14, 115, 122, 125, 128, 137, 141, 149, 220, 223, 226, 229, 232, 235, 238, 241, 250, 253, 277, 278, 283, 286, 304, 331, 334, 341], "self": [14, 142, 389, 390, 395, 435, 436], "tdcblackbox": [], "denois": [150, 242, 244, 245, 388, 407, 408, 409, 418], "alia": [], 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"test_chemistry_object": 362, "test_foldx": 364, "test_foldx_rfp_lambo": 365, "test_rasp": 366, "test_basic_loop_without_cr": 367, "test_force_isol": 369, "test_passing_array_of_str": 372, "test_embedding_problems_into_higher_dim": [374, 375], "test_embed_camelback_into_high_dimens": 375, "test_instancing_of_toy_continuous_problem": 376, "test_minimal_working_exampl": [379, 380], "test_seed": [381, 382], "test_seeding_in_white_nois": 382, "test_foldx_interfac": 384, "test_protein_util": 385, "api": [387, 405], "document": 387, "refer": [388, 405, 440, 441, 443, 446, 448, 450, 452, 453, 454], "ad": [389, 390], "new": [389, 390], "problem": [21, 389, 390, 392, 397, 428, 434, 435], "repositori": 389, "The": [389, 436, 438], "structur": 389, "A": 389, "gener": 389, "py": 389, "yml": 389, "why": 389, "conda": [389, 391], "your": [389, 391, 438], "option": 439, "make": 404, "avail": [], "depend": [], "ar": [392, 394], "met": [], "submit": [389, 390], "pull": [389, 390], "request": [389, 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394, "energi": 394, "singl": 394, "python": [394, 407], "set": [394, 404], "up": 394, "folder": [394, 404], "download": [394, 404], "pdb": 394, "repair": [394, 408, 409], "what": [394, 435, 438, 439], "pars": 394, "wildtyp": 394, "defin": [394, 434, 435, 436], "s": [389, 394, 446], "sasa": [394, 407], "score": 394, "conclus": [394, 436, 438], "rapid": 395, "stabil": [395, 407, 409, 434], "predict": 395, "how": [395, 396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 437, 440, 441, 442, 443, 444, 446, 448, 449, 450, 451, 452, 453, 454], "warn": 395, "further": 395, "read": [395, 439], "all": [397, 404, 436], "about": [396, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 435, 440, 441, 442, 443, 444, 446, 448, 449, 450, 451, 452, 453, 454], "drd3": 404, "dock": [403, 404], "tdc": [396, 399, 400, 401, 403, 404, 406, 410, 411, 412, 413, 414, 415, 416, 417, 419, 422, 423, 424, 427, 429, 430, 432], "add": 404, "binari": 404, "path": 404, "prepare_receptor": 404, "from": [], "sure": 404, "you": [404, 408, 409], "re": 404, "rfp": 407, "lambo": [407, 418], "we": [392, 407, 408, 409], "can": [407, 408, 409], "automat": 407, "solvent": 408, "access": [408, 422], "penal": 418, "logp": [418, 420], "keyword": [], "argument": [], "log": [420, 436], "solubl": 420, "quantit": 421, "estim": 421, "druglik": 421, "qed": 421, "synthet": 422, "jump": 425, "super": 425, "mario": 425, "bro": 425, "therapeut": [], "data": [], "common": [], "oracl": [], "name": 426, "see": [426, 440, 441, 442, 446, 449, 452, 454], "also": 426, "continu": [392, 428], "low": 428, "intrins": 428, "dimension": 428, "white": 431, "nois": 431, "observ": [433, 436], "isol": [66, 67, 68, 69, 70, 433, 439], "process": 433, "random": [434, 451], "mroug": 434, "check": 434, "result": 434, "poli_baselin": 435, "candid": 435, "want": 436, "more": [436, 439, 440, 441, 442, 446, 449, 452, 454], "complex": 436, "instanc": [69, 436], "simpl": 436, "initi": 436, "put": 436, "togeth": 436, "coupl": 436, "queri": 436, "dive": 437, "deeper": 437, "doe": 437, "under": [437, 439], "hood": [437, 439], "content": [437, 438], "usual": 438, "develop": 438, "loop": 438, "identifi": 438, "own": 438, "when": [], "have": [], "right": [], "Is": [], "factori": [], "entir": [], "need": [], "where": [], "thi": 425, "call": [], "bayesian": [440, 442, 446, 447, 448, 452, 454], "cma": 444, "es": 444, "graph": 445, "genet": 445, "latent": 447, "space": 447, "line": 448, "nsga": 449, "2": [415, 449], "templat": 453, "abstract_isolated_funct": 6, "black_box_inform": 11, "tdc_isolated_funct": 15, "foldx_isolated_funct": 27, "external_black_box": 67, "external_funct": 68, "isolated_black_box": 70, "inform": [114, 121, 124, 127, 130, 136, 139, 145, 148, 151, 160, 167, 173, 201, 213, 219, 222, 225, 228, 231, 234, 237, 240, 243, 249, 252, 255, 259, 264, 269, 272, 276, 282, 285, 288, 303, 323, 330, 333, 340, 389, 431], "isolated_funct": [131, 140, 152, 161, 168, 174, 202, 214, 244, 256, 273, 277, 389], "test_instancing_black_boxes_alon": 370, "specifi": 389, "__init__": 389, "happen": 439, "test_black_box_instanc": 368, "test_multi_objective_and_neg": 371, "test_core_promis": 378, "cluster": 425, "albuterol_similar": [113, 114, 115], "amlodipine_mpo": [120, 121, 122], "celecoxib_rediscoveri": [123, 124, 125], "deco_hop": [126, 127, 128], "drd2_dock": [135, 136, 137], "fexofenadine_mpo": [147, 148, 149], "gsk3_beta": [218, 219, 220], "isomer_c7h8n2o2": [221, 222, 223], "isomer_c9h10n2o2pf2cl": [224, 225, 226], "jnk3": [227, 228, 229], "median_1": [230, 231, 232], "median_2": [233, 234, 235], "mestranol_similar": [236, 237, 238], "osimetrinib_mpo": [239, 240, 241], "perindopril_mpo": [248, 249, 250], "ranolazine_mpo": [251, 252, 253], "scaffold_hop": [281, 282, 283], "sitagliptin_mpo": [284, 285, 286], "thiothixene_rediscoveri": [302, 303, 304], "troglitazone_rediscoveri": [329, 330, 331], "valsartan_smart": [332, 333, 334], "zaleplon_mpo": [339, 340, 341], "albuterol": 396, "similar": [396, 416], "drd2": 403, "gsk3\u03b2": 410, "mestranol": 416, "celecoxib": 400, "rediscoveri": [400, 427, 429], "thiothixen": 427, "troglitazon": 429, "amlodipin": 399, "mpo": [399, 406, 417, 419, 424, 432], "fexofenadin": 406, "osimetrinib": 417, "ranolazin": 419, "sitagliptin": 424, "zaleplon": 432, "deco": 401, "hop": [401, 423], "scaffold": 423, "isom": [411, 412], "c7h8n2o2": 411, "c9h10n2o2pf2cl": 412, "median": [414, 415], "1": 414, "valsartan": 430, "smart": 430, "c": 413, "jun": 413, "n": 413, "termin": 413, "kinas": 413, "3": 413, "abstract_benchmark": 2, "benchmark_inform": 10, "benchmark": [344, 345, 392], "test_benchmark_cr": 345, "hvarfner": 446, "vanilla": 446, "spars": 452, "axi": 452, "subspac": [441, 452], "saasbo": 452, "multi_observ": 71, "alebo": 440, "adapt": [440, 441], "linear": 440, "embed": 440, "trust": 454, "region": 454, "turbo": 454, "expand": 441, "baxu": 441, "bounc": 443, "probabilist": 450, "reparametr": 450, "algorithm_observer_wrapp": 40, "default_observ": 53, "ehrlich": [144, 145, 146, 405], "rmf_landscap": [271, 272, 273, 274], "conftest": 346, "toy_discrete_problem": 377}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 6, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinxcontrib.bibtex": 9, "sphinx": 56}}) \ No newline at end of file diff --git a/using_poli/the_basics/defining_a_problem_solver.html b/using_poli/the_basics/defining_a_problem_solver.html index 0eb1a92e..087eaf20 100644 --- a/using_poli/the_basics/defining_a_problem_solver.html +++ b/using_poli/the_basics/defining_a_problem_solver.html @@ -840,7 +840,7 @@

    An example: Ran

    Our implementation of RandomMutation is slightly different, since we allow users to query e.g. integer indices instead of strings.

    Take a look at the exact implementation on poli_baselines/solvers/simple/random_mutation.py.

    -

    In the next chapter, we apply this solver to the aloha problem we defined in the first chapter.

    +

    In the next chapter, we apply this solver to the aloha problem we defined in the first chapter.

    diff --git a/using_poli/the_basics/defining_an_observer.html b/using_poli/the_basics/defining_an_observer.html index 1b883216..bfcd52af 100644 --- a/using_poli/the_basics/defining_an_observer.html +++ b/using_poli/the_basics/defining_an_observer.html @@ -753,7 +753,7 @@

    Defining an observerAn abstract observer#

    All observers inherit from an AbstractObserver (which you can find on poli/core/util/abstract_observer.py). The abstract methods you need to overwrite are:

      -

    • initialize_observer(problem_info: ProblemSetupInformation, caller_info: object, x0: np.ndarray, y0: np.ndarray, seed: int) -> object, which gets called as part of the set-up of the objective function (when objective_factory.create is called).

      • +

    • initialize_observer(problem_setup_info: BlackBoxInformation, caller_info: object, seed: int) -> object, which gets called as part of the set-up of the objective function (when objective_factory.create is called).

    • observe(x: np.ndarray, y: np.ndarray, context: object) -> None, which gets called every time your optimization algorithms query the objective function.

    • finish(), which gets called either by the user, or by the object deletion at the end of the script.

    @@ -776,8 +776,6 @@

    An instance: a simple observerself, problem_setup_info: ProblemSetupInformation, caller_info: object, - x0: np.ndarray, - y0: np.ndarray, seed: int ) -> object: ... @@ -802,7 +800,7 @@

    Initializing the observerimport numpy as np -from poli.core.problem_setup_information import ProblemSetupInformation +from poli.core.black_box_information import BlackBoxInformation from poli.core.util.abstract_observer import AbstractObserver THIS_DIR = Path().resolve() @@ -822,10 +820,8 @@

    Initializing the observerdef initialize_observer( self, - problem_setup_info: ProblemSetupInformation, + problem_setup_info: BlackBoxInformation, caller_info: object, - x0: np.ndarray, - y0: np.ndarray, seed: int ) -> object: @@ -838,8 +834,6 @@

    Initializing the observermetadata["caller_info"] = caller_info # Saving the initial evaluations and seed - metadata["x0"] = x0.tolist() - metadata["y0"] = y0.tolist() metadata["seed"] = seed # Saving the metadata @@ -925,8 +919,6 @@

    Putting it all togetherself, problem_setup_info: ProblemSetupInformation, caller_info: object, - x0: np.ndarray, - y0: np.ndarray, seed: int ) -> object: @@ -939,8 +931,6 @@

    Putting it all togethermetadata["caller_info"] = caller_info # Saving the initial evaluations and seed - metadata["x0"] = x0.tolist() - metadata["y0"] = y0.tolist() metadata["seed"] = seed # Saving the metadata @@ -962,7 +952,7 @@

    Putting it all togetherLogging a couple queries of aloha#

    Using the aloha toy problem, let’s check that our observer logic works as expected:

    -
    +
    from poli import objective_factory
 
 # We create an instance of the observer
@@ -974,21 +964,19 @@ 
    Logging a couple queries of observer=observer,
 )
 f, x0 = problem.black_box, problem.x0
+
+# We initialize the observer
+observer.initialize_observer(
+    problem_setup_info=f.info,
+    caller_info={},
+    seed=None,
+)
+
+# We set the observer to track f.
+f.set_observer(observer)
    -
    - - -Hide code cell output - -
    -
    poli 🧪: Creating the objective aloha from the repository.
-poli 🧪: initializing the observer.
-
    -
    -
    -

    At this point, the observer __init__ call created a folder called results right next to this file, and we can load up the metadata just to be sure:

    @@ -999,7 +987,7 @@

    Logging a couple queries of

    -
    {'name': 'aloha', 'max_sequence_length': 5, 'aligned': True, 'fixed_length': True, 'deterministic': True, 'discrete': True, 'fidelity': None, 'alphabet': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'], 'log_transform_recommended': False, 'padding_token': '', 'caller_info': None, 'x0': [['A', 'L', 'O', 'O', 'F']], 'y0': [[3]], 'seed': None}
+
    {'name': 'aloha', 'max_sequence_length': 5, 'aligned': True, 'fixed_length': True, 'deterministic': True, 'discrete': True, 'fidelity': None, 'alphabet': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'], 'log_transform_recommended': False, 'padding_token': '', 'caller_info': {}, 'seed': None}
    diff --git a/using_poli/the_basics/intro_to_poli.html b/using_poli/the_basics/intro_to_poli.html index d6ef2f52..88960936 100644 --- a/using_poli/the_basics/intro_to_poli.html +++ b/using_poli/the_basics/intro_to_poli.html @@ -758,9 +758,9 @@

    What is poli?

    -

    poli is a library for creating and calling black box optimization functions, with a special focus on discrete sequence optimization. It stands for Protein Objectives Library, since some of the work done on drug design is done through representing proteins and small molecules as discrete sequences.

    +

    poli is a library for creating and calling black box objective functions, with a special focus on discrete sequence optimization. It stands for Protein Objectives Library, since some of the work done on drug design and protein engineering is done through representing proteins and small molecules as discrete sequences.

    We also build poli-baselines on top, allowing you to define black box optimization algorithms for discrete sequences.

    -

    These next chapters detail a basic example of how to use poli and poli-baselines. If you want to start coding now, continue to the next chapter!

    +

    These next chapters detail a basic example of how to use poli and poli-baselines.

    The rest of this intro details the usual development loops we assume you’ll follow when using poli and poli-baselines:

    The usual development loop#

    @@ -778,7 +778,7 @@

    Identify the objective function

    -
    ['aloha', 'dockstring', 'drd3_docking', 'foldx_rfp_lambo', 'foldx_sasa', 'foldx_stability', 'foldx_stability_and_sasa', 'gfp_cbas', 'gfp_select', 'penalized_logp_lambo', 'rasp', 'rdkit_logp', 'rdkit_qed', 'rfp_foldx_stability_and_sasa', 'sa_tdc', 'super_mario_bros', 'white_noise', 'toy_continuous_problem']
+
    ['albuterol_similarity', 'aloha', 'amlodipine_mpo', 'celecoxib_rediscovery', 'deco_hop', 'dockstring', 'drd2_docking', 'drd3_docking', 'ehrlich', 'fexofenadine_mpo', 'foldx_rfp_lambo', 'foldx_sasa', 'foldx_stability', 'foldx_stability_and_sasa', 'gfp_cbas', 'gfp_select', 'gsk3_beta', 'isomer_c7h8n2o2', 'isomer_c9h10n2o2pf2cl', 'jnk3', 'median_1', 'median_2', 'mestranol_similarity', 'osimetrinib_mpo', 'penalized_logp_lambo', 'perindopril_mpo', 'ranolazine_mpo', 'rasp', 'rdkit_logp', 'rdkit_qed', 'rfp_foldx_stability_and_sasa', 'rmf_landscape', 'sa_tdc', 'scaffold_hop', 'sitagliptin_mpo', 'super_mario_bros', 'thiothixene_rediscovery', 'toy_continuous_problem', 'troglitazone_rediscovery', 'valsartan_smarts', 'white_noise', 'zaleplon_mpo']
    @@ -786,7 +786,7 @@

    Identify the objective functionThe output is a list of problems you may be able to run.

    Note

    -

    Some objective functions have more requirements, like installing external dependencies. Check the page on all objective functions and click on the objective function you are interested in to get a detailed set of instructions on how to install and run it.

    +

    Most black box functions run out-of-the-box, but some have more requirements, like installing external dependencies. Check the page on all objective functions and click on the objective function you are interested in to get a detailed set of instructions on how to install and run it.

    In what follows, we will use the white_noise objective function. You could drop-in another function if desired.

    @@ -804,11 +804,6 @@

    Identify the objective function

    -
    -
    poli 🧪: Creating the objective white_noise from the repository.
-
    -
    -

    At this point, you can call f on arrays of shape [b, L]. In the specific case of white_noise, L can be any positive integer.

    @@ -839,38 +834,28 @@

    Using a solver, or creating your own< 
    x0: [['1' '2' '3']]
-y0: [[1.08390547]]
-
    -
    - - -

    Solvers implement a next_candidate() method, based on their history:

    -
    -
    -
    solver.next_candidate()
-
    -
    -
    -
    -
    array([['4', '2', '3']], dtype='<U1')
+y0: [[-0.47139683]]
    -

    RandomMutation simply selects one token at random from the alphabet:

    +

    Solvers implement a solve(max_iter: int) method, which runs the optimization for the provided budget.

    +

    In the specific example of RandomMutation, each step proposes a new candidate by choosing an element from the alphabet at random, and mutating a random position. This alphabet is part of the black box information:

    -
    solver.alphabet  # It's the same as f.info.alphabet
+
    print(f.info)
+print(f.info.alphabet)
    -
    ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
+
    BlackBoxInformation(name=white_noise, max_sequence_length=inf, aligned=False, fixed_length=False, discrete=True)
+['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
    -

    If you are interested in building your own solver, check out the chapter detailing how RandomMutation is implemented.

    +

    If you are interested in building your own solver, check out the chapter detailing how RandomMutation is implemented or our guide for contributing a new solver.

    Optimizing#

    @@ -889,7 +874,7 @@

    Optimizing

    -
    [['1' '5' '3']]
+
    [['7' '3' '3']]