gemseo / algos

# driver_lib module¶

## Driver library¶

A driver library aims to solve an OptimizationProblem using a particular algorithm from a particular family of numerical methods. This algorithm will be in charge of evaluating the objective and constraints functions at different points of the design space, using the DriverLib.execute() method. The most famous kinds of numerical methods to solve an optimization problem are optimization algorithms and design of experiments (DOE). A DOE driver browses the design space agnostically, i.e. without taking into account the function evaluations. On the contrary, an optimization algorithm uses this information to make the journey through design space as relevant as possible in order to reach as soon as possible the optimum. These families are implemented in DOELibrary and OptimizationLibrary.

Classes:

 Abstract class for DOE & optimization libraries interfaces. ProgressBar(*_, **__) Extend tqdm progress bar with better time units. TqdmToLogger([initial_value, newline]) Redirect tqdm output to the gemseo logger.
class gemseo.algos.driver_lib.DriverLib[source]

Abstract class for DOE & optimization libraries interfaces.

Lists available methods in the library for the proposed problem to be solved.

To integrate an optimization package, inherit from this class and put your file in gemseo.algos.doe or gemseo.algo.opt packages.

Constructor.

Attributes:

Methods:

 Deactivate the progress bar. driver_has_option(option_key) Check if the option key exists. ensure_bounds(orig_func[, normalize]) Project the design vector onto the design space before execution. execute(problem[, algo_name]) Executes the driver. filter_adapted_algorithms(problem) Filter the algorithms capable of solving the problem. Finalize the iteration observer. get_optimum_from_database([message, status]) Retrieves the optimum from the database and builds an optimization result object from it. get_x0_and_bounds_vects(normalize_ds) Gets x0, bounds, normalized or not depending on algo options, all as numpy arrays. init_iter_observer(max_iter, message) Initialize the iteration observer. init_options_grammar(algo_name) Initialize the options grammar. is_algo_requires_grad(algo_name) Returns True if the algorithm requires a gradient evaluation. is_algorithm_suited(algo_dict, problem) Check if the algorithm is suited to the problem according to algo_dict. new_iteration_callback([x_vect]) Callback called at each new iteration, i.e. every time a design vector that is not already in the database is proposed by the optimizer.
COMPLEX_STEP_METHOD = 'complex_step'
DESCRIPTION = 'description'
DIFFERENTIATION_METHODS = ['user', 'complex_step', 'finite_differences']
EQ_TOLERANCE = 'eq_tolerance'
FINITE_DIFF_METHOD = 'finite_differences'
HANDLE_EQ_CONS = 'handle_equality_constraints'
HANDLE_INEQ_CONS = 'handle_inequality_constraints'
INEQ_TOLERANCE = 'ineq_tolerance'
INTERNAL_NAME = 'internal_algo_name'
LIB = 'lib'
MAX_DS_SIZE_PRINT = 40
MAX_TIME = 'max_time'
NORMALIZE_DESIGN_SPACE_OPTION = 'normalize_design_space'
OPTIONS_DIR = 'options'
OPTIONS_MAP = {}
POSITIVE_CONSTRAINTS = 'positive_constraints'
PROBLEM_TYPE = 'problem_type'
ROUND_INTS_OPTION = 'round_ints'
USE_DATABASE_OPTION = 'use_database'
WEBSITE = 'website'
property algorithms

The available algorithms.

deactivate_progress_bar()[source]

Deactivate the progress bar.

Return type

None

driver_has_option(option_key)

Check if the option key exists.

Parameters

option_key (str) – The name of the option.

Returns

Whether the option is in the grammar.

Return type

bool

ensure_bounds(orig_func, normalize=True)[source]

Project the design vector onto the design space before execution.

Parameters
• orig_func – the original function

• normalize

if True, use the normalized design space

By default it is set to True.

Returns

the wrapped function

execute(problem, algo_name=None, **options)[source]

Executes the driver.

Parameters
• problem – the problem to be solved

• algo_name

name of the algorithm if None, use self.algo_name which may have been set by the factory (Default value = None)

By default it is set to None.

• options – the options dict for the algorithm

Filter the algorithms capable of solving the problem.

Parameters

problem (Any) – The opt_problem to be solved.

Returns

The list of adapted algorithms names.

Return type

bool

finalize_iter_observer()[source]

Finalize the iteration observer.

Return type

None

get_optimum_from_database(message=None, status=None)[source]

Retrieves the optimum from the database and builds an optimization result object from it.

Parameters
• message

Default value = None)

By default it is set to None.

• status

Default value = None)

By default it is set to None.

get_x0_and_bounds_vects(normalize_ds)[source]

Gets x0, bounds, normalized or not depending on algo options, all as numpy arrays.

Parameters

normalize_ds – if True, normalizes all input vars that are not integers, according to design space normalization policy

Returns

x, lower bounds, upper bounds

init_iter_observer(max_iter, message)[source]

Initialize the iteration observer.

It will handle the stopping criterion and the logging of the progress bar.

Parameters
• max_iter (int) – The maximum number of iterations.

• message (str) – The message to display at the beginning.

Raises

ValueError – If the max_iter is not greater than or equal to one.

Return type

None

init_options_grammar(algo_name)

Initialize the options grammar.

Parameters

algo_name (str) – The name of the algorithm.

Return type

gemseo.core.grammars.json_grammar.JSONGrammar

Returns True if the algorithm requires a gradient evaluation.

Parameters

algo_name – name of the algorithm

static is_algorithm_suited(algo_dict, problem)

Check if the algorithm is suited to the problem according to algo_dict.

Parameters
• algo_dict (Mapping[str, bool]) – the algorithm characteristics

• problem (Any) – the opt_problem to be solved

Return type

bool

new_iteration_callback(x_vect=None)[source]

Callback called at each new iteration, i.e. every time a design vector that is not already in the database is proposed by the optimizer.

Iterate the progress bar, implement the stop criteria.

Parameters

x_vect (Optional[numpy.ndarray]) –

The design variables values. If None, use the values of the last iteration.

By default it is set to None.

Raises

MaxTimeReached – If the elapsed time is greater than the maximum execution time.

Return type

None

class gemseo.algos.driver_lib.ProgressBar(*_, **__)[source]

Bases: tqdm.std.tqdm

Extend tqdm progress bar with better time units.

Use hour, day or week for slower processes.

Parameters
• iterable (iterable, optional) – Iterable to decorate with a progressbar. Leave blank to manually manage the updates.

• desc (str, optional) – Prefix for the progressbar.

• total (int or float, optional) – The number of expected iterations. If unspecified, len(iterable) is used if possible. If float(“inf”) or as a last resort, only basic progress statistics are displayed (no ETA, no progressbar). If gui is True and this parameter needs subsequent updating, specify an initial arbitrary large positive number, e.g. 9e9.

• leave (bool, optional) – If [default: True], keeps all traces of the progressbar upon termination of iteration. If None, will leave only if position is 0.

• file (io.TextIOWrapper or io.StringIO, optional) – Specifies where to output the progress messages (default: sys.stderr). Uses file.write(str) and file.flush() methods. For encoding, see write_bytes.

• ncols (int, optional) – The width of the entire output message. If specified, dynamically resizes the progressbar to stay within this bound. If unspecified, attempts to use environment width. The fallback is a meter width of 10 and no limit for the counter and statistics. If 0, will not print any meter (only stats).

• mininterval (float, optional) – Minimum progress display update interval [default: 0.1] seconds.

• maxinterval (float, optional) – Maximum progress display update interval [default: 10] seconds. Automatically adjusts miniters to correspond to mininterval after long display update lag. Only works if dynamic_miniters or monitor thread is enabled.

• miniters (int or float, optional) – Minimum progress display update interval, in iterations. If 0 and dynamic_miniters, will automatically adjust to equal mininterval (more CPU efficient, good for tight loops). If > 0, will skip display of specified number of iterations. Tweak this and mininterval to get very efficient loops. If your progress is erratic with both fast and slow iterations (network, skipping items, etc) you should set miniters=1.

• ascii (bool or str, optional) – If unspecified or False, use unicode (smooth blocks) to fill the meter. The fallback is to use ASCII characters ” 123456789#”.

• disable (bool, optional) – Whether to disable the entire progressbar wrapper [default: False]. If set to None, disable on non-TTY.

• unit (str, optional) – String that will be used to define the unit of each iteration [default: it].

• unit_scale (bool or int or float, optional) – If 1 or True, the number of iterations will be reduced/scaled automatically and a metric prefix following the International System of Units standard will be added (kilo, mega, etc.) [default: False]. If any other non-zero number, will scale total and n.

• dynamic_ncols (bool, optional) – If set, constantly alters ncols and nrows to the environment (allowing for window resizes) [default: False].

• smoothing (float, optional) – Exponential moving average smoothing factor for speed estimates (ignored in GUI mode). Ranges from 0 (average speed) to 1 (current/instantaneous speed) [default: 0.3].

• bar_format (str, optional) –

Specify a custom bar string formatting. May impact performance. [default: ‘{l_bar}{bar}{r_bar}’], where l_bar=’{desc}: {percentage:3.0f}%|’ and r_bar=’| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, ‘

’{rate_fmt}{postfix}]’

Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,

percentage, elapsed, elapsed_s, ncols, nrows, desc, unit, rate, rate_fmt, rate_noinv, rate_noinv_fmt, rate_inv, rate_inv_fmt, postfix, unit_divisor, remaining, remaining_s, eta.

Note that a trailing “: ” is automatically removed after {desc} if the latter is empty.

• initial (int or float, optional) – The initial counter value. Useful when restarting a progress bar [default: 0]. If using float, consider specifying {n:.3f} or similar in bar_format, or specifying unit_scale.

• position (int, optional) – Specify the line offset to print this bar (starting from 0) Automatic if unspecified. Useful to manage multiple bars at once (eg, from threads).

• postfix (dict or *, optional) – Specify additional stats to display at the end of the bar. Calls set_postfix(**postfix) if possible (dict).

• unit_divisor (float, optional) – [default: 1000], ignored unless unit_scale is True.

• write_bytes (bool, optional) – If (default: None) and file is unspecified, bytes will be written in Python 2. If True will also write bytes. In all other cases will default to unicode.

• lock_args (tuple, optional) – Passed to refresh for intermediate output (initialisation, iterating, and updating).

• nrows (int, optional) – The screen height. If specified, hides nested bars outside this bound. If unspecified, attempts to use environment height. The fallback is 20.

• colour (str, optional) – Bar colour (e.g. ‘green’, ‘#00ff00’).

• delay (float, optional) – Don’t display until [default: 0] seconds have elapsed.

• gui (bool, optional) – WARNING: internal parameter - do not use. Use tqdm.gui.tqdm(…) instead. If set, will attempt to use matplotlib animations for a graphical output [default: False].

Returns

out

Return type

decorated iterator.

Methods:

 clear([nolock]) Clear current bar display. Cleanup and (if leave=False) close the progressbar. display([msg, pos]) Use self.sp to display msg in the specified pos. external_write_mode([file, nolock]) Disable tqdm within context and refresh tqdm when exits. Formats a number of seconds as a clock time, [H:]MM:SS format_meter(n, total, elapsed, **kwargs) Intelligent scientific notation (.3g). format_sizeof(num[, suffix, divisor]) Formats a number (greater than unity) with SI Order of Magnitude prefixes. Get the global lock. pandas(**tqdm_kwargs) Registers the current tqdm class with refresh([nolock, lock_args]) Force refresh the display of this bar. reset([total]) Resets to 0 iterations for repeated use. set_description([desc, refresh]) Set/modify description of the progress bar. set_description_str([desc, refresh]) Set/modify description without ': ' appended. set_lock(lock) Set the global lock. set_postfix([ordered_dict, refresh]) Set/modify postfix (additional stats) with automatic formatting based on datatype. set_postfix_str([s, refresh]) Postfix without dictionary expansion, similar to prefix handling. status_printer(file) Overload the status_printer method to avoid the use of closures. Restart tqdm timer from last print time. update([n]) Manually update the progress bar, useful for streams such as reading files. wrapattr(stream, method[, total, bytes]) stream : file-like object. method : str, "read" or "write". The result of read() and the first argument of write() should have a len(). write(s[, file, end, nolock]) Print a message via tqdm (without overlap with bars).

Attributes:

 format_dict Public API for read-only member access. monitor monitor_interval
clear(nolock=False)

Clear current bar display.

close()

Cleanup and (if leave=False) close the progressbar.

display(msg=None, pos=None)

Use self.sp to display msg in the specified pos.

Parameters
• msg (str, optional. What to display (default: repr(self)).) – By default it is set to None.

• pos (int, optional. Position to moveto) –

(default: abs(self.pos)).

By default it is set to None.

classmethod external_write_mode(file=None, nolock=False)

Disable tqdm within context and refresh tqdm when exits. Useful when writing to standard output stream

property format_dict

Public API for read-only member access.

static format_interval(t)

Formats a number of seconds as a clock time, [H:]MM:SS

Parameters

t (int) – Number of seconds.

Returns

out – [H:]MM:SS

Return type

str

classmethod format_meter(n, total, elapsed, **kwargs)[source]
static format_num(n)

Intelligent scientific notation (.3g).

Parameters

n (int or float or Numeric) – A Number.

Returns

out – Formatted number.

Return type

str

static format_sizeof(num, suffix='', divisor=1000)

Formats a number (greater than unity) with SI Order of Magnitude prefixes.

Parameters
• num (float) – Number ( >= 1) to format.

• suffix (str, optional) –

Post-postfix [default: ‘’].

By default it is set to .

• divisor (float, optional) –

Divisor between prefixes [default: 1000].

By default it is set to 1000.

Returns

out – Number with Order of Magnitude SI unit postfix.

Return type

str

classmethod get_lock()

Get the global lock. Construct it if it does not exist.

monitor = <TMonitor(Thread-2, started daemon 140426366244608)>
monitor_interval = 10
moveto(n)
classmethod pandas(**tqdm_kwargs)
Registers the current tqdm class with

pandas.core. ( frame.DataFrame | series.Series | groupby.(generic.)DataFrameGroupBy | groupby.(generic.)SeriesGroupBy ).progress_apply

A new instance will be create every time progress_apply is called, and each instance will automatically close() upon completion.

Parameters

tqdm_kwargs (arguments for the tqdm instance) –

Examples

>>> import pandas as pd
>>> import numpy as np
>>> from tqdm import tqdm
>>> from tqdm.gui import tqdm as tqdm_gui
>>>
>>> df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))
>>> tqdm.pandas(ncols=50)  # can use tqdm_gui, optional kwargs, etc
>>> # Now you can use progress_apply instead of apply
>>> df.groupby(0).progress_apply(lambda x: x**2)


References

<https://stackoverflow.com/questions/18603270/ progress-indicator-during-pandas-operations-python>

refresh(nolock=False, lock_args=None)

Force refresh the display of this bar.

Parameters
• nolock (bool, optional) –

If True, does not lock. If [default: False]: calls acquire() on internal lock.

By default it is set to False.

• lock_args (tuple, optional) –

Passed to internal lock’s acquire(). If specified, will only display() if acquire() returns True.

By default it is set to None.

reset(total=None)

Resets to 0 iterations for repeated use.

Consider combining with leave=True.

Parameters

total (int or float, optional. Total to use for the new bar.) – By default it is set to None.

set_description(desc=None, refresh=True)

Set/modify description of the progress bar.

Parameters
• desc (str, optional) – By default it is set to None.

• refresh (bool, optional) –

Forces refresh [default: True].

By default it is set to True.

set_description_str(desc=None, refresh=True)

Set/modify description without ‘: ‘ appended.

classmethod set_lock(lock)

Set the global lock.

set_postfix(ordered_dict=None, refresh=True, **kwargs)

Set/modify postfix (additional stats) with automatic formatting based on datatype.

Parameters
• ordered_dict (dict or OrderedDict, optional) – By default it is set to None.

• refresh (bool, optional) –

Forces refresh [default: True].

By default it is set to True.

• kwargs (dict, optional) –

set_postfix_str(s='', refresh=True)

Postfix without dictionary expansion, similar to prefix handling.

status_printer(file)[source]

Overload the status_printer method to avoid the use of closures.

Parameters

file (Union[_io.TextIOWrapper, _io.StringIO]) – Specifies where to output the progress messages.

Returns

The function to print the status in the progress bar.

Return type

Callable[[str], None]

unpause()

Restart tqdm timer from last print time.

update(n=1)

Manually update the progress bar, useful for streams such as reading files. E.g.: >>> t = tqdm(total=filesize) # Initialise >>> for current_buffer in stream: … … … t.update(len(current_buffer)) >>> t.close() The last line is highly recommended, but possibly not necessary if t.update() will be called in such a way that filesize will be exactly reached and printed.

Parameters

n (int or float, optional) –

Increment to add to the internal counter of iterations [default: 1]. If using float, consider specifying {n:.3f} or similar in bar_format, or specifying unit_scale.

By default it is set to 1.

Returns

out – True if a display() was triggered.

Return type

bool or None

classmethod wrapattr(stream, method, total=None, bytes=True, **tqdm_kwargs)

stream : file-like object. method : str, “read” or “write”. The result of read() and

the first argument of write() should have a len().

>>> with tqdm.wrapattr(file_obj, "read", total=file_obj.size) as fobj:
...     while True:
...         if not chunk:
...             break

classmethod write(s, file=None, end='\n', nolock=False)

Print a message via tqdm (without overlap with bars).

class gemseo.algos.driver_lib.TqdmToLogger(initial_value='', newline='\n')[source]

Bases: _io.StringIO

Redirect tqdm output to the gemseo logger.

Methods:

 Close the IO object. detach Separate the underlying buffer from the TextIOBase and return it. Returns underlying file descriptor if one exists. Flush write buffers, if applicable. Retrieve the entire contents of the object. Return whether this is an 'interactive' stream. read([size]) Read at most size characters, returned as a string. Returns True if the IO object can be read. readline([size]) Read until newline or EOF. readlines([hint]) Return a list of lines from the stream. seek(pos[, whence]) Change stream position. Returns True if the IO object can be seeked. Tell the current file position. truncate([pos]) Truncate size to pos. Returns True if the IO object can be written. write(buf) Write buffer. writelines(lines, /) Write a list of lines to stream.

Attributes:

 closed encoding Encoding of the text stream. errors The error setting of the decoder or encoder. line_buffering newlines
close()

Close the IO object.

Attempting any further operation after the object is closed will raise a ValueError.

This method has no effect if the file is already closed.

closed
detach()

Separate the underlying buffer from the TextIOBase and return it.

After the underlying buffer has been detached, the TextIO is in an unusable state.

encoding

Encoding of the text stream.

Subclasses should override.

errors

The error setting of the decoder or encoder.

Subclasses should override.

fileno()

Returns underlying file descriptor if one exists.

OSError is raised if the IO object does not use a file descriptor.

flush()

Flush write buffers, if applicable.

This is not implemented for read-only and non-blocking streams.

getvalue()

Retrieve the entire contents of the object.

isatty()

Return whether this is an ‘interactive’ stream.

Return False if it can’t be determined.

line_buffering
newlines

Read at most size characters, returned as a string.

If the argument is negative or omitted, read until EOF is reached. Return an empty string at EOF.

Returns True if the IO object can be read.

Returns an empty string if EOF is hit immediately.

Return a list of lines from the stream.

hint can be specified to control the number of lines read: no more lines will be read if the total size (in bytes/characters) of all lines so far exceeds hint.

seek(pos, whence=0, /)

Change stream position.

Seek to character offset pos relative to position indicated by whence:

0 Start of stream (the default). pos should be >= 0; 1 Current position - pos must be 0; 2 End of stream - pos must be 0.

Returns the new absolute position.

seekable()

Returns True if the IO object can be seeked.

tell()

Tell the current file position.

truncate(pos=None, /)

Truncate size to pos.

The pos argument defaults to the current file position, as returned by tell(). The current file position is unchanged. Returns the new absolute position.

writable()

Returns True if the IO object can be written.

write(buf)[source]

Write buffer.

writelines(lines, /)

Write a list of lines to stream.

Line separators are not added, so it is usual for each of the lines provided to have a line separator at the end.