Source code for cmdstanpy.utils

"""
Utility functions
"""
import logging
import math
import os
import platform
import re
import shutil
import subprocess
import sys
import tempfile
from collections import OrderedDict
from collections.abc import Sequence
from numbers import Integral, Real
from typing import Dict, List, TextIO, Tuple, Union

import numpy as np
import pandas as pd
import ujson as json

from cmdstanpy import (
    _CMDSTAN_SAMPLING,
    _CMDSTAN_THIN,
    _CMDSTAN_WARMUP,
    _DOT_CMDSTAN,
    _DOT_CMDSTANPY,
    _TMPDIR,
)

EXTENSION = '.exe' if platform.system() == 'Windows' else ''


def get_logger():
    """cmdstanpy logger"""
    logger = logging.getLogger('cmdstanpy')
    if len(logger.handlers) == 0:
        logging.basicConfig(level=logging.INFO)
    return logger


def validate_dir(install_dir: str):
    """Check that specified install directory exists, can write."""
    if not os.path.exists(install_dir):
        try:
            os.makedirs(install_dir)
        except (IOError, OSError, PermissionError) as e:
            raise ValueError(
                'Cannot create directory: {}'.format(install_dir)
            ) from e
    else:
        if not os.path.isdir(install_dir):
            raise ValueError(
                'File exists, should be a directory: {}'.format(install_dir)
            )
        try:
            with open('tmp_test_w', 'w'):
                pass
            os.remove('tmp_test_w')  # cleanup
        except OSError as e:
            raise ValueError(
                'Cannot write files to directory {}'.format(install_dir)
            ) from e


def get_latest_cmdstan(cmdstan_dir: str) -> str:
    """
    Given a valid directory path, find all installed CmdStan versions
    and return highest (i.e., latest) version number.
    Assumes directory populated via script `install_cmdstan`.
    """
    versions = [
        ''.join(name.split('-')[1:])  # name may contain '-rc'
        for name in os.listdir(cmdstan_dir)
        if os.path.isdir(os.path.join(cmdstan_dir, name))
        and name.startswith('cmdstan-')
        and name[8].isdigit()
    ]
    # munge rc for sort, e.g. 2.25.0-rc1 -> 2.25.0.-99
    for i in range(len(versions)):  # # pylint: disable=C0200
        tmp = versions[i].split('rc')
        if len(tmp) == 1:
            versions[i] = '.'.join([tmp[0], '0'])
        else:
            rc_sortable = str(int(tmp[1]) - 100)
            versions[i] = '.'.join([tmp[0], rc_sortable])

    versions.sort(key=lambda s: list(map(int, s.split('.'))))
    if len(versions) == 0:
        return None
    latest = 'cmdstan-{}'.format(versions[len(versions) - 1])

    # unmunge
    tmp = latest.split('.')
    prefix = '.'.join(tmp[0:3])
    if int(tmp[3]) == 0:
        latest = prefix
    else:
        tmp[3] = 'rc' + str(int(tmp[3]) + 100)
        latest = '-'.join([prefix, tmp[3]])
    return latest


def validate_cmdstan_path(path: str) -> None:
    """
    Validate that CmdStan directory exists and binaries have been built.
    Throws exception if specified path is invalid.
    """
    if not os.path.isdir(path):
        raise ValueError('no such CmdStan directory {}'.format(path))
    if not os.path.exists(os.path.join(path, 'bin', 'stanc' + EXTENSION)):
        raise ValueError(
            'no CmdStan binaries found, '
            'run command line script "install_cmdstan"'
        )


[docs]def set_cmdstan_path(path: str) -> None: """ Validate, then set CmdStan directory path. """ validate_cmdstan_path(path) os.environ['CMDSTAN'] = path
[docs]def set_make_env(make: str) -> None: """ set MAKE environmental variable. """ os.environ['MAKE'] = make
[docs]def cmdstan_path() -> str: """ Validate, then return CmdStan directory path. """ cmdstan = '' if 'CMDSTAN' in os.environ: cmdstan = os.environ['CMDSTAN'] else: cmdstan_dir = os.path.expanduser(os.path.join('~', _DOT_CMDSTAN)) if not os.path.exists(cmdstan_dir): cmdstan_dir = os.path.expanduser(os.path.join('~', _DOT_CMDSTANPY)) if not os.path.exists(cmdstan_dir): raise ValueError( 'no CmdStan installation found, ' 'run command line script "install_cmdstan"' ) latest_cmdstan = get_latest_cmdstan(cmdstan_dir) if latest_cmdstan is None: raise ValueError( 'no CmdStan installation found, ' 'run command line script "install_cmdstan"' ) cmdstan = os.path.join(cmdstan_dir, latest_cmdstan) os.environ['CMDSTAN'] = cmdstan validate_cmdstan_path(cmdstan) return cmdstan
def cmdstan_version_at(maj: int, min: int) -> bool: """ Check that CmdStan version is at or above Maj.min version. Parses version string out of CmdStan makefile in CmdStan path dir. :param maj: Major version number :param min: Minor version number :return: True if version at or above, else False """ # pylint:disable=bare-except try: path = cmdstan_path() makefile = os.path.join(path, 'makefile') if not os.path.exists(makefile): raise ValueError( 'CmdStan installation {}: missing makefile'.format(path) ) version = None with open(makefile, 'r') as fd: contents = fd.read() start_idx = contents.find('CMDSTAN_VERSION := ') + len( 'CMDSTAN_VERSION := ' ) end_idx = contents.find('\n', start_idx) version = contents[start_idx:end_idx] if version is None: raise ValueError( 'Cannot parse version from makefile: {}'.format(makefile) ) splits = version.split('.') if len(splits) < 2: raise ValueError( 'Cannot parse version from makefile: {}'.format(makefile) ) cur_maj = int(splits[0]) cur_min = int(splits[1]) if cur_maj > maj or (cur_maj == maj and cur_min >= min): return True except: # noqa pass return False def cxx_toolchain_path(version: str = None) -> Tuple[str]: """ Validate, then activate C++ toolchain directory path. """ if platform.system() != 'Windows': raise RuntimeError( 'Functionality is currently only supported on Windows' ) if version is not None and not isinstance(version, str): raise TypeError('Format version number as a string') logger = get_logger() if 'CMDSTAN_TOOLCHAIN' in os.environ: toolchain_root = os.environ['CMDSTAN_TOOLCHAIN'] if os.path.exists(os.path.join(toolchain_root, 'mingw64')): compiler_path = os.path.join( toolchain_root, 'mingw64' if (sys.maxsize > 2 ** 32) else 'mingw32', 'bin', ) if os.path.exists(compiler_path): tool_path = os.path.join(toolchain_root, 'usr', 'bin') if not os.path.exists(tool_path): tool_path = '' compiler_path = '' logger.warning( 'Found invalid installion for RTools40 on %s', toolchain_root, ) toolchain_root = None else: compiler_path = '' logger.warning( 'Found invalid installion for RTools40 on %s', toolchain_root, ) toolchain_root = None elif os.path.exists(os.path.join(toolchain_root, 'mingw_64')): compiler_path = os.path.join( toolchain_root, 'mingw_64' if (sys.maxsize > 2 ** 32) else 'mingw_32', 'bin', ) if os.path.exists(compiler_path): tool_path = os.path.join(toolchain_root, 'bin') if not os.path.exists(tool_path): tool_path = '' compiler_path = '' logger.warning( 'Found invalid installion for RTools35 on %s', toolchain_root, ) toolchain_root = None else: compiler_path = '' logger.warning( 'Found invalid installion for RTools35 on %s', toolchain_root, ) toolchain_root = None else: rtools40_home = os.environ.get('RTOOLS40_HOME') cmdstan_dir = os.path.expanduser(os.path.join('~', _DOT_CMDSTAN)) cmdstan_dir_old = os.path.expanduser(os.path.join('~', _DOT_CMDSTANPY)) for toolchain_root in ( [rtools40_home] if rtools40_home is not None else [] ) + [ os.path.join(cmdstan_dir, 'RTools40'), os.path.join(cmdstan_dir_old, 'RTools40'), os.path.join(os.path.abspath("/"), "RTools40"), os.path.join(cmdstan_dir, 'RTools35'), os.path.join(cmdstan_dir_old, 'RTools35'), os.path.join(os.path.abspath("/"), "RTools35"), os.path.join(cmdstan_dir, 'RTools'), os.path.join(cmdstan_dir_old, 'RTools'), os.path.join(os.path.abspath("/"), "RTools"), os.path.join(os.path.abspath("/"), "RBuildTools"), ]: compiler_path = '' tool_path = '' if os.path.exists(toolchain_root): if version not in ('35', '3.5', '3'): compiler_path = os.path.join( toolchain_root, 'mingw64' if (sys.maxsize > 2 ** 32) else 'mingw32', 'bin', ) if os.path.exists(compiler_path): tool_path = os.path.join(toolchain_root, 'usr', 'bin') if not os.path.exists(tool_path): tool_path = '' compiler_path = '' logger.warning( 'Found invalid installation for RTools40 on %s', toolchain_root, ) toolchain_root = None else: break else: compiler_path = '' logger.warning( 'Found invalid installation for RTools40 on %s', toolchain_root, ) toolchain_root = None else: compiler_path = os.path.join( toolchain_root, 'mingw_64' if (sys.maxsize > 2 ** 32) else 'mingw_32', 'bin', ) if os.path.exists(compiler_path): tool_path = os.path.join(toolchain_root, 'bin') if not os.path.exists(tool_path): tool_path = '' compiler_path = '' logger.warning( 'Found invalid installation for RTools35 on %s', toolchain_root, ) toolchain_root = None else: break else: compiler_path = '' logger.warning( 'Found invalid installation for RTools35 on %s', toolchain_root, ) toolchain_root = None else: toolchain_root = None if not toolchain_root: raise ValueError( 'no RTools toolchain installation found, ' 'run command line script ' '"python -m cmdstanpy.install_cxx_toolchain"' ) logger.info('Add C++ toolchain to $PATH: %s', toolchain_root) os.environ['PATH'] = ';'.join( list( OrderedDict.fromkeys( [compiler_path, tool_path] + os.getenv('PATH', '').split(';') ) ) ) return compiler_path, tool_path def _rdump_array(key: str, val: np.ndarray) -> str: """Flatten numpy ndarray, format as Rdump variable declaration.""" c = 'c(' + ', '.join(map(str, val.T.flat)) + ')' if (val.size,) == val.shape: return '{key} <- {c}'.format(key=key, c=c) else: dim = '.Dim = c{}'.format(val.shape) struct = '{key} <- structure({c}, {dim})'.format(key=key, c=c, dim=dim) return struct def jsondump(path: str, data: Dict) -> None: """Dump a dict of data to a JSON file.""" data = data.copy() for key, val in data.items(): if type(val).__module__ == 'numpy': val = val.tolist() data[key] = val with open(path, 'w') as fd: json.dump(data, fd) def rdump(path: str, data: Dict) -> None: """Dump a dict of data to a R dump format file.""" with open(path, 'w') as fd: for key, val in data.items(): if isinstance(val, (np.ndarray, Sequence)): line = _rdump_array(key, np.asarray(val)) else: line = '{} <- {}'.format(key, val) print(line, file=fd) def rload(fname: str) -> dict: """Parse data and parameter variable values from an R dump format file. This parser only supports the subset of R dump data as described in the "Dump Data Format" section of the CmdStan manual, i.e., scalar, vector, matrix, and array data types. """ data_dict = {} with open(fname, 'r') as fd: lines = fd.readlines() # Variable data may span multiple lines, parse accordingly idx = 0 while idx < len(lines) and '<-' not in lines[idx]: idx += 1 if idx == len(lines): return None start_idx = idx idx += 1 while True: while idx < len(lines) and '<-' not in lines[idx]: idx += 1 next_var = idx var_data = ''.join(lines[start_idx:next_var]).replace('\n', '') lhs, rhs = [item.strip() for item in var_data.split('<-')] lhs = lhs.replace('"', '') # strip optional Jags double quotes rhs = rhs.replace('L', '') # strip R long int qualifier data_dict[lhs] = parse_rdump_value(rhs) if idx == len(lines): break start_idx = next_var idx += 1 return data_dict def parse_rdump_value(rhs: str) -> Union[int, float, np.array]: """Process right hand side of Rdump variable assignment statement. Value is either scalar, vector, or multi-dim structure. Use regex to capture structure values, dimensions. """ pat = re.compile( r'structure\(\s*c\((?P<vals>[^)]*)\)' r'(,\s*\.Dim\s*=\s*c\s*\((?P<dims>[^)]*)\s*\))?\)' ) val = None try: if rhs.startswith('structure'): parse = pat.match(rhs) if parse is None or parse.group('vals') is None: raise ValueError(rhs) vals = [float(v) for v in parse.group('vals').split(',')] val = np.array(vals, order='F') if parse.group('dims') is not None: dims = [int(v) for v in parse.group('dims').split(',')] val = np.array(vals).reshape(dims, order='F') elif rhs.startswith('c(') and rhs.endswith(')'): val = np.array([float(item) for item in rhs[2:-1].split(',')]) elif '.' in rhs or 'e' in rhs: val = float(rhs) else: val = int(rhs) except TypeError as e: raise ValueError('bad value in Rdump file: {}'.format(rhs)) from e return val def check_sampler_csv( path: str, is_fixed_param: bool = False, iter_sampling: int = None, iter_warmup: int = None, save_warmup: bool = False, thin: int = None, ) -> Dict: """Capture essential config, shape from stan_csv file.""" meta = scan_sampler_csv(path, is_fixed_param) if thin is None: thin = _CMDSTAN_THIN elif thin > _CMDSTAN_THIN: if 'thin' not in meta: raise ValueError( 'bad csv file {}, ' 'config error, expected thin = {}'.format(path, thin) ) if meta['thin'] != thin: raise ValueError( 'bad csv file {}, ' 'config error, expected thin = {}, found {}'.format( path, thin, meta['thin'] ) ) draws_sampling = iter_sampling if draws_sampling is None: draws_sampling = _CMDSTAN_SAMPLING draws_warmup = iter_warmup if draws_warmup is None: draws_warmup = _CMDSTAN_WARMUP draws_warmup = int(math.ceil(draws_warmup / thin)) draws_sampling = int(math.ceil(draws_sampling / thin)) if meta['draws_sampling'] != draws_sampling: raise ValueError( 'bad csv file {}, expected {} draws, found {}'.format( path, draws_sampling, meta['draws_sampling'] ) ) if save_warmup: if not ('save_warmup' in meta and meta['save_warmup'] == 1): raise ValueError( 'bad csv file {}, ' 'config error, expected save_warmup = 1'.format(path) ) if meta['draws_warmup'] != draws_warmup: raise ValueError( 'bad csv file {}, ' 'expected {} warmup draws, found {}'.format( path, draws_warmup, meta['draws_warmup'] ) ) return meta def scan_sampler_csv(path: str, is_fixed_param: bool = False) -> Dict: """Process sampler stan_csv output file line by line.""" dict = {} lineno = 0 with open(path, 'r') as fd: lineno = scan_config(fd, dict, lineno) lineno = scan_column_names(fd, dict, lineno) if not is_fixed_param: lineno = scan_warmup_iters(fd, dict, lineno) lineno = scan_metric(fd, dict, lineno) lineno = scan_sampling_iters(fd, dict, lineno) return dict def scan_optimize_csv(path: str) -> Dict: """Process optimizer stan_csv output file line by line.""" dict = {} lineno = 0 with open(path, 'r') as fd: lineno = scan_config(fd, dict, lineno) lineno = scan_column_names(fd, dict, lineno) line = fd.readline().lstrip(' #\t').rstrip() xs = line.split(',') dict['mle'] = [float(x) for x in xs] return dict def scan_generated_quantities_csv(path: str) -> Dict: """ Process standalone generated quantities stan_csv output file line by line. """ dict = {} lineno = 0 with open(path, 'r') as fd: lineno = scan_config(fd, dict, lineno) lineno = scan_column_names(fd, dict, lineno) return dict def scan_variational_csv(path: str) -> Dict: """Process advi stan_csv output file line by line.""" dict = {} lineno = 0 with open(path, 'r') as fd: lineno = scan_config(fd, dict, lineno) lineno = scan_column_names(fd, dict, lineno) line = fd.readline().lstrip(' #\t').rstrip() lineno += 1 if line.startswith('Stepsize adaptation complete.'): line = fd.readline().lstrip(' #\t\n') lineno += 1 if not line.startswith('eta'): raise ValueError( 'line {}: expecting eta, found:\n\t "{}"'.format( lineno, line ) ) line = fd.readline().lstrip(' #\t\n') lineno += 1 xs = line.split(',') variational_mean = [float(x) for x in xs] dict['variational_mean'] = variational_mean dict['variational_sample'] = pd.read_csv( path, comment='#', skiprows=lineno, header=None, float_precision='high', ) return dict def scan_config(fd: TextIO, config_dict: Dict, lineno: int) -> int: """ Scan initial stan_csv file comments lines and save non-default configuration information to config_dict. """ cur_pos = fd.tell() line = fd.readline().strip() while len(line) > 0 and line.startswith('#'): lineno += 1 if line.endswith('(Default)'): line = line.replace('(Default)', '') line = line.lstrip(' #\t') key_val = line.split('=') if len(key_val) == 2: if key_val[0].strip() == 'file' and not key_val[1].endswith('csv'): config_dict['data_file'] = key_val[1].strip() elif key_val[0].strip() != 'file': raw_val = key_val[1].strip() try: val = int(raw_val) except ValueError: try: val = float(raw_val) except ValueError: val = raw_val config_dict[key_val[0].strip()] = val cur_pos = fd.tell() line = fd.readline().strip() fd.seek(cur_pos) return lineno def scan_warmup_iters(fd: TextIO, config_dict: Dict, lineno: int) -> int: """ Check warmup iterations, if any. """ if 'save_warmup' not in config_dict: return lineno cur_pos = fd.tell() line = fd.readline().strip() draws_found = 0 while len(line) > 0 and not line.startswith('#'): lineno += 1 draws_found += 1 cur_pos = fd.tell() line = fd.readline().strip() fd.seek(cur_pos) config_dict['draws_warmup'] = draws_found return lineno def scan_column_names(fd: TextIO, config_dict: Dict, lineno: int) -> int: """ Process columns header, add to config_dict as 'column_names' """ line = fd.readline().strip() lineno += 1 names = line.split(',') config_dict['column_names_raw'] = tuple(names) config_dict['column_names'] = tuple(munge_varnames(names)) return lineno def munge_varnames(names: List) -> List: """ Change formatting for indices of container var elements from use of dot separator to array-like notation, e.g., rewrite label ``y_forecast.2.4`` to ``y_forecast[2,4]``. """ if names is None: raise ValueError('missing argument "names"') return [ re.sub(r',([\d,]+)$', r'[\1]', column.replace('.', ',')) for column in names ] def parse_sampler_vars(names: Tuple[str, ...]) -> Dict: """ Parses out names ending in `__` from list of CSV file column names. Return a dict mapping sampler variable name to Stan CSV file column, using zero-based column indexing. """ if names is None: raise ValueError('missing argument "names"') # note: value as tuple allows structured sampler vars # currently, all sampler vars a scalar, not checking for structure return {v: tuple([k]) for (k, v) in enumerate(names) if v.endswith('__')} def parse_stan_vars(names: Tuple[str, ...]) -> (Dict, Dict): """ Parses out Stan variable names (i.e., names not ending in `__`) from list of CSV file column names. Returns a pair of dicts which map variable names to dimensions and variable names to columns, respectively, using zero-based column indexing. Note: assumes: (a) munged varnames and (b) container vars are non-ragged and dense; no checks size, indices. """ if names is None: raise ValueError('missing argument "names"') dims_map = {} cols_map = {} idxs = [] for (idx, name) in enumerate(names): idxs.append(idx) var, *dims = name.split('[') if var.endswith('__'): idxs = [] elif len(dims) == 0: dims_map[var] = () cols_map[var] = tuple(idxs) idxs = [] else: if idx < len(names) - 1 and names[idx + 1].split('[')[0] == var: continue dims = [int(x) for x in dims[0][:-1].split(',')] dims_map[var] = tuple(dims) cols_map[var] = tuple(idxs) idxs = [] return (dims_map, cols_map) def scan_metric(fd: TextIO, config_dict: Dict, lineno: int) -> int: """ Scan step size, metric from stan_csv file comment lines, set config_dict entries 'metric' and 'num_unconstrained_params' """ if 'metric' not in config_dict: config_dict['metric'] = 'diag_e' metric = config_dict['metric'] line = fd.readline().strip() lineno += 1 if not line == '# Adaptation terminated': raise ValueError( 'line {}: expecting metric, found:\n\t "{}"'.format(lineno, line) ) line = fd.readline().strip() lineno += 1 label, step_size = line.split('=') if not label.startswith('# Step size'): raise ValueError( 'line {}: expecting step size, ' 'found:\n\t "{}"'.format(lineno, line) ) try: float(step_size.strip()) except ValueError as e: raise ValueError( 'line {}: invalid step size: {}'.format(lineno, step_size) ) from e line = fd.readline().strip() lineno += 1 if not ( ( metric == 'diag_e' and line == '# Diagonal elements of inverse mass matrix:' ) or ( metric == 'dense_e' and line == '# Elements of inverse mass matrix:' ) ): raise ValueError( 'line {}: invalid or missing mass matrix ' 'specification'.format(lineno) ) line = fd.readline().lstrip(' #\t') lineno += 1 num_unconstrained_params = len(line.split(',')) config_dict['num_unconstrained_params'] = num_unconstrained_params if metric == 'diag_e': return lineno else: for _ in range(1, num_unconstrained_params): line = fd.readline().lstrip(' #\t') lineno += 1 if len(line.split(',')) != num_unconstrained_params: raise ValueError( 'line {}: invalid or missing mass matrix ' 'specification'.format(lineno) ) return lineno def scan_sampling_iters(fd: TextIO, config_dict: Dict, lineno: int) -> int: """ Parse sampling iteration, save number of iterations to config_dict. """ draws_found = 0 num_cols = len(config_dict['column_names']) cur_pos = fd.tell() line = fd.readline().strip() while len(line) > 0 and not line.startswith('#'): lineno += 1 draws_found += 1 data = line.split(',') if len(data) != num_cols: raise ValueError( 'line {}: bad draw, expecting {} items, found {}'.format( lineno, num_cols, len(line.split(',')) ) ) cur_pos = fd.tell() line = fd.readline().strip() config_dict['draws_sampling'] = draws_found fd.seek(cur_pos) return lineno def read_metric(path: str) -> List[int]: """ Read metric file in JSON or Rdump format. Return dimensions of entry "inv_metric". """ if path.endswith('.json'): with open(path, 'r') as fd: metric_dict = json.load(fd) if 'inv_metric' in metric_dict: dims = np.asarray(metric_dict['inv_metric']) return list(dims.shape) else: raise ValueError( 'metric file {}, bad or missing' ' entry "inv_metric"'.format(path) ) else: dims = list(read_rdump_metric(path)) if dims is None: raise ValueError( 'metric file {}, bad or missing' ' entry "inv_metric"'.format(path) ) return dims def read_rdump_metric(path: str) -> List[int]: """ Find dimensions of variable named 'inv_metric' in Rdump data file. """ metric_dict = rload(path) if not ( 'inv_metric' in metric_dict and isinstance(metric_dict['inv_metric'], np.ndarray) ): raise ValueError( 'metric file {}, bad or missing entry "inv_metric"'.format(path) ) return list(metric_dict['inv_metric'].shape) def do_command(cmd: str, cwd: str = None, logger: logging.Logger = None) -> str: """ Spawn process, print stdout/stderr to console. Throws RuntimeError on non-zero returncode. """ if logger: logger.debug('cmd: %s', cmd) proc = subprocess.Popen( cmd, cwd=cwd, stdin=subprocess.DEVNULL, stdout=subprocess.PIPE, stderr=subprocess.PIPE, env=os.environ, ) stdout, stderr = proc.communicate() if proc.returncode: msg = 'ERROR\n' if stderr: msg = '{}{} '.format(msg, stderr.decode('utf-8').strip()) raise RuntimeError(msg) if stdout: return stdout.decode('utf-8').strip() return None def windows_short_path(path: str) -> str: """ Gets the short path name of a given long path. http://stackoverflow.com/a/23598461/200291 On non-Windows platforms, returns the path If (base)path does not exist, function raises RuntimeError """ if platform.system() != 'Windows': return path if os.path.isfile(path) or ( not os.path.isdir(path) and os.path.splitext(path)[1] != '' ): base_path, file_name = os.path.split(path) else: base_path, file_name = path, '' if not os.path.exists(base_path): raise RuntimeError( 'Windows short path function needs a valid directory. ' 'Base directory does not exist: "{}"'.format(base_path) ) import ctypes from ctypes import wintypes # pylint: disable=invalid-name _GetShortPathNameW = ctypes.windll.kernel32.GetShortPathNameW _GetShortPathNameW.argtypes = [ wintypes.LPCWSTR, wintypes.LPWSTR, wintypes.DWORD, ] _GetShortPathNameW.restype = wintypes.DWORD output_buf_size = 0 while True: output_buf = ctypes.create_unicode_buffer(output_buf_size) needed = _GetShortPathNameW(base_path, output_buf, output_buf_size) if output_buf_size >= needed: short_base_path = output_buf.value break else: output_buf_size = needed short_path = ( os.path.join(short_base_path, file_name) if file_name else short_base_path ) return short_path def create_named_text_file( dir: str, prefix: str, suffix: str, name_only: bool = False ) -> str: """ Create a named unique file, return filename. Flag 'name_only' will create then delete the tmp file; this lets us create filename args for commands which disallow overwriting existing files (e.g., 'stansummary'). """ fd = tempfile.NamedTemporaryFile( mode='w+', prefix=prefix, suffix=suffix, dir=dir, delete=name_only ) path = fd.name fd.close() return path
[docs]def install_cmdstan( version: str = None, dir: str = None, overwrite: bool = False, verbose: bool = False, ) -> bool: """ Download and install a CmdStan release from GitHub by running script ``install_cmdstan`` as a subprocess. Downloads the release tar.gz file to temporary storage. Retries GitHub requests in order to allow for transient network outages. Builds CmdStan executables and tests the compiler by building example model ``bernoulli.stan``. :param version: CmdStan version string, e.g. "2.24.1". Defaults to latest CmdStan release. :param dir: Path to install directory. Defaults to hidden directory ``$HOME/.cmdstan`` or ``$HOME/.cmdstanpy``, if the latter exists. If no directory is specified and neither of the above directories exist, directory ``$HOME/.cmdstan`` will be created and populated. :param overwrite: Boolean value; when ``True``, will overwrite and rebuild an existing CmdStan installation. Default is ``False``. :param verbose: Boolean value; when ``True``, output from CmdStan build processes will be streamed to the console. Default is ``False``. :return: Boolean value; ``True`` for success. """ logger = get_logger() python = sys.executable here = os.path.dirname(os.path.abspath(__file__)) path = os.path.join(here, 'install_cmdstan.py') cmd = [python, '-u', path] if version is not None: cmd.extend(['--version', version]) if dir is not None: cmd.extend(['--dir', dir]) if overwrite: cmd.extend(['--overwrite', 'TRUE']) if verbose: cmd.extend(['--verbose', 'TRUE']) proc = subprocess.Popen( cmd, stdin=subprocess.DEVNULL, stdout=subprocess.PIPE, stderr=subprocess.PIPE, env=os.environ, ) while proc.poll() is None: print(proc.stdout.readline().decode('utf-8').strip()) _, stderr = proc.communicate() if proc.returncode: logger.warning('CmdStan installation failed.') if stderr: logger.warning(stderr.decode('utf-8').strip()) return False return True
class MaybeDictToFilePath: """Context manager for json files.""" def __init__( self, *objs: Union[str, dict, list], logger: logging.Logger = None ): self._unlink = [False] * len(objs) self._paths = [''] * len(objs) self._logger = logger or get_logger() i = 0 for obj in objs: if isinstance(obj, dict): data_file = create_named_text_file( dir=_TMPDIR, prefix='', suffix='.json' ) self._logger.debug('input tempfile: %s', data_file) if any( not item for item in obj if isinstance(item, (Sequence, np.ndarray)) ): rdump(data_file, obj) else: jsondump(data_file, obj) self._paths[i] = data_file self._unlink[i] = True elif isinstance(obj, str): if not os.path.exists(obj): raise ValueError("File doesn't exist {}".format(obj)) self._paths[i] = obj elif isinstance(obj, list): err_msgs = [] missing_obj_items = [] for j, obj_item in enumerate(obj): if not isinstance(obj_item, str): err_msgs.append( ( 'List element {} must be a filename string,' ' found {}' ).format(j, obj_item) ) elif not os.path.exists(obj_item): missing_obj_items.append( "File doesn't exist: {}".format(obj_item) ) if err_msgs: raise ValueError('\n'.join(err_msgs)) if missing_obj_items: raise ValueError('\n'.join(missing_obj_items)) self._paths[i] = obj elif obj is None: self._paths[i] = None elif i == 1 and isinstance(obj, (Integral, Real)): self._paths[i] = obj else: raise ValueError('data must be string or dict') i += 1 def __enter__(self): return self._paths def __exit__(self, exc_type, exc_val, exc_tb): for can_unlink, path in zip(self._unlink, self._paths): if can_unlink and path: try: os.remove(path) except PermissionError: pass class TemporaryCopiedFile: """Context manager for tmpfiles, handles spaces in filepath.""" def __init__(self, file_path: str): self._path = None self._tmpdir = None if ' ' in os.path.abspath(file_path) and platform.system() == 'Windows': base_path, file_name = os.path.split(os.path.abspath(file_path)) os.makedirs(base_path, exist_ok=True) try: short_base_path = windows_short_path(base_path) if os.path.exists(short_base_path): file_path = os.path.join(short_base_path, file_name) except RuntimeError: pass if ' ' in os.path.abspath(file_path): tmpdir = tempfile.mkdtemp() if ' ' in tmpdir: raise RuntimeError( 'Unable to generate temporary path without spaces! \n' + 'Please move your stan file to location without spaces.' ) _, path = tempfile.mkstemp(suffix='.stan', dir=tmpdir) shutil.copy(file_path, path) self._path = path self._tmpdir = tmpdir else: self._path = file_path def __enter__(self): return self._path, self._tmpdir is not None def __exit__(self, exc_type, exc_val, exc_tb): if self._tmpdir: shutil.rmtree(self._tmpdir, ignore_errors=True)