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black codestyle #3239

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13 changes: 11 additions & 2 deletions pymc3/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,15 @@
from .distributions import *
from .glm import *
from . import gp
from .math import logaddexp, logsumexp, logit, invlogit, expand_packed_triangular, probit, invprobit
from .math import (
logaddexp,
logsumexp,
logit,
invlogit,
expand_packed_triangular,
probit,
invprobit,
)
from .model import *
from .model_graph import model_to_graphviz
from .stats import *
Expand All @@ -28,7 +36,8 @@
from .data import *

import logging
_log = logging.getLogger('pymc3')

_log = logging.getLogger("pymc3")
if not logging.root.handlers:
_log.setLevel(logging.INFO)
handler = logging.StreamHandler()
Expand Down
11 changes: 5 additions & 6 deletions pymc3/backends/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -122,9 +122,8 @@
from ..backends.sqlite import SQLite
from ..backends.hdf5 import HDF5

_shortcuts = {'text': {'backend': Text,
'name': 'mcmc'},
'sqlite': {'backend': SQLite,
'name': 'mcmc.sqlite'},
'hdf5': {'backend': HDF5,
'name': 'mcmc.hdf5'}}
_shortcuts = {
"text": {"backend": Text, "name": "mcmc"},
"sqlite": {"backend": SQLite, "name": "mcmc.sqlite"},
"hdf5": {"backend": HDF5, "name": "mcmc.hdf5"},
}
97 changes: 59 additions & 38 deletions pymc3/backends/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
from ..model import modelcontext
from .report import SamplerReport, merge_reports

logger = logging.getLogger('pymc3')
logger = logging.getLogger("pymc3")


class BackendError(Exception):
Expand Down Expand Up @@ -58,10 +58,8 @@ def __init__(self, name, model=None, vars=None, test_point=None):
test_point_.update(test_point)
test_point = test_point_
var_values = list(zip(self.varnames, self.fn(test_point)))
self.var_shapes = {var: value.shape
for var, value in var_values}
self.var_dtypes = {var: value.dtype
for var, value in var_values}
self.var_shapes = {var: value.shape for var, value in var_values}
self.var_dtypes = {var: value.dtype for var, value in var_values}
self.chain = None
self._is_base_setup = False
self.sampler_vars = None
Expand All @@ -87,8 +85,9 @@ def _set_sampler_vars(self, sampler_vars):
for stats in sampler_vars:
for key, dtype in stats.items():
if dtypes.setdefault(key, dtype) != dtype:
raise ValueError("Sampler statistic %s appears with "
"different types." % key)
raise ValueError(
"Sampler statistic %s appears with " "different types." % key
)

self.sampler_vars = sampler_vars

Expand Down Expand Up @@ -137,7 +136,7 @@ def __getitem__(self, idx):
try:
return self.point(int(idx))
except (ValueError, TypeError): # Passed variable or variable name.
raise ValueError('Can only index with slice or integer')
raise ValueError("Can only index with slice or integer")

def __len__(self):
raise NotImplementedError
Expand Down Expand Up @@ -181,13 +180,14 @@ def get_sampler_stats(self, varname, sampler_idx=None, burn=0, thin=1):
if sampler_idx is not None:
return self._get_sampler_stats(varname, sampler_idx, burn, thin)

sampler_idxs = [i for i, s in enumerate(self.sampler_vars)
if varname in s]
sampler_idxs = [i for i, s in enumerate(self.sampler_vars) if varname in s]
if not sampler_idxs:
raise KeyError("Unknown sampler stat %s" % varname)

vals = np.stack([self._get_sampler_stats(varname, i, burn, thin)
for i in sampler_idxs], axis=-1)
vals = np.stack(
[self._get_sampler_stats(varname, i, burn, thin) for i in sampler_idxs],
axis=-1,
)
if vals.shape[-1] == 1:
return vals[..., 0]
else:
Expand Down Expand Up @@ -267,13 +267,14 @@ def __init__(self, straces):

self._report = SamplerReport()
for strace in straces:
if hasattr(strace, '_warnings'):
if hasattr(strace, "_warnings"):
self._report._add_warnings(strace._warnings, strace.chain)

def __repr__(self):
template = '<{}: {} chains, {} iterations, {} variables>'
return template.format(self.__class__.__name__,
self.nchains, len(self), len(self.varnames))
template = "<{}: {} chains, {} iterations, {} variables>"
return template.format(
self.__class__.__name__, self.nchains, len(self), len(self.varnames)
)

@property
def nchains(self):
Expand Down Expand Up @@ -310,16 +311,26 @@ def __getitem__(self, idx):
var = str(var)
if var in self.varnames:
if var in self.stat_names:
warnings.warn("Attribute access on a trace object is ambigous. "
"Sampler statistic and model variable share a name. Use "
"trace.get_values or trace.get_sampler_stats.")
warnings.warn(
"Attribute access on a trace object is ambigous. "
"Sampler statistic and model variable share a name. Use "
"trace.get_values or trace.get_sampler_stats."
)
return self.get_values(var, burn=burn, thin=thin)
if var in self.stat_names:
return self.get_sampler_stats(var, burn=burn, thin=thin)
raise KeyError("Unknown variable %s" % var)

_attrs = set(['_straces', 'varnames', 'chains', 'stat_names',
'supports_sampler_stats', '_report'])
_attrs = set(
[
"_straces",
"varnames",
"chains",
"stat_names",
"supports_sampler_stats",
"_report",
]
)

def __getattr__(self, name):
# Avoid infinite recursion when called before __init__
Expand All @@ -330,14 +341,17 @@ def __getattr__(self, name):
name = str(name)
if name in self.varnames:
if name in self.stat_names:
warnings.warn("Attribute access on a trace object is ambigous. "
"Sampler statistic and model variable share a name. Use "
"trace.get_values or trace.get_sampler_stats.")
warnings.warn(
"Attribute access on a trace object is ambigous. "
"Sampler statistic and model variable share a name. Use "
"trace.get_values or trace.get_sampler_stats."
)
return self.get_values(name)
if name in self.stat_names:
return self.get_sampler_stats(name)
raise AttributeError("'{}' object has no attribute '{}'".format(
type(self).__name__, name))
raise AttributeError(
"'{}' object has no attribute '{}'".format(type(self).__name__, name)
)

def __len__(self):
chain = self.chains[-1]
Expand Down Expand Up @@ -392,10 +406,12 @@ def add_values(self, vals, overwrite=False):
l_samples = len(self) * len(self.chains)
l_v = len(v)
if l_v != l_samples:
warnings.warn("The length of the values you are trying to "
"add ({}) does not match the number ({}) of "
"total samples in the trace "
"(chains * iterations)".format(l_v, l_samples))
warnings.warn(
"The length of the values you are trying to "
"add ({}) does not match the number ({}) of "
"total samples in the trace "
"(chains * iterations)".format(l_v, l_samples)
)

v = np.squeeze(v.reshape(len(chains), len(self), -1))

Expand Down Expand Up @@ -424,8 +440,9 @@ def remove_values(self, name):
chain.vars.remove(va)
del chain.samples[name]

def get_values(self, varname, burn=0, thin=1, combine=True, chains=None,
squeeze=True):
def get_values(
self, varname, burn=0, thin=1, combine=True, chains=None, squeeze=True
):
"""Get values from traces.

Parameters
Expand All @@ -452,14 +469,16 @@ def get_values(self, varname, burn=0, thin=1, combine=True, chains=None,
chains = self.chains
varname = str(varname)
try:
results = [self._straces[chain].get_values(varname, burn, thin)
for chain in chains]
results = [
self._straces[chain].get_values(varname, burn, thin) for chain in chains
]
except TypeError: # Single chain passed.
results = [self._straces[chains].get_values(varname, burn, thin)]
return _squeeze_cat(results, combine, squeeze)

def get_sampler_stats(self, varname, burn=0, thin=1, combine=True,
chains=None, squeeze=True):
def get_sampler_stats(
self, varname, burn=0, thin=1, combine=True, chains=None, squeeze=True
):
"""Get sampler statistics from the trace.

Parameters
Expand Down Expand Up @@ -487,8 +506,10 @@ def get_sampler_stats(self, varname, burn=0, thin=1, combine=True,
except TypeError:
chains = [chains]

results = [self._straces[chain].get_sampler_stats(varname, None, burn, thin)
for chain in chains]
results = [
self._straces[chain].get_sampler_stats(varname, None, burn, thin)
for chain in chains
]
return _squeeze_cat(results, combine, squeeze)

def _slice(self, slice):
Expand Down
47 changes: 28 additions & 19 deletions pymc3/backends/hdf5.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,14 +2,15 @@
import h5py
from contextlib import contextmanager


@contextmanager
def activator(instance):
if isinstance(instance.hdf5_file, h5py.File):
if instance.hdf5_file.id: # if file is open, keep open
yield
return
# if file is closed/not referenced: open, do job, then close
instance.hdf5_file = h5py.File(instance.name, 'a')
instance.hdf5_file = h5py.File(instance.name, "a")
yield
instance.hdf5_file.close()
return
Expand Down Expand Up @@ -50,21 +51,21 @@ def activate_file(self):
@property
def samples(self):
g = self.hdf5_file.require_group(str(self.chain))
if 'name' not in g.attrs:
g.attrs['name'] = self.chain
return g.require_group('samples')
if "name" not in g.attrs:
g.attrs["name"] = self.chain
return g.require_group("samples")

@property
def stats(self):
g = self.hdf5_file.require_group(str(self.chain))
if 'name' not in g.attrs:
g.attrs['name'] = self.chain
return g.require_group('stats')
if "name" not in g.attrs:
g.attrs["name"] = self.chain
return g.require_group("stats")

@property
def chains(self):
with self.activate_file:
return [v.attrs['name'] for v in self.hdf5_file.values()]
return [v.attrs["name"] for v in self.hdf5_file.values()]

@property
def is_new_file(self):
Expand All @@ -84,19 +85,19 @@ def nchains(self):
@property
def records_stats(self):
with self.activate_file:
return self.hdf5_file.attrs['records_stats']
return self.hdf5_file.attrs["records_stats"]

@records_stats.setter
def records_stats(self, v):
with self.activate_file:
self.hdf5_file.attrs['records_stats'] = bool(v)
self.hdf5_file.attrs["records_stats"] = bool(v)

def _resize(self, n):
for v in self.samples.values():
v.resize(n, axis=0)
for key, group in self.stats.items():
for statds in group.values():
statds.resize((n, ))
statds.resize((n,))

@property
def sampler_vars(self):
Expand All @@ -123,10 +124,15 @@ def sampler_vars(self, values):
if not data.keys(): # no pre-recorded stats
for varname, dtype in sampler.items():
if varname not in data:
data.create_dataset(varname, (self.draws,), dtype=dtype, maxshape=(None,))
data.create_dataset(
varname, (self.draws,), dtype=dtype, maxshape=(None,)
)
elif data.keys() != sampler.keys():
raise ValueError(
"Sampler vars can't change, names incompatible: {} != {}".format(data.keys(), sampler.keys()))
"Sampler vars can't change, names incompatible: {} != {}".format(
data.keys(), sampler.keys()
)
)
self.records_stats = True

def setup(self, draws, chain, sampler_vars=None):
Expand All @@ -146,16 +152,18 @@ def setup(self, draws, chain, sampler_vars=None):
with self.activate_file:
for varname, shape in self.var_shapes.items():
if varname not in self.samples:
self.samples.create_dataset(name=varname, shape=(draws, ) + shape,
dtype=self.var_dtypes[varname],
maxshape=(None, ) + shape)
self.samples.create_dataset(
name=varname,
shape=(draws,) + shape,
dtype=self.var_dtypes[varname],
maxshape=(None,) + shape,
)
self.draw_idx = len(self)
self.draws = self.draw_idx + draws
self._set_sampler_vars(sampler_vars)
self._is_base_setup = True
self._resize(self.draws)


def close(self):
with self.activate_file:
if self.draw_idx == self.draws:
Expand Down Expand Up @@ -190,8 +198,9 @@ def _slice(self, idx):
start, stop, step = idx.indices(len(self))
sliced = ndarray.NDArray(model=self.model, vars=self.vars)
sliced.chain = self.chain
sliced.samples = {v: self.samples[v][start:stop:step]
for v in self.varnames}
sliced.samples = {
v: self.samples[v][start:stop:step] for v in self.varnames
}
sliced.draw_idx = (stop - start) // step
return sliced

Expand Down
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