import os
import re
import io
import yaml
import numpy as np
from scipy.io import loadmat
from scipy.io.matlab.mio5_params import mat_struct
# HACK: fix loading number in scientific notation
#
# https://stackoverflow.com/questions/30458977/yaml-loads-5e-6-as-string-and-not-a-number
#
# An apparent bug in python-yaml prevents it from regognizing
# scientific notation as a float. The following is a modified version
# of the parser that recognize scientific notation appropriately.
loader = yaml.SafeLoader
loader.add_implicit_resolver(
'tag:yaml.org,2002:float',
re.compile('''^(?:
[-+]?(?:[0-9][0-9_]*)\\.[0-9_]*(?:[eE][-+]?[0-9]+)?
|[-+]?(?:[0-9][0-9_]*)(?:[eE][-+]?[0-9]+)
|\\.[0-9_]+(?:[eE][-+][0-9]+)?
|[-+]?[0-9][0-9_]*(?::[0-5]?[0-9])+\\.[0-9_]*
|[-+]?\\.(?:inf|Inf|INF)
|\\.(?:nan|NaN|NAN))$''', re.X),
list('-+0123456789.'))
def dictlist2recarray(l):
def dtype(v):
if isinstance(v, int):
return float
else:
return type(v)
# get dtypes from first element dict
dtypes = [(k, dtype(v)) for k,v in l[0].items()]
values = [tuple(el.values()) for el in l]
out = np.array(values, dtype=dtypes)
return out.view(np.recarray)
class Struct(object):
"""Matlab struct-like object
This is a simple implementation of a MATLAB struct-like object
that stores values as attributes of a simple class: and allows
assigning to attributes recursively, e.g.:
>>> s = Struct()
>>> s.a = 4
>>> s.b = Struct()
>>> s.b.c = 8
Various classmethods allow creating one of these objects from YAML
file, a nested dict, or a MATLAB struct object.
"""
# FIXME: This would be a way to allow setting nested struct
# attributes, e.g.:
#
# >>> s = Struct()
# >>> s.a.b.c = 4
#
# Usage of __getattr__ like this is dangerous and creates
# non-intuitive behavior (i.e. an empty struct is returned when
# accessing attributes that don't exist). Is there a way to
# accomplish this without that adverse side affect?
#
# def __getattr__(self, name):
# if name not in self.__dict__:
# self.__dict__[name] = Struct()
# return self.__dict__[name]
##########
def __contains__(self, item):
return item in self.__dict__
def to_dict(self, array=False):
"""Return nested dictionary representation of Struct.
If `array` is True any lists encountered will be turned into
numpy arrays, and lists of Structs will be turned into record
arrays. This is needed to convert to structure arrays in
matlab.
"""
d = {}
for k,v in self.__dict__.items():
if isinstance(v, type(self)):
d[k] = v.to_dict(array=array)
else:
if isinstance(v, list):
try:
# this should fail if the elements of v are
# not Struct
# FIXME: need cleaner way to do this
v = [i.to_dict(array=array) for i in v]
if array:
v = dictlist2recarray(v)
except AttributeError:
if array:
v = np.array(v)
elif isinstance(v, int):
v = float(v)
d[k] = v
return d
def to_yaml(self, path=None):
"""Return YAML representation of Struct.
Write YAML to `path` if specified.
"""
y = yaml.dump(self.to_dict(), default_flow_style=False)
if path:
with open(path, 'w') as f:
f.write(y)
else:
return y
# def __repr__(self):
# return self.to_yaml().strip('\n')
def __str__(self):
return '<GWINC Struct: {}>'.format(list(self.__dict__.keys()))
def __iter__(self):
return iter(self.__dict__)
def walk(self):
"""Iterate over all leaves in the struct tree.
"""
for k,v in self.__dict__.items():
if isinstance(v, type(self)):
for sk,sv in v.walk():
yield k+'.'+sk, sv
else:
try:
for i,vv in enumerate(v):
for sk,sv in vv.walk():
yield '{}[{}].{}'.format(k,i,sk), sv
except (AttributeError, TypeError):
yield k, v
def to_txt(self, path=None, fmt='0.6e', delimiter=': ', end=''):
"""Return text represenation of Struct, one element per line.
Struct keys use '.' to indicate hierarchy. The `fmt` keyword
controls the formatting of numeric values. MATLAB code can
generated with the following parameters:
>>> ifo.to_txt(delimiter=' = ', end=';')
Write text to `path` if specified.
"""
txt = io.StringIO()
for k, v in sorted(self.walk()):
if isinstance(v, (int, long, float, complex)):
base = fmt
elif isinstance(v, np.ndarray):
v = np.array2string(v, separator='', max_line_width=np.Inf, formatter={'all':lambda x: "{:0.6e} ".format(x)})
base = 's'
else:
base = 's'
txt.write(u'{key}{delimiter}{value:{base}}{end}\n'.format(
key=k, value=v, base=base,
delimiter=delimiter,
end=end,
))
if path:
with open(path, 'w') as f:
f.write(txt.getvalue())
else:
return txt.getvalue()
@classmethod
def from_dict(cls, d):
"""Create Struct from nested dict.
"""
c = cls()
for k,v in d.items():
if type(v) == dict:
c.__dict__[k] = Struct.from_dict(v)
else:
try:
c.__dict__[k] = list(map(Struct.from_dict, v))
except (AttributeError, TypeError):
c.__dict__[k] = v
return c
@classmethod
def from_matstruct(cls, s):
"""Create Struct from scipy.io.matlab mat_struct object.
"""
c = cls()
try:
s = s['ifo']
except:
pass
for k,v in s.__dict__.items():
if k in ['_fieldnames']:
# skip these fields
pass
elif type(v) is mat_struct:
c.__dict__[k] = Struct.from_matstruct(v)
else:
# handle lists of Structs
try:
c.__dict__[k] = list(map(Struct.from_matstruct, v))
except:
c.__dict__[k] = v
# try:
# c.__dict__[k] = float(v)
# except:
# c.__dict__[k] = v
return c
@classmethod
def from_file(cls, path):
"""Load Struct from .yaml or MATLAB .mat file.
File type will be determined by extension.
"""
(root, ext) = os.path.splitext(path)
with open(path, 'r') as f:
if ext in ['.yaml', '.yml']:
d = yaml.load(f, Loader=loader)
return cls.from_dict(d)
elif ext == '.mat':
s = loadmat(f, squeeze_me=True, struct_as_record=False)
return cls.from_matstruct(s)
else:
raise IOError("Unknown file type: {}".format(ext))