def get_bias_and_variance_from_files(self):
bias = array(load_from_text_file(
os.path.join(self.output_directory, self.bias_file_name),
convert_to_float=True))
variance = array(load_from_text_file(
os.path.join(self.output_directory, self.variance_file_name),
convert_to_float=True))
if variance.ndim == 1:
variance.reshape(variance.size, 1)
ahat={}
v = {}
for l in range(bias.size):
ahat[l] = bias[l]
v[l] = variance[l,:]
return (ahat, v)
def __init__(self, filename, package_order=['core'], additional_datasets={}, cache_file_location=None,
transformation_pair = (None, None), **kwargs):
"""The file 'filename' has the following structure:
1. line: base_year calibration_year
2 lines per each variable:
1. variable_name
2. bias variance
"""
content = load_from_text_file(filename)
nvar = (content.size-1)/2
self.base_year, self.year = map(lambda x: int(x), content[0].split(' '))
self.variable_names = []
self.ahat = {}
self.v = {}
self.weight_components = {}
self.package_order = package_order
counter = 1
for i in range(nvar):
self.variable_names.append(content[counter])
counter += 1
splitted_row = content[counter].split(' ')
self.ahat[i], self.v[i] = map(lambda x: array([float(x)]), splitted_row)
self.weight_components[i] = array([1.])
counter += 1
self.weights = array([1.])
self.number_of_runs = 1
self.additional_datasets = additional_datasets
if cache_file_location is not None:
BayesianMelding.set_cache_attributes(self, cache_file_location, **kwargs)
self.transformation_pair_for_prediction = transformation_pair
def __init__(self,
filename,
package_order=['core'],
additional_datasets={}):
"""The file 'filename' has the following structure:
1. line: base_year calibration_year
2 lines per each variable:
1. variable_name
2. bias variance
"""
content = load_from_text_file(filename)
nvar = (content.size - 1) / 2
self.base_year, self.year = map(lambda x: int(x),
content[0].split(' '))
self.variable_names = []
self.ahat = {}
self.v = {}
self.weight_components = {}
self.package_order = package_order
counter = 1
for i in range(nvar):
self.variable_names.append(content[counter])
counter += 1
splitted_row = content[counter].split(' ')
self.ahat[i], self.v[i] = map(lambda x: array([float(x)]),
splitted_row)
self.weight_components[i] = array([1.])
counter += 1
self.weights = array([1.])
self.number_of_runs = 1
self.additional_datasets = additional_datasets
def __init__(self, filename, package_order=['core'], additional_datasets={}):
"""The file 'filename' has the following structure:
1. line: base_year calibration_year
2 lines per each variable:
1. variable_name
2. bias variance
"""
content = load_from_text_file(filename)
nvar = (content.size-1)/2
self.base_year, self.year = map(lambda x: int(x), content[0].split(' '))
self.variable_names = []
self.ahat = {}
self.v = {}
self.weight_components = {}
self.package_order = package_order
counter = 1
for i in range(nvar):
self.variable_names.append(content[counter])
counter += 1
splitted_row = content[counter].split(' ')
self.ahat[i], self.v[i] = map(lambda x: array([float(x)]), splitted_row)
self.weight_components[i] = array([1.])
counter += 1
self.weights = array([1.])
self.number_of_runs = 1
self.additional_datasets = additional_datasets
def convert_file(self, file_directory, file_name, output_directory):
file_path = os.path.join(file_directory, file_name)
file_stem, extension = os.path.splitext(file_name)
if not os.path.exists(output_directory):
os.makedirs(output_directory)
if extension in self.old_to_new_extension_mapping_for_binary_files():
# Copy file to name with new extension
new_extension = self.old_to_new_extension_mapping_for_binary_files()[extension]
new_file_path = os.path.join(output_directory, "%s%s" % (file_stem, new_extension))
copyfile(file_path, new_file_path)
elif extension == ".txt":
data = load_from_text_file(file_path)
numpy_array = numpy.array(data)
storage = file_flt_storage.storage_file(None)
storage._write_to_file(output_directory, file_stem, numpy_array)
else:
copyfile(file_path, os.path.join(output_directory, file_name))
def convert_file(self, file_directory, file_name, output_directory):
file_path = os.path.join(file_directory, file_name)
file_stem, extension = os.path.splitext(file_name)
if not os.path.exists(output_directory):
os.makedirs(output_directory)
if extension in self.old_to_new_extension_mapping_for_binary_files():
# Copy file to name with new extension
new_extension = self.old_to_new_extension_mapping_for_binary_files(
)[extension]
new_file_path = os.path.join(output_directory,
'%s%s' % (file_stem, new_extension))
copyfile(file_path, new_file_path)
elif extension == '.txt':
data = load_from_text_file(file_path)
numpy_array = numpy.array(data)
storage = file_flt_storage.storage_file(None)
storage._write_to_file(output_directory, file_stem, numpy_array)
else:
copyfile(file_path, os.path.join(output_directory, file_name))
def get_urbansim_last_year(self, config):
self.run_remote_python_process('%s/%s/write_last_urbansim_year.py' % (self.remote_opus_path, self.script_path),
'-d %s -o %s/last_year.txt' % (config['cache_directory'], self.remote_communication_path))
self.copy_file_from_remote_host('last_year.txt', self.local_output_path)
return load_from_text_file('%s/last_year.txt' % self.local_output_path, convert_to_float=True)[0]
def get_urbansim_last_year(self, config):
self.run_remote_python_process('%s/%s/write_last_urbansim_year.py' % (self.remote_opus_path, self.script_path),
'-d %s -o %s/last_year.txt' % (config['cache_directory'], self.remote_communication_path))
self.copy_file_from_remote_host('last_year.txt', self.local_output_path)
return load_from_text_file('%s/last_year.txt' % self.local_output_path, convert_to_float=True)[0]
def _set_cache_set(self, filename):
self.cache_set = load_from_text_file(filename)
self.full_cache_file_name = filename
logger.log_status('Multiple Runs consist of %s runs (loaded from %s)' %
(self.cache_set.size, filename))
def _set_cache_set(self, filename):
self.cache_set = load_from_text_file(filename)
self.full_cache_file_name = filename
logger.log_status('Multiple Runs consist of %s runs (loaded from %s)' % (self.cache_set.size, filename))
def get_weights_from_file(self):
file = os.path.join(self.output_directory, self.weights_file_name)
if not os.path.exists(file):
raise StandardError, "Directory %s must contain a file '%s'. Use method 'compute_weights'." % (self.output_directory,
self.weights_file_name)
return array(load_from_text_file(file, convert_to_float=True))
