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elif method == 'correlation coefficient':
temp_minus_mean = template - np.mean(template)
match_value = np.sum(temp_minus_mean**2)
else:
raise ValueError('Matching method not implemented')
condition = ((np.round(transformed_array, decimals=3)>=match_value*raw_tolerance) &
(np.round(transformed_array, decimals=3)<=match_value*(1./raw_tolerance)))
return np.transpose(condition.nonzero())"
4285,"def normalise_correlation(image_tile_dict, transformed_array, template, normed_tolerance=1):
""""""Calculates the normalisation coefficients of potential match positions
Then normalises the correlation at these positions, and returns them
if they do indeed constitute a match
""""""
template_norm = np.linalg.norm(template)
image_norms = {(x,y):np.linalg.norm(image_tile_dict[(x,y)])*template_norm for (x,y) in image_tile_dict.keys()}
match_points = image_tile_dict.keys()
# for correlation, then need to transofrm back to get correct value for division
h, w = template.shape
#points_from_transformed_array = [(match[0] + h - 1, match[1] + w - 1) for match in match_points]
image_matches_normalised = {match_points[i]:transformed_array[match_points[i][0], match_points[i][1]]/image_norms[match_points[i]] for i in range(len(match_points))}
result = {key:value for key, value in image_matches_normalised.items() if np.round(value, decimals=3) >= normed_tolerance}
return result.keys()"
4286,"def normalise_correlation_coefficient(image_tile_dict, transformed_array, template, normed_tolerance=1):
""""""As above, but for when the correlation coefficient matching method is used
""""""
template_mean = np.mean(template)
template_minus_mean = template - template_mean
template_norm = np.linalg.norm(template_minus_mean)
image_norms = {(x,y):np.linalg.norm(image_tile_dict[(x,y)]- np.mean(image_tile_dict[(x,y)]))*template_norm for (x,y) in image_tile_dict.keys()}
match_points = image_tile_dict.keys()
# for correlation, then need to transofrm back to get correct value for division
h, w = template.shape
image_matches_normalised = {match_points[i]:transformed_array[match_points[i][0], match_points[i][1]]/image_norms[match_points[i]] for i in range(len(match_points))}
normalised_matches = {key:value for key, value in image_matches_normalised.items() if np.round(value, decimals=3) >= normed_tolerance}
return normalised_matches.keys()"
4287,"def calculate_squared_differences(image_tile_dict, transformed_array, template, sq_diff_tolerance=0.1):
""""""As above, but for when the squared differences matching method is used
""""""
template_norm_squared = np.sum(template**2)
image_norms_squared = {(x,y):np.sum(image_tile_dict[(x,y)]**2) for (x,y) in image_tile_dict.keys()}
match_points = image_tile_dict.keys()
# for correlation, then need to transofrm back to get correct value for division
h, w = template.shape
image_matches_normalised = {match_points[i]:-2*transformed_array[match_points[i][0], match_points[i][1]] + image_norms_squared[match_points[i]] + template_norm_squared for i in range(len(match_points))}
#print image_matches_normalised
cutoff = h*w*255**2*sq_diff_tolerance
normalised_matches = {key:value for key, value in image_matches_normalised.items() if np.round(value, decimals=3) <= cutoff}
return normalised_matches.keys()"
4288,"def __init_os_api(self):
""""""
Initialise client objects for talking to OpenStack API.
This is in a separate function so to be called by ``__init__`` and
``__setstate__``.
""""""
loader = loading.get_plugin_loader('password')
auth = loader.load_from_options(auth_url=self._os_auth_url,
username=self._os_username,
password=self._os_password,
project_name=self._os_tenant_name)
sess = session.Session(auth=auth)
self.nova_client = nova_client.Client(self.nova_api_version, session=sess)
self.neutron_client = neutron_client.Client(session=sess)
self.glance_client = glance_client.Client('2', session=sess)
self.cinder_client = cinder_client.Client('2', session=sess)"
4289,"def stop_instance(self, instance_id):
""""""Stops the instance gracefully.
:param str instance_id: instance identifier
""""""
instance = self._load_instance(instance_id)
instance.delete()
del self._instances[instance_id]"
4290,"def get_ips(self, instance_id):
""""""Retrieves all IP addresses associated to a given instance.
:return: tuple (IPs)
""""""
instance = self._load_instance(instance_id)
IPs = sum(instance.networks.values(), [])
return IPs"
4291,"def is_instance_running(self, instance_id):
""""""Checks if the instance is up and running.
:param str instance_id: instance identifier
:return: bool - True if running, False otherwise
""""""
# Here, it's always better if we update the instance.
instance = self._load_instance(instance_id, force_reload=True)
return instance.status == 'ACTIVE'"
4292,"def _check_keypair(self, name, public_key_path, private_key_path):
""""""First checks if the keypair is valid, then checks if the keypair
is registered with on the cloud. If not the keypair is added to the
users ssh keys.
:param str name: name of the ssh key
:param str public_key_path: path to the ssh public key file
:param str private_key_path: path to the ssh private key file