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"""render sample comand line tool. This is invoked interally by ``two4two.blender.render``. """ import json import os from pathlib import Path import sys import bpy # the two4two package is not visible for the blender python. # we therfore add the package directory to the path. blend_dir = os.path.dirname(bpy.data.filepath) package_base_dir = str(Path(__file__).parents[2]) if package_base_dir not in sys.path: sys.path.append(package_base_dir) from two4two._blender.scene import Scene # noqa: E402 from two4two.scene_parameters import SceneParameters # noqa: E402 def _render_files(param_file: str, save_location: str, save_blender_file: str): with open(param_file) as fparam: for line in fparam.readlines(): params = SceneParameters.load(json.loads(line)) scene = Scene(params) image_fname = os.path.join(save_location, params.filename) mask_fname = os.path.join(save_location, params.mask_filename) scene.render(image_fname, mask_fname, ) if save_blender_file == "True": scene.save_blender_file( os.path.join(save_location, f"{params.id}.blender")) if __name__ == '__main__': try: # starts coverage if tests are running # otherwise nothing happens import coverage coverage.process_startup() except ImportError: pass _render_files(sys.argv[-3], sys.argv[-2], sys.argv[-1])
StarcoderdataPython
6635275
<reponame>hldh214/libcloud # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ VMware vCloud driver. """ import copy import sys import re import base64 import os from libcloud.utils.py3 import httplib from libcloud.utils.py3 import urlencode from libcloud.utils.py3 import urlparse from libcloud.utils.py3 import b from libcloud.utils.py3 import next from libcloud.utils.py3 import ET urlparse = urlparse.urlparse import time from xml.parsers.expat import ExpatError from libcloud.common.base import XmlResponse, ConnectionUserAndKey from libcloud.common.types import InvalidCredsError, LibcloudError from libcloud.compute.providers import Provider from libcloud.compute.types import NodeState from libcloud.compute.base import Node, NodeDriver, NodeLocation from libcloud.compute.base import NodeSize, NodeImage """ From vcloud api "The VirtualQuantity element defines the number of MB of memory. This should be either 512 or a multiple of 1024 (1 GB)." """ VIRTUAL_MEMORY_VALS = [512] + [1024 * i for i in range(1, 9)] # Default timeout (in seconds) for long running tasks DEFAULT_TASK_COMPLETION_TIMEOUT = 600 DEFAULT_API_VERSION = '0.8' """ Valid vCloud API v1.5 input values. """ VIRTUAL_CPU_VALS_1_5 = [i for i in range(1, 9)] FENCE_MODE_VALS_1_5 = ['bridged', 'isolated', 'natRouted'] IP_MODE_VALS_1_5 = ['POOL', 'DHCP', 'MANUAL', 'NONE'] def fixxpath(root, xpath): """ElementTree wants namespaces in its xpaths, so here we add them.""" namespace, root_tag = root.tag[1:].split("}", 1) fixed_xpath = "/".join(["{%s}%s" % (namespace, e) for e in xpath.split("/")]) return fixed_xpath def get_url_path(url): return urlparse(url.strip()).path class Vdc(object): """ Virtual datacenter (vDC) representation """ def __init__(self, id, name, driver, allocation_model=None, cpu=None, memory=None, storage=None): self.id = id self.name = name self.driver = driver self.allocation_model = allocation_model self.cpu = cpu self.memory = memory self.storage = storage def __repr__(self): return ('<Vdc: id=%s, name=%s, driver=%s ...>' % (self.id, self.name, self.driver.name)) class Capacity(object): """ Represents CPU, Memory or Storage capacity of vDC. """ def __init__(self, limit, used, units): self.limit = limit self.used = used self.units = units def __repr__(self): return ('<Capacity: limit=%s, used=%s, units=%s>' % (self.limit, self.used, self.units)) class ControlAccess(object): """ Represents control access settings of a node """ class AccessLevel(object): READ_ONLY = 'ReadOnly' CHANGE = 'Change' FULL_CONTROL = 'FullControl' def __init__(self, node, everyone_access_level, subjects=None): self.node = node self.everyone_access_level = everyone_access_level if not subjects: subjects = [] self.subjects = subjects def __repr__(self): return ('<ControlAccess: node=%s, everyone_access_level=%s, ' 'subjects=%s>' % (self.node, self.everyone_access_level, self.subjects)) class Subject(object): """ User or group subject """ def __init__(self, type, name, access_level, id=None): self.type = type self.name = name self.access_level = access_level self.id = id def __repr__(self): return ('<Subject: type=%s, name=%s, access_level=%s>' % (self.type, self.name, self.access_level)) class InstantiateVAppXML(object): def __init__(self, name, template, net_href, cpus, memory, password=<PASSWORD>, row=None, group=None): self.name = name self.template = template self.net_href = net_href self.cpus = cpus self.memory = memory self.password = password self.row = row self.group = group self._build_xmltree() def tostring(self): return ET.tostring(self.root) def _build_xmltree(self): self.root = self._make_instantiation_root() self._add_vapp_template(self.root) instantiation_params = ET.SubElement(self.root, "InstantiationParams") # product and virtual hardware self._make_product_section(instantiation_params) self._make_virtual_hardware(instantiation_params) network_config_section = ET.SubElement(instantiation_params, "NetworkConfigSection") network_config = ET.SubElement(network_config_section, "NetworkConfig") self._add_network_association(network_config) def _make_instantiation_root(self): return ET.Element( "InstantiateVAppTemplateParams", {'name': self.name, 'xml:lang': 'en', 'xmlns': "http://www.vmware.com/vcloud/v0.8", 'xmlns:xsi': "http://www.w3.org/2001/XMLSchema-instance"} ) def _add_vapp_template(self, parent): return ET.SubElement( parent, "VAppTemplate", {'href': self.template} ) def _make_product_section(self, parent): prod_section = ET.SubElement( parent, "ProductSection", {'xmlns:q1': "http://www.vmware.com/vcloud/v0.8", 'xmlns:ovf': "http://schemas.dmtf.org/ovf/envelope/1"} ) if self.password: self._add_property(prod_section, 'password', self.password) if self.row: self._add_property(prod_section, 'row', self.row) if self.group: self._add_property(prod_section, 'group', self.group) return prod_section def _add_property(self, parent, ovfkey, ovfvalue): return ET.SubElement( parent, "Property", {'xmlns': 'http://schemas.dmtf.org/ovf/envelope/1', 'ovf:key': ovfkey, 'ovf:value': ovfvalue} ) def _make_virtual_hardware(self, parent): vh = ET.SubElement( parent, "VirtualHardwareSection", {'xmlns:q1': "http://www.vmware.com/vcloud/v0.8"} ) self._add_cpu(vh) self._add_memory(vh) return vh def _add_cpu(self, parent): cpu_item = ET.SubElement( parent, "Item", {'xmlns': "http://schemas.dmtf.org/ovf/envelope/1"} ) self._add_instance_id(cpu_item, '1') self._add_resource_type(cpu_item, '3') self._add_virtual_quantity(cpu_item, self.cpus) return cpu_item def _add_memory(self, parent): mem_item = ET.SubElement( parent, 'Item', {'xmlns': "http://schemas.dmtf.org/ovf/envelope/1"} ) self._add_instance_id(mem_item, '2') self._add_resource_type(mem_item, '4') self._add_virtual_quantity(mem_item, self.memory) return mem_item def _add_instance_id(self, parent, id): elm = ET.SubElement( parent, 'InstanceID', {'xmlns': 'http://schemas.dmtf.org/wbem/wscim/1/cim-schema/2/' 'CIM_ResourceAllocationSettingData'} ) elm.text = id return elm def _add_resource_type(self, parent, type): elm = ET.SubElement( parent, 'ResourceType', {'xmlns': 'http://schemas.dmtf.org/wbem/wscim/1/cim-schema/2/' 'CIM_ResourceAllocationSettingData'} ) elm.text = type return elm def _add_virtual_quantity(self, parent, amount): elm = ET.SubElement( parent, 'VirtualQuantity', {'xmlns': 'http://schemas.dmtf.org/wbem/wscim/1/cim-schema/2/' 'CIM_ResourceAllocationSettingData'} ) elm.text = amount return elm def _add_network_association(self, parent): return ET.SubElement( parent, 'NetworkAssociation', {'href': self.net_href} ) class VCloudResponse(XmlResponse): def success(self): return self.status in (httplib.OK, httplib.CREATED, httplib.NO_CONTENT, httplib.ACCEPTED) class VCloudConnection(ConnectionUserAndKey): """ Connection class for the vCloud driver """ responseCls = VCloudResponse token = None host = None def request(self, *args, **kwargs): self._get_auth_token() return super(VCloudConnection, self).request(*args, **kwargs) def check_org(self): # the only way to get our org is by logging in. self._get_auth_token() def _get_auth_headers(self): """Some providers need different headers than others""" return { 'Authorization': "Basic %s" % base64.b64encode( b('%s:%s' % (self.user_id, self.key))).decode('utf-8'), 'Content-Length': '0', 'Accept': 'application/*+xml' } def _get_auth_token(self): if not self.token: self.connection.request(method='POST', url='/api/v0.8/login', headers=self._get_auth_headers()) resp = self.connection.getresponse() headers = resp.headers body = ET.XML(resp.text) try: self.token = headers['set-cookie'] except KeyError: raise InvalidCredsError() self.driver.org = get_url_path( body.find(fixxpath(body, 'Org')).get('href') ) def add_default_headers(self, headers): headers['Cookie'] = self.token headers['Accept'] = 'application/*+xml' return headers class VCloudNodeDriver(NodeDriver): """ vCloud node driver """ type = Provider.VCLOUD name = 'vCloud' website = 'http://www.vmware.com/products/vcloud/' connectionCls = VCloudConnection org = None _vdcs = None NODE_STATE_MAP = {'0': NodeState.PENDING, '1': NodeState.PENDING, '2': NodeState.PENDING, '3': NodeState.PENDING, '4': NodeState.RUNNING} features = {'create_node': ['password']} def __new__(cls, key, secret=None, secure=True, host=None, port=None, api_version=DEFAULT_API_VERSION, **kwargs): if cls is VCloudNodeDriver: if api_version == '0.8': cls = VCloudNodeDriver elif api_version == '1.5': cls = VCloud_1_5_NodeDriver elif api_version == '5.1': cls = VCloud_5_1_NodeDriver elif api_version == '5.5': cls = VCloud_5_5_NodeDriver else: raise NotImplementedError( "No VCloudNodeDriver found for API version %s" % (api_version)) return super(VCloudNodeDriver, cls).__new__(cls) @property def vdcs(self): """ vCloud virtual data centers (vDCs). :return: list of vDC objects :rtype: ``list`` of :class:`Vdc` """ if not self._vdcs: self.connection.check_org() # make sure the org is set. res = self.connection.request(self.org) self._vdcs = [ self._to_vdc( self.connection.request(get_url_path(i.get('href'))).object ) for i in res.object.findall(fixxpath(res.object, "Link")) if i.get('type') == 'application/vnd.vmware.vcloud.vdc+xml' ] return self._vdcs def _to_vdc(self, vdc_elm): return Vdc(vdc_elm.get('href'), vdc_elm.get('name'), self) def _get_vdc(self, vdc_name): vdc = None if not vdc_name: # Return the first organisation VDC found vdc = self.vdcs[0] else: for v in self.vdcs: if v.name == vdc_name: vdc = v if vdc is None: raise ValueError('%s virtual data centre could not be found', vdc_name) return vdc @property def networks(self): networks = [] for vdc in self.vdcs: res = self.connection.request(get_url_path(vdc.id)).object networks.extend( [network for network in res.findall( fixxpath(res, 'AvailableNetworks/Network') )] ) return networks def _to_image(self, image): image = NodeImage(id=image.get('href'), name=image.get('name'), driver=self.connection.driver) return image def _to_node(self, elm): state = self.NODE_STATE_MAP[elm.get('status')] name = elm.get('name') public_ips = [] private_ips = [] # Following code to find private IPs works for Terremark connections = elm.findall('%s/%s' % ( '{http://schemas.dmtf.org/ovf/envelope/1}NetworkConnectionSection', fixxpath(elm, 'NetworkConnection')) ) if not connections: connections = elm.findall( fixxpath( elm, 'Children/Vm/NetworkConnectionSection/NetworkConnection')) for connection in connections: ips = [ip.text for ip in connection.findall(fixxpath(elm, "IpAddress"))] if connection.get('Network') == 'Internal': private_ips.extend(ips) else: public_ips.extend(ips) node = Node(id=elm.get('href'), name=name, state=state, public_ips=public_ips, private_ips=private_ips, driver=self.connection.driver) return node def _get_catalog_hrefs(self): res = self.connection.request(self.org) catalogs = [ i.get('href') for i in res.object.findall(fixxpath(res.object, "Link")) if i.get('type') == 'application/vnd.vmware.vcloud.catalog+xml' ] return catalogs def _wait_for_task_completion(self, task_href, timeout=DEFAULT_TASK_COMPLETION_TIMEOUT): start_time = time.time() res = self.connection.request(get_url_path(task_href)) status = res.object.get('status') while status != 'success': if status == 'error': # Get error reason from the response body error_elem = res.object.find(fixxpath(res.object, 'Error')) error_msg = "Unknown error" if error_elem is not None: error_msg = error_elem.get('message') raise Exception("Error status returned by task %s.: %s" % (task_href, error_msg)) if status == 'canceled': raise Exception("Canceled status returned by task %s." % task_href) if (time.time() - start_time >= timeout): raise Exception("Timeout (%s sec) while waiting for task %s." % (timeout, task_href)) time.sleep(5) res = self.connection.request(get_url_path(task_href)) status = res.object.get('status') def destroy_node(self, node): node_path = get_url_path(node.id) # blindly poweroff node, it will throw an exception if already off try: res = self.connection.request('%s/power/action/poweroff' % node_path, method='POST') self._wait_for_task_completion(res.object.get('href')) except Exception: pass try: res = self.connection.request('%s/action/undeploy' % node_path, method='POST') self._wait_for_task_completion(res.object.get('href')) except ExpatError: # The undeploy response is malformed XML atm. # We can remove this whent he providers fix the problem. pass except Exception: # Some vendors don't implement undeploy at all yet, # so catch this and move on. pass res = self.connection.request(node_path, method='DELETE') return res.status == httplib.ACCEPTED def reboot_node(self, node): res = self.connection.request('%s/power/action/reset' % get_url_path(node.id), method='POST') return res.status in [httplib.ACCEPTED, httplib.NO_CONTENT] def list_nodes(self): return self.ex_list_nodes() def ex_list_nodes(self, vdcs=None): """ List all nodes across all vDCs. Using 'vdcs' you can specify which vDCs should be queried. :param vdcs: None, vDC or a list of vDCs to query. If None all vDCs will be queried. :type vdcs: :class:`Vdc` :rtype: ``list`` of :class:`Node` """ if not vdcs: vdcs = self.vdcs if not isinstance(vdcs, (list, tuple)): vdcs = [vdcs] nodes = [] for vdc in vdcs: res = self.connection.request(get_url_path(vdc.id)) elms = res.object.findall(fixxpath( res.object, "ResourceEntities/ResourceEntity") ) vapps = [ (i.get('name'), i.get('href')) for i in elms if i.get('type') == 'application/vnd.vmware.vcloud.vApp+xml' and i.get('name') ] for vapp_name, vapp_href in vapps: try: res = self.connection.request( get_url_path(vapp_href), headers={'Content-Type': 'application/vnd.vmware.vcloud.vApp+xml'} ) nodes.append(self._to_node(res.object)) except Exception: # The vApp was probably removed since the previous vDC # query, ignore e = sys.exc_info()[1] if not (e.args[0].tag.endswith('Error') and e.args[0].get('minorErrorCode') == 'ACCESS_TO_RESOURCE_IS_FORBIDDEN'): raise return nodes def _to_size(self, ram): ns = NodeSize( id=None, name="%s Ram" % ram, ram=ram, disk=None, bandwidth=None, price=None, driver=self.connection.driver ) return ns def list_sizes(self, location=None): sizes = [self._to_size(i) for i in VIRTUAL_MEMORY_VALS] return sizes def _get_catalogitems_hrefs(self, catalog): """Given a catalog href returns contained catalog item hrefs""" res = self.connection.request( get_url_path(catalog), headers={ 'Content-Type': 'application/vnd.vmware.vcloud.catalog+xml' } ).object cat_items = res.findall(fixxpath(res, "CatalogItems/CatalogItem")) cat_item_hrefs = [i.get('href') for i in cat_items if i.get('type') == 'application/vnd.vmware.vcloud.catalogItem+xml'] return cat_item_hrefs def _get_catalogitem(self, catalog_item): """Given a catalog item href returns elementree""" res = self.connection.request( get_url_path(catalog_item), headers={ 'Content-Type': 'application/vnd.vmware.vcloud.catalogItem+xml' } ).object return res def list_images(self, location=None): images = [] for vdc in self.vdcs: res = self.connection.request(get_url_path(vdc.id)).object res_ents = res.findall(fixxpath( res, "ResourceEntities/ResourceEntity") ) images += [ self._to_image(i) for i in res_ents if i.get('type') == 'application/vnd.vmware.vcloud.vAppTemplate+xml' ] for catalog in self._get_catalog_hrefs(): for cat_item in self._get_catalogitems_hrefs(catalog): res = self._get_catalogitem(cat_item) res_ents = res.findall(fixxpath(res, 'Entity')) images += [ self._to_image(i) for i in res_ents if i.get('type') == 'application/vnd.vmware.vcloud.vAppTemplate+xml' ] def idfun(image): return image.id return self._uniquer(images, idfun) def _uniquer(self, seq, idfun=None): if idfun is None: def idfun(x): return x seen = {} result = [] for item in seq: marker = idfun(item) if marker in seen: continue seen[marker] = 1 result.append(item) return result def create_node(self, **kwargs): """ Creates and returns node. :keyword ex_network: link to a "Network" e.g., ``https://services.vcloudexpress...`` :type ex_network: ``str`` :keyword ex_vdc: Name of organisation's virtual data center where vApp VMs will be deployed. :type ex_vdc: ``str`` :keyword ex_cpus: number of virtual cpus (limit depends on provider) :type ex_cpus: ``int`` :type ex_row: ``str`` :type ex_group: ``str`` """ name = kwargs['name'] image = kwargs['image'] size = kwargs['size'] # Some providers don't require a network link try: network = kwargs.get('ex_network', self.networks[0].get('href')) except IndexError: network = '' password = <PASSWORD> auth = self._get_and_check_auth(kwargs.get('auth')) password = <PASSWORD> instantiate_xml = InstantiateVAppXML( name=name, template=image.id, net_href=network, cpus=str(kwargs.get('ex_cpus', 1)), memory=str(size.ram), password=password, row=kwargs.get('ex_row', None), group=kwargs.get('ex_group', None) ) vdc = self._get_vdc(kwargs.get('ex_vdc', None)) # Instantiate VM and get identifier. content_type = \ 'application/vnd.vmware.vcloud.instantiateVAppTemplateParams+xml' res = self.connection.request( '%s/action/instantiateVAppTemplate' % get_url_path(vdc.id), data=instantiate_xml.tostring(), method='POST', headers={'Content-Type': content_type} ) vapp_path = get_url_path(res.object.get('href')) # Deploy the VM from the identifier. res = self.connection.request('%s/action/deploy' % vapp_path, method='POST') self._wait_for_task_completion(res.object.get('href')) # Power on the VM. res = self.connection.request('%s/power/action/powerOn' % vapp_path, method='POST') res = self.connection.request(vapp_path) node = self._to_node(res.object) if getattr(auth, "generated", False): node.extra['password'] = auth.password return node class HostingComConnection(VCloudConnection): """ vCloud connection subclass for Hosting.com """ host = "vcloud.safesecureweb.com" def _get_auth_headers(self): """hosting.com doesn't follow the standard vCloud authentication API""" return { 'Authentication': base64.b64encode(b('%s:%s' % (self.user_id, self.key))), 'Content-Length': '0' } class HostingComDriver(VCloudNodeDriver): """ vCloud node driver for Hosting.com """ connectionCls = HostingComConnection class TerremarkConnection(VCloudConnection): """ vCloud connection subclass for Terremark """ host = "services.vcloudexpress.terremark.com" class TerremarkDriver(VCloudNodeDriver): """ vCloud node driver for Terremark """ connectionCls = TerremarkConnection def list_locations(self): return [NodeLocation(0, "Terremark Texas", 'US', self)] class VCloud_1_5_Connection(VCloudConnection): def _get_auth_headers(self): """Compatibility for using v1.5 API under vCloud Director 5.1""" return { 'Authorization': "Basic %s" % base64.b64encode( b('%s:%s' % (self.user_id, self.key))).decode('utf-8'), 'Content-Length': '0', 'Accept': 'application/*+xml;version=1.5' } def _get_auth_token(self): if not self.token: # Log In self.connection.request(method='POST', url='/api/sessions', headers=self._get_auth_headers()) resp = self.connection.getresponse() headers = resp.headers # Set authorization token try: self.token = headers['x-vcloud-authorization'] except KeyError: raise InvalidCredsError() # Get the URL of the Organization body = ET.XML(resp.text) self.org_name = body.get('org') org_list_url = get_url_path( next((link for link in body.findall(fixxpath(body, 'Link')) if link.get('type') == 'application/vnd.vmware.vcloud.orgList+xml')).get('href') ) if self.proxy_url is not None: self.connection.set_http_proxy(self.proxy_url) self.connection.request(method='GET', url=org_list_url, headers=self.add_default_headers({})) body = ET.XML(self.connection.getresponse().text) self.driver.org = get_url_path( next((org for org in body.findall(fixxpath(body, 'Org')) if org.get('name') == self.org_name)).get('href') ) def add_default_headers(self, headers): headers['Accept'] = 'application/*+xml;version=1.5' headers['x-vcloud-authorization'] = self.token return headers class VCloud_5_5_Connection(VCloud_1_5_Connection): def add_default_headers(self, headers): headers['Accept'] = 'application/*+xml;version=5.5' headers['x-vcloud-authorization'] = self.token return headers class Instantiate_1_5_VAppXML(object): def __init__(self, name, template, network, vm_network=None, vm_fence=None): self.name = name self.template = template self.network = network self.vm_network = vm_network self.vm_fence = vm_fence self._build_xmltree() def tostring(self): return ET.tostring(self.root) def _build_xmltree(self): self.root = self._make_instantiation_root() if self.network is not None: instantionation_params = ET.SubElement(self.root, 'InstantiationParams') network_config_section = ET.SubElement(instantionation_params, 'NetworkConfigSection') ET.SubElement( network_config_section, 'Info', {'xmlns': 'http://schemas.dmtf.org/ovf/envelope/1'} ) network_config = ET.SubElement(network_config_section, 'NetworkConfig') self._add_network_association(network_config) self._add_vapp_template(self.root) def _make_instantiation_root(self): return ET.Element( 'InstantiateVAppTemplateParams', {'name': self.name, 'deploy': 'false', 'powerOn': 'false', 'xml:lang': 'en', 'xmlns': 'http://www.vmware.com/vcloud/v1.5', 'xmlns:xsi': 'http://www.w3.org/2001/XMLSchema-instance'} ) def _add_vapp_template(self, parent): return ET.SubElement( parent, 'Source', {'href': self.template} ) def _add_network_association(self, parent): if self.vm_network is None: # Don't set a custom vApp VM network name parent.set('networkName', self.network.get('name')) else: # Set a custom vApp VM network name parent.set('networkName', self.vm_network) configuration = ET.SubElement(parent, 'Configuration') ET.SubElement(configuration, 'ParentNetwork', {'href': self.network.get('href')}) if self.vm_fence is None: fencemode = self.network.find(fixxpath(self.network, 'Configuration/FenceMode')).text else: fencemode = self.vm_fence ET.SubElement(configuration, 'FenceMode').text = fencemode class VCloud_1_5_NodeDriver(VCloudNodeDriver): connectionCls = VCloud_1_5_Connection # Based on # http://pubs.vmware.com/vcloud-api-1-5/api_prog/ # GUID-843BE3AD-5EF6-4442-B864-BCAE44A51867.html NODE_STATE_MAP = {'-1': NodeState.UNKNOWN, '0': NodeState.PENDING, '1': NodeState.PENDING, '2': NodeState.PENDING, '3': NodeState.PENDING, '4': NodeState.RUNNING, '5': NodeState.RUNNING, '6': NodeState.UNKNOWN, '7': NodeState.UNKNOWN, '8': NodeState.STOPPED, '9': NodeState.UNKNOWN, '10': NodeState.UNKNOWN} def list_locations(self): return [NodeLocation(id=self.connection.host, name=self.connection.host, country="N/A", driver=self)] def ex_find_node(self, node_name, vdcs=None): """ Searches for node across specified vDCs. This is more effective than querying all nodes to get a single instance. :param node_name: The name of the node to search for :type node_name: ``str`` :param vdcs: None, vDC or a list of vDCs to search in. If None all vDCs will be searched. :type vdcs: :class:`Vdc` :return: node instance or None if not found :rtype: :class:`Node` or ``None`` """ if not vdcs: vdcs = self.vdcs if not getattr(vdcs, '__iter__', False): vdcs = [vdcs] for vdc in vdcs: res = self.connection.request(get_url_path(vdc.id)) xpath = fixxpath(res.object, "ResourceEntities/ResourceEntity") entity_elems = res.object.findall(xpath) for entity_elem in entity_elems: if entity_elem.get('type') == \ 'application/vnd.vmware.vcloud.vApp+xml' and \ entity_elem.get('name') == node_name: path = get_url_path(entity_elem.get('href')) headers = {'Content-Type': 'application/vnd.vmware.vcloud.vApp+xml'} res = self.connection.request(path, headers=headers) return self._to_node(res.object) return None def destroy_node(self, node): try: self.ex_undeploy_node(node) except Exception: # Some vendors don't implement undeploy at all yet, # so catch this and move on. pass res = self.connection.request(get_url_path(node.id), method='DELETE') return res.status == httplib.ACCEPTED def reboot_node(self, node): res = self.connection.request('%s/power/action/reset' % get_url_path(node.id), method='POST') if res.status in [httplib.ACCEPTED, httplib.NO_CONTENT]: self._wait_for_task_completion(res.object.get('href')) return True else: return False def ex_deploy_node(self, node, ex_force_customization=False): """ Deploys existing node. Equal to vApp "start" operation. :param node: The node to be deployed :type node: :class:`Node` :param ex_force_customization: Used to specify whether to force customization on deployment, if not set default value is False. :type ex_force_customization: ``bool`` :rtype: :class:`Node` """ if ex_force_customization: vms = self._get_vm_elements(node.id) for vm in vms: self._ex_deploy_node_or_vm(vm.get('href'), ex_force_customization=True) else: self._ex_deploy_node_or_vm(node.id) res = self.connection.request(get_url_path(node.id)) return self._to_node(res.object) def _ex_deploy_node_or_vm(self, vapp_or_vm_path, ex_force_customization=False): data = {'powerOn': 'true', 'forceCustomization': str(ex_force_customization).lower(), 'xmlns': 'http://www.vmware.com/vcloud/v1.5'} deploy_xml = ET.Element('DeployVAppParams', data) path = get_url_path(vapp_or_vm_path) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.deployVAppParams+xml' } res = self.connection.request('%s/action/deploy' % path, data=ET.tostring(deploy_xml), method='POST', headers=headers) self._wait_for_task_completion(res.object.get('href')) def ex_undeploy_node(self, node): """ Undeploys existing node. Equal to vApp "stop" operation. :param node: The node to be deployed :type node: :class:`Node` :rtype: :class:`Node` """ data = {'xmlns': 'http://www.vmware.com/vcloud/v1.5'} undeploy_xml = ET.Element('UndeployVAppParams', data) undeploy_power_action_xml = ET.SubElement(undeploy_xml, 'UndeployPowerAction') undeploy_power_action_xml.text = 'shutdown' headers = { 'Content-Type': 'application/vnd.vmware.vcloud.undeployVAppParams+xml' } try: res = self.connection.request( '%s/action/undeploy' % get_url_path(node.id), data=ET.tostring(undeploy_xml), method='POST', headers=headers) self._wait_for_task_completion(res.object.get('href')) except Exception: undeploy_power_action_xml.text = 'powerOff' res = self.connection.request( '%s/action/undeploy' % get_url_path(node.id), data=ET.tostring(undeploy_xml), method='POST', headers=headers) self._wait_for_task_completion(res.object.get('href')) res = self.connection.request(get_url_path(node.id)) return self._to_node(res.object) def ex_power_off_node(self, node): """ Powers on all VMs under specified node. VMs need to be This operation is allowed only when the vApp/VM is powered on. :param node: The node to be powered off :type node: :class:`Node` :rtype: :class:`Node` """ return self._perform_power_operation(node, 'powerOff') def ex_power_on_node(self, node): """ Powers on all VMs under specified node. This operation is allowed only when the vApp/VM is powered off or suspended. :param node: The node to be powered on :type node: :class:`Node` :rtype: :class:`Node` """ return self._perform_power_operation(node, 'powerOn') def ex_shutdown_node(self, node): """ Shutdowns all VMs under specified node. This operation is allowed only when the vApp/VM is powered on. :param node: The node to be shut down :type node: :class:`Node` :rtype: :class:`Node` """ return self._perform_power_operation(node, 'shutdown') def ex_suspend_node(self, node): """ Suspends all VMs under specified node. This operation is allowed only when the vApp/VM is powered on. :param node: The node to be suspended :type node: :class:`Node` :rtype: :class:`Node` """ return self._perform_power_operation(node, 'suspend') def _perform_power_operation(self, node, operation): res = self.connection.request( '%s/power/action/%s' % (get_url_path(node.id), operation), method='POST') self._wait_for_task_completion(res.object.get('href')) res = self.connection.request(get_url_path(node.id)) return self._to_node(res.object) def ex_get_control_access(self, node): """ Returns the control access settings for specified node. :param node: node to get the control access for :type node: :class:`Node` :rtype: :class:`ControlAccess` """ res = self.connection.request( '%s/controlAccess' % get_url_path(node.id)) everyone_access_level = None is_shared_elem = res.object.find( fixxpath(res.object, "IsSharedToEveryone")) if is_shared_elem is not None and is_shared_elem.text == 'true': everyone_access_level = res.object.find( fixxpath(res.object, "EveryoneAccessLevel")).text # Parse all subjects subjects = [] xpath = fixxpath(res.object, "AccessSettings/AccessSetting") for elem in res.object.findall(xpath): access_level = elem.find(fixxpath(res.object, "AccessLevel")).text subject_elem = elem.find(fixxpath(res.object, "Subject")) if subject_elem.get('type') == \ 'application/vnd.vmware.admin.group+xml': subj_type = 'group' else: subj_type = 'user' path = get_url_path(subject_elem.get('href')) res = self.connection.request(path) name = res.object.get('name') subject = Subject(type=subj_type, name=name, access_level=access_level, id=subject_elem.get('href')) subjects.append(subject) return ControlAccess(node, everyone_access_level, subjects) def ex_set_control_access(self, node, control_access): """ Sets control access for the specified node. :param node: node :type node: :class:`Node` :param control_access: control access settings :type control_access: :class:`ControlAccess` :rtype: ``None`` """ xml = ET.Element('ControlAccessParams', {'xmlns': 'http://www.vmware.com/vcloud/v1.5'}) shared_to_everyone = ET.SubElement(xml, 'IsSharedToEveryone') if control_access.everyone_access_level: shared_to_everyone.text = 'true' everyone_access_level = ET.SubElement(xml, 'EveryoneAccessLevel') everyone_access_level.text = control_access.everyone_access_level else: shared_to_everyone.text = 'false' # Set subjects if control_access.subjects: access_settings_elem = ET.SubElement(xml, 'AccessSettings') for subject in control_access.subjects: setting = ET.SubElement(access_settings_elem, 'AccessSetting') if subject.id: href = subject.id else: res = self.ex_query(type=subject.type, filter='name==' + subject.name) if not res: raise LibcloudError('Specified subject "%s %s" not found ' % (subject.type, subject.name)) href = res[0]['href'] ET.SubElement(setting, 'Subject', {'href': href}) ET.SubElement(setting, 'AccessLevel').text = subject.access_level headers = { 'Content-Type': 'application/vnd.vmware.vcloud.controlAccess+xml' } self.connection.request( '%s/action/controlAccess' % get_url_path(node.id), data=ET.tostring(xml), headers=headers, method='POST') def ex_get_metadata(self, node): """ :param node: node :type node: :class:`Node` :return: dictionary mapping metadata keys to metadata values :rtype: dictionary mapping ``str`` to ``str`` """ res = self.connection.request('%s/metadata' % (get_url_path(node.id))) xpath = fixxpath(res.object, 'MetadataEntry') metadata_entries = res.object.findall(xpath) res_dict = {} for entry in metadata_entries: key = entry.findtext(fixxpath(res.object, 'Key')) value = entry.findtext(fixxpath(res.object, 'Value')) res_dict[key] = value return res_dict def ex_set_metadata_entry(self, node, key, value): """ :param node: node :type node: :class:`Node` :param key: metadata key to be set :type key: ``str`` :param value: metadata value to be set :type value: ``str`` :rtype: ``None`` """ metadata_elem = ET.Element( 'Metadata', {'xmlns': "http://www.vmware.com/vcloud/v1.5", 'xmlns:xsi': "http://www.w3.org/2001/XMLSchema-instance"} ) entry = ET.SubElement(metadata_elem, 'MetadataEntry') key_elem = ET.SubElement(entry, 'Key') key_elem.text = key value_elem = ET.SubElement(entry, 'Value') value_elem.text = value # send it back to the server res = self.connection.request( '%s/metadata' % get_url_path(node.id), data=ET.tostring(metadata_elem), headers={ 'Content-Type': 'application/vnd.vmware.vcloud.metadata+xml' }, method='POST') self._wait_for_task_completion(res.object.get('href')) def ex_query(self, type, filter=None, page=1, page_size=100, sort_asc=None, sort_desc=None): """ Queries vCloud for specified type. See http://www.vmware.com/pdf/vcd_15_api_guide.pdf for details. Each element of the returned list is a dictionary with all attributes from the record. :param type: type to query (r.g. user, group, vApp etc.) :type type: ``str`` :param filter: filter expression (see documentation for syntax) :type filter: ``str`` :param page: page number :type page: ``int`` :param page_size: page size :type page_size: ``int`` :param sort_asc: sort in ascending order by specified field :type sort_asc: ``str`` :param sort_desc: sort in descending order by specified field :type sort_desc: ``str`` :rtype: ``list`` of dict """ # This is a workaround for filter parameter encoding # the urllib encodes (name==Developers%20Only) into # %28name%3D%3DDevelopers%20Only%29) which is not accepted by vCloud params = { 'type': type, 'pageSize': page_size, 'page': page, } if sort_asc: params['sortAsc'] = sort_asc if sort_desc: params['sortDesc'] = sort_desc url = '/api/query?' + urlencode(params) if filter: if not filter.startswith('('): filter = '(' + filter + ')' url += '&filter=' + filter.replace(' ', '+') results = [] res = self.connection.request(url) for elem in res.object: if not elem.tag.endswith('Link'): result = elem.attrib result['type'] = elem.tag.split('}')[1] results.append(result) return results def create_node(self, **kwargs): """ Creates and returns node. If the source image is: - vApp template - a new vApp is instantiated from template - existing vApp - a new vApp is cloned from the source vApp. Can not clone more vApps is parallel otherwise resource busy error is raised. @inherits: :class:`NodeDriver.create_node` :keyword image: OS Image to boot on node. (required). Can be a NodeImage or existing Node that will be cloned. :type image: :class:`NodeImage` or :class:`Node` :keyword ex_network: Organisation's network name for attaching vApp VMs to. :type ex_network: ``str`` :keyword ex_vdc: Name of organisation's virtual data center where vApp VMs will be deployed. :type ex_vdc: ``str`` :keyword ex_vm_names: list of names to be used as a VM and computer name. The name must be max. 15 characters long and follow the host name requirements. :type ex_vm_names: ``list`` of ``str`` :keyword ex_vm_cpu: number of virtual CPUs/cores to allocate for each vApp VM. :type ex_vm_cpu: ``int`` :keyword ex_vm_memory: amount of memory in MB to allocate for each vApp VM. :type ex_vm_memory: ``int`` :keyword ex_vm_script: full path to file containing guest customisation script for each vApp VM. Useful for creating users & pushing out public SSH keys etc. :type ex_vm_script: ``str`` :keyword ex_vm_network: Override default vApp VM network name. Useful for when you've imported an OVF originating from outside of the vCloud. :type ex_vm_network: ``str`` :keyword ex_vm_fence: Fence mode for connecting the vApp VM network (ex_vm_network) to the parent organisation network (ex_network). :type ex_vm_fence: ``str`` :keyword ex_vm_ipmode: IP address allocation mode for all vApp VM network connections. :type ex_vm_ipmode: ``str`` :keyword ex_deploy: set to False if the node shouldn't be deployed (started) after creation :type ex_deploy: ``bool`` :keyword ex_force_customization: Used to specify whether to force customization on deployment, if not set default value is False. :type ex_force_customization: ``bool`` :keyword ex_clone_timeout: timeout in seconds for clone/instantiate VM operation. Cloning might be a time consuming operation especially when linked clones are disabled or VMs are created on different datastores. Overrides the default task completion value. :type ex_clone_timeout: ``int`` :keyword ex_admin_password: set the node admin password explicitly. :type ex_admin_password: ``str`` """ name = kwargs['name'] image = kwargs['image'] ex_vm_names = kwargs.get('ex_vm_names') ex_vm_cpu = kwargs.get('ex_vm_cpu') ex_vm_memory = kwargs.get('ex_vm_memory') ex_vm_script = kwargs.get('ex_vm_script') ex_vm_fence = kwargs.get('ex_vm_fence', None) ex_network = kwargs.get('ex_network', None) ex_vm_network = kwargs.get('ex_vm_network', None) ex_vm_ipmode = kwargs.get('ex_vm_ipmode', None) ex_deploy = kwargs.get('ex_deploy', True) ex_force_customization = kwargs.get('ex_force_customization', False) ex_vdc = kwargs.get('ex_vdc', None) ex_clone_timeout = kwargs.get('ex_clone_timeout', DEFAULT_TASK_COMPLETION_TIMEOUT) ex_admin_password = kwargs.get('ex_admin_password', None) self._validate_vm_names(ex_vm_names) self._validate_vm_cpu(ex_vm_cpu) self._validate_vm_memory(ex_vm_memory) self._validate_vm_fence(ex_vm_fence) self._validate_vm_ipmode(ex_vm_ipmode) ex_vm_script = self._validate_vm_script(ex_vm_script) # Some providers don't require a network link if ex_network: network_href = self._get_network_href(ex_network) network_elem = self.connection.request( get_url_path(network_href)).object else: network_elem = None vdc = self._get_vdc(ex_vdc) if self._is_node(image): vapp_name, vapp_href = self._clone_node(name, image, vdc, ex_clone_timeout) else: vapp_name, vapp_href = self._instantiate_node(name, image, network_elem, vdc, ex_vm_network, ex_vm_fence, ex_clone_timeout) self._change_vm_names(vapp_href, ex_vm_names) self._change_vm_cpu(vapp_href, ex_vm_cpu) self._change_vm_memory(vapp_href, ex_vm_memory) self._change_vm_script(vapp_href, ex_vm_script) self._change_vm_ipmode(vapp_href, ex_vm_ipmode) if ex_admin_password is not None: self.ex_change_vm_admin_password(vapp_href, ex_admin_password) # Power on the VM. if ex_deploy: res = self.connection.request(get_url_path(vapp_href)) node = self._to_node(res.object) # Retry 3 times: when instantiating large number of VMs at the same # time some may fail on resource allocation retry = 3 while True: try: self.ex_deploy_node(node, ex_force_customization) break except Exception: if retry <= 0: raise retry -= 1 time.sleep(10) res = self.connection.request(get_url_path(vapp_href)) node = self._to_node(res.object) return node def _instantiate_node(self, name, image, network_elem, vdc, vm_network, vm_fence, instantiate_timeout): instantiate_xml = Instantiate_1_5_VAppXML( name=name, template=image.id, network=network_elem, vm_network=vm_network, vm_fence=vm_fence ) # Instantiate VM and get identifier. headers = { 'Content-Type': 'application/vnd.vmware.vcloud.instantiateVAppTemplateParams+xml' } res = self.connection.request( '%s/action/instantiateVAppTemplate' % get_url_path(vdc.id), data=instantiate_xml.tostring(), method='POST', headers=headers ) vapp_name = res.object.get('name') vapp_href = res.object.get('href') task_href = res.object.find(fixxpath(res.object, "Tasks/Task")).get( 'href') self._wait_for_task_completion(task_href, instantiate_timeout) return vapp_name, vapp_href def _clone_node(self, name, sourceNode, vdc, clone_timeout): clone_xml = ET.Element( "CloneVAppParams", {'name': name, 'deploy': 'false', 'powerOn': 'false', 'xmlns': "http://www.vmware.com/vcloud/v1.5", 'xmlns:xsi': "http://www.w3.org/2001/XMLSchema-instance"} ) ET.SubElement(clone_xml, 'Description').text = 'Clone of ' + sourceNode.name ET.SubElement(clone_xml, 'Source', {'href': sourceNode.id}) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.cloneVAppParams+xml' } res = self.connection.request( '%s/action/cloneVApp' % get_url_path(vdc.id), data=ET.tostring(clone_xml), method='POST', headers=headers ) vapp_name = res.object.get('name') vapp_href = res.object.get('href') task_href = res.object.find( fixxpath(res.object, "Tasks/Task")).get('href') self._wait_for_task_completion(task_href, clone_timeout) res = self.connection.request(get_url_path(vapp_href)) vms = res.object.findall(fixxpath(res.object, "Children/Vm")) # Fix the networking for VMs for i, vm in enumerate(vms): # Remove network network_xml = ET.Element("NetworkConnectionSection", { 'ovf:required': 'false', 'xmlns': "http://www.vmware.com/vcloud/v1.5", 'xmlns:ovf': 'http://schemas.dmtf.org/ovf/envelope/1'}) ET.SubElement(network_xml, "ovf:Info").text = \ 'Specifies the available VM network connections' headers = { 'Content-Type': 'application/vnd.vmware.vcloud.networkConnectionSection+xml' } res = self.connection.request( '%s/networkConnectionSection' % get_url_path(vm.get('href')), data=ET.tostring(network_xml), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) # Re-add network network_xml = vm.find(fixxpath(vm, 'NetworkConnectionSection')) network_conn_xml = network_xml.find( fixxpath(network_xml, 'NetworkConnection')) network_conn_xml.set('needsCustomization', 'true') network_conn_xml.remove( network_conn_xml.find(fixxpath(network_xml, 'IpAddress'))) network_conn_xml.remove( network_conn_xml.find(fixxpath(network_xml, 'MACAddress'))) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.networkConnectionSection+xml' } res = self.connection.request( '%s/networkConnectionSection' % get_url_path(vm.get('href')), data=ET.tostring(network_xml), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) return vapp_name, vapp_href def ex_set_vm_cpu(self, vapp_or_vm_id, vm_cpu): """ Sets the number of virtual CPUs for the specified VM or VMs under the vApp. If the vapp_or_vm_id param represents a link to an vApp all VMs that are attached to this vApp will be modified. Please ensure that hot-adding a virtual CPU is enabled for the powered on virtual machines. Otherwise use this method on undeployed vApp. :keyword vapp_or_vm_id: vApp or VM ID that will be modified. If a vApp ID is used here all attached VMs will be modified :type vapp_or_vm_id: ``str`` :keyword vm_cpu: number of virtual CPUs/cores to allocate for specified VMs :type vm_cpu: ``int`` :rtype: ``None`` """ self._validate_vm_cpu(vm_cpu) self._change_vm_cpu(vapp_or_vm_id, vm_cpu) def ex_set_vm_memory(self, vapp_or_vm_id, vm_memory): """ Sets the virtual memory in MB to allocate for the specified VM or VMs under the vApp. If the vapp_or_vm_id param represents a link to an vApp all VMs that are attached to this vApp will be modified. Please ensure that hot-change of virtual memory is enabled for the powered on virtual machines. Otherwise use this method on undeployed vApp. :keyword vapp_or_vm_id: vApp or VM ID that will be modified. If a vApp ID is used here all attached VMs will be modified :type vapp_or_vm_id: ``str`` :keyword vm_memory: virtual memory in MB to allocate for the specified VM or VMs :type vm_memory: ``int`` :rtype: ``None`` """ self._validate_vm_memory(vm_memory) self._change_vm_memory(vapp_or_vm_id, vm_memory) def ex_add_vm_disk(self, vapp_or_vm_id, vm_disk_size): """ Adds a virtual disk to the specified VM or VMs under the vApp. If the vapp_or_vm_id param represents a link to an vApp all VMs that are attached to this vApp will be modified. :keyword vapp_or_vm_id: vApp or VM ID that will be modified. If a vApp ID is used here all attached VMs will be modified :type vapp_or_vm_id: ``str`` :keyword vm_disk_size: the disk capacity in GB that will be added to the specified VM or VMs :type vm_disk_size: ``int`` :rtype: ``None`` """ self._validate_vm_disk_size(vm_disk_size) self._add_vm_disk(vapp_or_vm_id, vm_disk_size) @staticmethod def _validate_vm_names(names): if names is None: return hname_re = re.compile( '^(([a-zA-Z]|[a-zA-Z][a-zA-Z0-9]*)[\-])*([A-Za-z]|[A-Za-z][A-Za-z0-9]*[A-Za-z0-9])$') # NOQA for name in names: if len(name) > 15: raise ValueError( 'The VM name "' + name + '" is too long for the computer ' 'name (max 15 chars allowed).') if not hname_re.match(name): raise ValueError('The VM name "' + name + '" can not be ' 'used. "' + name + '" is not a valid ' 'computer name for the VM.') @staticmethod def _validate_vm_memory(vm_memory): if vm_memory is None: return elif vm_memory not in VIRTUAL_MEMORY_VALS: raise ValueError( '%s is not a valid vApp VM memory value' % vm_memory) @staticmethod def _validate_vm_cpu(vm_cpu): if vm_cpu is None: return elif vm_cpu not in VIRTUAL_CPU_VALS_1_5: raise ValueError('%s is not a valid vApp VM CPU value' % vm_cpu) @staticmethod def _validate_vm_disk_size(vm_disk): if vm_disk is None: return elif int(vm_disk) < 0: raise ValueError('%s is not a valid vApp VM disk space value', vm_disk) @staticmethod def _validate_vm_script(vm_script): if vm_script is None: return # Try to locate the script file if not os.path.isabs(vm_script): vm_script = os.path.expanduser(vm_script) vm_script = os.path.abspath(vm_script) if not os.path.isfile(vm_script): raise LibcloudError( "%s the VM script file does not exist" % vm_script) try: open(vm_script).read() except Exception: raise return vm_script @staticmethod def _validate_vm_fence(vm_fence): if vm_fence is None: return elif vm_fence not in FENCE_MODE_VALS_1_5: raise ValueError('%s is not a valid fencing mode value' % vm_fence) @staticmethod def _validate_vm_ipmode(vm_ipmode): if vm_ipmode is None: return elif vm_ipmode == 'MANUAL': raise NotImplementedError( 'MANUAL IP mode: The interface for supplying ' 'IPAddress does not exist yet') elif vm_ipmode not in IP_MODE_VALS_1_5: raise ValueError( '%s is not a valid IP address allocation mode value' % vm_ipmode) def _change_vm_names(self, vapp_or_vm_id, vm_names): if vm_names is None: return vms = self._get_vm_elements(vapp_or_vm_id) for i, vm in enumerate(vms): if len(vm_names) <= i: return # Get GuestCustomizationSection res = self.connection.request( '%s/guestCustomizationSection' % get_url_path(vm.get('href'))) # Update GuestCustomizationSection res.object.find( fixxpath(res.object, 'ComputerName')).text = vm_names[i] # Remove AdminPassword from customization section admin_pass = res.object.find(fixxpath(res.object, 'AdminPassword')) if admin_pass is not None: res.object.remove(admin_pass) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.guestCustomizationSection+xml' } res = self.connection.request( '%s/guestCustomizationSection' % get_url_path(vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) # Update Vm name req_xml = ET.Element("Vm", { 'name': vm_names[i], 'xmlns': "http://www.vmware.com/vcloud/v1.5"}) res = self.connection.request( get_url_path(vm.get('href')), data=ET.tostring(req_xml), method='PUT', headers={ 'Content-Type': 'application/vnd.vmware.vcloud.vm+xml'} ) self._wait_for_task_completion(res.object.get('href')) def _change_vm_cpu(self, vapp_or_vm_id, vm_cpu): if vm_cpu is None: return vms = self._get_vm_elements(vapp_or_vm_id) for vm in vms: # Get virtualHardwareSection/cpu section res = self.connection.request( '%s/virtualHardwareSection/cpu' % get_url_path(vm.get('href'))) # Update VirtualQuantity field xpath = ('{http://schemas.dmtf.org/wbem/wscim/1/cim-schema/2/' 'CIM_ResourceAllocationSettingData}VirtualQuantity') res.object.find(xpath).text = str(vm_cpu) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.rasdItem+xml' } res = self.connection.request( '%s/virtualHardwareSection/cpu' % get_url_path(vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) def _change_vm_memory(self, vapp_or_vm_id, vm_memory): if vm_memory is None: return vms = self._get_vm_elements(vapp_or_vm_id) for vm in vms: # Get virtualHardwareSection/memory section res = self.connection.request( '%s/virtualHardwareSection/memory' % get_url_path(vm.get('href'))) # Update VirtualQuantity field xpath = ('{http://schemas.dmtf.org/wbem/wscim/1/cim-schema/2/' 'CIM_ResourceAllocationSettingData}VirtualQuantity') res.object.find(xpath).text = str(vm_memory) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.rasdItem+xml' } res = self.connection.request( '%s/virtualHardwareSection/memory' % get_url_path( vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) def _add_vm_disk(self, vapp_or_vm_id, vm_disk): if vm_disk is None: return rasd_ns = ('{http://schemas.dmtf.org/wbem/wscim/1/cim-schema/2/' 'CIM_ResourceAllocationSettingData}') vms = self._get_vm_elements(vapp_or_vm_id) for vm in vms: # Get virtualHardwareSection/disks section res = self.connection.request( '%s/virtualHardwareSection/disks' % get_url_path(vm.get('href'))) existing_ids = [] new_disk = None for item in res.object.findall(fixxpath(res.object, 'Item')): # Clean Items from unnecessary stuff for elem in item: if elem.tag == '%sInstanceID' % rasd_ns: existing_ids.append(int(elem.text)) if elem.tag in ['%sAddressOnParent' % rasd_ns, '%sParent' % rasd_ns]: item.remove(elem) if item.find('%sHostResource' % rasd_ns) is not None: new_disk = item new_disk = copy.deepcopy(new_disk) disk_id = max(existing_ids) + 1 new_disk.find('%sInstanceID' % rasd_ns).text = str(disk_id) new_disk.find('%sElementName' % rasd_ns).text = 'Hard Disk ' + str(disk_id) new_disk.find('%sHostResource' % rasd_ns).set( fixxpath(new_disk, 'capacity'), str(int(vm_disk) * 1024)) res.object.append(new_disk) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.rasditemslist+xml' } res = self.connection.request( '%s/virtualHardwareSection/disks' % get_url_path( vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) def _change_vm_script(self, vapp_or_vm_id, vm_script): if vm_script is None: return vms = self._get_vm_elements(vapp_or_vm_id) try: script = open(vm_script).read() except Exception: return # ElementTree escapes script characters automatically. Escape # requirements: # http://www.vmware.com/support/vcd/doc/rest-api-doc-1.5-html/types/ # GuestCustomizationSectionType.html for vm in vms: # Get GuestCustomizationSection res = self.connection.request( '%s/guestCustomizationSection' % get_url_path(vm.get('href'))) # Attempt to update any existing CustomizationScript element try: res.object.find( fixxpath(res.object, 'CustomizationScript')).text = script except Exception: # CustomizationScript section does not exist, insert it just # before ComputerName for i, e in enumerate(res.object): if e.tag == \ '{http://www.vmware.com/vcloud/v1.5}ComputerName': break e = ET.Element( '{http://www.vmware.com/vcloud/v1.5}CustomizationScript') e.text = script res.object.insert(i, e) # Remove AdminPassword from customization section due to an API # quirk admin_pass = res.object.find(fixxpath(res.object, 'AdminPassword')) if admin_pass is not None: res.object.remove(admin_pass) # Update VM's GuestCustomizationSection headers = { 'Content-Type': 'application/vnd.vmware.vcloud.guestCustomizationSection+xml' } res = self.connection.request( '%s/guestCustomizationSection' % get_url_path(vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) def _change_vm_ipmode(self, vapp_or_vm_id, vm_ipmode): if vm_ipmode is None: return vms = self._get_vm_elements(vapp_or_vm_id) for vm in vms: res = self.connection.request( '%s/networkConnectionSection' % get_url_path(vm.get('href'))) net_conns = res.object.findall( fixxpath(res.object, 'NetworkConnection')) for c in net_conns: c.find(fixxpath(c, 'IpAddressAllocationMode')).text = vm_ipmode headers = { 'Content-Type': 'application/vnd.vmware.vcloud.networkConnectionSection+xml' } res = self.connection.request( '%s/networkConnectionSection' % get_url_path(vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) def _update_or_insert_section(self, res, section, prev_section, text): try: res.object.find( fixxpath(res.object, section)).text = text except Exception: # "section" section does not exist, insert it just # before "prev_section" for i, e in enumerate(res.object): tag = '{http://www.vmware.com/vcloud/v1.5}%s' % prev_section if e.tag == tag: break e = ET.Element( '{http://www.vmware.com/vcloud/v1.5}%s' % section) e.text = text res.object.insert(i, e) return res def ex_change_vm_admin_password(self, vapp_or_vm_id, ex_admin_password): """ Changes the admin (or root) password of VM or VMs under the vApp. If the vapp_or_vm_id param represents a link to an vApp all VMs that are attached to this vApp will be modified. :keyword vapp_or_vm_id: vApp or VM ID that will be modified. If a vApp ID is used here all attached VMs will be modified :type vapp_or_vm_id: ``str`` :keyword ex_admin_password: <PASSWORD> to be used. :type ex_admin_password: ``str`` :rtype: ``None`` """ if ex_admin_password is None: return vms = self._get_vm_elements(vapp_or_vm_id) for vm in vms: # Get GuestCustomizationSection res = self.connection.request( '%s/guestCustomizationSection' % get_url_path(vm.get('href'))) headers = { 'Content-Type': 'application/vnd.vmware.vcloud.guestCustomizationSection+xml' } # Fix API quirk. # If AdminAutoLogonEnabled==False the guestCustomizationSection # must have AdminAutoLogonCount==0, even though # it might have AdminAutoLogonCount==1 when requesting it for # the first time. auto_logon = res.object.find( fixxpath(res.object, "AdminAutoLogonEnabled")) if auto_logon is not None and auto_logon.text == 'false': self._update_or_insert_section(res, "AdminAutoLogonCount", "ResetPasswordRequired", '0') # If we are establishing a password we do not want it # to be automatically chosen. self._update_or_insert_section(res, 'AdminPasswordAuto', 'AdminPassword', 'false') # API does not allow to set AdminPassword if # AdminPasswordEnabled is not enabled. self._update_or_insert_section(res, 'AdminPasswordEnabled', 'AdminPasswordAuto', 'true') self._update_or_insert_section(res, '<PASSWORD>', 'AdminAutoLogonEnabled', ex_admin_password) res = self.connection.request( '%s/guestCustomizationSection' % get_url_path(vm.get('href')), data=ET.tostring(res.object), method='PUT', headers=headers ) self._wait_for_task_completion(res.object.get('href')) def _get_network_href(self, network_name): network_href = None # Find the organisation's network href res = self.connection.request(self.org) links = res.object.findall(fixxpath(res.object, 'Link')) for l in links: if l.attrib['type'] == \ 'application/vnd.vmware.vcloud.orgNetwork+xml' \ and l.attrib['name'] == network_name: network_href = l.attrib['href'] if network_href is None: raise ValueError( '%s is not a valid organisation network name' % network_name) else: return network_href def _get_vm_elements(self, vapp_or_vm_id): res = self.connection.request(get_url_path(vapp_or_vm_id)) if res.object.tag.endswith('VApp'): vms = res.object.findall(fixxpath(res.object, 'Children/Vm')) elif res.object.tag.endswith('Vm'): vms = [res.object] else: raise ValueError( 'Specified ID value is not a valid VApp or Vm identifier.') return vms def _is_node(self, node_or_image): return isinstance(node_or_image, Node) def _to_node(self, node_elm): # Parse snapshots and VMs as extra if node_elm.find(fixxpath(node_elm, "SnapshotSection")) is None: snapshots = None else: snapshots = [] for snapshot_elem in node_elm.findall( fixxpath(node_elm, 'SnapshotSection/Snapshot')): snapshots.append({ "created": snapshot_elem.get("created"), "poweredOn": snapshot_elem.get("poweredOn"), "size": snapshot_elem.get("size"), }) vms = [] for vm_elem in node_elm.findall(fixxpath(node_elm, 'Children/Vm')): public_ips = [] private_ips = [] xpath = fixxpath(vm_elem, 'NetworkConnectionSection/NetworkConnection') for connection in vm_elem.findall(xpath): ip = connection.find(fixxpath(connection, "IpAddress")) if ip is not None: private_ips.append(ip.text) external_ip = connection.find( fixxpath(connection, "ExternalIpAddress")) if external_ip is not None: public_ips.append(external_ip.text) elif ip is not None: public_ips.append(ip.text) xpath = ('{http://schemas.dmtf.org/ovf/envelope/1}' 'OperatingSystemSection') os_type_elem = vm_elem.find(xpath) if os_type_elem is not None: os_type = os_type_elem.get( '{http://www.vmware.com/schema/ovf}osType') else: os_type = None vm = { 'id': vm_elem.get('href'), 'name': vm_elem.get('name'), 'state': self.NODE_STATE_MAP[vm_elem.get('status')], 'public_ips': public_ips, 'private_ips': private_ips, 'os_type': os_type } vms.append(vm) # Take the node IP addresses from all VMs public_ips = [] private_ips = [] for vm in vms: public_ips.extend(vm['public_ips']) private_ips.extend(vm['private_ips']) # Find vDC vdc_id = next(link.get('href') for link in node_elm.findall(fixxpath(node_elm, 'Link')) if link.get('type') == 'application/vnd.vmware.vcloud.vdc+xml') vdc = next(vdc for vdc in self.vdcs if vdc.id == vdc_id) extra = {'vdc': vdc.name, 'vms': vms} if snapshots is not None: extra['snapshots'] = snapshots node = Node(id=node_elm.get('href'), name=node_elm.get('name'), state=self.NODE_STATE_MAP[node_elm.get('status')], public_ips=public_ips, private_ips=private_ips, driver=self.connection.driver, extra=extra) return node def _to_vdc(self, vdc_elm): def get_capacity_values(capacity_elm): if capacity_elm is None: return None limit = int(capacity_elm.findtext(fixxpath(capacity_elm, 'Limit'))) used = int(capacity_elm.findtext(fixxpath(capacity_elm, 'Used'))) units = capacity_elm.findtext(fixxpath(capacity_elm, 'Units')) return Capacity(limit, used, units) cpu = get_capacity_values( vdc_elm.find(fixxpath(vdc_elm, 'ComputeCapacity/Cpu'))) memory = get_capacity_values( vdc_elm.find(fixxpath(vdc_elm, 'ComputeCapacity/Memory'))) storage = get_capacity_values( vdc_elm.find(fixxpath(vdc_elm, 'StorageCapacity'))) return Vdc(id=vdc_elm.get('href'), name=vdc_elm.get('name'), driver=self, allocation_model=vdc_elm.findtext( fixxpath(vdc_elm, 'AllocationModel')), cpu=cpu, memory=memory, storage=storage) class VCloud_5_1_NodeDriver(VCloud_1_5_NodeDriver): @staticmethod def _validate_vm_memory(vm_memory): if vm_memory is None: return None elif (vm_memory % 4) != 0: # The vcd 5.1 virtual machine memory size must be a multiple of 4 # MB raise ValueError( '%s is not a valid vApp VM memory value' % (vm_memory)) class VCloud_5_5_NodeDriver(VCloud_5_1_NodeDriver): """Use 5.5 Connection class to explicitly set 5.5 for the version in Accept headers """ connectionCls = VCloud_5_5_Connection def ex_create_snapshot(self, node): """ Creates new snapshot of a virtual machine or of all the virtual machines in a vApp. Prior to creation of the new snapshots, any existing user created snapshots associated with the virtual machines are removed. :param node: node :type node: :class:`Node` :rtype: :class:`Node` """ snapshot_xml = ET.Element( "CreateSnapshotParams", {'memory': 'true', 'name': 'name', 'quiesce': 'true', 'xmlns': "http://www.vmware.com/vcloud/v1.5", 'xmlns:xsi': "http://www.w3.org/2001/XMLSchema-instance"} ) ET.SubElement(snapshot_xml, 'Description').text = 'Description' content_type = 'application/vnd.vmware.vcloud.createSnapshotParams+xml' headers = { 'Content-Type': content_type } return self._perform_snapshot_operation(node, "createSnapshot", snapshot_xml, headers) def ex_remove_snapshots(self, node): """ Removes all user created snapshots for a vApp or virtual machine. :param node: node :type node: :class:`Node` :rtype: :class:`Node` """ return self._perform_snapshot_operation(node, "removeAllSnapshots", None, None) def ex_revert_to_snapshot(self, node): """ Reverts a vApp or virtual machine to the current snapshot, if any. :param node: node :type node: :class:`Node` :rtype: :class:`Node` """ return self._perform_snapshot_operation(node, "revertToCurrentSnapshot", None, None) def _perform_snapshot_operation(self, node, operation, xml_data, headers): res = self.connection.request( '%s/action/%s' % (get_url_path(node.id), operation), data=ET.tostring(xml_data) if xml_data is not None else None, method='POST', headers=headers) self._wait_for_task_completion(res.object.get('href')) res = self.connection.request(get_url_path(node.id)) return self._to_node(res.object) def ex_acquire_mks_ticket(self, vapp_or_vm_id, vm_num=0): """ Retrieve a mks ticket that you can use to gain access to the console of a running VM. If successful, returns a dict with the following keys: - host: host (or proxy) through which the console connection is made - vmx: a reference to the VMX file of the VM for which this ticket was issued - ticket: screen ticket to use to authenticate the client - port: host port to be used for console access :param vapp_or_vm_id: vApp or VM ID you want to connect to. :type vapp_or_vm_id: ``str`` :param vm_num: If a vApp ID is provided, vm_num is position in the vApp VM list of the VM you want to get a screen ticket. Default is 0. :type vm_num: ``int`` :rtype: ``dict`` """ vm = self._get_vm_elements(vapp_or_vm_id)[vm_num] try: res = self.connection.request('%s/screen/action/acquireMksTicket' % (get_url_path(vm.get('href'))), method='POST') output = { "host": res.object.find(fixxpath(res.object, 'Host')).text, "vmx": res.object.find(fixxpath(res.object, 'Vmx')).text, "ticket": res.object.find(fixxpath(res.object, 'Ticket')).text, "port": res.object.find(fixxpath(res.object, 'Port')).text, } return output except Exception: return None
StarcoderdataPython
3323754
<reponame>yoonjieun/blender import bpy class RemoveDuplicateMaterial(bpy.types.Operator): ''' replace material with 3 characters at the end to material without number ex) 'material.001' --> 'material' 'material.099' --> 'material' ''' bl_idname = "lazypic.remove_duplicate_material" bl_label = "remove_duplicate_material" bl_options = {'REGISTER', 'UNDO'} def execute(self, context): #make all material list mat_list = [mat.name for mat in bpy.data.materials] #remove duplicate material name for obj in bpy.context.scene.objects: for objmat in obj.material_slots: if objmat.material.name[-3:].isnumeric(): # last 3 character are numbers if objmat.material.name[:-4] in mat_list: #material without number exist objmat.material=bpy.data.materials[objmat.material.name[:-4]] #replace duplicated material to orign material #remove unused matrials for material in bpy.data.materials: if not material.users: bpy.data.materials.remove(material) return {'FINISHED'}
StarcoderdataPython
9678262
# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """srcnn evaluation""" import argparse import mindspore as ms import mindspore.nn as nn from mindspore import context, Tensor from mindspore.train.model import Model from mindspore.train.serialization import load_checkpoint, load_param_into_net from src.config import srcnn_cfg as config from src.dataset import create_eval_dataset from src.srcnn import SRCNN from src.metric import SRCNNpsnr if __name__ == '__main__': parser = argparse.ArgumentParser(description="srcnn eval") parser.add_argument('--dataset_path', type=str, required=True, help="Dataset, default is None.") parser.add_argument('--checkpoint_path', type=str, required=True, help="checkpoint file path") parser.add_argument('--device_target', type=str, default='GPU', choices=("GPU"), help="Device target, support GPU.") args, _ = parser.parse_known_args() if args.device_target == "GPU": context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, save_graphs=False) else: raise ValueError("Unsupported device target.") eval_ds = create_eval_dataset(args.dataset_path) net = SRCNN() lr = Tensor(config.lr, ms.float32) opt = nn.Adam(params=net.trainable_params(), learning_rate=lr, eps=1e-07) loss = nn.MSELoss(reduction='mean') param_dict = load_checkpoint(args.checkpoint_path) load_param_into_net(net, param_dict) net.set_train(False) model = Model(net, loss_fn=loss, optimizer=opt, metrics={'PSNR': SRCNNpsnr()}) res = model.eval(eval_ds, dataset_sink_mode=False) print("result ", res)
StarcoderdataPython
1687502
import sys import pathlib from .Group import Group from .Zn import Zn from .Zn_coprime import Zn_coprime from .Klein4 import Klein4 from .Sn import Sn from .Element import Element from .order import O # Import helpers module sys.path.insert(1, pathlib.Path(__file__).parent.absolute().__str__() + '/helpers') from divisible_by import divisible_by from is_prime import is_prime from find_primes_up_to import find_primes_up_to from prime_factorization import prime_factorization from phi import phi from permutation import permute_n, permute __all__ = ['Group', 'Zn']
StarcoderdataPython
1676165
<filename>server/the_water_project/tags/models.py from django.db import models class Tag(models.Model): name = models.CharField(max_length=25) # FIXME: Should I made the "name" field unique? def __str__(self): return self.name
StarcoderdataPython
3224680
# # Copyright (c) 2018 Juniper Networks, Inc. All rights reserved. # import re import socket from cfgm_common import PERMS_RX from vnc_api.gen.resource_common import VirtualDns from vnc_cfg_api_server.resources._resource_base import ResourceMixin class VirtualDnsServer(ResourceMixin, VirtualDns): @classmethod def pre_dbe_create(cls, tenant_name, obj_dict, db_conn): # enable domain level sharing for virtual DNS domain_uuid = obj_dict.get('parent_uuid') if domain_uuid is None: domain_uuid = db_conn.fq_name_to_uuid('domain', obj_dict['fq_name'][0:1]) share_item = { 'tenant': 'domain:%s' % domain_uuid, 'tenant_access': PERMS_RX } obj_dict['perms2'].setdefault('share', []).append(share_item) return cls.validate_dns_server(obj_dict, db_conn) @classmethod def pre_dbe_update(cls, id, fq_name, obj_dict, db_conn, **kwargs): return cls.validate_dns_server(obj_dict, db_conn) @classmethod def pre_dbe_delete(cls, id, obj_dict, db_conn): vdns_name = ":".join(obj_dict['fq_name']) if 'parent_uuid' in obj_dict: ok, read_result = cls.dbe_read(db_conn, 'domain', obj_dict['parent_uuid']) if not ok: return ok, read_result, None virtual_DNSs = read_result.get('virtual_DNSs') or [] for vdns in virtual_DNSs: ok, read_result = cls.dbe_read(db_conn, 'virtual_DNS', vdns['uuid']) if not ok: code, msg = read_result if code == 404: continue return ok, (code, msg), None vdns_data = read_result['virtual_DNS_data'] if 'next_virtual_DNS' in vdns_data: if vdns_data['next_virtual_DNS'] == vdns_name: return ( False, (403, "Virtual DNS server is referred" " by other virtual DNS servers"), None) return True, "", None @classmethod def is_valid_dns_name(cls, name): if len(name) > 255: return False if name.endswith("."): # A single trailing dot is legal # strip exactly one dot from the right, if present name = name[:-1] disallowed = re.compile(r'[^A-Z\d-]', re.IGNORECASE) return all( # Split by labels and verify individually (label and len(label) <= 63 and # length is within proper range # no bordering hyphens not label.startswith("-") and not label.endswith("-") and not disallowed.search(label)) # contains only legal char for label in name.split(".")) @classmethod def is_valid_ipv4_address(cls, address): parts = address.split(".") if len(parts) != 4: return False for item in parts: try: if not 0 <= int(item) <= 255: return False except ValueError: return False return True @classmethod def is_valid_ipv6_address(cls, address): try: socket.inet_pton(socket.AF_INET6, address) except socket.error: return False return True @classmethod def validate_dns_server(cls, obj_dict, db_conn): if 'fq_name' in obj_dict: virtual_dns = obj_dict['fq_name'][1] disallowed = re.compile(r'[^A-Z\d-]', re.IGNORECASE) if disallowed.search(virtual_dns) or virtual_dns.startswith("-"): msg = ("Special characters are not allowed in Virtual DNS " "server name") return False, (403, msg) vdns_data = obj_dict['virtual_DNS_data'] if not cls.is_valid_dns_name(vdns_data['domain_name']): return ( False, (403, "Domain name does not adhere to DNS name requirements")) record_order = ["fixed", "random", "round-robin"] if not str(vdns_data['record_order']).lower() in record_order: return (False, (403, "Invalid value for record order")) ttl = vdns_data['default_ttl_seconds'] if ttl < 0 or ttl > 2147483647: return (False, (400, "Invalid value for TTL")) if 'next_virtual_DNS' in vdns_data: vdns_next = vdns_data['next_virtual_DNS'] if not vdns_next or vdns_next is None: return True, "" next_vdns = vdns_data['next_virtual_DNS'].split(":") # check that next vdns exists try: next_vdns_uuid = db_conn.fq_name_to_uuid( 'virtual_DNS', next_vdns) except Exception: if not cls.is_valid_ipv4_address( vdns_data['next_virtual_DNS']): return ( False, (400, "Invalid Virtual Forwarder(next virtual dns server)")) else: return True, "" # check that next virtual dns servers arent referring to each other # above check doesnt allow during create, but entry could be # modified later ok, read_result = cls.dbe_read(db_conn, 'virtual_DNS', next_vdns_uuid) if ok: next_vdns_data = read_result['virtual_DNS_data'] if 'next_virtual_DNS' in next_vdns_data: vdns_name = ":".join(obj_dict['fq_name']) if next_vdns_data['next_virtual_DNS'] == vdns_name: return ( False, (403, "Cannot have Virtual DNS Servers " "referring to each other")) return True, ""
StarcoderdataPython
5172056
""" Methods used to convert/handle raw input data """ import os import json import h5py import numpy as np import csv import execnet def init_obj_catalogue(path_to_data): obj_dict = {} subfols = sorted(os.listdir(os.path.join(path_to_data, 'test-item-data'))) known_classes = sorted(os.listdir(os.path.join(path_to_data, 'train-item-data'))) for i,class_fol in enumerate(subfols): cname = class_fol.lower() try: with open(os.path.join(path_to_data, 'test-item-data',class_fol, cname+'.json')) as fin: obj_node = json.load(fin) #start from json data given obj_node['known'] = True if class_fol in known_classes else False #Known v Novel? except FileNotFoundError: print("No json file found for object %s" % cname) print("Adding empty node") obj_node = {"dimensions": [0,0,0] } obj_node['known'] = True #'Empty' is known at training time obj_node['label'] = str(i + 1) # add class label in same format as gt (starts from 1) obj_dict[cname] = obj_node return obj_dict def load_emb_space(args,fname='snapshot-test-results.h5'): """ Assumes the input are the HDF5 files as produced by the baselines provided at https://github.com/andyzeng/arc-robot-vision/image-matching """ if args.baseline =="imprk-net" or args.set=='KMi': path_to_hdf5 = os.path.join(args.test_res, args.baseline, 'snapshots-with-class',fname) tgt_impr = h5py.File(path_to_hdf5, 'r') return np.array(tgt_impr['prodFeat'], dtype='<f4'), np.array(tgt_impr['testFeat'], dtype='<f4'),\ None, None else: path_to_hdf5 = args.test_res tgt_novel = os.path.join(path_to_hdf5, 'snapshots-no-class', 'results-snapshot-8000.h5') #default folder structure by Zeng et al. tgt_known = os.path.join(path_to_hdf5, 'snapshots-with-class', 'results-snapshot-170000.h5') nnetf = h5py.File(tgt_novel, 'r') knetf = h5py.File(tgt_known, 'r') return np.array(knetf['prodFeat'], dtype='<f4'), np.array(knetf['testFeat'], dtype='<f4'), \ np.array(nnetf['prodFeat'], dtype='<f4'), np.array(nnetf['testFeat'], dtype='<f4') def load_camera_intrinsics_txt(path_to_intr): """ Expects 3x3 intrinsics matrix as tab-separated txt """ intrinsics=[] with open(path_to_intr) as f: reader = csv.reader(f,delimiter='\t') for row in reader: if row==[]: continue for cell in row: if cell=='': continue try: intrinsics.append(float(cell.split(" ")[1])) except IndexError: try: intrinsics.append(float(cell.split(" ")[1])) except IndexError: intrinsics.append(float(cell)) return intrinsics ################################################################## # # Creating txt ground truth files in the same format as ARC2017 # ################################################################## def arcify(root_img_path): base = root_img_path.split('/')[-1] for root, dirs, files in os.walk(root_img_path): for name in dirs: imgpaths=[] imglabels=[] first =True for sroot, sdirs, sfiles in os.walk(os.path.join(root_img_path,name)): if first: obj_classes=sdirs first = False continue if sfiles: classname = sroot.split('/')[-1] label = obj_classes.index(classname) + 1 imgpaths.extend([os.path.join(base,name,classname,f) for f in sfiles]) imglabels.extend([str(label) for f in sfiles]) # as many labels an no of files in that subfolder lname = name.split("-imgs")[0] with open(os.path.join(root_img_path,name+'.txt'), mode='w') as outf, \ open(os.path.join(root_img_path,lname+'-labels.txt'), mode='w') as outl: outf.write('\n'.join(imgpaths)) outl.write('\n'.join(imglabels)) break # skip outer for, after first folder level def create_class_map(path_to_json): """ Assuming arcify was already run locally """ base= path_to_json.split("class_to_index.json")[0] path_train = os.path.join(base,"train-product-imgs") class_names = os.listdir(path_train) class_index={} try: with open(os.path.join(base,"train-product-imgs.txt")) as fpath, \ open(os.path.join(base, "train-product-labels.txt")) as flabels: fileps= fpath.read().splitlines() labels = flabels.read().splitlines() except FileNotFoundError: print("Run arcify method locally before to generate reference txts") return 0 for pth, label in zip(fileps, labels): category = pth.split("train-product-imgs/")[1].split("/")[0] if category not in class_index.keys(): class_index[category] = label with open(path_to_json, 'w') as fout: json.dump(class_index, fout) print("Class - numeric index mapping saved locally") return None def call_python_version(Version, Module, Function, ArgumentList): gw = execnet.makegateway("popen//python=python%s" % Version) channel = gw.remote_exec(""" from %s import %s as the_function channel.send(the_function(*channel.receive())) """ % (Module, Function)) channel.send(ArgumentList) return channel.receive() def list_depth_filenames(input_path): """ Returns path to files containing "depth" ih their name Expects a macro folder with sub-folder structure divided class by class e.g., passing ./data will search over ./data/class1, ./data/class2 ... etc. """ fnamelist = [] for root, dirs, files in os.walk(input_path): for name in dirs: base = os.path.join(root, name) fnamelist.extend([os.path.join(base,f) for f in os.listdir(base) if 'depth' in f]) if len(fnamelist)> 0 : return fnamelist else: return None
StarcoderdataPython
8122606
from __future__ import unicode_literals from pepper.framework import AbstractComponent, AbstractBackend from pepper.framework.component import ContextComponent, TextToSpeechComponent, SpeechRecognitionComponent from pepper.language import Utterance from pepper import config import urllib import re from threading import Timer from typing import Optional class SubtitlesComponent(AbstractComponent): SUBTITLES_URL = "https://bramkraai.github.io/subtitle?text={}" SUBTITLES_TIMEOUT = 15 def __init__(self, backend): # type: (AbstractBackend) -> None super(SubtitlesComponent, self).__init__(backend) self._subtitles_timeout_timer = None # type: Optional[Timer] self.require(SubtitlesComponent, TextToSpeechComponent) self.require(SubtitlesComponent, SpeechRecognitionComponent) def say(self, text, animation=None, block=False): # type: (str, str, bool) -> None self._show_subtitles('{}:/"{}"'.format(config.NAME, text)) super(SubtitlesComponent, self).say(text, animation, block) def on_transcript(self, hypotheses, audio): speaker = "Human" try: if isinstance(self, ContextComponent) and self.context.chatting: speaker = self.context.chat.speaker except AttributeError as e: pass self._show_subtitles('{}:/"{}"'.format(speaker, hypotheses[0].transcript)) super(SubtitlesComponent, self).on_transcript(hypotheses, audio) def _show_subtitles(self, text): # Stop Timeout Timer if running if self._subtitles_timeout_timer: self._subtitles_timeout_timer.cancel() # Show Subtitles text_websafe = urllib.quote(''.join([i for i in re.sub(r'\\\\\S+\\\\', "", text) if ord(i) < 128])) self.backend.tablet.show(self.SUBTITLES_URL.format(text_websafe)) # Start Timeout Timer self._subtitles_timeout_timer = Timer(self.SUBTITLES_TIMEOUT, self.backend.tablet.hide) self._subtitles_timeout_timer.start()
StarcoderdataPython
6462999
import os.path as osp from setuptools import find_packages, setup requirements = ["h5py==2.10.0", "matplotlib==3.3.4", "munch==2.5.0", "open3d==0.9.0", "PyYAML==5.3.1"] setup( name="vrcnet", version="1.0.0", author="paul007pl", packages=find_packages(), install_requires=requirements, )
StarcoderdataPython
358734
<filename>pyplus/autotest/__init__.py from .manager import Manager def add(*args, **kwargs): return Manager().add(*args, **kwargs)
StarcoderdataPython
6665107
<reponame>arthurdarcet/motor<filename>motor/core.py<gh_stars>1-10 # Copyright 2011-present MongoDB, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import unicode_literals, absolute_import """Framework-agnostic core of Motor, an asynchronous driver for MongoDB.""" import functools import sys import textwrap import pymongo import pymongo.auth import pymongo.common import pymongo.database import pymongo.errors import pymongo.mongo_client import pymongo.mongo_replica_set_client import pymongo.son_manipulator from pymongo.bulk import BulkOperationBuilder from pymongo.database import Database from pymongo.change_stream import ChangeStream from pymongo.collection import Collection from pymongo.cursor import Cursor, _QUERY_OPTIONS from pymongo.command_cursor import CommandCursor from .metaprogramming import (AsyncCommand, AsyncRead, AsyncWrite, coroutine_annotation, create_class_with_framework, DelegateMethod, motor_coroutine, MotorCursorChainingMethod, ReadOnlyProperty) from .motor_common import callback_type_error from motor.docstrings import * HAS_SSL = True try: import ssl except ImportError: ssl = None HAS_SSL = False PY35 = sys.version_info >= (3, 5) class AgnosticBase(object): def __eq__(self, other): if (isinstance(other, self.__class__) and hasattr(self, 'delegate') and hasattr(other, 'delegate')): return self.delegate == other.delegate return NotImplemented def __init__(self, delegate): self.delegate = delegate def __repr__(self): return '%s(%r)' % (self.__class__.__name__, self.delegate) class AgnosticBaseProperties(AgnosticBase): codec_options = ReadOnlyProperty() read_preference = ReadOnlyProperty() read_concern = ReadOnlyProperty() write_concern = ReadOnlyProperty() class AgnosticClient(AgnosticBaseProperties): __motor_class_name__ = 'MotorClient' __delegate_class__ = pymongo.mongo_client.MongoClient address = ReadOnlyProperty() arbiters = ReadOnlyProperty() close = DelegateMethod() close_cursor = AsyncCommand() database_names = AsyncRead() drop_database = AsyncCommand().unwrap('MotorDatabase') event_listeners = ReadOnlyProperty() fsync = AsyncCommand() get_database = DelegateMethod(doc=get_database_doc).wrap(Database) get_default_database = DelegateMethod().wrap(Database) HOST = ReadOnlyProperty() is_mongos = ReadOnlyProperty() is_primary = ReadOnlyProperty() kill_cursors = AsyncCommand() list_databases = AsyncRead().wrap(CommandCursor) list_database_names = AsyncRead() local_threshold_ms = ReadOnlyProperty() max_bson_size = ReadOnlyProperty() max_idle_time_ms = ReadOnlyProperty() max_message_size = ReadOnlyProperty() max_pool_size = ReadOnlyProperty() max_write_batch_size = ReadOnlyProperty() min_pool_size = ReadOnlyProperty() nodes = ReadOnlyProperty() PORT = ReadOnlyProperty() primary = ReadOnlyProperty() read_concern = ReadOnlyProperty() retry_writes = ReadOnlyProperty() secondaries = ReadOnlyProperty() server_info = AsyncRead() server_selection_timeout = ReadOnlyProperty() start_session = AsyncRead(doc=start_session_doc) unlock = AsyncCommand() def __init__(self, *args, **kwargs): """Create a new connection to a single MongoDB instance at *host:port*. Takes the same constructor arguments as :class:`~pymongo.mongo_client.MongoClient`, as well as: :Parameters: - `io_loop` (optional): Special :class:`tornado.ioloop.IOLoop` instance to use instead of default """ if 'io_loop' in kwargs: io_loop = kwargs.pop('io_loop') else: io_loop = self._framework.get_event_loop() kwargs.setdefault('connect', False) delegate = self.__delegate_class__(*args, **kwargs) super(AgnosticBaseProperties, self).__init__(delegate) if io_loop: self._framework.check_event_loop(io_loop) self.io_loop = io_loop else: self.io_loop = self._framework.get_event_loop() def get_io_loop(self): return self.io_loop def __getattr__(self, name): if name.startswith('_'): raise AttributeError( "%s has no attribute %r. To access the %s" " database, use client['%s']." % ( self.__class__.__name__, name, name, name)) return self[name] def __getitem__(self, name): db_class = create_class_with_framework( AgnosticDatabase, self._framework, self.__module__) return db_class(self, name) def wrap(self, obj): if obj.__class__ == Database: db_class = create_class_with_framework( AgnosticDatabase, self._framework, self.__module__) return db_class(self, obj.name, _delegate=obj) elif obj.__class__ == CommandCursor: command_cursor_class = create_class_with_framework( AgnosticCommandCursor, self._framework, self.__module__) return command_cursor_class(obj, self) class AgnosticDatabase(AgnosticBaseProperties): __motor_class_name__ = 'MotorDatabase' __delegate_class__ = Database add_user = AsyncCommand() authenticate = AsyncCommand() collection_names = AsyncRead() command = AsyncCommand(doc=cmd_doc) create_collection = AsyncCommand().wrap(Collection) current_op = AsyncRead() dereference = AsyncRead() drop_collection = AsyncCommand().unwrap('MotorCollection') error = AsyncRead(doc="OBSOLETE") eval = AsyncCommand() get_collection = DelegateMethod().wrap(Collection) last_status = AsyncRead(doc="OBSOLETE") list_collection_names = AsyncRead() list_collections = AsyncRead() logout = AsyncCommand() name = ReadOnlyProperty() previous_error = AsyncRead(doc="OBSOLETE") profiling_info = AsyncRead() profiling_level = AsyncRead() remove_user = AsyncCommand() reset_error_history = AsyncCommand(doc="OBSOLETE") set_profiling_level = AsyncCommand() validate_collection = AsyncRead().unwrap('MotorCollection') incoming_manipulators = ReadOnlyProperty() incoming_copying_manipulators = ReadOnlyProperty() outgoing_manipulators = ReadOnlyProperty() outgoing_copying_manipulators = ReadOnlyProperty() def __init__(self, client, name, **kwargs): self._client = client delegate = kwargs.get('_delegate') or Database( client.delegate, name, **kwargs) super(self.__class__, self).__init__(delegate) @property def client(self): """This MotorDatabase's :class:`MotorClient`.""" return self._client def __getattr__(self, name): if name.startswith('_'): raise AttributeError( "%s has no attribute %r. To access the %s" " collection, use database['%s']." % ( self.__class__.__name__, name, name, name)) return self[name] def __getitem__(self, name): collection_class = create_class_with_framework( AgnosticCollection, self._framework, self.__module__) return collection_class(self, name) def __call__(self, *args, **kwargs): database_name = self.delegate.name client_class_name = self._client.__class__.__name__ if database_name == 'open_sync': raise TypeError( "%s.open_sync() is unnecessary Motor 0.2, " "see changelog for details." % client_class_name) raise TypeError( "MotorDatabase object is not callable. If you meant to " "call the '%s' method on a %s object it is " "failing because no such method exists." % ( database_name, client_class_name)) def wrap(self, collection): # Replace pymongo.collection.Collection with MotorCollection. klass = create_class_with_framework( AgnosticCollection, self._framework, self.__module__) return klass(self, collection.name, _delegate=collection) def add_son_manipulator(self, manipulator): """Add a new son manipulator to this database. Newly added manipulators will be applied before existing ones. :Parameters: - `manipulator`: the manipulator to add """ # We override add_son_manipulator to unwrap the AutoReference's # database attribute. if isinstance(manipulator, pymongo.son_manipulator.AutoReference): db = manipulator.database db_class = create_class_with_framework( AgnosticDatabase, self._framework, self.__module__) if isinstance(db, db_class): # db is a MotorDatabase; get the PyMongo Database instance. manipulator.database = db.delegate self.delegate.add_son_manipulator(manipulator) def get_io_loop(self): return self._client.get_io_loop() class AgnosticCollection(AgnosticBaseProperties): __motor_class_name__ = 'MotorCollection' __delegate_class__ = Collection bulk_write = AsyncCommand(doc=bulk_write_doc) count = AsyncRead() create_index = AsyncCommand() create_indexes = AsyncCommand(doc=create_indexes_doc) delete_many = AsyncCommand(doc=delete_many_doc) delete_one = AsyncCommand(doc=delete_one_doc) distinct = AsyncRead() drop = AsyncCommand(doc=drop_doc) drop_index = AsyncCommand() drop_indexes = AsyncCommand() ensure_index = AsyncCommand() find_and_modify = AsyncCommand() find_one = AsyncRead(doc=find_one_doc) find_one_and_delete = AsyncCommand(doc=find_one_and_delete_doc) find_one_and_replace = AsyncCommand(doc=find_one_and_replace_doc) find_one_and_update = AsyncCommand(doc=find_one_and_update_doc) full_name = ReadOnlyProperty() group = AsyncRead() index_information = AsyncRead(doc=index_information_doc) inline_map_reduce = AsyncRead() insert = AsyncWrite() insert_many = AsyncWrite(doc=insert_many_doc) insert_one = AsyncCommand(doc=insert_one_doc) map_reduce = AsyncCommand(doc=mr_doc).wrap(Collection) name = ReadOnlyProperty() options = AsyncRead() reindex = AsyncCommand() remove = AsyncWrite() rename = AsyncCommand() replace_one = AsyncCommand(doc=replace_one_doc) save = AsyncWrite() update = AsyncWrite(doc=update_doc) update_many = AsyncCommand(doc=update_many_doc) update_one = AsyncCommand(doc=update_one_doc) with_options = DelegateMethod().wrap(Collection) _async_aggregate = AsyncRead(attr_name='aggregate') _async_list_indexes = AsyncRead(attr_name='list_indexes') __parallel_scan = AsyncRead(attr_name='parallel_scan') def __init__(self, database, name, codec_options=None, read_preference=None, write_concern=None, read_concern=None, _delegate=None): db_class = create_class_with_framework( AgnosticDatabase, self._framework, self.__module__) if not isinstance(database, db_class): raise TypeError("First argument to MotorCollection must be " "MotorDatabase, not %r" % database) delegate = _delegate or Collection( database.delegate, name, codec_options=codec_options, read_preference=read_preference, write_concern=write_concern, read_concern=read_concern) super(self.__class__, self).__init__(delegate) self.database = database def __getattr__(self, name): # Dotted collection name, like "foo.bar". if name.startswith('_'): full_name = "%s.%s" % (self.name, name) raise AttributeError( "%s has no attribute %r. To access the %s" " collection, use database['%s']." % ( self.__class__.__name__, name, full_name, full_name)) return self[name] def __getitem__(self, name): collection_class = create_class_with_framework( AgnosticCollection, self._framework, self.__module__) return collection_class(self.database, self.name + '.' + name) def __call__(self, *args, **kwargs): raise TypeError( "MotorCollection object is not callable. If you meant to " "call the '%s' method on a MotorCollection object it is " "failing because no such method exists." % self.delegate.name) def find(self, *args, **kwargs): """Create a :class:`MotorCursor`. Same parameters as for PyMongo's :meth:`~pymongo.collection.Collection.find`. Note that ``find`` does not take a `callback` parameter, nor does it return a Future, because ``find`` merely creates a :class:`MotorCursor` without performing any operations on the server. ``MotorCursor`` methods such as :meth:`~MotorCursor.to_list` or :meth:`~MotorCursor.count` perform actual operations. """ if 'callback' in kwargs: raise pymongo.errors.InvalidOperation( "Pass a callback to each, to_list, or count, not to find.") cursor = self.delegate.find(*args, **kwargs) cursor_class = create_class_with_framework( AgnosticCursor, self._framework, self.__module__) return cursor_class(cursor, self) def aggregate(self, pipeline, **kwargs): """Execute an aggregation pipeline on this collection. The aggregation can be run on a secondary if the client is connected to a replica set and its ``read_preference`` is not :attr:`PRIMARY`. :Parameters: - `pipeline`: a single command or list of aggregation commands - `session` (optional): a :class:`~pymongo.client_session.ClientSession`, created with :meth:`~MotorClient.start_session`. - `**kwargs`: send arbitrary parameters to the aggregate command Returns a :class:`MotorCommandCursor` that can be iterated like a cursor from :meth:`find`:: pipeline = [{'$project': {'name': {'$toUpper': '$name'}}}] cursor = collection.aggregate(pipeline) while (yield cursor.fetch_next): doc = cursor.next_object() print(doc) In Python 3.5 and newer, aggregation cursors can be iterated elegantly in native coroutines with `async for`:: async def f(): async for doc in collection.aggregate(pipeline): print(doc) .. versionchanged:: 1.0 :meth:`aggregate` now **always** returns a cursor. .. versionchanged:: 0.5 :meth:`aggregate` now returns a cursor by default, and the cursor is returned immediately without a ``yield``. See :ref:`aggregation changes in Motor 0.5 <aggregate_changes_0_5>`. .. versionchanged:: 0.2 Added cursor support. .. _aggregate command: http://docs.mongodb.org/manual/applications/aggregation """ if kwargs.get('cursor') is False: kwargs.pop('cursor') # One-shot aggregation, no cursor. Send command now, return Future. return self._async_aggregate(pipeline, **kwargs) else: if 'callback' in kwargs: raise pymongo.errors.InvalidOperation( "Pass a callback to to_list or each, not to aggregate.") kwargs.setdefault('cursor', {}) cursor_class = create_class_with_framework( AgnosticLatentCommandCursor, self._framework, self.__module__) # Latent cursor that will send initial command on first "async for". return cursor_class(self, self._async_aggregate, pipeline, **kwargs) def watch(self, pipeline=None, full_document='default', resume_after=None, max_await_time_ms=None, batch_size=None, collation=None, session=None): """Watch changes on this collection. Returns a :class:`~MotorChangeStream` cursor which iterates over changes on this collection. Introduced in MongoDB 3.6. A change stream continues waiting indefinitely for matching change events. Code like the following allows a program to cancel the change stream and exit. .. code-block:: python3 change_stream = None async def watch_collection(): global change_stream # Using the change stream in an "async with" block # ensures it is canceled promptly if your code breaks # from the loop or throws an exception. async with db.collection.watch() as change_stream: async for change in stream: print(change) # Tornado from tornado.ioloop import IOLoop def main(): loop = IOLoop.current() # Start watching collection for changes. loop.add_callback(watch_collection) try: loop.start() except KeyboardInterrupt: pass finally: if change_stream is not None: change_stream.close() # asyncio from asyncio import get_event_loop def main(): loop = get_event_loop() task = loop.create_task(watch_collection) try: loop.run_forever() except KeyboardInterrupt: pass finally: if change_stream is not None: change_stream.close() # Prevent "Task was destroyed but it is pending!" loop.run_until_complete(task) The :class:`~MotorChangeStream` async iterable blocks until the next change document is returned or an error is raised. If the :meth:`~MotorChangeStream.next` method encounters a network error when retrieving a batch from the server, it will automatically attempt to recreate the cursor such that no change events are missed. Any error encountered during the resume attempt indicates there may be an outage and will be raised. .. code-block:: python3 try: pipeline = [{'$match': {'operationType': 'insert'}}] async with db.collection.watch(pipeline) as stream: async for change in stream: print(change) except pymongo.errors.PyMongoError: # The ChangeStream encountered an unrecoverable error or the # resume attempt failed to recreate the cursor. logging.error('...') For a precise description of the resume process see the `change streams specification`_. :Parameters: - `pipeline` (optional): A list of aggregation pipeline stages to append to an initial ``$changeStream`` stage. Not all pipeline stages are valid after a ``$changeStream`` stage, see the MongoDB documentation on change streams for the supported stages. - `full_document` (optional): The fullDocument option to pass to the ``$changeStream`` stage. Allowed values: 'default', 'updateLookup'. Defaults to 'default'. When set to 'updateLookup', the change notification for partial updates will include both a delta describing the changes to the document, as well as a copy of the entire document that was changed from some time after the change occurred. - `resume_after` (optional): The logical starting point for this change stream. - `max_await_time_ms` (optional): The maximum time in milliseconds for the server to wait for changes before responding to a getMore operation. - `batch_size` (optional): The maximum number of documents to return per batch. - `collation` (optional): The :class:`~pymongo.collation.Collation` to use for the aggregation. - `session` (optional): a :class:`~pymongo.client_session.ClientSession`. :Returns: A :class:`~MotorChangeStream`. See the :ref:`tornado_change_stream_example`. .. versionadded:: 1.2 .. mongodoc:: changeStreams .. _change streams specification: https://github.com/mongodb/specifications/blob/master/source/change-streams.rst """ cursor_class = create_class_with_framework( AgnosticChangeStream, self._framework, self.__module__) # Latent cursor that will send initial command on first "async for". return cursor_class(self, pipeline, full_document, resume_after, max_await_time_ms, batch_size, collation, session) def list_indexes(self, session=None): """Get a cursor over the index documents for this collection. :: async def print_indexes(): for index in await db.test.list_indexes(): print(index) If the only index is the default index on ``_id``, this might print:: SON([('v', 1), ('key', SON([('_id', 1)])), ('name', '_id_'), ('ns', 'test.test')]) """ cursor_class = create_class_with_framework( AgnosticLatentCommandCursor, self._framework, self.__module__) # Latent cursor that will send initial command on first "async for". return cursor_class(self, self._async_list_indexes, session=session) def parallel_scan(self, num_cursors, **kwargs): """Scan this entire collection in parallel. Returns a list of up to ``num_cursors`` cursors that can be iterated concurrently. As long as the collection is not modified during scanning, each document appears once in one of the cursors' result sets. For example, to process each document in a collection using some function ``process_document()``:: @gen.coroutine def process_cursor(cursor): while (yield cursor.fetch_next): process_document(cursor.next_object()) # Get up to 4 cursors. cursors = yield collection.parallel_scan(4) yield [process_cursor(cursor) for cursor in cursors] # All documents have now been processed. If ``process_document()`` is a coroutine, do ``yield process_document(document)``. With a replica set, pass `read_preference` of :attr:`~pymongo.read_preference.ReadPreference.SECONDARY_PREFERRED` to scan a secondary. :Parameters: - `num_cursors`: the number of cursors to return - `session` (optional): a :class:`~pymongo.client_session.ClientSession`, created with :meth:`~MotorClient.start_session`. .. note:: Requires server version **>= 2.5.5**. """ io_loop = self.get_io_loop() original_future = self._framework.get_future(io_loop) # Return a future, or if user passed a callback chain it to the future. callback = kwargs.pop('callback', None) retval = self._framework.future_or_callback(original_future, callback, io_loop) # Once we have PyMongo Cursors, wrap in MotorCursors and resolve the # future with them, or pass them to the callback. self._framework.add_future( io_loop, self.__parallel_scan(num_cursors, **kwargs), self._scan_callback, original_future) return retval def _scan_callback(self, original_future, future): try: command_cursors = future.result() except Exception as exc: original_future.set_exception(exc) else: command_cursor_class = create_class_with_framework( AgnosticCommandCursor, self._framework, self.__module__) motor_command_cursors = [ command_cursor_class(cursor, self) for cursor in command_cursors] original_future.set_result(motor_command_cursors) def initialize_unordered_bulk_op(self, bypass_document_validation=False): """Initialize an unordered batch of write operations. Operations will be performed on the server in arbitrary order, possibly in parallel. All operations will be attempted. :Parameters: - `bypass_document_validation`: (optional) If ``True``, allows the write to opt-out of document level validation. Default is ``False``. Returns a :class:`~motor.MotorBulkOperationBuilder` instance. See :ref:`unordered_bulk` for examples. .. versionchanged:: 1.0 Added bypass_document_validation support .. versionadded:: 0.2 """ bob_class = create_class_with_framework( AgnosticBulkOperationBuilder, self._framework, self.__module__) return bob_class(self, ordered=False, bypass_document_validation=bypass_document_validation) def initialize_ordered_bulk_op(self, bypass_document_validation=False): """Initialize an ordered batch of write operations. Operations will be performed on the server serially, in the order provided. If an error occurs all remaining operations are aborted. :Parameters: - `bypass_document_validation`: (optional) If ``True``, allows the write to opt-out of document level validation. Default is ``False``. Returns a :class:`~motor.MotorBulkOperationBuilder` instance. See :ref:`ordered_bulk` for examples. .. versionchanged:: 1.0 Added bypass_document_validation support .. versionadded:: 0.2 """ bob_class = create_class_with_framework( AgnosticBulkOperationBuilder, self._framework, self.__module__) return bob_class(self, ordered=True, bypass_document_validation=bypass_document_validation) def wrap(self, obj): if obj.__class__ is Collection: # Replace pymongo.collection.Collection with MotorCollection. return self.__class__(self.database, obj.name, _delegate=obj) elif obj.__class__ is Cursor: return AgnosticCursor(obj, self) elif obj.__class__ is CommandCursor: command_cursor_class = create_class_with_framework( AgnosticCommandCursor, self._framework, self.__module__) return command_cursor_class(obj, self) elif obj.__class__ is ChangeStream: change_stream_class = create_class_with_framework( AgnosticChangeStream, self._framework, self.__module__) return change_stream_class(obj, self) else: return obj def get_io_loop(self): return self.database.get_io_loop() class AgnosticBaseCursor(AgnosticBase): """Base class for AgnosticCursor and AgnosticCommandCursor""" _refresh = AsyncRead() address = ReadOnlyProperty() cursor_id = ReadOnlyProperty() alive = ReadOnlyProperty() batch_size = MotorCursorChainingMethod() session = ReadOnlyProperty() def __init__(self, cursor, collection): """Don't construct a cursor yourself, but acquire one from methods like :meth:`MotorCollection.find` or :meth:`MotorCollection.aggregate`. .. note:: There is no need to manually close cursors; they are closed by the server after being fully iterated with :meth:`to_list`, :meth:`each`, or :attr:`fetch_next`, or automatically closed by the client when the :class:`MotorCursor` is cleaned up by the garbage collector. """ # 'cursor' is a PyMongo Cursor, CommandCursor, or a _LatentCursor. super(AgnosticBaseCursor, self).__init__(delegate=cursor) self.collection = collection self.started = False self.closed = False # python.org/dev/peps/pep-0492/#api-design-and-implementation-revisions if PY35: exec(textwrap.dedent(""" def __aiter__(self): return self async def __anext__(self): # An optimization: skip the "await" if possible. if self._buffer_size() or await self.fetch_next: return self.next_object() raise StopAsyncIteration() """), globals(), locals()) def _get_more(self): """Initial query or getMore. Returns a Future.""" if not self.alive: raise pymongo.errors.InvalidOperation( "Can't call get_more() on a MotorCursor that has been" " exhausted or killed.") self.started = True return self._refresh() @property @coroutine_annotation def fetch_next(self): """A Future used with `gen.coroutine`_ to asynchronously retrieve the next document in the result set, fetching a batch of documents from the server if necessary. Resolves to ``False`` if there are no more documents, otherwise :meth:`next_object` is guaranteed to return a document. .. _`gen.coroutine`: http://tornadoweb.org/en/stable/gen.html .. testsetup:: fetch_next MongoClient().test.test_collection.delete_many({}) collection = MotorClient().test.test_collection .. doctest:: fetch_next >>> @gen.coroutine ... def f(): ... yield collection.insert_many([{'_id': i} for i in range(5)]) ... cursor = collection.find().sort([('_id', 1)]) ... while (yield cursor.fetch_next): ... doc = cursor.next_object() ... sys.stdout.write(str(doc['_id']) + ', ') ... print('done') ... >>> IOLoop.current().run_sync(f) 0, 1, 2, 3, 4, done While it appears that fetch_next retrieves each document from the server individually, the cursor actually fetches documents efficiently in `large batches`_. In Python 3.5 and newer, cursors can be iterated elegantly and very efficiently in native coroutines with `async for`: .. doctest:: fetch_next >>> async def f(): ... async for doc in collection.find(): ... sys.stdout.write(str(doc['_id']) + ', ') ... print('done') ... >>> IOLoop.current().run_sync(f) 0, 1, 2, 3, 4, done .. _`large batches`: https://docs.mongodb.com/manual/tutorial/iterate-a-cursor/#cursor-batches """ if not self._buffer_size() and self.alive: # Return the Future, which resolves to number of docs fetched or 0. return self._get_more() elif self._buffer_size(): future = self._framework.get_future(self.get_io_loop()) future.set_result(True) return future else: # Dead future = self._framework.get_future(self.get_io_loop()) future.set_result(False) return future def next_object(self): """Get a document from the most recently fetched batch, or ``None``. See :attr:`fetch_next`. """ if not self._buffer_size(): return None return next(self.delegate) def each(self, callback): """Iterates over all the documents for this cursor. :meth:`each` returns immediately, and `callback` is executed asynchronously for each document. `callback` is passed ``(None, None)`` when iteration is complete. Cancel iteration early by returning ``False`` from the callback. (Only ``False`` cancels iteration: returning ``None`` or 0 does not.) .. testsetup:: each from tornado.ioloop import IOLoop MongoClient().test.test_collection.delete_many({}) collection = MotorClient().test.test_collection .. doctest:: each >>> def inserted(result, error): ... if error: ... raise error ... cursor = collection.find().sort([('_id', 1)]) ... cursor.each(callback=each) ... >>> def each(result, error): ... if error: ... raise error ... elif result: ... sys.stdout.write(str(result['_id']) + ', ') ... else: ... # Iteration complete ... IOLoop.current().stop() ... print('done') ... >>> collection.insert_many( ... [{'_id': i} for i in range(5)], callback=inserted) >>> IOLoop.current().start() 0, 1, 2, 3, 4, done .. note:: Unlike other Motor methods, ``each`` requires a callback and does not return a Future, so it cannot be used in a coroutine. ``async for``, :meth:`to_list`, :attr:`fetch_next` are much easier to use. :Parameters: - `callback`: function taking (document, error) """ if not callable(callback): raise callback_type_error self._each_got_more(callback, None) def _each_got_more(self, callback, future): if future: try: future.result() except Exception as error: callback(None, error) return while self._buffer_size() > 0: doc = next(self.delegate) # decrements self.buffer_size # Quit if callback returns exactly False (not None). Note we # don't close the cursor: user may want to resume iteration. if callback(doc, None) is False: return # The callback closed this cursor? if self.closed: return if self.alive and (self.cursor_id or not self.started): self._framework.add_future( self.get_io_loop(), self._get_more(), self._each_got_more, callback) else: # Complete self._framework.call_soon( self.get_io_loop(), functools.partial(callback, None, None)) @coroutine_annotation def to_list(self, length, callback=None): """Get a list of documents. .. testsetup:: to_list MongoClient().test.test_collection.delete_many({}) from tornado import ioloop .. doctest:: to_list >>> from motor.motor_tornado import MotorClient >>> collection = MotorClient().test.test_collection >>> >>> @gen.coroutine ... def f(): ... yield collection.insert_many([{'_id': i} for i in range(4)]) ... cursor = collection.find().sort([('_id', 1)]) ... docs = yield cursor.to_list(length=2) ... while docs: ... print(docs) ... docs = yield cursor.to_list(length=2) ... ... print('done') ... >>> ioloop.IOLoop.current().run_sync(f) [{'_id': 0}, {'_id': 1}] [{'_id': 2}, {'_id': 3}] done :Parameters: - `length`: maximum number of documents to return for this call, or None - `callback` (optional): function taking (documents, error) If a callback is passed, returns None, else returns a Future. .. versionchanged:: 0.2 `callback` must be passed as a keyword argument, like ``to_list(10, callback=callback)``, and the `length` parameter is no longer optional. """ if length is not None: if not isinstance(length, int): raise TypeError('length must be an int, not %r' % length) elif length < 0: raise ValueError('length must be non-negative') if self._query_flags() & _QUERY_OPTIONS['tailable_cursor']: raise pymongo.errors.InvalidOperation( "Can't call to_list on tailable cursor") to_list_future = self._framework.get_future(self.get_io_loop()) # Run future_or_callback's type checking before we change anything. retval = self._framework.future_or_callback(to_list_future, callback, self.get_io_loop()) if not self.alive: to_list_future.set_result([]) else: the_list = [] self._framework.add_future( self.get_io_loop(), self._get_more(), self._to_list, length, the_list, to_list_future) return retval def _to_list(self, length, the_list, to_list_future, get_more_result): # get_more_result is the result of self._get_more(). # to_list_future will be the result of the user's to_list() call. try: result = get_more_result.result() collection = self.collection fix_outgoing = collection.database.delegate._fix_outgoing if length is None: n = result else: n = min(length, result) for _ in range(n): the_list.append(fix_outgoing(self._data().popleft(), collection)) reached_length = (length is not None and len(the_list) >= length) if reached_length or not self.alive: to_list_future.set_result(the_list) else: self._framework.add_future( self.get_io_loop(), self._get_more(), self._to_list, length, the_list, to_list_future) except Exception as exc: to_list_future.set_exception(exc) def get_io_loop(self): return self.collection.get_io_loop() @motor_coroutine def close(self): """Explicitly kill this cursor on the server. Call like (in Tornado): .. code-block:: python yield cursor.close() """ if not self.closed: self.closed = True yield self._framework.yieldable(self._close()) def _buffer_size(self): return len(self._data()) # Paper over some differences between PyMongo Cursor and CommandCursor. def _query_flags(self): raise NotImplementedError def _data(self): raise NotImplementedError def _clear_cursor_id(self): raise NotImplementedError def _close_exhaust_cursor(self): raise NotImplementedError def _killed(self): raise NotImplementedError @motor_coroutine def _close(self): raise NotImplementedError() class AgnosticCursor(AgnosticBaseCursor): __motor_class_name__ = 'MotorCursor' __delegate_class__ = Cursor address = ReadOnlyProperty() count = AsyncRead() collation = MotorCursorChainingMethod() distinct = AsyncRead() explain = AsyncRead() add_option = MotorCursorChainingMethod() remove_option = MotorCursorChainingMethod() limit = MotorCursorChainingMethod() skip = MotorCursorChainingMethod() max_scan = MotorCursorChainingMethod() sort = MotorCursorChainingMethod(doc=cursor_sort_doc) hint = MotorCursorChainingMethod() where = MotorCursorChainingMethod() max_await_time_ms = MotorCursorChainingMethod() max_time_ms = MotorCursorChainingMethod() min = MotorCursorChainingMethod() max = MotorCursorChainingMethod() comment = MotorCursorChainingMethod() _Cursor__die = AsyncRead() def rewind(self): """Rewind this cursor to its unevaluated state.""" self.delegate.rewind() self.started = False return self def clone(self): """Get a clone of this cursor.""" return self.__class__(self.delegate.clone(), self.collection) def __copy__(self): return self.__class__(self.delegate.__copy__(), self.collection) def __deepcopy__(self, memo): return self.__class__(self.delegate.__deepcopy__(memo), self.collection) def _query_flags(self): return self.delegate._Cursor__query_flags def _data(self): return self.delegate._Cursor__data def _clear_cursor_id(self): self.delegate._Cursor__id = 0 def _close_exhaust_cursor(self): # If an exhaust cursor is dying without fully iterating its results, # it must close the socket. PyMongo's Cursor does this, but we've # disabled its cleanup so we must do it ourselves. if self.delegate._Cursor__exhaust: manager = self.delegate._Cursor__exhaust_mgr if manager.sock: manager.sock.close() manager.close() def _killed(self): return self.delegate._Cursor__killed @motor_coroutine def _close(self): yield self._framework.yieldable(self._Cursor__die()) class AgnosticCommandCursor(AgnosticBaseCursor): __motor_class_name__ = 'MotorCommandCursor' __delegate_class__ = CommandCursor _CommandCursor__die = AsyncRead() def _query_flags(self): return 0 def _data(self): return self.delegate._CommandCursor__data def _clear_cursor_id(self): self.delegate._CommandCursor__id = 0 def _close_exhaust_cursor(self): # MongoDB doesn't have exhaust command cursors yet. pass def _killed(self): return self.delegate._CommandCursor__killed @motor_coroutine def _close(self): yield self._framework.yieldable(self._CommandCursor__die()) class _LatentCursor(object): """Take the place of a PyMongo CommandCursor until aggregate() begins.""" alive = True _CommandCursor__data = [] _CommandCursor__id = None _CommandCursor__killed = False cursor_id = None def clone(self): return _LatentCursor() def rewind(self): pass class AgnosticLatentCommandCursor(AgnosticCommandCursor): __motor_class_name__ = 'MotorLatentCommandCursor' def __init__(self, collection, start, *args, **kwargs): # We're being constructed without yield or await, like: # # cursor = collection.aggregate(pipeline) # # ... so we can't send the "aggregate" command to the server and get # a PyMongo CommandCursor back yet. Set self.delegate to a latent # cursor until the first yield or await triggers _get_more(), which # will execute the callback "start", which gets a PyMongo CommandCursor. super(self.__class__, self).__init__(_LatentCursor(), collection) self.start = start self.args = args self.kwargs = kwargs def _get_more(self): if not self.started: self.started = True original_future = self._framework.get_future(self.get_io_loop()) future = self.start( *self.args, **self.kwargs) self.start = self.args = self.kwargs = None self._framework.add_future( self.get_io_loop(), future, self._on_get_more, original_future) return original_future return super(self.__class__, self)._get_more() def _on_get_more(self, original_future, future): try: # "result" is a CommandCursor from PyMongo's aggregate(). self.delegate = future.result() except Exception as exc: original_future.set_exception(exc) else: # _get_more is complete. original_future.set_result(len(self.delegate._CommandCursor__data)) class AgnosticBulkOperationBuilder(AgnosticBase): __motor_class_name__ = 'MotorBulkOperationBuilder' __delegate_class__ = BulkOperationBuilder find = DelegateMethod() insert = DelegateMethod() execute = AsyncCommand() def __init__(self, collection, ordered, bypass_document_validation): self.io_loop = collection.get_io_loop() delegate = BulkOperationBuilder(collection.delegate, ordered, bypass_document_validation) super(self.__class__, self).__init__(delegate) def get_io_loop(self): return self.io_loop class AgnosticChangeStream(AgnosticBase): """A change stream cursor. Should not be called directly by application developers. See :meth:`~MotorCollection.watch` for example usage. .. versionadded: 1.2 .. mongodoc:: changeStreams """ __delegate_class__ = ChangeStream __motor_class_name__ = 'MotorChangeStream' _close = AsyncCommand(attr_name='close') def __init__(self, collection, pipeline, full_document, resume_after, max_await_time_ms, batch_size, collation, session): super(self.__class__, self).__init__(delegate=None) self._collection = collection self._kwargs = {'pipeline': pipeline, 'full_document': full_document, 'resume_after': resume_after, 'max_await_time_ms': max_await_time_ms, 'batch_size': batch_size, 'collation': collation, 'session': session} def _next(self): # This method is run on a thread. try: if not self.delegate: self.delegate = self._collection.delegate.watch(**self._kwargs) return self.delegate.next() except StopIteration: raise StopAsyncIteration() @coroutine_annotation(callback=False) def next(self): """Advance the cursor. This method blocks until the next change document is returned or an unrecoverable error is raised. Raises :exc:`StopAsyncIteration` if this change stream is closed. You can iterate the change stream by calling ``await change_stream.next()`` repeatedly, or with an "async for" loop: .. code-block:: python3 async for change in db.collection.watch(): print(change) """ loop = self.get_io_loop() return self._framework.run_on_executor(loop, self._next) @coroutine_annotation(callback=False) def close(self): """Close this change stream. Stops any "async for" loops using this change stream. """ if self.delegate: return self._close() # Never started. future = self._framework.get_future(self.get_io_loop()) future.set_result(None) return future if PY35: exec(textwrap.dedent(""" async def __aiter__(self): return self __anext__ = next async def __aenter__(self): return self async def __aexit__(self, exc_type, exc_val, exc_tb): if self.delegate: self.delegate.close() """), globals(), locals()) def get_io_loop(self): return self._collection.get_io_loop() def __enter__(self): raise RuntimeError('Use a change stream in "async with", not "with"') def __exit__(self, exc_type, exc_val, exc_tb): pass
StarcoderdataPython
87919
<filename>inference/run_inference.py import gc import os from typing import List import numpy as np import tifffile import torch from torch import nn from torch.utils.data import Dataset, DataLoader from tqdm import tqdm from inference.tiling import Tiler, TileSlice from training.val_dataset import normalize_band class SliceDataset(Dataset): def __init__(self, scene_dir: str, tiler: Tiler) -> None: super().__init__() self.scene_dir = scene_dir self.tiler = tiler self.slices = tiler.generate_slices() self.vv_full = tifffile.imread(os.path.join(self.scene_dir, "VV_dB.tif")) self.vh_full = tifffile.imread(os.path.join(self.scene_dir, "VH_dB.tif")) def __getitem__(self, index): slice = self.slices[index] vv = self.tiler.get_crop(self.vv_full, slice) vh = self.tiler.get_crop(self.vh_full, slice) vv = normalize_band(vv) vh = normalize_band(vh) img = torch.from_numpy(np.stack([vv, vh], axis=0)).float() return img, np.array([slice.row, slice.column, slice.y, slice.x]) def __len__(self): return len(self.slices) def predict_scene_and_return_mm(models: List[nn.Module], dataset_dir, scene_id: str, use_fp16: bool = False, rotate=False, output_dir=None): vh_full = tifffile.memmap(os.path.join(dataset_dir, scene_id, "VH_dB.tif"), mode="r") height, width = vh_full.shape tiler = Tiler(height, width, 3584, overlap=704) vessel_preds = np.zeros_like(vh_full, dtype=np.uint8) fishing_preds = np.zeros_like(vh_full, dtype=np.uint8) length_preds = np.zeros_like(vh_full, dtype=np.float16) center_preds = np.zeros_like(vh_full, dtype=np.uint8) slice_dataset = SliceDataset(os.path.join(dataset_dir, scene_id), tiler) slice_loader = DataLoader( slice_dataset, batch_size=1, shuffle=False, num_workers=8, pin_memory=False ) for batch, slice_vals in tqdm(slice_loader): slice = TileSlice(*slice_vals[0]) with torch.no_grad(): batch = batch.cuda() with torch.cuda.amp.autocast(enabled=use_fp16): outputs = [] for model in models: output = model(batch) sigmoid_keys = ["fishing_mask", "vessel_mask"] for k in sigmoid_keys: output[k] = torch.sigmoid(output[k]) if rotate: out180 = model(torch.rot90(batch, 2, dims=(2, 3))) for key in list(output.keys()): val = torch.rot90(out180[key], 2, dims=(2, 3)) if key in sigmoid_keys: val = torch.sigmoid(val) output[key] += val output[key] *= 0.5 outputs.append(output) output = {} for k in outputs[0].keys(): vs = [o[k][:, :3] for o in outputs] output[k] = sum(vs) / len(models) vessel_mask = (output["vessel_mask"][0][0] * 255).cpu().numpy().astype(np.uint8) fishing_mask = (output["fishing_mask"][0][0] * 255).cpu().numpy().astype(np.uint8) center_mask = torch.clamp(output["center_mask"][0][0], 0, 255).cpu().numpy().astype(np.uint8) length_mask = output["length_mask"][0][0].cpu().numpy().astype(np.float16) tiler.update_crop(vessel_preds, vessel_mask, slice) tiler.update_crop(fishing_preds, fishing_mask, slice) tiler.update_crop(center_preds, center_mask, slice) tiler.update_crop(length_preds, length_mask, slice) # tiler.update_crop(conf_preds, conf_mask, slice) if output_dir: os.makedirs(os.path.join(output_dir, scene_id), exist_ok=True) np.save(os.path.join(output_dir, scene_id, "center_preds"), center_preds) np.save(os.path.join(output_dir, scene_id, "vessel_preds"), vessel_preds) np.save(os.path.join(output_dir, scene_id, "fishing_preds"), fishing_preds) np.save(os.path.join(output_dir, scene_id, "length_preds"), length_preds) gc.collect() return { "center_mask": center_preds, "vessel_mask": vessel_preds, "fishing_mask": fishing_preds, "length_mask": length_preds, }
StarcoderdataPython
1841048
<filename>waitlist/blueprints/xup/submission.py import logging from datetime import datetime from flask import request, flash, redirect, url_for, render_template, abort from flask_login import current_user, login_required import re from waitlist.blueprints.api.fittings.self import self_remove_fit from waitlist.data.names import WaitlistNames from waitlist.data.sse import EntryAddedSSE, send_server_sent_event,\ FitAddedSSE from waitlist.storage.database import WaitlistGroup, WaitlistEntry, Shipfit,\ TeamspeakDatum, InvType, FitModule, MarketGroup, HistoryEntry, Waitlist,\ ShipCheckCollection from waitlist.storage.modules import resist_ships, logi_ships from waitlist.utility.history_utils import create_history_object from waitlist.utility.fitting_utils import get_fit_format, parse_dna_fitting,\ parse_eft, get_waitlist_type_for_fit from waitlist.base import db from . import bp from flask_babel import gettext, ngettext from typing import Dict, List, Tuple from waitlist.utility.constants import location_flags, groups from waitlist.utility.settings import sget_active_ts_id from waitlist.utility.config import disable_teamspeak, disable_scruffy_mode import operator logger = logging.getLogger(__name__) @bp.route('/submit', methods=['POST']) @login_required def submit(): """ Parse the submited fitts Check which fits need additional Info Rattlesnake, Rokh, that other ugly thing Caldari BS lvl Basilisk, Scimitar Logi Lvl -> put info into comment of the fit """ # used for spawning the right SSEs _newEntryCreated = False _newFits = [] fittings = request.form['fits'] group_id = int(request.form['groupID']) logger.info("%s submitted %s for group %d", current_user.get_eve_name(), fittings, group_id) eve_id = current_user.get_eve_id() group = db.session.query(WaitlistGroup).filter(WaitlistGroup.groupID == group_id).one() if not group.enabled: # xups are disabled atm flash(gettext("X-UP is disabled!!!")) return redirect(url_for("index")) poke_me = 'pokeMe' in request.form if current_user.poke_me != poke_me: current_user.poke_me = poke_me db.session.commit() # check if it is scruffy if not disable_scruffy_mode and fittings.lower().startswith("scruffy"): # scruffy mode scruffy fittings = fittings.lower() _, _, ship_type = fittings.rpartition(" ") ship_types = [] # check for , to see if it is a multi value shiptype allowed_types = [tpl[0].strip() for tpl in db.session.query(Waitlist.waitlistType).filter((~Waitlist.group.has(WaitlistGroup.queueID == Waitlist.id)) & (Waitlist.groupID == group_id))] if "," in ship_type: for stype in ship_type.split(","): stype = stype.strip() if stype in allowed_types: ship_types.append(stype) else: if ship_type in allowed_types: ship_types.append(ship_type) # check if shiptype is valid if len(ship_types) <= 0: flash(gettext("Valid entries are scruffy %(types)s", types=','.join(allowed_types)), 'danger') return redirect(url_for('index')) queue = group.xuplist wl_entry = db.session.query(WaitlistEntry).filter( (WaitlistEntry.waitlist_id == queue.id) & (WaitlistEntry.user == eve_id)).first() if wl_entry is None: wl_entry = WaitlistEntry() wl_entry.creation = datetime.utcnow() wl_entry.user = eve_id queue.entries.append(wl_entry) _newEntryCreated = True h_entry = create_history_object(current_user.get_eve_id(), "xup") for stype in ship_types: wl = db.session.query(Waitlist).filter( (Waitlist.groupID == group_id) & (Waitlist.waitlistType == stype) ).first() target_wl_id = None if wl is not None: target_wl_id = wl.id if target_wl_id is None: target_wl_id = db.session.query(ShipCheckCollection).filter( (ShipCheckCollection.waitlistGroupID == group_id) ).one().defaultTargetID fit: Shipfit = Shipfit() fit.ship_type = 0 # #System >.> fit.wl_type = stype fit.modules = ':' fit.targetWaitlistID = target_wl_id wl_entry.fittings.append(fit) if not _newEntryCreated: _newFits.append(fit) h_entry.fittings.append(fit) db.session.add(h_entry) db.session.commit() if _newEntryCreated: event = EntryAddedSSE(wl_entry, group_id, queue.id, True) send_server_sent_event(event) else: for fit in _newFits: event = FitAddedSSE(group_id, queue.id, wl_entry.id, fit, True, wl_entry.user) send_server_sent_event(event) flash(gettext("You were added as %(ship_type)s", ship_type=ship_type), "success") return redirect(url_for('index') + "?groupId=" + str(group_id)) # ### END SCRUFFY CODE logilvl = request.form['logi'] if logilvl == "": logilvl = "0" caldari_bs_lvl = request.form['cbs'] if caldari_bs_lvl == "": caldari_bs_lvl = "0" logilvl = int(logilvl) caldari_bs_lvl = int(caldari_bs_lvl) newbro = request.form.get('newbro', "off") newbro = (newbro is not "off") current_user.is_new = newbro current_user.cbs_level = caldari_bs_lvl current_user.lc_level = logilvl logger.debug("Fittings to parse: %s", fittings) # lets normalize linebreaks fittings = fittings.replace("[\n\r]+", "\n") fittings = fittings.strip() # lets first find out what kind of fitting is used end_line_idx = fittings.find('\n') + 1 first_line = fittings[:end_line_idx] format_type = get_fit_format(first_line) fits = [] if format_type == "eft": # split fittings up in its fittings string_fits = [] fit_iter = re.finditer("\[.*,.*\]", fittings) s_idx = 0 first_iter = True for fitMatch in fit_iter: if not first_iter: e_idx = fitMatch.start() - 1 string_fits.append(fittings[s_idx:e_idx].split('\n')) else: first_iter = False s_idx = fitMatch.start() string_fits.append(fittings[s_idx:].split('\n')) logger.debug("Split fittings into %d fits", len(string_fits)) for fit in string_fits: try: dbfit = parse_eft(fit) if dbfit is None: abort(400, "Fit was not parseable.") fits.append(dbfit) except ValueError: abort(400, "Invalid module amounts") else: # parse chat links lines = fittings.split('\n') for line in lines: fit_iter = re.finditer( "<url=fitting:(\d+):((?:\d+_{0,1};\d+:)+:)>", line) for fitMatch in fit_iter: ship_type = int(fitMatch.group(1)) dna_fit = fitMatch.group(2) fit = Shipfit() fit.ship_type = ship_type fit.modules = dna_fit mod_list = parse_dna_fitting(dna_fit) for location_flag, mod_map in enumerate(mod_list): for mod_id in mod_map: mod = mod_map[mod_id] # lets check the value actually exists inv_type = db.session.query(InvType).get(mod[0]) if inv_type is None: raise ValueError( 'No module with ID=' + str(mod[0])) db_module = FitModule(moduleID=mod[0], amount=mod[1], locationFlag=location_flag) fit.moduleslist.append(db_module) fits.append(fit) fit_count = len(fits) logger.debug("Parsed %d fits", fit_count) if fit_count <= 0: flash(ngettext("You submitted one fit to be check by a fleet comp before getting on the waitlist.", "You submitted %(num)d fits to be check by a fleet comp before getting on the waitlist.", fit_count), "danger") return redirect(url_for('index') + "?groupId=" + str(group_id)) for fit in fits: if fit.ship_type in resist_ships: if logilvl == 0: pass # TODO ask for caldari bs lvl if fit.comment is None: fit.comment = "<b>Cal BS: " + str(caldari_bs_lvl) + "</b>" else: fit.comment += " <b>Cal BS: " + str(caldari_bs_lvl) + "</b>" else: if fit.ship_type in logi_ships: if logilvl == 0: pass # TODO ask for logi if logilvl <= 3: comment_string = "<b class=\"bg-danger\">Logi: {0}</b>" else: comment_string = "<b>Logi: {0}</b>" if fit.comment is None: fit.comment = comment_string.format(logilvl) else: fit.comment += " " + comment_string.format(logilvl) # get current users id eve_id = current_user.get_eve_id() fits_ready = [] # split his fits into types for the different waitlist_entries for fit in fits: tag, waitlist_id = get_waitlist_type_for_fit(fit, group_id) fit.wl_type = tag fit.targetWaitlistID = waitlist_id fits_ready.append(fit) # get the waitlist entries of this user queue = group.xuplist wl_entry = db.session.query(WaitlistEntry).filter( (WaitlistEntry.waitlist_id == queue.id) & (WaitlistEntry.user == eve_id)).first() if wl_entry is None: wl_entry = WaitlistEntry() wl_entry.creation = datetime.utcnow() wl_entry.user = eve_id queue.entries.append(wl_entry) _newEntryCreated = True logger.info("%s submitted %s fits to be checked by a fleetcomp", current_user.get_eve_name(), len(fits_ready)) for fit in fits_ready: logger.debug("%s submits %s", current_user.get_eve_name(), fit.get_dna()) wl_entry.fittings.append(fit) h_entry = create_history_object(current_user.get_eve_id(), HistoryEntry.EVENT_XUP, None, fits_ready) db.session.add(h_entry) db.session.commit() if _newEntryCreated: event = EntryAddedSSE(wl_entry, group_id, queue.id, True) send_server_sent_event(event) else: for fit in fits_ready: event = FitAddedSSE(group_id, queue.id, wl_entry.id, fit, True, wl_entry.user) send_server_sent_event(event) flash(ngettext("You submitted one fit to be check by a fleet comp before getting on the waitlist.", "You submitted %(num)d fits to be check by a fleet comp before getting on the waitlist.", fit_count), "success") return redirect(url_for('index') + "?groupId=" + str(group_id)) @bp.route('/', methods=['GET']) @login_required def index(): new_bro = current_user.is_new # noinspection PyPep8 defaultgroup = db.session.query(WaitlistGroup).filter(WaitlistGroup.enabled == True) \ .order_by(WaitlistGroup.ordering).first() # noinspection PyPep8 activegroups = db.session.query(WaitlistGroup).filter(WaitlistGroup.enabled == True).all() ts_settings = None ts_id = sget_active_ts_id() if not disable_teamspeak and ts_id is not None: ts_settings = db.session.query(TeamspeakDatum).get(ts_id) return render_template("xup.html", newbro=new_bro, group=defaultgroup, groups=activegroups, ts=ts_settings) @bp.route("/<int:fit_id>", methods=['GET']) @login_required def update(fit_id: int): new_bro: bool = current_user.is_new # noinspection PyPep8 defaultgroup = db.session.query(WaitlistGroup).filter(WaitlistGroup.enabled == True) \ .order_by(WaitlistGroup.ordering).first() # noinspection PyPep8 activegroups = db.session.query(WaitlistGroup).filter(WaitlistGroup.enabled == True).all() ts_settings = None ts_id = sget_active_ts_id() if ts_id is not None: ts_settings = db.session.query(TeamspeakDatum).get(ts_id) return render_template("xup.html", newbro=new_bro, group=defaultgroup, groups=activegroups, update=True, oldFitID=fit_id, ts=ts_settings) @bp.route("/update", methods=['POST']) @login_required def update_submit(): oldfit_id_str = request.form.get('old-fit-id') try: old_fit_id = int(oldfit_id_str) except ValueError: abort(400, "No valid id for the fit to update given!") return None response = submit() self_remove_fit(old_fit_id) return response
StarcoderdataPython
6675224
<gh_stars>0 # -*- coding: utf-8 -*- # Coded by <NAME> # 2020-12-13 # IDE: Jupyter Notebook def F(a, b): if a == 1: return 1 elif a > 10: while a > 10: aStr = str(a) aLen = len(aStr) a = a - pow(10, aLen - 1) if a == 0 and b != 0: return 10 elif a == 6 and b != 0: return 6 elif a == 5 and b != 0: return 5 else: a = a if b == 0: return 1 elif b > 100: # a가 2, 4, 8, 9 가능 3, 7은 4번 마다, 5, 6, 1은 무조건 가능. 10은 조정 해놓음 while b > 100: bStr = str(b) bLen = len(bStr) b = b - pow(10, bLen - 1) res = pow(a, b) if res >= 10: while res >= 10: resStr = str(res) resLen = len(resStr) res = res - pow(10, resLen - 1) if res == 0: return 10 else: return res T = int(input()) for i in range(T): a, b = map(int, input().split()) print(F(a, b))
StarcoderdataPython
11361416
<filename>modules/2.79/bpy/types/NodeSocketVectorAcceleration.py<gh_stars>0 NodeSocketVectorAcceleration.links = None
StarcoderdataPython
11283852
<reponame>hide-dog/kaggle_titanic # ------------------------------------------------ # import # ------------------------------------------------ import re # ------------------------------------------------ # read file # ------------------------------------------------ def rewrite_train_file(inf, of): # read file with open(inf) as f: lines = f.readlines() #end s = len(lines) for i in range(s-1): # del name n = re.findall('".+"', lines[i+1])[0] stn = lines[i+1].find(n) enn = stn + len(n) lines[i+1] = lines[i+1][:stn] + lines[i+1][enn:] # split l = lines[i+1].split(",") # refine data line = "" # Pclass if l[2] == "": l[2] = "3" else: pass #end # Name l[3] = "1" # Sex if l[4] == "male": l[4] = "1" else: l[4] = "0" #end # Age if l[5] == "": l[5] = "30" else: pass #end # SibSp if l[6] == "": l[6] = "1" else: pass #end # Parch if l[7] == "": l[7] = "0" else: pass #end # Ticket l[8] = "1" # Fare if l[9] == "": l[9] = "20.0" else: pass #end # Cabin l[10] = "1" # Embarked if l[11].find("S") > -1: l[11] = "0" elif l[11].find("C") > -1: l[11] = "1" elif l[11].find("Q") > -1: l[11] = "2" else: l[11] = "0" #end for j in range(len(l)): if j == len(l) - 1: line = line + l[j] + "\n" else: line = line + l[j] + "," #end #end lines[i+1] = line #end # write file with open(of, "w") as f: for i in range(len(lines)): f.write(lines[i]) #end #end #end # ------------------------------------------------ # main # ------------------------------------------------ def main(): # rewrite file rewrite_train_file("train.csv", "train.txt") rewrite_train_file("test.csv", "test.txt") #end if __name__ == "__main__": main()
StarcoderdataPython
3588203
raise ImportError("AWS Cognito can be configured via GenericOAuthenticator")
StarcoderdataPython
1678891
import os import re import shutil import datetime import jinja2 _template_pattern = re.compile(r"^.*(\.t)\.[^\.]+$") def default_template_arguments(): return {"now":datetime.datetime.now()} def apply_template_dir(src_dir, dest_dir, template_params, filter_name=None): # print(f"D {src_dir} -> {dest_dir}") if not os.path.exists(dest_dir): os.makedirs(dest_dir) for item in os.listdir(src_dir): if filter_name and not filter_name(src_dir, item): continue s = os.path.join(src_dir, item) if os.path.isdir(s): d = os.path.join(dest_dir, item) apply_template_dir(s, d, template_params, filter_name) else: match = _template_pattern.match(item) if match: i,j = match.span(1) d = os.path.join(dest_dir, item[:i] + item[j:]) with open(s, "r", encoding='utf8') as sf: t = jinja2.Template(sf.read()) dtext = t.render(template_params) with open(d, "w", encoding='utf8') as df: df.write(dtext) #print(f"T {s} -> {d}") else: d = os.path.join(dest_dir, item) shutil.copyfile(s,d) #print(f"C {s} -> {d}")
StarcoderdataPython
9788340
<reponame>HumbleRetreat/meru from unittest.mock import create_autospec import pytest from meru.handlers import handle_action, register_action_handler @pytest.mark.asyncio async def test_dont_handle_unknown_action(dummy_action): with pytest.raises(StopAsyncIteration): await handle_action(dummy_action()).__anext__() @pytest.mark.xfail @pytest.mark.asyncio @pytest.mark.freeze_time async def test_handle_async_generator_handler( dummy_action, dummy_state_cls, mocker, mocked_states ): """ This test will fail, because I have no idea how to create a stub with annotations. """ mocker.patch("meru.handlers.HANDLERS", {}) async def dummy_handler(action: dummy_action, state: dummy_state_cls): yield dummy_action() stub = create_autospec(dummy_handler) register_action_handler(stub) await handle_action(dummy_action()).__anext__() stub.assert_awaited_once_with( action=dummy_action(), state=mocked_states[dummy_state_cls], )
StarcoderdataPython
12824304
import inspect import pytest from sqlalchemy.exc import ArgumentError from sqlalchemy.ext.declarative import declared_attr def test_name(db): class FOOBar(db.Model): id = db.Column(db.Integer, primary_key=True) class BazBar(db.Model): id = db.Column(db.Integer, primary_key=True) class Ham(db.Model): __tablename__ = "spam" id = db.Column(db.Integer, primary_key=True) assert FOOBar.__tablename__ == "foo_bar" assert BazBar.__tablename__ == "baz_bar" assert Ham.__tablename__ == "spam" def test_single_name(db): """Single table inheritance should not set a new name.""" class Duck(db.Model): id = db.Column(db.Integer, primary_key=True) class Mallard(Duck): pass assert "__tablename__" not in Mallard.__dict__ assert Mallard.__tablename__ == "duck" def test_joined_name(db): """Model has a separate primary key; it should set a new name.""" class Duck(db.Model): id = db.Column(db.Integer, primary_key=True) class Donald(Duck): id = db.Column(db.Integer, db.ForeignKey(Duck.id), primary_key=True) assert Donald.__tablename__ == "donald" def test_mixin_id(db): """Primary key provided by mixin should still allow model to set tablename. """ class Base: id = db.Column(db.Integer, primary_key=True) class Duck(Base, db.Model): pass assert not hasattr(Base, "__tablename__") assert Duck.__tablename__ == "duck" def test_mixin_attr(db): """A declared attr tablename will be used down multiple levels of inheritance. """ class Mixin: @declared_attr def __tablename__(cls): # noqa: B902 return cls.__name__.upper() class Bird(Mixin, db.Model): id = db.Column(db.Integer, primary_key=True) class Duck(Bird): # object reference id = db.Column(db.ForeignKey(Bird.id), primary_key=True) class Mallard(Duck): # string reference id = db.Column(db.ForeignKey("DUCK.id"), primary_key=True) assert Bird.__tablename__ == "BIRD" assert Duck.__tablename__ == "DUCK" assert Mallard.__tablename__ == "MALLARD" def test_abstract_name(db): """Abstract model should not set a name. Subclass should set a name.""" class Base(db.Model): __abstract__ = True id = db.Column(db.Integer, primary_key=True) class Duck(Base): pass assert "__tablename__" not in Base.__dict__ assert Duck.__tablename__ == "duck" def test_complex_inheritance(db): """Joined table inheritance, but the new primary key is provided by a mixin, not directly on the class. """ class Duck(db.Model): id = db.Column(db.Integer, primary_key=True) class IdMixin: @declared_attr def id(cls): # noqa: B902 return db.Column(db.Integer, db.ForeignKey(Duck.id), primary_key=True) class RubberDuck(IdMixin, Duck): pass assert RubberDuck.__tablename__ == "rubber_duck" def test_manual_name(db): """Setting a manual name prevents generation for the immediate model. A name is generated for joined but not single-table inheritance. """ class Duck(db.Model): __tablename__ = "DUCK" id = db.Column(db.Integer, primary_key=True) type = db.Column(db.String) __mapper_args__ = {"polymorphic_on": type} class Daffy(Duck): id = db.Column(db.Integer, db.ForeignKey(Duck.id), primary_key=True) __mapper_args__ = {"polymorphic_identity": "Warner"} class Donald(Duck): __mapper_args__ = {"polymorphic_identity": "Disney"} assert Duck.__tablename__ == "DUCK" assert Daffy.__tablename__ == "daffy" assert "__tablename__" not in Donald.__dict__ assert Donald.__tablename__ == "DUCK" # polymorphic condition for single-table query assert 'WHERE "DUCK".type' in str(Donald.query) def test_primary_constraint(db): """Primary key will be picked up from table args.""" class Duck(db.Model): id = db.Column(db.Integer) __table_args__ = (db.PrimaryKeyConstraint(id),) assert Duck.__table__ is not None assert Duck.__tablename__ == "duck" def test_no_access_to_class_property(db): """Ensure the implementation doesn't access class properties or declared attrs while inspecting the unmapped model. """ class class_property: def __init__(self, f): self.f = f def __get__(self, instance, owner): return self.f(owner) class Duck(db.Model): id = db.Column(db.Integer, primary_key=True) class ns: is_duck = False floats = False class Witch(Duck): @declared_attr def is_duck(self): # declared attrs will be accessed during mapper configuration, # but make sure they're not accessed before that info = inspect.getouterframes(inspect.currentframe())[2] assert info[3] != "_should_set_tablename" ns.is_duck = True @class_property def floats(self): ns.floats = True assert ns.is_duck assert not ns.floats def test_metadata_has_table(db): user = db.Table("user", db.Column("id", db.Integer, primary_key=True)) class User(db.Model): pass assert User.__table__ is user def test_correct_error_for_no_primary_key(db): with pytest.raises(ArgumentError) as info: class User(db.Model): pass assert "could not assemble any primary key" in str(info.value) def test_single_has_parent_table(db): class Duck(db.Model): id = db.Column(db.Integer, primary_key=True) class Call(Duck): pass assert Call.__table__ is Duck.__table__ assert "__table__" not in Call.__dict__
StarcoderdataPython
296527
from actstream.models import Follow from rest_framework import serializers from grandchallenge.notifications.models import Notification class NotificationSerializer(serializers.ModelSerializer): class Meta: model = Notification fields = ("read",) class FollowSerializer(serializers.ModelSerializer): class Meta: model = Follow fields = ("pk", "flag")
StarcoderdataPython
6528899
<reponame>darwinbeing/deepdriving-tensorflow<filename>python/modules/deep_learning/trainer/__init__.py from .CFactory import CFactory from .CTrainer import CTrainer
StarcoderdataPython
9611644
from Clusters.models import ClusterDetails from Clusters.serializers import ClusterDetailsSerializer from django.http import JsonResponse from django.shortcuts import render from rest_framework import viewsets from rest_framework.generics import GenericAPIView def index(request): return render(request, 'index.html', context={}, status=200) class ClusterDetailsView(viewsets.ModelViewSet): queryset = ClusterDetails.objects.all() serializer_class = ClusterDetailsSerializer class ClustersView(GenericAPIView): http_method_names = ('post', 'create') serializer_class = ClusterDetailsSerializer def post(self, request, **kwargs): print('ClustersView - post') post_data = request.data post_data.pop('url', None) if post_data.get('action') == 'delete': selected_ids = post_data.get('selected_ids') ClusterDetails.objects.filter(id__in=selected_ids).delete() else: ClusterDetails.objects.filter(id=post_data.pop('id')).update(**post_data) return JsonResponse({'status': 'success'}, safe=False) def create(self, request, **kwargs): print('ClustersView - create') ClusterDetails( cluster_name=request.data['cluster_name'], nodes_count=request.data['nodes_count'] ).save() return JsonResponse({'status': 'success'}, safe=False)
StarcoderdataPython
6571513
<filename>apps/utils/management/commands/introspect.py<gh_stars>0 from django.core.management.base import AppCommand from django.db.models import get_models from django.db.models.fields.related import OneToOneField, ForeignKey class Command(AppCommand): help = "Generate search template with all fields for each model in an app" def printfield(self, field, accessor): print """ {%% if %s %%} <dt>%s</dt> <dd>{{ %s }}</dd> {%% endif %%}""" % (accessor, field.verbose_name, accessor) # print '{{ %s }}' % accessor def handle_app(self, app, **options): models = get_models(app) processed_models = set() for model in models: if model in processed_models: continue processed_models.add(model) print model for field in model._meta.fields: fieldaccessor = 'object.%s' % field.name self.printfield(field, fieldaccessor) for related in model._meta.get_all_related_objects(): processed_models.add(related.model) accessor = related.get_accessor_name() if isinstance(related.field, OneToOneField): for field in related.model._meta.fields: fieldaccessor = 'object.%s.%s' % (accessor, field.name) self.printfield(field, fieldaccessor) elif isinstance(related.field, ForeignKey): print '{%% for related in objects.%s %%}' % accessor for field in related.model._meta.fields: fieldaccessor = 'related.%s' % field.name self.printfield(field, fieldaccessor) print '{% endfor %}'
StarcoderdataPython
6588241
#integer right triangles """" If p is the perimeter of a right angle triangle with integral length sides, {a,b,c}, there are exactly three solutions for p = 120. {20,48,52}, {24,45,51}, {30,40,50} For which value of p ≤ 1000, is the number of solutions maximised? """"" import math, time def gcd(a, b): while b != 0: a, b = b, a % b return a def project_euler_1(limit): res = 0 cnt = 0 for k in range(12, 1001): n = 0 for i in range(1, int(k * (1 - math.sqrt(2) / 2))): for j in range(int(k * (1 - math.sqrt(2) / 2)), k // 2): if i ** 2 + j ** 2 == (k - i - j) ** 2: n += 1 if cnt < n: res = k cnt = n print(res) def project_euler_2(limit): t = [0] * (limit + 1) for i in range(2, int((limit // 2) ** 0.5)): for j in range(1, i): if (i - j) % 2 == 1 and gcd(i, j) == 1: s = 2 * i * (i + j) for x in range(s, limit + 1, s): t[x] += 1 print(t.index(max(t))) if __name__ == '__main__': start = time.clock() project_euler_2(1000) print('Runtime is ', time.clock() - start)
StarcoderdataPython
1972555
"""Ampio data models.""" from __future__ import annotations import base64 from collections import defaultdict import datetime as dt from enum import Enum, IntEnum import logging from typing import Any, Callable, Dict, List, Optional, Union import attr from homeassistant.const import ( CONF_DEVICE, CONF_DEVICE_CLASS, CONF_FRIENDLY_NAME, CONF_ICON, CONF_NAME, CONF_UNIT_OF_MEASUREMENT, ) from homeassistant.helpers import device_registry from .const import ( CONF_ALARM_TOPIC, CONF_ARMED_TOPIC, CONF_AWAY_ZONES, CONF_BRIGHTNESS_COMMAND_TOPIC, CONF_BRIGHTNESS_STATE_TOPIC, CONF_CLOSING_STATE_TOPIC, CONF_COMMAND_TOPIC, CONF_ENTRYTIME_TOPIC, CONF_EXITTIME10_TOPIC, CONF_EXITTIME_TOPIC, CONF_HOME_ZONES, CONF_OPENING_STATE_TOPIC, CONF_RAW_TOPIC, CONF_RGB_COMMAND_TOPIC, CONF_RGB_STATE_TOPIC, CONF_STATE_TOPIC, CONF_TILT_POSITION_TOPIC, CONF_UNIQUE_ID, CONF_WHITE_VALUE_COMMAND_TOPIC, CONF_WHITE_VALUE_STATE_TOPIC, DOMAIN, ) from .validators import ( AMPIO_DESCRIPTIONS_SCHEMA, AMPIO_DEVICES_SCHEMA, ATTR_A, ATTR_AU, ATTR_I, ATTR_O, ATTR_D, ATTR_DATE_PROD, ATTR_FLAG, ATTR_MAC, ATTR_N, ATTR_NAME, ATTR_PCB, ATTR_PROTOCOL, ATTR_SOFTWARE, ATTR_T, ATTR_TYPE, ATTR_USERMAC, ) DEVICE_CLASSES = { "B": "battery", "BC": "battery_charging", "C": "cold", "CO": "connectivity", "D": "door", "GD": "garage_door", "GA": "gas", "HE": "heat", "L": "light", "LO": "lock", "MI": "moisture", "M": "motion", "MV": "moving", "OC": "occupancy", "O": "opening", "P": "plug", "PW": "power", "PR": "presence", "PB": "problem", "S": "safety", "SO": "sound", "V": "vibration", "W": "window", # switches "OU": "outlet", # sensors "T": "temperature", "H": "humidity", "I": "illuminance", "SS": "signal_strength", "PS": "pressure", "TS": "timestamp", # covers "VA": "valve", "G": "garage", "BL": "blind", } TYPE_CODES = { 44: "MSENS", 3: "MROL-4s", 4: "MPR-8s", 5: "MDIM-8s", 8: "MDOT-4", 10: "MSERV-3s", 11: "MDOT-9", 12: "MRGBu-1", 17: "MLED-1", 22: "MRT-16s", 25: "MCON", 26: "MOC-4", 27: "MDOT-15LCD", 33: "MDOT-2", 34: "METEO-1s", 38: "MRDN-1s", 49: "MWRC", } class ModuleCodes(IntEnum): """Module codes enum.""" MLED1 = 17 MCON = 25 MDIM8s = 5 MSENS = 44 MDOT2 = 33 DOMAIN = "ampio" _LOGGER = logging.getLogger(__name__) PublishPayloadType = Union[str, bytes, int, float, None] @attr.s(slots=True, frozen=True) class Message: """MQTT Message.""" topic = attr.ib(type=str) payload = attr.ib(type=PublishPayloadType) qos = attr.ib(type=int) retain = attr.ib(type=bool) subscribed_topic = attr.ib(type=str, default=None) timestamp = attr.ib(type=dt.datetime, default=None) MessageCallbackType = Callable[[Message], None] def extract_index_from_topic(topic: str) -> Optional[int]: """Takes last part of topic as number.""" parts = topic.split("/") try: return int(parts[-1]) except ValueError: return None @attr.s(slots=True, frozen=True) class IndexIntData: """Represents the index from last part of topic with data.""" index = attr.ib(type=int) value = attr.ib(type=int) @classmethod def from_msg(cls, msg: Message) -> Optional[IndexIntData]: """Create from MQTT message.""" index = extract_index_from_topic(msg.topic) if index is None: _LOGGER.error("Unable to extract index from topic: %s", msg.topic) return None try: value = int(msg.payload) except ValueError: _LOGGER.error("Unable to parse data message tp ind: %s", msg.payload) return None return cls(index, value) class ItemTypes(str, Enum): """Item type codes.""" # OW = "t" # # BinaryFlag = "f" # BinaryInput254 = "i" # BinaryInput509 = "i" # BinaryOutput254 = "o" # BinaryOutput509 = "o" # AnalogInput254 = "a" # AnalogInput509 = "a" # AnalogOutput254 = "au" # AnalogOutput509 = "au" Temperature = "t" BinaryFlag = "f" BinaryInput = "i" BinaryOutput = "o" AnalogInput = "a" AnalogOutput = "au" def base64decode(value: str): """Decode base64 string.""" try: return base64.b64decode(value).decode("utf-8").strip() except UnicodeDecodeError: return base64.b64decode(value).decode("cp1254").strip() def base64encode(value: str): """Encode base64 string.""" return base64.b64encode(value.encode("utf-8")) @attr.s() class ItemName: """Name of the ampio module Item (input, output, flag, etc).""" d = attr.ib(type=str, converter=base64decode) # pylint: disable=invalid-name name = attr.ib(type=str) device_class = attr.ib(type=str) prefix = attr.ib(type=str) @name.default def extract_name(self): """Compute name.""" parts = self.d.split(":") if len(parts) > 1: return "".join(parts[1:]) return self.d @device_class.default def extract_device_class(self): """Compute device_class.""" parts = self.d.split(":") if len(parts) > 1: prefix = parts[0] return DEVICE_CLASSES.get(prefix) return None @prefix.default def extract_prefix(self): """Extrct device type code from name.""" parts = self.d.split(":") if len(parts) > 1: return parts[0] return None @classmethod def from_topic_payload(cls, payload: Dict) -> List[ItemName]: """Read from topic payload.""" names: Dict[str, Union[int, Dict]] = AMPIO_DESCRIPTIONS_SCHEMA(payload) result = {} for name in names[ATTR_D]: name_data = name[ATTR_D] name_type = name[ATTR_T] name_index = name[ATTR_N] if name_type not in result.keys(): result[name_type] = {} result[name_type][name_index] = ItemName(name_data) return result @attr.s() class AmpioModuleInfo: """Ampio Module Information.""" mac = attr.ib(type=str, converter=str.upper) user_mac = attr.ib(type=str, converter=str.upper) code = attr.ib(type=int) pcb = attr.ib(type=int) software = attr.ib(type=int) protocol = attr.ib(type=int) date_prod = attr.ib(type=str) i = attr.ib(type=int) # pylint: disable=invalid-name o = attr.ib(type=int) # pylint: disable=invalid-name a = attr.ib(type=int) # pylint: disable=invalid-name au = attr.ib(type=int) # pylint: disable=invalid-name t = attr.ib(type=int) # pylint: disable=invalid-name flags = attr.ib(type=int) name = attr.ib(type=str, converter=base64decode) names = attr.ib(factory=dict) configs = attr.ib(factory=dict) unique_ids = attr.ib(factory=set) def update_configs(self) -> None: """Update the config data for entities.""" self.configs = defaultdict(list) # clean up current configs self.unique_ids = set() for index, item in self.names.get(ItemTypes.BinaryFlag, {}).items(): data = AmpioFlagConfig.from_ampio_device(self, item, index + 1) if data: self.configs["switch"].append(data.config) self.unique_ids.add(data.unique_id) for index, item in self.names.get(ItemTypes.Temperature, {}).items(): data = AmpioTempSensorConfig.from_ampio_device(self, item, index + 1) if data: self.configs["sensor"].append(data.config) self.unique_ids.add(data.unique_id) @property def part_number(self) -> str: """Return module part number (code).""" return TYPE_CODES.get(self.code, self.code) @property def model(self) -> str: """Return model name.""" return f"{self.part_number} [{self.mac.upper()}/{self.user_mac.upper()}]" def as_hass_device(self) -> Dict[str, Any]: """Return info in hass device format.""" return { "connections": {(device_registry.CONNECTION_NETWORK_MAC, self.user_mac)}, "identifiers": {(DOMAIN, self.user_mac)}, "name": self.name, "manufacturer": "Ampio", "model": self.model, "sw_version": self.software, "via_device": (DOMAIN, "ampio-mqtt"), } @classmethod def from_topic_payload(cls, payload: dict) -> List[AmpioModuleInfo]: """Create a module object from topic payload.""" devices = AMPIO_DEVICES_SCHEMA(payload) result = [] for device in devices[ATTR_D]: klass = CLASS_FACTORY.get(device[ATTR_TYPE], AmpioModuleInfo) result.append( klass( device[ATTR_MAC], device[ATTR_USERMAC], device[ATTR_TYPE], device[ATTR_PCB], device[ATTR_SOFTWARE], device[ATTR_PROTOCOL], device[ATTR_DATE_PROD], device[ATTR_I], device[ATTR_O], device[ATTR_A], device[ATTR_AU], device[ATTR_T], device[ATTR_FLAG], device[ATTR_NAME], ) ) return result def get_config_for_component(self, component: str) -> List: """Return list of entities for specific component.""" return self.configs.get(component, []) class MSENSModuleInfo(AmpioModuleInfo): """MSENS Ampio module information.""" def update_configs(self) -> None: super().update_configs() for ampio_config in ( AmpioTempSensorConfig.from_ampio_device( self, ItemName(base64encode("T:Temperature")) ), AmpioHumiditySensorConfig.from_ampio_device( self, ItemName(base64encode("HU:Humidity")) ), AmpioPressureSensorConfig.from_ampio_device( self, ItemName(base64encode("OS:Pressure")) ), AmpioNoiseSensorConfig.from_ampio_device( self, ItemName(base64encode("SS:Noise")) ), AmpioIlluminanceSensorConfig.from_ampio_device( self, ItemName(base64encode("I:Illuminance")) ), AmpioAirqualitySensorConfig.from_ampio_device( self, ItemName(base64encode("Air Quality")) ), ): if ampio_config: self.configs["sensor"].append(ampio_config.config) self.unique_ids.add(ampio_config.unique_id) class MCONModuleInfo(AmpioModuleInfo): """MCON Ampio module information.""" def update_configs(self) -> None: """Update config.""" super().update_configs() if self.software % 100 == 1: # INTEGRA for index, item in self.names.get(ItemTypes.BinaryInput, {}).items(): data = AmpioBinarySensorExtendedConfig.from_ampio_device( self, item, index ) if data: self.configs["binary_sensor"].append(data.config) self.unique_ids.add(data.unique_id) # for index, item in self.names.get(ItemTypes.BinaryInput509, {}).items(): # data = AmpioBinarySensorExtendedConfig.from_ampio_device( # self, item, index + 255 # ) # if data: # self.configs["binary_sensor"].append(data.config) # self.unique_ids.add(data.unique_id) data = AmpioSatelConfig.from_ampio_device(self) if data: self.configs["alarm_control_panel"].append(data.config) self.unique_ids.add(data.unique_id) class MLED1ModuleInfo(AmpioModuleInfo): """MLED-1 Ampio module information.""" def update_configs(self) -> None: super().update_configs() _LOGGER.debug("MLED1: %s", self.names) for index, item in self.names.get(ItemTypes.AnalogOutput.value, {}).items(): data = AmpioDimmableLightConfig.from_ampio_device(self, item, index) if data: self.configs["light"].append(data.config) self.unique_ids.add(data.unique_id) class MDIM8sModuleInfo(AmpioModuleInfo): """MDIM-8s Ampio module information.""" def update_configs(self) -> None: super().update_configs() _LOGGER.debug("MDIM8s: %s", self.names) for index, item in self.names.get(ItemTypes.BinaryOutput, {}).items(): data = AmpioDimmableLightConfig.from_ampio_device(self, item, index) if data: self.configs["light"].append(data.config) self.unique_ids.add(data.unique_id) class MOC4ModuleInfo(AmpioModuleInfo): """MOC-4 Ampio module information.""" def update_configs(self) -> None: super().update_configs() _LOGGER.debug("MDIM8s: %s", self.names) for index, item in self.names.get(ItemTypes.BinaryOutput, {}).items(): data = AmpioDimmableLightConfig.from_ampio_device(self, item, index) if data: self.configs["light"].append(data.config) self.unique_ids.add(data.unique_id) class MPR8sModuleInfo(AmpioModuleInfo): """MPR-8s Ampio module information.""" def update_configs(self) -> None: super().update_configs() for index, item in self.names.get(ItemTypes.BinaryOutput, {}).items(): if item.device_class == "light": data = AmpioLightConfig.from_ampio_device(self, item, index) self.configs["light"].append(data.config) self.unique_ids.add(data.unique_id) else: data = AmpioSwitchConfig.from_ampio_device(self, item, index) self.configs["switch"].append(data.config) self.unique_ids.add(data.unique_id) for index, item in self.names.get(ItemTypes.BinaryInput, {}).items(): data = AmpioBinarySensorConfig.from_ampio_device(self, item, index) if data: self.configs["binary_sensor"].append(data.config) self.unique_ids.add(data.unique_id) class MDOTModuleInfo(AmpioModuleInfo): """Generic MDOT Ampio module information class.""" _BUTTONS: int def update_configs(self) -> None: """Generat module configuration.""" super().update_configs() for index in range(1, self._BUTTONS + 1 ): # regardles of names module has always fixed physical touch buttons item = self.names.get(ItemTypes.BinaryInput, {}).get(index) if item is None: item = ItemName(base64encode(f"{self.name} Button {index}")) data = AmpioTouchSensorConfig.from_ampio_device(self, item, index) if data: self.configs["binary_sensor"].append(data.config) self.unique_ids.add(data.unique_id) class MDOT2ModuleInfo(MDOTModuleInfo): """MDOT-2 Ampio module information.""" _BUTTONS = 2 class MDOT4ModuleInfo(MDOTModuleInfo): """MDOT-4 Ampio module information.""" _BUTTONS = 4 class MDOT9ModuleInfo(MDOTModuleInfo): """MDOT-9 Ampio module information.""" _BUTTONS = 9 class MDOT15LCDModuleInfo(MDOTModuleInfo): """MDOT-15LCD Ampio module information.""" _BUTTONS = 15 class MRGBu1ModuleInfo(AmpioModuleInfo): """MRGB-1u Ampio module information.""" def update_configs(self) -> None: """Update module specific configuration.""" super().update_configs() data = AmpioRGBLightConfig.from_ampio_device(self, None, 1) if data: self.configs["light"].append(data.config) self.unique_ids.add(data.unique_id) class MSERV3sModuleInfo(AmpioModuleInfo): """MSERV-3s Ampio module information.""" def update_configs(self) -> None: super().update_configs() for index, item in self.names.get(ItemTypes.BinaryOutput, {}).items(): data = AmpioSwitchConfig.from_ampio_device(self, item, index) if data: self.configs["switch"].append(data.config) self.unique_ids.add(data.unique_id) for index, item in self.names.get(ItemTypes.BinaryInput, {}).items(): data = AmpioBinarySensorConfig.from_ampio_device(self, item, index) if data: self.configs["binary_sensor"].append(data.config) self.unique_ids.add(data.unique_id) class MROL4sModuleInfo(AmpioModuleInfo): """MROL-4s Ampio module information.""" def update_configs(self) -> None: super().update_configs() for index, item in self.names.get(ItemTypes.BinaryOutput, {}).items(): data = AmpioCoverConfig.from_ampio_device(self, item, index) if data: self.configs["cover"].append(data.config) self.unique_ids.add(data.unique_id) for index, item in self.names.get(ItemTypes.BinaryInput, {}).items(): data = AmpioBinarySensorConfig.from_ampio_device(self, item, index) if data: self.configs["binary_sensor"].append(data.config) self.unique_ids.add(data.unique_id) CLASS_FACTORY = { 44: MSENSModuleInfo, 25: MCONModuleInfo, 17: MLED1ModuleInfo, 5: MDIM8sModuleInfo, 26: MOC4ModuleInfo, 4: MPR8sModuleInfo, 33: MDOT2ModuleInfo, 8: MDOT4ModuleInfo, 11: MDOT9ModuleInfo, 27: MDOT15LCDModuleInfo, 12: MRGBu1ModuleInfo, 10: MSERV3sModuleInfo, 3: MROL4sModuleInfo, } @attr.s class AmpioConfig: """Generic Ampio Config class.""" config = attr.ib(type=dict) @property def unique_id(self): """Return unique_id from config.""" return self.config.get(CONF_UNIQUE_ID) class AmpioTempSensorConfig(AmpioConfig): """Ampio Temperature Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" if not item.name: name = f"Temperature {ampio_device.name}" else: name = item.name mac = ampio_device.user_mac config = { CONF_UNIQUE_ID: f"ampio-{mac}-t{index}", CONF_NAME: f"ampio-{mac}-t{index}", CONF_FRIENDLY_NAME: name, CONF_UNIT_OF_MEASUREMENT: "°C", CONF_DEVICE_CLASS: "temperature", CONF_STATE_TOPIC: f"ampio/from/{mac}/state/t/{index}", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioHumiditySensorConfig(AmpioConfig): """Ampio Humidity Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac if ampio_device.pcb < 3: # MSENS-1 state_topic = f"ampio/from/{mac}/state/au32/0" else: state_topic = f"ampio/from/{mac}/state/au16l/1" name = f"Humidity {ampio_device.name}" config = { CONF_UNIQUE_ID: f"ampio-{mac}-h{index}", CONF_NAME: f"ampio-{mac}-h{index}", CONF_FRIENDLY_NAME: name, CONF_UNIT_OF_MEASUREMENT: "%", CONF_DEVICE_CLASS: "humidity", CONF_STATE_TOPIC: state_topic, CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioPressureSensorConfig(AmpioConfig): """Ampio Pressure Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac if ampio_device.pcb < 3: # MSENS-1 state_topic = f"ampio/from/{mac}/state/au32/1" else: state_topic = f"ampio/from/{mac}/state/au16l/6" name = f"Pressure {ampio_device.name}" config = { CONF_UNIQUE_ID: f"ampio-{mac}-ps{index}", CONF_NAME: f"ampio-{mac}-ps{index}", CONF_FRIENDLY_NAME: name, CONF_DEVICE_CLASS: "pressure", CONF_STATE_TOPIC: state_topic, CONF_UNIT_OF_MEASUREMENT: "hPa", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioNoiseSensorConfig(AmpioConfig): """Ampio Noise Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" if ampio_device.pcb < 3: # MSENS-1 return None mac = ampio_device.user_mac name = f"Noise {ampio_device.name}" config = { CONF_UNIQUE_ID: f"ampio-{mac}-n{index}", CONF_NAME: f"ampio-{mac}-n{index}", CONF_FRIENDLY_NAME: name, CONF_DEVICE_CLASS: "signal_strength", CONF_STATE_TOPIC: f"ampio/from/{mac}/state/au16l/3", CONF_UNIT_OF_MEASUREMENT: "dB", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioIlluminanceSensorConfig(AmpioConfig): """Ampio Illuminance Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" if ampio_device.pcb < 3: # MSENS-1 return None mac = ampio_device.user_mac name = f"Illuminance {ampio_device.name}" config = { CONF_UNIQUE_ID: f"ampio-{mac}-i{index}", CONF_NAME: f"ampio-{mac}-i{index}", CONF_FRIENDLY_NAME: name, CONF_DEVICE_CLASS: "illuminance", CONF_STATE_TOPIC: f"ampio/from/{mac}/state/au16l/4", CONF_UNIT_OF_MEASUREMENT: "lx", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioAirqualitySensorConfig(AmpioConfig): """Ampio AirQuality Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac if ampio_device.pcb < 3: # MSENS-1 return None name = f"Air Quality {ampio_device.name}" config = { CONF_UNIQUE_ID: f"ampio-{mac}-aq{index}", CONF_NAME: f"ampio-{mac}-aq{index}", CONF_FRIENDLY_NAME: name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/au16l/5", CONF_UNIT_OF_MEASUREMENT: "AQI", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioTouchSensorConfig(AmpioConfig): """Ampio Binary Sensor Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac config = { CONF_UNIQUE_ID: f"ampio-{mac}-i{index}", CONF_NAME: f"ampio-{mac}-i{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/i/{index}", CONF_DEVICE: ampio_device.as_hass_device(), CONF_DEVICE_CLASS: "opening", } return cls(config=config) class AmpioBinarySensorExtendedConfig(AmpioConfig): """Ampio Binary Sensor Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac device_class = item.device_class config = { CONF_UNIQUE_ID: f"ampio-{mac}-bi{index}", CONF_NAME: f"ampio-{mac}-bi{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/bi/{index}", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class: config[CONF_DEVICE_CLASS] = device_class return cls(config=config) class AmpioBinarySensorConfig(AmpioConfig): """Ampio Binary Sensor Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac device_class = item.device_class config = { CONF_UNIQUE_ID: f"ampio-{mac}-i{index}", CONF_NAME: f"ampio-{mac}-i{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/i/{index}", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class: config[CONF_DEVICE_CLASS] = device_class return cls(config=config) class AmpioDimmableLightConfig(AmpioConfig): """Ampio Dimable Light Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac device_class = item.device_class config = { CONF_UNIQUE_ID: f"ampio-{mac}-a{index}", CONF_NAME: f"ampio-{mac}-a{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/o/{index}", CONF_COMMAND_TOPIC: f"ampio/to/{mac}/o/{index}/cmd", CONF_BRIGHTNESS_COMMAND_TOPIC: f"ampio/to/{mac}/o/{index}/cmd", CONF_BRIGHTNESS_STATE_TOPIC: f"ampio/from/{mac}/state/a/{index}", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class: config[CONF_DEVICE_CLASS] = device_class if ampio_device.code == ModuleCodes.MLED1: config[CONF_ICON] = "mdi:spotlight" return cls(config=config) class AmpioLightConfig(AmpioConfig): """Ampio Light Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac device_class = item.device_class config = { CONF_UNIQUE_ID: f"ampio-{mac}-a{index}", CONF_NAME: f"ampio-{mac}-a{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/o/{index}", CONF_COMMAND_TOPIC: f"ampio/to/{mac}/o/{index}/cmd", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class: config[CONF_DEVICE_CLASS] = device_class return cls(config=config) class AmpioRGBLightConfig(AmpioConfig): """Ampio RGB Light Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item=None, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac name = ampio_device.name or "RGBW" index = 1 config = { CONF_UNIQUE_ID: f"ampio-{mac}-rgbw{index}", CONF_NAME: f"ampio-{mac}-rgbw{index}", CONF_FRIENDLY_NAME: name, CONF_RGB_STATE_TOPIC: f"ampio/from/{mac}/state/rgbw/{index}", CONF_RGB_COMMAND_TOPIC: f"ampio/to/{mac}/rgbw/{index}/cmd", CONF_WHITE_VALUE_STATE_TOPIC: f"ampio/from/{mac}/state/a/4", CONF_WHITE_VALUE_COMMAND_TOPIC: f"ampio/to/{mac}/o/4/cmd", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config) class AmpioSwitchConfig(AmpioConfig): """Ampio Switch Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac device_class = item.device_class config = { CONF_UNIQUE_ID: f"ampio-{mac}-bo{index}", CONF_NAME: f"ampio-{mac}-bo{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/o/{index}", CONF_COMMAND_TOPIC: f"ampio/to/{mac}/o/{index}/cmd", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class: config[CONF_DEVICE_CLASS] = device_class if device_class == "heat": config[CONF_ICON] = "mdi:radiator" return cls(config=config) class AmpioFlagConfig(AmpioConfig): """Ampio Flag Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac device_class = item.device_class config = { CONF_UNIQUE_ID: f"ampio-{mac}-f{index}", CONF_NAME: f"ampio-{mac}-f{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/f/{index}", CONF_COMMAND_TOPIC: f"ampio/to/{mac}/f/{index}/cmd", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class: config[CONF_DEVICE_CLASS] = device_class config[CONF_ICON] = "mdi:flag" return cls(config=config) class AmpioCoverConfig(AmpioConfig): """Ampio Cover Entity Configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo, item: ItemName, index=1): """Create config from ampio device.""" mac = ampio_device.user_mac icon = None device_class = item.device_class if device_class is None: device_class = "shutter" if device_class == "valve": icon = "mdi:valve" config = { CONF_UNIQUE_ID: f"ampio-{mac}-co{index}", CONF_NAME: f"ampio-{mac}-co{index}", CONF_FRIENDLY_NAME: item.name, CONF_STATE_TOPIC: f"ampio/from/{mac}/state/a/{index}", CONF_CLOSING_STATE_TOPIC: f"ampio/from/{mac}/state/o/{2*(index-1)+1}", CONF_OPENING_STATE_TOPIC: f"ampio/from/{mac}/state/o/{2*(index)}", CONF_COMMAND_TOPIC: f"ampio/to/{mac}/o/{index}/cmd", CONF_RAW_TOPIC: f"ampio/to/{mac}/raw", CONF_DEVICE: ampio_device.as_hass_device(), } if device_class not in ["garage", "valve"]: config.update( {CONF_TILT_POSITION_TOPIC: f"ampio/from/{mac}/state/a/{6+index}",} ) if device_class: config[CONF_DEVICE_CLASS] = device_class if icon: config[CONF_ICON] = icon return cls(config=config) class AmpioSatelConfig(AmpioConfig): """Ampio Satel single Entity configuration.""" @classmethod def from_ampio_device(cls, ampio_device: AmpioModuleInfo): """Create alarm config from ampio device.""" away = set() home = set() items: Dict[int, ItemName] = ampio_device.names.get( ItemTypes.AnalogOutput, {} ).items() mac = ampio_device.user_mac for index, item in items: if item.prefix in ("A", "B", None): # Away or Both or Not defined away.add(index) if item.prefix in ("H", "B"): # Home or Both home.add(index) mac = ampio_device.user_mac prefix = f"ampio/from/{mac}/state" config = { CONF_AWAY_ZONES: away, CONF_HOME_ZONES: home, CONF_UNIQUE_ID: f"ampio-{mac}-alarm", CONF_NAME: f"ampio-{mac}-alarm", CONF_FRIENDLY_NAME: ampio_device.name, CONF_RAW_TOPIC: f"ampio/to/{mac}/raw", CONF_ARMED_TOPIC: f"{prefix}/armed/+", CONF_ALARM_TOPIC: f"{prefix}/alarm/+", CONF_ENTRYTIME_TOPIC: f"{prefix}/entrytime/+", CONF_EXITTIME10_TOPIC: f"{prefix}/exittime10/+", CONF_EXITTIME_TOPIC: f"{prefix}/exittime/+", CONF_DEVICE: ampio_device.as_hass_device(), } return cls(config=config)
StarcoderdataPython
3486389
import bs4 from urllib.request import urlopen #import datetime as dt import pandas as pd import re import json import sqlite3 con = sqlite3.connect('db/fsdb01.db3') class Price2DB: def get_daily_price_naver(self, cd, count): url = 'https://fchart.stock.naver.com/sise.nhn?symbol='+cd+'&timeframe=day&count='+str(count)+'&requestType=0' source = urlopen(url).read() soup = bs4.BeautifulSoup(source, 'lxml') prices = soup.find_all('item') daily = [] for p in prices: data = p['data'].split('|') trade_date = pd.to_datetime(data[0]).date() price_open = float(data[1]) price_high = float(data[2]) price_low = float(data[3]) price_close = float(data[4]) trade_volume = int(data[5]) daily.append([trade_date, price_open, price_high, price_low, price_close, trade_volume]) df = pd.DataFrame(daily, columns=['trade_date', 'price_open', 'price_high', 'price_low', 'price_close', 'trade_volume']) df['Code'] = cd return(df) def make_query(self, df): query_string = '' for i in range(len(df)): # 시/고/저/종 query = 'INSERT or REPLACE INTO price_daily (trade_date, code, price_open, price_high, price_low, price_close, trade_volume) VALUES ' query = query + '("' + str(df.iloc[i, 0]) + '", '\ + '"' + str(df.iloc[i, 6]) + '", '\ + str(df.iloc[i, 1]) + ', '\ + str(df.iloc[i, 2]) + ', '\ + str(df.iloc[i, 3]) + ', '\ + str(df.iloc[i, 4]) + ', '\ + str(df.iloc[i, 5]) + '); ' query_string = query_string + query return(query_string) def db_update(self, query_string): with con: cur = con.cursor() cur.executescript(query_string) class DB2DF: def make_df(self, s_cd): if type(s_cd) == str: cds = [] cds.append(s_cd) else: cds = s_cd price_df = pd.DataFrame() for cd in cds: tmp = dict() sql = 'SELECT trade_date, price_close FROM price_daily WHERE code=?' with con: cur = con.cursor() cur.execute(sql, [cd]) rows = cur.fetchall() for r in rows: tmp[r[0]] = r[1] sr = pd.Series(tmp) sr.name = cd price_df = pd.concat([price_df, sr], axis=1, sort=True) return(price_df)
StarcoderdataPython
9715647
from django.db import models from django.urls import reverse # Create your models here. class Funcionario(models.Model): nome = models.CharField(max_length=25) sobrenome = models.CharField(max_length=25) cargo = models.CharField(max_length=25) email = models.CharField(max_length=30) mostrar = models.BooleanField(default=True) class Meta: db_table = 'funcionarios' def __str__(self): return self.nome def get_absolute_url(self): return reverse("atualizar-funcionario", kwargs={'funcionario_id':self.id}) def get_delete_url(self): return reverse("deletar-funcionario", kwargs={'funcionario_id':self.id})
StarcoderdataPython
9745456
import collections import itertools import jinja2 import json import nbformat import pathlib import shutil import sys import tempfile import tqdm from nbconvert import HTMLExporter, PDFExporter ROOT = "cfm" TITLE = "Computing for mathematics" DESCRIPTION = "An undergraduate course introducing programming, through Python, to mathematicians." KEYWORDS = "python, mathematics, jupyter" AUTHOR = "<NAME>" def get_id(path): """ Return the id of a file """ stem = path.stem try: return stem[: stem.index("-")] except ValueError: stem = stem.lower() stem = stem.replace(" ", "-") stem = stem.replace(",", "") return stem def get_name(path): """ Return the name of a file """ stem = path.stem try: return stem[stem.index("-") :].replace("-", " ").lstrip() except ValueError: return stem def convert_html(nb_path, tags_to_ignore=["solution"]): """ Convert a notebook to html """ contents = nb_path.read_text() nb = json.loads(contents) cells = [] for cell in nb["cells"]: if "tags" not in cell["metadata"] or all( tag not in cell["metadata"]["tags"] for tag in tags_to_ignore ): cells.append(cell) nb["cells"] = cells temporary_nb = tempfile.NamedTemporaryFile() with open(temporary_nb.name, "w") as f: f.write(json.dumps(nb)) html_exporter = HTMLExporter() html_exporter.template_file = "basic" return html_exporter.from_file(temporary_nb) def render_template(template_file, template_vars, searchpath="./templates/"): """ Render a jinja2 template """ templateLoader = jinja2.FileSystemLoader(searchpath=searchpath) template_env = jinja2.Environment(loader=templateLoader) template = template_env.get_template(template_file) return template.render(template_vars) def make_dir( path, directory, previous_url=None, next_url=None, chapters=None, **kwargs ): """ Create a directory for the name of the file """ path_id = get_id(path) p = pathlib.Path(f"./{directory}/{path_id}") p.mkdir(exist_ok=True) nb, _ = convert_html(path) check = False nb = nb.replace("{{root}}", ROOT) html = render_template( "content.html", { "nb": nb, "root": ROOT, "id": path_id, "previous_url": previous_url, "next_url": next_url, "chapters": chapters, **kwargs, }, ) (p / "index.html").write_text(html) def make_collection( paths, directory, make_previous_url=True, make_next_url=True, chapters=None, **kwargs, ): number_of_paths = len(paths) for index, filename in enumerate(paths): previous_path = paths[(index - 1) % number_of_paths] previous_id = get_id(previous_path) next_path = paths[(index + 1) % number_of_paths] next_id = get_id(next_path) make_dir( pathlib.Path(filename), directory=directory, previous_url=previous_id, next_url=next_id, chapters=chapters, **kwargs, ) Chapter = collections.namedtuple("chapter", ["dir", "title", "nb"]) if __name__ == "__main__": nb_dir = pathlib.Path("nbs") chapter_paths = sorted(nb_dir.glob("./chapters/*ipynb")) other_paths = list(nb_dir.glob("./other/*ipynb")) chapters = [] for path in tqdm.tqdm(sorted(chapter_paths)): chapters.append(Chapter(f"{get_id(path)}", get_name(path), str(path))) for paths, directory in [ (chapter_paths, "chapters"), (other_paths, "other"), ]: make_collection( paths=paths, directory=directory, chapters=chapters, title=TITLE, description=DESCRIPTION, keywords=KEYWORDS, author=AUTHOR, ) html = render_template( "home.html", { "chapters": chapters, "root": ROOT, "title": TITLE, "description": DESCRIPTION, "keywords": KEYWORDS, "author": AUTHOR, }, ) with open("index.html", "w") as f: f.write(html)
StarcoderdataPython
11326595
<filename>book2vec/core.py import numpy as np import json from typing import List, Union from sklearn.metrics.pairwise import cosine_similarity import pandas as pd import logging logger = logging.getLogger(__name__) class Book2VecAnalysis: def __init__(self, file_obj=None): self.loaded = False self.embedding_matrix = None self.vocab_size = None self.index_to_review = None self.index_to_metadata = None if file_obj: self.load(file_obj) def load(self, file_obj): json_data = json.load(file_obj) self.embedding_matrix = json_data["embedding_matrix"] self.vocab_size = json_data["vocab_size"] self.index_to_review = { int(k): v for k, v in json_data["index_to_review"].items() } self.index_to_metadata = { int(k): v for k, v in json_data["index_to_metadata"].items() } self.loaded = True def get_suggestions(self, idxs: Union[List[int], int]) -> pd.DataFrame: """ Takes a list of book IDs and returns a list of suggestions. This is calculated by taking the mean of the closest 100 books to the given book IDs. :param idxs: :return: """ if isinstance(idxs, int): idxs = [idxs] suggestions = pd.concat( {idx: self._get_nearest(idx, 250) for idx in idxs}, axis=1, join="outer" ) suggestions["cumulative"] = suggestions.mean(axis=1) suggestions.sort_values(by="cumulative", ascending=False, inplace=True) return suggestions[~suggestions.index.isin(idxs)] def _get_nearest(self, idx: int, limit: int = None) -> pd.Series: """ Calculates the nearest neighbours of the given book via consine similarity :param idx: the book ID :param limit: if provided will limit to this number of nearest neighbours :return: a DataFrame containing the similarity values with book ID as index """ x = np.array(self.embedding_matrix[idx]).reshape((1, -1)) y = np.array(self.embedding_matrix) similarity_values = cosine_similarity(x, y).T similarity_values = pd.Series(similarity_values.flatten()) if limit: similarity_values = similarity_values.sort_values(ascending=False) return similarity_values[:limit] return similarity_values
StarcoderdataPython
4958293
import hashlib h = hashlib.new('ripemd160') h.update(input().encode('utf-8')) print(h.hexdigest())
StarcoderdataPython
1911898
# Copyright (C) 2009 The MITRE Corporation. See the toplevel # file LICENSE for license terms. # XML reader/writer. from MAT.DocumentIO import declareDocumentIO, DocumentFileIO, SaveError from MAT.Document import LoadError from MAT.Annotation import AnnotationAttributeType, StringAttributeType, FloatAttributeType, \ BooleanAttributeType, IntAttributeType, AttributeValueList, AttributeValueSet import xml.parsers.expat, xml.sax.saxutils, re, base64 import sys from MAT import json # We need to know what the annotations are in the task, # if we're supposed to filter out the "junk" tags and only translate # the tags for the task. # There are going to be a couple special things in here # now. First, there will be the <_mat:atypes> element, which # optionally declares all the available annotation types and # their attributes and types. This is important for recording # spanless annotations and for recording annotations which have # annotation-valued attributes (and the attribute for that will be # _mat:id). So <_mat:atypes> looks like this: # <_mat:atypes><atype name="..." hasSpan="yes|no"><attr name="..." type="string|attribute"/>...</atype></atypes> # It will have no whitespace at all, so it doesn't count toward # the offsets, and it should appear, if it appears at all, # before the first annotation. If I can, when I render, I'll # put it at the beginning of the document, but if it's # an overlay, it'll go immediately before the first annotation. class _ParserState: def __init__(self, annotDoc, inputIsOverlay, translateAll): self.inputIsOverlay = inputIsOverlay self.xmlTranslateAll = translateAll if self.xmlTranslateAll: # The annotDoc will likely come in with an annotation repository. # It's not enough to cut it off from the global repository; # we have to convince it that the annotation types it ALREADY # has are not closed. annotDoc.unlockAtypeRepository() self.annotDoc = annotDoc # The parser expects BYTES, not unicode characters. # The documentation does not make this clear at all. self.parser = xml.parsers.expat.ParserCreate("UTF-8") self.parser.StartElementHandler = self._startElement self.parser.EndElementHandler = self._endElement self.parser.CharacterDataHandler = self._handleCdata self.parser.CommentHandler = self._handleComment self.parser.DefaultHandler = self._handleDefault self.stack = [] self.pos = 0 self.signalChunks = [] self._digestingAtypes = False self._digestedAtypes = False self._curAtype = None # The annotation attributes must be postponed, because some of # them may be annotation-valued. self._annotPairs = [] self._idMap = {} def _addSignalChunk(self, chunk): self.signalChunks.append(chunk) self.pos += len(chunk) # VERY subtle bug. Because inputIsOverlay counts in BYTES, # and because I have to pass a byte string to the parser, I # can't store the input as a Unicode string; I have to encode # it into UTF-8 first. def parse(self, s): # Boy, this is hideous. XML doesn't permit CRLF - each # XML processor is obligated to convert them to LF. The # only way to block that is to replace \r with the # appropriate entity - but then the parser barfs on any # &#xD outside the toplevel tag, because it's not actual whitespace. # Poo. # So the answer is to do the replacement ONLY inside the # toplevel tag. That's easy enough. if s.find("\r") > -1: # Find the first toplevel tag. # Exclude ! (comment and doctype) and ? (xmldesc and processing instruction). # This will barf if there's nothing in the toplevel tag. mStart = re.search("<([^!?][^\s>]*)", s) if mStart is not None: # Gotta be something in the toplevel tag in order for # me to care. topStart = mStart.start() topEnd = re.search("</" + mStart.group(1) + ">", s).end() s = s[:topStart] + s[topStart:topEnd].replace("\r", "&#xD;") + s[topEnd:] self.input = s.encode('utf-8') self.parser.Parse(self.input, True) # Now that we're done parsing, we have to update all the # attributes for those which have annotation-valued attributes. atypeAttrHash = {} for newAnnot, attrDict in self._annotPairs: atype = newAnnot.atype try: attrHash = atypeAttrHash[atype] except KeyError: attrHash = {} for t in atype.attr_list: # Barf. if isinstance(t, AnnotationAttributeType): # The IDs are all strings. We need to look # them up in the _idMap. if t.aggregation == "list": attrHash[t.name] = lambda x: AttributeValueList([self._idMap[v] for v in x.split(",")]) elif t.aggregation == "set": attrHash[t.name] = lambda x: AttributeValueSet([self._idMap[v] for v in x.split(",")]) else: attrHash[t.name] = lambda x: self._idMap[x] elif isinstance(t, StringAttributeType): if t.aggregation == "set": attrHash[t.name] = lambda x: AttributeValueSet(x.split(",")) elif t.aggregation == "list": attrHash[t.name] = lambda x: AttributeValueList(x.split(",")) else: attrHash[t.name] = lambda x: x else: if isinstance(t, FloatAttributeType): mapper = float elif isinstance(t, IntAttributeType): mapper = int elif isinstance(t, BooleanAttributeType): mapper = lambda x: x == "yes" if t.aggregation == "set": attrHash[t.name] = lambda x: AttributeValueSet([mapper(v) for v in x.split(",")]) elif t.aggregation == "list": attrHash[t.name] = lambda x: AttributeValueList([mapper(v) for v in x.split(",")]) else: attrHash[t.name] = mapper atypeAttrHash[atype] = attrHash for k, v in attrDict.items(): newAnnot[k] = attrHash[k](v) newSignal = "".join(self.signalChunks) if self.annotDoc.signal and (self.annotDoc.signal != newSignal): raise LoadError, "signal from XML file doesn't match original signal" self.annotDoc.signal = newSignal if self.inputIsOverlay: self.annotDoc.metadata["signal_type"] = "xml" def _startElement(self, eltName, attrDict): if eltName == "_mat:atype": if not self._digestingAtypes: raise LoadError, "found _mat:atype outside _mat:atypes" self._digestAtype(attrDict) return elif eltName == "_mat:attr": if not self._digestingAtypes: raise LoadError, "found _mat:attr outside _mat:atypes" self._digestAttr(attrDict) return elif eltName == "_mat:atypes": self._digestingAtypes = True return if (not self.xmlTranslateAll) and (not self.annotDoc.findAnnotationType(eltName, create = False)): if self.inputIsOverlay: # There doesn't appear to be any way of finding the # end of the element in the input from the parser bindings, grrr. # So we have to look for ">" in the signal. tag = self.input[self.parser.CurrentByteIndex:self.input.find(">", self.parser.CurrentByteIndex) + 1] self._addSignalChunk(tag) return # If the atypes were declared, you don't want to check the attributes. t = self.annotDoc.findAnnotationType(eltName, create = not self._digestedAtypes) if not self._digestedAtypes: for key in attrDict.keys(): if key != "_mat:id": t.ensureAttribute(key) if t.hasSpan: newAnnot = self.annotDoc.createAnnotation(self.pos, self.pos, t, blockAdd = True) else: newAnnot = self.annotDoc.createSpanlessAnnotation(t, blockAdd = True) id = attrDict.get("_mat:id") if id is not None: newAnnot.setID(id) self._idMap[id] = newAnnot del attrDict["_mat:id"] self._annotPairs.append((newAnnot, attrDict)) self.stack[0:0] = [newAnnot] def _digestAtype(self, attrDict): self._curAtype = self.annotDoc.findAnnotationType(attrDict["name"], hasSpan = attrDict["hasSpan"] == "yes") def _digestAttr(self, attrDict): self._curAtype.ensureAttribute(attrDict["name"], aType = attrDict.get("type"), aggregation = attrDict.get("aggregation")) def _endElement(self, eltName): if eltName in ("_mat:attr", "_mat:atype"): return elif eltName == "_mat:atypes": self._digestingAtypes = False self._digestedAtypes = True return if (not self.xmlTranslateAll) and (not self.annotDoc.findAnnotationType(eltName, create = False)): if self.inputIsOverlay: tag = self.input[self.parser.CurrentByteIndex:self.input.find(">", self.parser.CurrentByteIndex) + 1] self._addSignalChunk(tag) return if self.stack[0].atype.lab == eltName: if self.stack[0].atype.hasSpan: self.stack[0].end = self.pos self.annotDoc._addAnnotation(self.stack[0]) self.stack[0:1] = [] else: raise LoadError, "annotation close doesn't match annotation open" # I'm going to do something special with comments: I'm going to # dump the document metadata in a comment when I encounter it. I believe # the comment can appear after the final tag, so I'll put it at the very # end of the file. METADATA_PAT = re.compile("^ _mat_metadata_ (.*) $") def _handleComment(self, data): m = self.METADATA_PAT.match(data) if m is None: if self.inputIsOverlay: # Pass through the comment. self._addSignalChunk("<!--") self._addSignalChunk(data) self._addSignalChunk("-->") else: # We've got the metadata. jsonMetadata = base64.b64decode(m.group(1)) self.annotDoc.metadata = json.loads(jsonMetadata) def _handleCdata(self, data): if self.inputIsOverlay: data = xml.sax.saxutils.escape(data) self._addSignalChunk(data) # Pass through anything you find if it's a default. def _handleDefault(self, data): if self.inputIsOverlay: self._addSignalChunk(data) from MAT.Operation import OpArgument, OptionTemplate class XMLDocumentIO(DocumentFileIO): def __init__(self, xml_input_is_overlay = False, xml_translate_all = False, signal_is_xml = False, xml_output_tag_exclusions = None, xml_output_exclude_metadata = False, encoding = None, **kw): # Changing the default encoding. if encoding is None: encoding = "utf-8" DocumentFileIO.__init__(self, encoding = encoding, **kw) if xml_input_is_overlay: signal_is_xml = True self.excludeMetadata = xml_output_exclude_metadata self.xmlInputIsOverlay = xml_input_is_overlay self.tagExclusions = None if xml_output_tag_exclusions is not None: if type(xml_output_tag_exclusions) is str: xml_output_tag_exclusions = xml_output_tag_exclusions.split(",") if xml_output_tag_exclusions == [""]: xml_output_tag_exclusions = [] self.tagExclusions = dict([(t, True) for t in xml_output_tag_exclusions]) self.signalIsXML = signal_is_xml self.xmlTranslateAll = xml_translate_all # This must be implemented by the children. s is a Unicode string. # annotDoc is an annotated document. def deserialize(self, s, annotDoc): # If there's no global annotation type repository, we want xmlTranslateAll to be True. state = _ParserState(annotDoc, self.xmlInputIsOverlay, self.xmlTranslateAll or (not annotDoc.atypeRepository.globalTypeRepository)) state.parse(s) def writeToUnicodeString(self, annotDoc): signalIsXML = self.signalIsXML or \ (annotDoc.metadata.has_key("signal_type") and annotDoc.metadata["signal_type"] == "xml") # Get all the annotations. Let's not care about overlap right now, # since overlap will happen if I'm writing everything out, because # it'll be nested. So just get the annotations and then # sort them, and if we ever get a crossing dependency, we'll # have to check otherwise. # Split the atypes into spanned and spanless. spanned = [] spanless = [] # I used to remove the tag exclusions when I collect the # indices, but I need to do it earlier in order to figure out # if I need a top element or not. annots = [] spanlessAnnots = [] for atype in annotDoc.atypeDict.keys(): if self.tagExclusions and self.tagExclusions.has_key(atype.lab): continue if atype.hasSpan: spanned.append(atype.lab) else: spanless.append(atype.lab) if spanned: annots = annotDoc.getAnnotations(atypes = spanned) if spanless: spanlessAnnots = annotDoc.getAnnotations(atypes = spanless) # We now know they can nest. So let's sort them. # Sort them first by earliest start, latest end. annots.sort(self._cmpAnnot) # Now, I can loop through the annots, and keep a stack, # and we know when to pop the stack because of # how the indexes work. indices = {} lastAnnot = None for annot in annots: if lastAnnot and \ (((lastAnnot.start < annot.start) and (lastAnnot.end < annot.end)) or \ ((lastAnnot.start > annot.start) and (lastAnnot.end > annot.end))): raise SaveError, "crossing dependencies" try: indices[annot.start][0].append(annot) except KeyError: indices[annot.start] = [[annot], []] try: indices[annot.end][1].append(annot) except KeyError: indices[annot.end] = [[], [annot]] indexList = indices.keys() indexList.sort() segs = [] # So we need to add a toplevel XML tag if we don't already have one, and if # we're not adding our own info. # The signal is not XML, and # There are no spanless annotations, or # The maximal annotation starts after the beginning, or # the maximal annotation ends before the end, or # there are spanless annots, which will be inserted as zero-length # annots before the first spanned annotation, or # we add metadata, which will insert the annotation types # in a similar position. addTop = (not signalIsXML) and \ ((not annots) or \ (annots[0].start > 0) or \ (annots[0].end < len(annotDoc.signal)) or \ spanlessAnnots or \ (not self.excludeMetadata)) if addTop: segs.append("<__top>") pos = 0 atypesInserted = False for i in indexList: if pos < i: seg = annotDoc.signal[pos:i] if not signalIsXML: seg = xml.sax.saxutils.escape(seg) segs.append(seg) pos = i [starts, ends] = indices[i] # Reverse the ends. ends.reverse() for endAnnot in ends: segs.append("</" + endAnnot.atype.lab + ">") for startAnnot in starts: if not atypesInserted: if not self.excludeMetadata: segs.append(self._formatAtypes(annotDoc)) atypesInserted = True if spanlessAnnots: for sAnnot in spanlessAnnots: segs.append(self._formatAnnot(sAnnot, spanless = True)) segs.append(self._formatAnnot(startAnnot)) if pos < len(annotDoc.signal): seg = annotDoc.signal[pos:] if not signalIsXML: seg = xml.sax.saxutils.escape(seg) segs.append(seg) if addTop: segs.append("</__top>") if not self.excludeMetadata: segs.append("<!-- _mat_metadata_ "+ base64.b64encode(json.dumps(annotDoc.metadata)) + " -->") return "".join(segs) def _cmpAnnot(self, ann1, ann2): return cmp(ann1.start, ann2.start) or -cmp(ann1.end, ann2.end) def _formatAtypes(self, annotDoc): segs = ["<_mat:atypes>"] for atype in annotDoc.atypeDict.keys(): segs.append("<_mat:atype name='%s' hasSpan='%s'>" % (atype.lab, (atype.hasSpan and "yes") or "no")) for attr in atype.attr_list: segs.append("<_mat:attr name='%s' type='%s' aggregation='%s'/>" % (attr.name, attr._typename_, attr.aggregation or "none")) segs.append("</_mat:atype>") segs.append("</_mat:atypes>") return "".join(segs) def _formatAnnot(self, annot, spanless = False): elts = ["<", annot.atype.lab] if annot.attrs: for attr, val in zip(annot.atype.attr_list, annot.attrs): if val is not None: # Handle annotations specially. if attr._typename_ == "annotation": if attr.aggregation: v = ",".join([str(a.id) for a in val]) else: v = str(val.id) else: v = attr.toStringNonNull(val) elts.append(" " + attr.name + "="+ xml.sax.saxutils.quoteattr(v)) if annot.id is not None: elts.append(" _mat:id=" + xml.sax.saxutils.quoteattr(annot.id)) if spanless: elts.append("/>") else: elts.append(">") return "".join(elts) # Best to use the OpArgument infrastructure, so we can extract # arguments cleanly from CGI and cmdline. inputArgs = OptionTemplate([OpArgument("xml_input_is_overlay", help = "If specified, the input XML will be treated as a mix of task-relevant annotations and underlying XML, and the extracted signal will be a well-formed XML file"), OpArgument("xml_translate_all", help = "If specified, all tags will be converted, whether or not they're found in whatever task is specified")], heading = "Options for XML input") outputArgs = OptionTemplate([OpArgument("signal_is_xml", help = "If specified, the underlying signal will be treated as a well-formed XML file when the output file is rendered. If the input file type is also 'xml-inline', use the --xml_input_is_overlay flag to control this setting instead."), OpArgument("xml_output_tag_exclusions", help = "A comma-delimited list of annotation labels to exclude from the XML output", hasArg = True), OpArgument("xml_output_exclude_metadata", help = "Normally, the XML writer saves the document metadata inside an XML comment, so it can be read back in by the XML reader. This flag causes the metadata not to be written.")], heading = "Options for XML output") declareDocumentIO("xml-inline", XMLDocumentIO, True, True) # # And now, the "fake" version, for when somebody just randomly inserted SGML-ish tags. # # ONLY a reader. class FakeXMLIO(DocumentFileIO): def writeToUnicodeString(self, annotDoc): raise NotImplementedError # In fake xml IO, it's just SGML-ish tags. def deserialize(self, s, annotDoc): signalStrings = [] startI = 0 contentLen = 0 for m in self.TAG_LOCATOR.finditer(s): startTag, content, endTag = m.groups() # Let's do all the bookkeeping first. prefix = s[startI:m.start()] contentLen += len(prefix) signalStrings.append(prefix) annotStart = contentLen signalStrings.append(content) contentLen += len(content) annotEnd = contentLen startI = m.end() # Now, let's take the startTag eapart. labToks = startTag.split(None, 1) if labToks[0] != endTag: raise LoadError, ("mismatched start and end tags (%s vs. %s) at %d" % (labToks[0], endTag, m.start())) t = annotDoc.findAnnotationType(endTag, create = True) attrs = {} if len(labToks) > 1: # There are attributes. Grab a token (no whitespace, no =), then # look for an =, then find the following value. attrStr = labToks[1] while attrStr: m = self.ATTR_NAME_LOCATOR.match(attrStr) if m is None: raise LoadError, ("ill-formed attribute string '%s'" % labToks[1]) attr = m.group(1) t.ensureAttribute(attr) attrStr = attrStr[m.end():] # Now, we need a value. m = self.ATTR_VALUE_LOCATOR.match(attrStr) if m is None: raise LoadError, ("ill-formed attribute string '%s'" % labToks[1]) val = m.group(2) # Since this sucks up trailing whitespace, it should # terminate the string when we reach the end of it. attrStr = attrStr[m.end():] attrs[attr] = val # OK, now we add the annotation. annotDoc.createAnnotation(annotStart, annotEnd, t, attrs) signalStrings.append(s[startI:]) annotDoc.signal = "".join(signalStrings) TAG_LOCATOR = re.compile("\<([^>]+)\>", re.S) ATTR_NAME_LOCATOR = re.compile("^\s*([^\s=]+)\s*=\s*") # The escape for the double quote isn't strictly necessary, # but it works better with the Python Emacs mode. ATTR_VALUE_LOCATOR = re.compile("""^([\"'])(.*?)\\1\s*""") # We can't quite do this the way we did the fake XML IO reader, because # we have (a) null annotations and (b) nested annotations. So we need # to look for the tags, and keep gathering input. # Because this is pseudo-XML, there may be <> in the signal. So if # we find a tag which we can't parse, assume it's signal. def _parseTag(self, startTag): labToks = startTag.split(None, 1) attrs = {} if len(labToks) > 1: # There are attributes. Grab a token (no whitespace, no =), then # look for an =, then find the following value. attrStr = labToks[1] while attrStr: m = self.ATTR_NAME_LOCATOR.match(attrStr) if m is None: # Attribute string is ill-formed. return None, None attr = m.group(1) attrStr = attrStr[m.end():] # Now, we need a value. m = self.ATTR_VALUE_LOCATOR.match(attrStr) if m is None: # Attribute string is ill-formed. return None, None val = m.group(2) # Since this sucks up trailing whitespace, it should # terminate the string when we reach the end of it. attrStr = attrStr[m.end():] attrs[attr] = val return labToks[0], attrs # Toplevel. def deserialize(self, s, annotDoc): annotations = [] tagStack = [] signalStrings = [] startI = 0 contentLen = 0 NULL, OPEN, CLOSE = 0, 1, 2 while True: m = self.TAG_LOCATOR.search(s, startI) if m is None: signalStrings.append(s[startI:]) break tagContent = m.group(1) # If it starts with a /, it's an end tag. # if it ends with a /, it's a null tag. if tagContent[-1] == "/": tagLiteral = tagContent[:-1] tagStatus = NULL elif tagContent[0] == "/": tagLiteral = tagContent[1:] tagStatus = CLOSE else: tagLiteral = tagContent tagStatus = OPEN if tagStatus in (NULL, OPEN): label, attrs = self._parseTag(tagLiteral) if label is None: # Probably actually signal instead. Skip it. Well, don't # skip the WHOLE thing; the pattern may have captured # a real tag too. print >> sys.stderr, "Found bogus tag match '%s'; treating first character as text and trying again." % s[m.start():m.end()].encode('ascii', 'replace') signalStrings.append(s[startI:m.start() + 1]) contentLen += ((m.start() + 1) - startI) startI = m.start() + 1 continue # So now, we know it's a non-bogus tag. prefix = s[startI:m.start()] contentLen += len(prefix) signalStrings.append(prefix) annotLoc = contentLen startI = m.end() if tagStatus is NULL: annotations.append([label, attrs, annotLoc, annotLoc]) elif tagStatus is CLOSE: # Gotta match what's on the top of the stack. tagContent = tagContent[1:] if not tagStack: raise IOError, "no start tag for end tag" elif tagStack[-1][0] != tagContent: raise IOError, "mismatch start and end tags (%s vs %s)" % (tagStack[-1][0], tagContent) else: [label, attrs, startIdx] = tagStack[-1] tagStack[-1:] = [] annotations.append([label, attrs, startIdx, annotLoc]) else: label, attrs = self._parseTag(tagContent) tagStack.append([label, attrs, annotLoc]) # OK, now we add the annotations. for t, attrs, annotStart, annotEnd in annotations: annotDoc.createAnnotation(annotStart, annotEnd, t, attrs) annotDoc.signal = "".join(signalStrings) declareDocumentIO('fake-xml-inline', FakeXMLIO, True, False)
StarcoderdataPython
220328
#!/usr/bin/env python __author__ = '<NAME>' import argparse from RouToolPa.Routines import DrawingRoutines parser = argparse.ArgumentParser() parser.add_argument("-i", "--input_file", action="store", dest="input_file", help="Input file with data") parser.add_argument("-o", "--output_prefix", action="store", dest="output_prefix", help="Prefix of output files") parser.add_argument("-s", "--separator", action="store", dest="separator", default="\t", help="Separator between values in input file. Default - '\\t' ") parser.add_argument("-a", "--x_column_index", action="store", dest="x_column_index", type=int, help="Index of column with x values. 0-based") parser.add_argument("-b", "--y_column_index", action="store", dest="y_column_index", type=int, help="Index of column with y values. 0-based") parser.add_argument("-n", "--min_x", action="store", dest="min_x", type=float, help="Minimum x value to show. Default - not set") parser.add_argument("-x", "--max_x", action="store", dest="max_x", type=float, help="Maximum x value to show. Default - not set") parser.add_argument("-q", "--min_y", action="store", dest="min_y", type=float, help="Minimum y value to show. Default - not set") parser.add_argument("-r", "--max_y", action="store", dest="max_y", type=float, help="Maximum y value to show. Default - not set") parser.add_argument("-e", "--extensions", action="store", dest="extensions", type=lambda x: x.split(","), default=["png", "svg"], help="Comma-separated list of extensions for histogram files") parser.add_argument("-l", "--xlabel", action="store", dest="xlabel", help="X label") parser.add_argument("-y", "--ylabel", action="store", dest="ylabel", help="Y label") parser.add_argument("-t", "--title", action="store", dest="title", help="Title of histogram") parser.add_argument("--width", action="store", dest="width", default=6, type=int, help="Figure width. Default: 6") parser.add_argument("--height", action="store", dest="height", default=6, type=int, help="Figure height. Default: 6") parser.add_argument("-m", "--markersize", action="store", dest="markersize", default=2, type=int, help="Size of marker. Default: 2") parser.add_argument("--ylog", action="store", dest="ylogbase", default=10, type=int, help="Log base for figure with logarithmic scale on y axis. Default: 10") parser.add_argument("--type", action="store", dest="type", default="plot", help="Type of figure. Allowed: plot(default), scatter") parser.add_argument("-g", "--grid", action="store_true", dest="grid", help="Show grid. Default: False") args = parser.parse_args() DrawingRoutines.draw_plot(args.input_file, args.output_prefix, x_column_index=args.x_column_index, y_column_index=args.y_column_index, separator=args.separator, min_x=args.min_x, max_x=args.max_x, min_y=args.min_y, max_y=args.max_y, extensions=args.extensions, xlabel=args.xlabel, ylabel=args.ylabel, title=args.title, width=args.width, height=args.height, markersize=args.markersize, ylogbase=args.ylogbase, type=args.type, grid=args.grid, correlation=True) """ data = np.loadtxt(args.input_file, comments="#", usecols=(args.x_column_index, args.y_column_index)) plt.figure(1, figsize=(args.width, args.height), dpi=300) plt.subplot(1, 1, 1) if args.type == "plot": plt.plot(data[:, 0], data[:, 1], markersize=args.markersize) elif args.type == "scatter": plt.scatter(data[:, 0], data[:, 1], s=args.markersize) plt.xlim(xmin=args.min_x, xmax=args.max_x) plt.ylim(ymin=args.min_y, ymax=args.max_y) if args.xlabel: plt.xlabel(args.xlabel) if args.ylabel: plt.ylabel(args.ylabel) if args.title: plt.title(args.title) if args.grid: plt.grid() print("Kendal's tau") print(stats.kendalltau(data[:, 0], data[:, 1])) print("Pearson's r") print(stats.pearsonr(data[:, 0], data[:, 1])) for ext in args.extensions: plt.savefig("%s.%s.%s" % (args.output_prefix, args.type, ext)) plt.yscale("log") for ext in args.extensions: plt.savefig("%s.%s.ylog%i.%s" % (args.output_prefix, args.type, args.ylogbase, ext)) """
StarcoderdataPython
6640196
import re import pandas as pd from bs4 import BeautifulSoup import mechanize data = pd.read_csv('goodreads_bestsellers.csv') for rownum, row in data.iterrows(): print row['url'] br = mechanize.Browser() r = br.open(row['url']) soup = BeautifulSoup(r.read(), 'html.parser') pages = soup.find(itemprop="numberOfPages").get_text() print pages data.loc[rownum, 'Pages'] = pages data.to_csv('goodreads_bestsellers.csv', index = False)
StarcoderdataPython
3523852
# coding: utf-8 # app: mesa de atención # module: forms # date: jueves, 14 de junio de 2018 - 08:56 # description: Formulario para la bitácora de ciudadanos rechazados en mac # pylint: disable=W0613,R0201,R0903 from crispy_forms.helper import FormHelper from crispy_forms.layout import Layout, Submit, Div, HTML, Field, Button from crispy_forms.bootstrap import FormActions from django import forms from apps.mesas.models import Registro class MesaForm(forms.ModelForm): def __init__(self, *args, **kwargs): super(MesaForm, self).__init__(*args, **kwargs) self.helper = FormHelper() self.helper.layout = Layout( Div( Field('modulo', wrapper_class='col-md-2', autocomplete='off'), Field('fecha', wrapper_class='col-md-2', autocomplete='off'), Field('lugar', wrapper_class='col-md-3'), css_class='row' ), Div( Field('sexo', wrapper_class='col-md-2'), Field('causa', wrapper_class='col-md-3'), Field('observaciones', wrapper_class='col-md-6', rows='3'), css_class='row' ), Div( HTML('<hr>'), FormActions( Submit('save', 'Guardar cambios'), Button('cancel', 'Cancelar') ) ) ) class Meta: model = Registro fields = '__all__'
StarcoderdataPython
8068255
# python3 construct.py 0 8 & # python3 construct.py 1 8 & # python3 construct.py 2 8 & # python3 construct.py 3 8 & # python3 construct.py 4 8 & # python3 construct.py 5 8 & # python3 construct.py 6 8 & # python3 construct.py 7 8 & import os import sys import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.patches as patches from statistics import mean def weird_division(n, d): return n / d if d else 0 def labeling(price, bp, k): label = [] for i, p, in enumerate(price[:-k]): slope = (mean(price[i+1:i+k+1])-price[i])/price[i] if abs(slope) < bp: label.append(0) else: label.append(weird_division(slope,abs(slope))) return label def calc_profit(price, label): total_profit = 0 trade_times = 0 status = label[0] start_price = price[0] for i, lbl in enumerate(label[1:]): if lbl == status or lbl == 0: continue else: total_profit += (price[i+1]-start_price)*status # print((price[i+1]-start_price),status) trade_times += 1 if status != 0 else 0 status = lbl start_price = price[i+1] if trade_times == 0: trade_times = 1 return total_profit, trade_times def main(): prices = np.load('price_201001~06.npy', allow_pickle=True) thread_no = int(sys.argv[1]) thread_num = 8 if len(sys.argv) > 2: thread_num =int(sys.argv[2]) # lbl = labeling(prices[0], 0.0,10) # # print(lbl) # print(calc_profit(prices[0], lbl)) # plot_labeling(prices[0], lbl) ### apply thread channel: ### usage: ### python construct.py 0 8 return_dir = os.path.join(os.getcwd(), 'total_return/') if not os.path.isdir(return_dir): os.makedirs(return_dir) time_dir = os.path.join(os.getcwd(), 'trade_time/') if not os.path.isdir(time_dir): os.makedirs(time_dir) for i, price in enumerate(prices): if i % thread_num != thread_no: continue total_profit_mat = [] trade_time_mat = [] for k in range(10, 201, 10): total_profit_vec = [] trade_time_vec = [] for bp in np.arange(0.0000,0.0051,0.0001): lbl = labeling(price, bp, k) tr, tt = calc_profit(price, lbl) # print(tr) total_profit_vec.append(tr) trade_time_vec.append(tt) total_profit_mat.append(total_profit_vec) trade_time_mat.append(trade_time_vec) np.save('total_return/{}.npy'.format(i),total_profit_mat) np.save('trade_time/{}.npy'.format(i),trade_time_mat) def trans2rect(label): status = label[0] position = 0 width = 1 rects = [] for i,l in enumerate(label[1:]): if status == l: width += 1 else: rects.append((status,position,width)) status = l position = i+1 width = 1 return rects def plot_labeling(price, label): rects = trans2rect(label) ymin, ymax = min(price), max(price)-min(price) for rect in rects: color = (1,1,1) if rect[0]==1: color = (1, .2, .2) elif rect[0]==-1: color = (.2, 1, .2) elif rect[0]==0: color = (.8, .8, .8) plt.gca().add_patch(patches.Rectangle((rect[1], ymin), rect[2], ymax,color=color, alpha=0.5)) plt.plot(price) plt.show() if __name__ == '__main__': main()
StarcoderdataPython
8141609
import pandas as pd import numpy as np import matplotlib import matplotlib.pyplot as plt from sklearn import preprocessing matplotlib.use("Agg") import datetime import torch from finrl.config import config from finrl.marketdata.yahoodownloader import YahooDownloader from finrl.preprocessing.preprocessors import FeatureEngineer from finrl.preprocessing.data import data_split from finrl.env.multi_env_stocktrading import StockTradingEnv from finrl.lxcalgorithms.gateway import Gateway from finrl.model.multi_models import DRLAgent from finrl.trade.backtest import backtest_stats as BackTestStats def getEveryDay(begin_date,end_date): # 前闭后闭 date_list = [] begin_date = datetime.datetime.strptime(begin_date, "%Y-%m-%d") end_date = datetime.datetime.strptime(end_date,"%Y-%m-%d") while begin_date <= end_date: date_str = begin_date.strftime("%Y-%m-%d") date_list.append(date_str) begin_date += datetime.timedelta(days=1) return date_list def train_one(): """ train an agent """ print("==============Start Fetching Data===========") print('GPU is :', torch.cuda.is_available()) start_date = config.START_DATE, end_date = config.START_TRADE_DATE, start_date = start_date[0] end_date = end_date[0] date_list = getEveryDay(start_date,end_date) food = Gateway() now = datetime.datetime.now().strftime("%Y%m%d-%Hh%M") for i in range(0,1): df = YahooDownloader( start_date=start_date, end_date=end_date, ticker_list=config.DOW_30_TICKER, ).lxc_fetch_data() print("==============Start Feature Engineering===========") fe = FeatureEngineer( use_technical_indicator=True, tech_indicator_list=config.TECHNICAL_INDICATORS_LIST, use_turbulence=True, user_defined_feature=False, ) processed = fe.preprocess_data(df) train = data_split(processed, start_date, end_date) stock_dimension = len(train.tic.unique()) #print("train.tic.unique() is:") #print(train.tic.unique()) print('stock_dimension is:', stock_dimension) state_space = ( 1 + 2 * stock_dimension + len(config.TECHNICAL_INDICATORS_LIST) * stock_dimension ) env_kwargs = { "hmax": 100, "initial_amount": 1000000, "buy_cost_pct": 0.001, "sell_cost_pct": 0.001, "state_space": state_space, "stock_dim": stock_dimension, "tech_indicator_list": config.TECHNICAL_INDICATORS_LIST, # "action_space": stock_dimension, "action_space": 1, "reward_scaling": 1e-4 } e_train_gym = StockTradingEnv(df=train, **env_kwargs) env_train, _ = e_train_gym.get_sb_env() agent = DRLAgent(env=env_train) print("==============Model Training===========") print("start training ddpg model") ##################################################################################################a2c print("start pre_training model") multi_number = stock_dimension #temp = agent.get_model(model_name="a2c", lxc_stock_number=0) #agent.train_model(model=temp, tb_log_name="a2c", total_timesteps=1000) #print("e_train_gym.normal_high is:", e_train_gym.normal_high) #print("e_train_gym.normal_low is:", e_train_gym.normal_low) #e_trade_gym.normal_high = e_train_gym.normal_high #e_trade_gym.normal_low = e_train_gym.normal_low print("start main_training model") for j in range(0, multi_number): if(j+1>food.agents_number): model_a2c = agent.get_model(model_name="a2c", lxc_stock_number=j,all_stock_number = multi_number) model_a2c.all_stock_number = multi_number model_a2c.env.reset() if(j!=0): trained_a2c = agent.get_pre_model(model=model_a2c, tb_log_name="a2c", total_timesteps=1000, lxcName="lxcMulti" + str(j - 1)) trained_a2c.lxc_stock_number = j trained_a2c.all_stock_number = multi_number trained_a2c = trained_a2c.online_learning(total_timesteps=1000, tb_log_name="a2c") agent.save_pre_model(model=trained_a2c, tb_log_name="a2c", total_timesteps=1000, lxcName="lxcMulti" + str(j)) else: trained_a2c = agent.train_lxc_model( # model=model_a2c, tb_log_name="a2c", total_timesteps=80000,lxcType=1,lxcName="lxc2" model=model_a2c, tb_log_name="a2c", total_timesteps=1000, lxcType= None, lxcName="lxcMulti" + str(j) ) food.agents.append(trained_a2c) print(j,"'s model is trained done") else: print("here!!!") food.agents[j].all_stock_number = multi_number food.agents[j].env = env_train food.agents[j] = food.agents[j].online_learning(total_timesteps=1000, tb_log_name="a2c") env_train.reset() food.agents_number = multi_number # names=["date","open","high","low","close","volume","tic","day",] # df = pd.read_csv("./" + config.DATA_SAVE_DIR + "/" + "20210315-07h382" + ".csv",index_col=0) print('GPU is :', torch.cuda.is_available()) ######################################################################### print("==============Start Trading===========") start_date = config.START_TRADE_DATE, end_date = config.END_DATE, df_account_value = pd.DataFrame() df_actions = pd.DataFrame() start_date = start_date[0] end_date = end_date[0] date_list = getEveryDay(start_date, end_date) time_step = 30 #for i in range(0, len(date_list) - time_step, time_step): for i in range(0, 1): df = YahooDownloader( start_date=start_date, end_date=end_date, ticker_list=config.DOW_30_TICKER, ).lxc_fetch_data() print("==============Start Feature Engineering===========") fe = FeatureEngineer( use_technical_indicator=True, tech_indicator_list=config.TECHNICAL_INDICATORS_LIST, use_turbulence=True, user_defined_feature=False, ) processed = fe.preprocess_data(df) train = data_split(processed, start_date, end_date) stock_dimension = len(train.tic.unique()) # print("train.tic.unique() is:") # print(train.tic.unique()) print('stock_dimension is:', stock_dimension) state_space = ( 1 + 2 * stock_dimension + len(config.TECHNICAL_INDICATORS_LIST) * stock_dimension ) env_kwargs = { "hmax": 100, "initial_amount": 1000000, "buy_cost_pct": 0.001, "sell_cost_pct": 0.001, "state_space": state_space, "stock_dim": stock_dimension, "tech_indicator_list": config.TECHNICAL_INDICATORS_LIST, # "action_space": stock_dimension, "action_space": 1, "reward_scaling": 1e-4 } e_train_gym = StockTradingEnv(df=train,turbulence_threshold=250.0, **env_kwargs) env_train, _ = e_train_gym.get_sb_env() agent = DRLAgent(env=env_train) print("==============Model Training===========") print("start training ddpg model") ##################################################################################################a2c print("start pre_training model") multi_number = stock_dimension # temp = agent.get_model(model_name="a2c", lxc_stock_number=0) # agent.train_model(model=temp, tb_log_name="a2c", total_timesteps=1000) # print("e_train_gym.normal_high is:", e_train_gym.normal_high) # print("e_train_gym.normal_low is:", e_train_gym.normal_low) # e_trade_gym.normal_high = e_train_gym.normal_high # e_trade_gym.normal_low = e_train_gym.normal_low print("start main_training model") #################################检测是否有新股票上市################################## for j in range(food.agents_number,multi_number): model_a2c = agent.get_model(model_name="a2c", lxc_stock_number=j, all_stock_number=multi_number) model_a2c.all_stock_number = multi_number model_a2c.env.reset() trained_a2c = agent.get_pre_model(model=model_a2c, tb_log_name="a2c", total_timesteps=1000,lxcName="lxcMulti" + str(food.agents_number-1)) trained_a2c.lxc_stock_number = j trained_a2c.all_stock_number = multi_number food.agents.append(trained_a2c) food.agents_number = multi_number #################################测试################################## temp_account_value, temp_actions = DRLAgent.Multi_DRL_prediction( model=food.agents, environment=e_train_gym,all_stock_number=multi_number ) #print("temp_account_value is:",temp_account_value) #print("temp_actions is:", temp_actions) df_account_value = df_account_value.append(temp_account_value) df_actions = df_actions.append(temp_actions) #print("df_account_value is:", df_account_value) #print("df_actions is:", df_actions) #exit(0) ################################再训练###################################### ''' for j in range(0, multi_number): food.agents[j].all_stock_number = multi_number env_train.reset() food.agents[j].env = env_train food.agents[j] = food.agents[j].online_learning(total_timesteps=1000, tb_log_name="a2c") agent.save_pre_model(model=model_a2c, tb_log_name="a2c", total_timesteps=1000,lxcName="lxcMulti" + str(j)) #env_train.reset() ''' ''' df_account_value, df_actions = DRLAgent.DRL_prediction( model=multi_A2C, environment=e_trade_gym,lxc_env = e_train_gym # model=trained_ddpg, environment=e_trade_gym ) ''' print("df_account_value is:",df_account_value) print("df_actions is:",df_actions) df_account_value.to_csv( "./" + config.RESULTS_DIR + "/df_account_value_" + now + ".csv" ) df_actions.to_csv("./" + config.RESULTS_DIR + "/df_actions_" + now + ".csv") print("==============Get Backtest all Results===========") perf_stats_all = BackTestStats(df_account_value) perf_stats_all = pd.DataFrame(perf_stats_all) perf_stats_all.to_csv("./" + config.RESULTS_DIR + "/perf_stats_all_" + now + ".csv")
StarcoderdataPython
6524467
<filename>eduFaucet_config-EXAMPLE.py # Common config for EduFaucet VERSION = '1.0' GITHUB = 'https://github.com/bitcoinedu-io/EduFaucet' DBFILE = 'eduFaucet-db.sqlite3' rpc_user = 'BTE' rpc_pass = '<PASSWORD>' URL = 'http://%s:%s@localhost:8908' % (rpc_user, rpc_pass) chaininfo = { 'name': 'EduFaucet', 'unit': 'BTE' } params = { 'SubsidyHalvingInterval': 210000, # blocks, miner reward halving 'PowTargetTimespan': 1*24*60*60, # sec, retarget time: one day 'PowTargetSpacing': 10*60, # sec, block time 10 min 'DifficultyAdjustmentInterval': 144 # blocks, PowTargetTimespan / PowTargetSpacing }
StarcoderdataPython
12828774
# Github : https://github.com/adarsh2104 # HR-Profile: https://www.hackerrank.com/adarsh_2104 # Challenge : https://www.hackerrank.com/challenges/s10-quartiles # Max Score : 30 def find_median(array): if len(array) % 2 == 1: return array[len(array) // 2] else: return (array[len(array) // 2] + array[len(array) // 2 - 1]) // 2 n = input() input_array = sorted([int(x) for x in input().split()]) print(find_median(input_array[:len(input_array)//2])) print(find_median(input_array)) print(find_median(input_array[len(input_array) // 2 + len(input_array) % 2:]))
StarcoderdataPython
1608778
<reponame>renjunxiang/enjoy_myself import pandas as pd import os import numpy as np # DIR = os.path.dirname(__file__) DIR = 'D:\\github\\enjoy_myself\\crawler\\crawler_story' data = np.load(DIR + '/data/' + '女频言情.npy') data = pd.DataFrame(data, columns=['title', 'url', 'author', 'size', 'update', 'describtions', 'stars', 'classify']) from TextClustering.TextClustering import TextClustering model = TextClustering(texts=list(data.iloc[:, 5])) model.text_cut(stopwords_path='default') model.creat_vocab(size=50, window=5, vocab_savepath=DIR + '/model/size50_window5.model') # model.word2matrix(method='frequency', top=50) model.word2matrix(method='vector', top=20, similar_n=10) model.decomposition() print('前两个成分的特征占比:', model.pca.explained_variance_ratio_[0:2].sum()) model.clustering(X=model.decomposition_data, model_name='KMeans', n_clusters=10) model.show_decomposition(background=True, show=True, pixel=None, textsize=50)
StarcoderdataPython
295137
<gh_stars>1-10 import os cur_dir = os.path.dirname(__file__) eosio_token_abi = None with open(os.path.join(cur_dir, 'data/eosio.token.abi'), 'r') as f: eosio_token_abi = f.read() with open(os.path.join(cur_dir, 'data/eosio.system_eosio.abi'), 'r') as f: eosio_system_abi_eosio = f.read() with open(os.path.join(cur_dir, 'data/eosio.system_uuos.abi'), 'r') as f: eosio_system_abi_uuos = f.read() eosio_system_abi = dict( EOS = eosio_system_abi_eosio, UUOS = eosio_system_abi_uuos )
StarcoderdataPython
1713307
from mxnet import nd from mxnet.gluon import nn from models.pointnet_globalfeat import PointNetfeat_vanilla class PointNetDenseCls(nn.Block): def __init__(self, num_points=2500, k=2, routing=None): super(PointNetDenseCls, self).__init__() self.num_points = num_points self.k = k self.feat = PointNetfeat_vanilla(num_points, global_feat=False, routing=routing) self.conv1 = nn.Conv1D(512, 1) self.conv2 = nn.Conv1D(256, 1) self.conv3 = nn.Conv1D(128, 1) self.conv4 = nn.Conv1D(self.k, 1) self.bn1 = nn.BatchNorm(in_channels=512) self.bn2 = nn.BatchNorm(in_channels=256) self.bn3 = nn.BatchNorm(in_channels=128) def forward(self, x): x, trans = self.feat(x) x = nd.relu(self.bn1(self.conv1(x))) x = nd.relu(self.bn2(self.conv2(x))) x = nd.relu(self.bn3(self.conv3(x))) x = self.conv4(x) x = nd.transpose(x, (0,2,1)) return x, trans
StarcoderdataPython
1880392
from flask import render_template, jsonify from werkzeug.exceptions import HTTPException from backend.restplus import api from backend.ws.devices import ns as devices_namespace def ndb_wsgi_middleware(wsgi_app, client): def middleware(environ, start_response): with client.context(): return wsgi_app(environ, start_response) return middleware def create_app(app, client): app.wsgi_app = ndb_wsgi_middleware(app.wsgi_app, client) # Wrap the app in middleware. @app.route('/') def vue_client(): return render_template('index.html') @app.errorhandler(Exception) def default_error_handler(e): '''Default error handler''' # pass through HTTP errors if isinstance(e, HTTPException): return jsonify(error=str(e)), getattr(e, 'code', 500) return jsonify(error=str(e)), 500 api.init_app(app) api.add_namespace(devices_namespace)
StarcoderdataPython
79075
<filename>mavenn/__init__.py """MAVE-NN software package.""" # The functions imported here are the ONLY "maven.xxx()" functions that # users are expected to interact with # To regularize log calculations import numpy as np TINY = np.sqrt(np.finfo(np.float32).tiny) # Primary model class from mavenn.src.model import Model # For running functional tests from mavenn.tests import run_tests # Examples from mavenn.src.examples import list_tutorials from mavenn.src.examples import run_demo from mavenn.src.examples import load_example_dataset from mavenn.src.examples import load_example_model # For loading models from mavenn.src.utils import load from mavenn.src.utils import split_dataset # For visualizing G-P maps from mavenn.src.visualization import heatmap from mavenn.src.visualization import heatmap_pairwise
StarcoderdataPython
9695869
""" This file is part of pybacnet. pybacnet is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. pybacnet is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with pybacnet. If not, see <http://www.gnu.org/licenses/>. """ """ Copyright (c) 2013 Building Robotics, Inc. """ """ @author <NAME> <<EMAIL>> @author <NAME> <<EMAIL>> """ import json import re import operator import sys from twisted.internet import threads, defer from smap.driver import SmapDriver from smap.util import periodicSequentialCall, find from smap import actuate from pybacnet import bacnet def _get_class(name): cmps = name.split('.') assert len(cmps) > 1 (mod_name, class_name) = ('.'.join(cmps[:-1]), cmps[-1]) if mod_name in sys.modules: mod = sys.modules[mod_name] else: mod = __import__(mod_name, globals(), locals(), [class_name]) return getattr(mod, class_name) class BACnetDriver(SmapDriver): """Driver for polling BACnet points""" def setup(self, opts): bacnet.Init(opts.get('iface', 'eth0'), '47900') with open(opts.get('db'), 'r') as fp: self.db = json.load(fp) self.rate = int(opts.get('rate', 60)) self.devices = map(re.compile, opts.get('devices', ['.*'])) self.points = map(re.compile, opts.get('points', ['.*'])) self.ffilter = _get_class(opts.get('filter')) if opts.get('filter') else None self.pathnamer = _get_class(opts.get('pathnamer')) if opts.get('pathnamer') else None self.actuators = _get_class(opts.get('actuators')) if opts.get('actuators') else None if self.actuators: act_names = [a['name'] for a in self.actuators] for (dev, obj, path) in self._iter_points(): unit = str(obj['unit']).strip() if unit.isdigit(): unit = str(bacnet.type_str(int(unit))) self.add_timeseries(path, unit, data_type='double') # Add actuators if self.actuators and obj['name'] in act_names: actuator = find(lambda a: a['name'] == obj['name'], self.actuators) setup = {'obj': obj, 'dev': dev} if obj['props']['type'] in [bacnet.OBJECT_ANALOG_INPUT, bacnet.OBJECT_ANALOG_OUTPUT, bacnet.OBJECT_ANALOG_VALUE]: setup['range'] = actuator['range'] setup['application_tag'] = bacnet.BACNET_APPLICATION_TAG_REAL act = ContinuousActuator(**setup) data_type = 'double' elif obj['props']['type'] in [bacnet.OBJECT_BINARY_INPUT, bacnet.OBJECT_BINARY_OUTPUT, bacnet.OBJECT_BINARY_VALUE]: setup['application_tag'] = bacnet.BACNET_APPLICATION_TAG_ENUMERATED act = BinaryActuator(**setup) data_type = 'long' elif obj['props']['type'] in [bacnet.OBJECT_MULTI_STATE_INPUT, bacnet.OBJECT_MULTI_STATE_OUTPUT, bacnet.OBJECT_MULTI_STATE_VALUE]: setup['application_tag'] = bacnet.BACNET_APPLICATION_TAG_ENUMERATED setup['states'] = actuator['states'] act = DiscreteActuator(**setup) data_type = 'long' if act: print "adding actuator:", path, unit, act self.add_actuator(path + "_act", unit, act, data_type=data_type, write_limit=5) @staticmethod def _matches(s, pats): return len(filter(None, map(lambda p: p.match(s), pats))) > 0 def get_path(self, dev, obj): if self.pathnamer: path = str(self.pathnamer(dev['name'], obj['name'])) else: path = str('/' + dev['name'] + '/' + obj['name']) return (dev, obj, path) def _iter_points(self): for dev in self.db: if self.ffilter: for obj in dev['objs']: if self.ffilter(dev['name'], obj['name']): yield self.get_path(dev, obj) else: if not self._matches(dev['name'], self.devices): continue for obj in dev['objs'][1:]: if not self._matches(obj['name'], self.points): continue yield self.get_path(dev, obj) def start(self): self.caller = periodicSequentialCall(self.update) self.caller.start(self.rate) @defer.inlineCallbacks def update(self): for (dev, obj, path) in self._iter_points(): try: val = yield threads.deferToThread(bacnet.read_prop, dev['props'], obj['props']['type'], obj['props']['instance'], bacnet.PROP_PRESENT_VALUE, -1) except IOError: pass else: self._add(path, float(val)) class BACnetActuator(actuate.SmapActuator): def __init__(self, **opts): self.dev = opts['dev'] self.obj = opts['obj'] self.priority = 16 self.application_tag = opts['application_tag'] def get_state(self, request): return bacnet.read_prop(self.dev['props'], self.obj['props']['type'], self.obj['props']['instance'], bacnet.PROP_PRESENT_VALUE, -1) def set_state(self, request, state): if 'priority' in request.args: self.priority = int(request.args['priority'][0]) if 'clear' in request.args: self.clear() else: bacnet.write_prop(self.dev['props'], self.obj['props']['type'], self.obj['props']['instance'], bacnet.PROP_PRESENT_VALUE, self.application_tag, str(state), self.priority) return self.get_state(None) def clear(self): return bacnet.write_prop(self.dev['props'], self.obj['props']['type'], self.obj['props']['instance'], bacnet.PROP_PRESENT_VALUE, bacnet.BACNET_APPLICATION_TAG_NULL, "", self.priority) class ContinuousActuator(BACnetActuator, actuate.ContinuousActuator): def __init__(self, **opts): actuate.ContinuousActuator.__init__(self, opts['range']) BACnetActuator.__init__(self, **opts) class BinaryActuator(BACnetActuator, actuate.BinaryActuator): def __init__(self, **opts): actuate.BinaryActuator.__init__(self) BACnetActuator.__init__(self, **opts) class DiscreteActuator(BACnetActuator, actuate.NStateActuator): def __init__(self, **opts): actuate.NStateActuator.__init__(self, opts['states']) BACnetActuator.__init__(self, **opts)
StarcoderdataPython
9752742
# Write a program that reads a string and returns a table of the letters of the alphabet in alphabetical order # which occur in the string together with the number of times each letter occurs. # Case should be ignored. def lettercount(s): tally = {} s = s.lower() for letter in s: if not letter.isalpha(): continue tally[letter] = tally.get(letter, 0) + 1 letterlist = list(tally.items()) letterlist.sort() for pair in letterlist: print("".join(str(pair[0])), "".join(str(pair[1]))) # so it doesn't return a list of tuples, ie format cleanup # lettercount("The Quick Brown Fox Jumps Over The Lazy Dog") #test case
StarcoderdataPython
5151944
<gh_stars>0 from copy import deepcopy from typing import List, Union, Optional, Tuple, Dict from fedot.core.dag.graph import Graph from fedot.core.dag.graph_operator import GraphOperator from fedot.core.pipelines.node import Node, PrimaryNode, SecondaryNode from fedot.core.pipelines.pipeline import Pipeline class PipelineBuilder: """ Builder for incremental construction of directed acyclic Pipelines. Semantics: - Forward-only & addition-only (can't prepend or delete nodes). - Doesn't throw, doesn't fail: methods always have a way to interpret input given current graph state. - Is not responsible for the validity of resulting Pipeline (e.g. correct order, valid operations). - Builds always new pipelines (on copies of nodes), preserves its state between builds. State doesn't leak outside. """ OperationType = Union[str, Tuple[str, dict]] def __init__(self, *initial_nodes: Optional[Node]): """ Create builder with prebuilt nodes as origins of the branches. """ self.heads: List[Node] = list(filter(None, initial_nodes)) @property def _iend(self) -> int: return len(self.heads) def add_node(self, operation_type: Optional[str], branch_idx: int = 0, params: Optional[Dict] = None): """ Add single node to pipeline branch of specified index. If there are no heads => adds single PrimaryNode. If there is single head => adds single SecondaryNode using head as input. If there are several heads => adds single SecondaryNode using as input the head indexed by head_idx. If input is None => do nothing. If branch_idx is out of bounds => appends new PrimaryNode. :param operation_type: new operation, possibly None :param branch_idx: index of the head to use as input for the new node :param params: parameters dictionary for the specific operation :return: self """ if not operation_type: return self params = self._pack_params(operation_type, params) if branch_idx < len(self.heads): input_node = self.heads[branch_idx] self.heads[branch_idx] = SecondaryNode(operation_type, nodes_from=[input_node], content=params) else: self.heads.append(PrimaryNode(operation_type, content=params)) return self def add_sequence(self, *operation_type: OperationType, branch_idx: int = 0): """ Same as .node() but for many operations at once. :param operation_type: operations for new nodes, either as an operation name or as a tuple of operation name and operation parameters. """ for operation in operation_type: operation, params = self._unpack_operation(operation) self.add_node(operation, branch_idx, params) return self def grow_branches(self, *operation_type: Optional[OperationType]): """ Add single node to each branch. Argument position means index of the branch to grow. None operation means don't grow that branch. If there are no nodes => creates new branches. If number of input nodes is bigger than number of branches => extra operations create new branches. :param operation_type: operations for new nodes, either as an operation name or as a tuple of operation name and operation parameters. :return: self """ for i, operation in enumerate(operation_type): operation, params = self._unpack_operation(operation) self.add_node(operation, i, params) return self def add_branch(self, *operation_type: Optional[OperationType], branch_idx: int = 0): """ Create branches at the tip of branch with branch_idx. None operations are filtered out. Number of new branches equals to number of provided operations. If there are no heads => will add several primary nodes. If there is single head => add several SecondaryNodes using head as the previous. If there are several heads => branch head indexed by head_idx. If branch_idx is out of bounds => adds PrimaryNodes as new heads at the end. If no not-None operations are provided, nothing is changed. :param operation_type: operations for new nodes, either as an operation name or as a tuple of operation name and operation parameters. :param branch_idx: index of the branch for branching its tip :return: self """ operations = list(filter(None, operation_type)) if not operations: return self if branch_idx < len(self.heads): input_node = self.heads.pop(branch_idx) for i, operation in enumerate(operations): operation, params = self._unpack_operation(operation) self.heads.insert(branch_idx + i, SecondaryNode(operation, nodes_from=[input_node], content=self._pack_params(operation, params))) else: for operation in operations: operation, params = self._unpack_operation(operation) self.add_node(operation, self._iend, params) return self def join_branches(self, operation_type: Optional[str], params: Optional[Dict] = None): """ Joins all current branches with provided operation as ensemble node. If there are no branches => does nothing. If there is single branch => adds single SecondaryNode using it as input. If there are several branches => adds single SecondaryNode using all heads as inputs. :param operation_type: operation to use for joined node :param params: parameters dictionary for the specific operation :return: self """ if self.heads and operation_type: content = self._pack_params(operation_type, params) new_head = SecondaryNode(operation_type, nodes_from=self.heads, content=content) self.heads = [new_head] return self def reset(self): """ Reset builder state. """ self.heads = [] def merge_with(self, following_builder) -> Optional['PipelineBuilder']: return merge_pipeline_builders(self, following_builder) def to_nodes(self) -> List[Node]: """ Return list of final nodes and reset internal state. :return: list of final nodes, possibly empty. """ return deepcopy(self.heads) def to_pipeline(self) -> Optional[Pipeline]: """ Builds new Pipeline from current tips of branches. Preserves builder state. :return: Pipeline if there exist nodes, None if there're no nodes. """ return Pipeline(self.to_nodes()) if self.heads else None @staticmethod def _unpack_operation(operation: Optional[OperationType]) -> Tuple[Optional[str], Optional[Dict]]: if isinstance(operation, str) or operation is None: return operation, None else: return operation @staticmethod def _pack_params(name: str, params: Optional[dict]) -> Optional[dict]: return {'name': name, 'params': params} if params else None def merge_pipeline_builders(previous: PipelineBuilder, following: PipelineBuilder) -> Optional[PipelineBuilder]: """ Merge two pipeline builders. Merging is defined for cases one-to-many and many-to-one nodes, i.e. one final node to many initial nodes and many final nodes to one initial node. Merging is undefined for the case of many-to-many nodes and None is returned. Merging of the builder with itself is well-defined and leads to duplication of the pipeline. If one of the builders is empty -- the other one is returned, no merging is performed. State of the passed builders is preserved as they were, after merging new builder is returned. :return: PipelineBuilder if merging is well-defined, None otherwise. """ if not following.heads: return previous elif not previous.heads: return following lhs_nodes_final = previous.to_nodes() rhs_tmp_graph = Graph(following.to_nodes()) rhs_nodes_initial = list(filter(lambda node: not node.nodes_from, rhs_tmp_graph.nodes)) # If merging one-to-one or one-to-many if len(lhs_nodes_final) == 1: final_node = lhs_nodes_final[0] for initial_node in rhs_nodes_initial: rhs_tmp_graph.update_node(initial_node, SecondaryNode(initial_node.operation.operation_type, nodes_from=[final_node])) # If merging many-to-one elif len(rhs_nodes_initial) == 1: initial_node = rhs_nodes_initial[0] rhs_tmp_graph.update_node(initial_node, SecondaryNode(initial_node.operation.operation_type, nodes_from=lhs_nodes_final)) # Merging is not defined for many-to-many case else: return None # Check that Graph didn't mess up with node types if not all(map(lambda n: isinstance(n, Node), rhs_tmp_graph.nodes)): raise ValueError("Expected Graph only with nodes of type 'Node'") # Need all root_nodes, hence GraphOperator (Pipeline.root_node returns just a single node or throws) root_nodes = GraphOperator(rhs_tmp_graph).root_node() merged_builder = PipelineBuilder(root_nodes) if isinstance(root_nodes, Node) else PipelineBuilder(*root_nodes) return merged_builder
StarcoderdataPython
12819916
<gh_stars>10-100 import json import os import time import sys import numpy as np import pandas as pd import torch import torch.nn as nn import torch.nn.functional as F from dataset import prepare_dataset from experiments.utils import construct_passport_kwargs_from_dict from models.alexnet_passport_private import AlexNetPassportPrivate from models.resnet_passport_private import ResNetPrivate from models.layers.passportconv2d import PassportBlock from models.layers.passportconv2d_private import PassportPrivateBlock from models.losses.sign_loss import SignLoss import shutil class DatasetArgs(): pass def train_maximize(origpassport, fakepassport, model, optimizer, criterion, trainloader, device, type): model.train() loss_meter = 0 signloss_meter = 0 maximizeloss_meter = 0 mseloss_meter = 0 csloss_meter = 0 acc_meter = 0 signacc_meter = 0 start_time = time.time() mse_criterion = nn.MSELoss() cs_criterion = nn.CosineSimilarity() #余弦相似性 for k, (d, t) in enumerate(trainloader): d = d.to(device) t = t.to(device) optimizer.zero_grad() # if scheme == 1: # pred = model(d) # else: pred = model(d, ind=1) #private graph loss = criterion(pred, t) signloss = torch.tensor(0.).to(device) signacc = torch.tensor(0.).to(device) count = 0 for m in model.modules(): if isinstance(m, SignLoss): signloss += m.loss signacc += m.acc count += 1 maximizeloss = torch.tensor(0.).to(device) mseloss = torch.tensor(0.).to(device) csloss = torch.tensor(0.).to(device) for l, r in zip(origpassport, fakepassport): mse = mse_criterion(l, r) cs = cs_criterion(l.view(1, -1), r.view(1, -1)).mean() csloss += cs mseloss += mse maximizeloss += 1 / mse if 'fake2-' in type : (loss).backward() #only cross-entropy loss backward fake2 elif 'fake3-' in type : (loss + maximizeloss).backward() #csloss do not backward kafe3 else: # print("FFFFFFFFFFFFFFFFFF") (loss + maximizeloss + signloss).backward() #csloss backward #fake3_S torch.nn.utils.clip_grad_norm_(fakepassport, 2) #梯度裁剪 optimizer.step() acc = (pred.max(dim=1)[1] == t).float().mean() loss_meter += loss.item() acc_meter += acc.item() signloss_meter += signloss.item() signacc_meter += signacc.item() / count maximizeloss_meter += maximizeloss.item() mseloss_meter += mseloss.item() csloss_meter += csloss.item() print(f'Batch [{k + 1}/{len(trainloader)}]: ' f'Loss: {loss_meter / (k + 1):.4f} ' f'Acc: {acc_meter / (k + 1):.4f} ' f'Sign Loss: {signloss_meter / (k + 1):.4f} ' f'Sign Acc: {signacc_meter / (k + 1):.4f} ' f'MSE Loss: {mseloss_meter / (k + 1):.4f} ' f'Maximize Dist: {maximizeloss_meter / (k + 1):.4f} ' f'CS: {csloss_meter / (k + 1):.4f} ({time.time() - start_time:.2f}s)', end='\r') print() loss_meter /= len(trainloader) acc_meter /= len(trainloader) signloss_meter /= len(trainloader) signacc_meter /= len(trainloader) maximizeloss_meter /= len(trainloader) mseloss_meter /= len(trainloader) csloss_meter /= len(trainloader) return {'loss': loss_meter, 'signloss': signloss_meter, 'acc': acc_meter, 'signacc': signacc_meter, 'maximizeloss': maximizeloss_meter, 'mseloss': mseloss_meter, 'csloss': csloss_meter, 'time': start_time - time.time()} def test_fake(model, criterion, valloader, device): model.eval() loss_meter = 0 signloss_meter = 0 acc_meter = 0 signacc_meter = 0 start_time = time.time() with torch.no_grad(): for k, (d, t) in enumerate(valloader): d = d.to(device) t = t.to(device) # if scheme == 1: # pred = model(d) # else: pred = model(d, ind=1) loss = criterion(pred, t) signloss = torch.tensor(0.).to(device) signacc = torch.tensor(0.).to(device) count = 0 for m in model.modules(): if isinstance(m, SignLoss): signloss += m.get_loss() signacc += m.get_acc() count += 1 acc = (pred.max(dim=1)[1] == t).float().mean() loss_meter += loss.item() acc_meter += acc.item() signloss_meter += signloss.item() try: signacc_meter += signacc.item() / count except: pass print(f'Batch [{k + 1}/{len(valloader)}]: ' f'Loss: {loss_meter / (k + 1):.4f} ' f'Acc: {acc_meter / (k + 1):.4f} ' f'Sign Loss: {signloss_meter / (k + 1):.4f} ' f'Sign Acc: {signacc_meter / (k + 1):.4f} ({time.time() - start_time:.2f}s)', end='\r') print() loss_meter /= len(valloader) acc_meter /= len(valloader) signloss_meter /= len(valloader) signacc_meter /= len(valloader) return {'loss': loss_meter, 'signloss': signloss_meter, 'acc': acc_meter, 'signacc': signacc_meter, 'time': time.time() - start_time} if __name__ == '__main__': import argparse parser = argparse.ArgumentParser( description='fake attack 3: create another passport maximized from current passport') # parser.add_argument('--rep', default=1, type=int, help='training id') parser.add_argument('--rep', default=1, type=str, help='training comment') parser.add_argument('--arch', default='resnet18', choices=['alexnet', 'resnet18']) parser.add_argument('--dataset', default='cifar100', choices=['cifar10', 'cifar100']) parser.add_argument('--flipperc', default=0, type=float, help='flip percentange 0~1') parser.add_argument('--scheme', default=1, choices=[1, 2, 3], type=int) parser.add_argument('--loadpath', default='', help='path to model to be attacked') parser.add_argument('--passport-config', default='', help='path to passport config') args = parser.parse_args() args.scheme = 3 args.loadpath = "/data-x/g12/zhangjie/DeepIPR/baseline/resnet18_cifar100_v3_all/" # print(args.loadpath.split('/')[-2]) # sys.exit(0) print(args.loadpath)
StarcoderdataPython
5010111
# -*- coding: utf-8 -*- # Импорт библиотек import logging import os.path import sys import time import click import pandas as pd from datetime import datetime, timedelta from terminaltables import AsciiTable sys.path.append(os.path.join(os.path.dirname(__file__), '..')) from cointrader import db, STRATEGIES from cointrader.config import Config, get_path_to_config from cointrader.exchange import Poloniex, Market from cointrader.bot import init_db, get_bot, create_bot, Active, Bots_list # Создание лога logging.basicConfig(format=u'%(levelname)-8s [%(asctime)s] %(message)s', level=logging.DEBUG, filename=u'cointrader.log') log = logging.getLogger(__name__) class Context(object): """Docstring for Context. """ def __init__(self): self.exchange = None @property def nonce(self): """ Returns a nonce Used in authentication """ return int((time.time() + 0.5) * 1000 * 1050) # Создание пустого декоратора pass_context = click.make_pass_decorator(Context, ensure=True) # Создание группы команд @click.group() @pass_context def main(ctx): """Console script for cointrader on the Poloniex exchange :param ctx: """ init_db() config = Config(open(get_path_to_config(), "r")) ctx.exchange = Poloniex(config, ctx.nonce) # Добавляем команды @click.command() @click.argument("market") @click.option("--resolution", help="Resolution of the chart which is used for trend analysis", default="30m") @click.option("--automatic", help="Start cointrader in automatic mode.", is_flag=True) @click.option("--strategy", help="Stratgegy used for trading.", default="trend", type=click.Choice(STRATEGIES.keys())) @click.option("--verbose", help="Вывод на экран логируемых сообщений.", is_flag=False) @click.option("--percent", help="Процент торговли от всей суммы.", is_flag=False) @click.option("--best", help="", is_flag=False) @click.option("--searchpoint", help="", is_flag=False) @click.option("--btc", help="trading value of BTC", default=0.0, type=float) @click.option("--update_profit", help="Start circle updates profit list for bots", is_flag=False) # @click.option("--best_pass_nth", help="", default="0") @pass_context def start(ctx, market, resolution, automatic, strategy, verbose, percent, best, searchpoint, btc, update_profit): """Start a new bot on the given market and the given amount of BTC""" # Build the market on which the bot will operate # First check if the given market is a valid market. If not exit # here with a error message. # If the market is valid create a real market instance of and # instance for backtests depending on the user input. market = set_market(ctx, market, backtrade=True) # Check if the given resolution is supported if not ctx.exchange.is_valid_resolution(resolution): valid_resolutions = ", ".join(ctx.exchange.resolutions.keys()) click.echo("Resolution {} is not supported.\n" "Please choose one of the following: {}".format(resolution, valid_resolutions)) sys.exit(1) # Initialise a strategy. strategy = STRATEGIES[strategy]() start, end = set_start_end() best_pair, best_testing_market = find_best_pair(automatic, ctx, end, market, percent, resolution, start, strategy, verbose, searchpoint, btc, update_profit) trade_to_minus = False # if int(best_pass_nth) == 0: if not best_testing_market: trade_to_minus = True elif best_pair is not None: if best and not is_active(best_pair["market"]): print("\nВыбрана пара: %s, заработок: %f" % (best_pair["market"]._name, best_pair["profit"])) best_pair["market"]._backtrade = False bot = get_bot(best_pair["market"], strategy, resolution, start, end, verbose, percent, automatic, memory_only=False, btc=btc) # trade_to_minus = bot.start(backtest=False, automatic=automatic) trade_to_minus = bot.start(backtest=False, automatic=True) delete_bot(bot) elif best_testing_market[-1]["profit"] > 1 and not best and not is_active(best_testing_market[-1]["market"]): best_testing_market[-1]["market"]._backtrade = False bot = get_bot(best_testing_market[-1]["market"], strategy, resolution, start, end, verbose, percent, automatic, memory_only=False, btc=btc) trade_to_minus = bot.start(backtest=False, automatic=automatic) delete_bot(bot) if trade_to_minus: print("На данной паре заработок отсутсвует.") if best: to_do = True elif trade_to_minus: to_do = True else: to_do = False if to_do: while to_do: if trade_to_minus: best_pair, best_testing_market = find_best_pair(automatic, ctx, end, market, percent, resolution, start, strategy, verbose, searchpoint, btc=btc) for item in best_testing_market: item["market"]._backtrade = False if not is_active(item["market"]): print("\nВыбрана пара: %s, заработок: %f" % (item["market"]._name, item["profit"])) bot = get_bot(item["market"], strategy, resolution, start, end, verbose, percent, automatic, memory_only=False, btc=btc) to_do = bot.start(backtest=False, automatic=automatic) delete_bot(bot) trade_to_minus = True def delete_bot(bot): try: for active in bot.activity: db.delete(active) for current_trade in bot.trades: db.delete(current_trade) db.delete(bot) db.commit() del bot finally: pass def is_active(market): activities = db.query(Active).filter(Active.currency == market._name).first() if activities is None: return False else: return True def find_best_pair(automatic, ctx, end, market, percent, resolution, start, strategy, verbose, searchpoint, btc, update_profit=False): to_do = True while to_do: test_markets = [] bot = get_bot(market, strategy, resolution, start, end, verbose, percent, automatic, memory_only=False, btc=btc) df = pd.DataFrame.from_dict(bot._market._exchange.markets, orient='index') if len(df): while not test_markets: if update_profit: mask = (df['volume'] > 50) else: mask = (df['volume'] > 50) & (df['change'] > -15) & (df['change'] < 3) test_markets = print_top_trends(ctx, df, market, backtrade=False, searchpoint=searchpoint, mask=mask) if not test_markets: time.sleep(1) if update_profit: print("Ищу пары по условию: (df['volume'] > 50) & (df['change'] > -15) & (df['change'] < 15)") else: print("Ищу пары по условию: (df['volume'] > 50) & (df['change'] > -15) & (df['change'] < 3)") delete_bot(bot) best_testing_market = [] test_markets.append(set_market(ctx, market._name, backtrade=True)) index = 0 for current_market in test_markets: if index > 7 and not update_profit: break bot = create_bot(current_market, strategy, resolution, start, end, verbose, percent, automatic=True, btc=btc) for trade in bot.trades: try: if trade != bot.trades[0]: db.delete(trade) except: pass if bot.spread > 0.5: print( "Валюта {} имеет порог покупки {:.2f}%, будет пропущена.".format(bot._market.currency, bot.spread)) continue bot.start(backtest=True, automatic=True) delete_bot(bot) if bot.profit > 1 and bot.trend != 'Рынок ВВЕРХ': best_testing_market.append({"market": bot._market, "profit": bot.profit}) if not is_active(bot._market) and not update_profit: break index += 1 from operator import itemgetter best_testing_market = sorted(best_testing_market, key=itemgetter('profit'), reverse=True) best_pair = best_markets_print(best_testing_market) if update_profit and best_testing_market: bots_list = Bots_list('list =' + str(best_testing_market)) exec(bots_list) db.add(bots_list) db.commit else: to_do = False return best_pair, best_testing_market def best_markets_print(best_testing_market): best_pair = None out = [["ПАРА", "ЗАРАБОТОК"]] for item in best_testing_market: if item["profit"] > 0: if best_pair == None: best_pair = item elif item["profit"] > best_pair["profit"]: best_pair = item values = [] values.append(item["market"]._name) values.append(round(item["profit"], 2)) out.append(values) table = AsciiTable(out).table print("\n".join(["\nПрибыльные пары:", table])) return best_pair def print_top_trends(ctx, df, market, backtrade, searchpoint, mask): df['change'] = df.change.astype(float) df['volume'] = df.volume.astype(float) df_filtered = df[mask] df_filtered = df_filtered.sort_values(by=['change'], ascending=True) test_markets = [] out = [["ПАРА", "ОБЪЕМ", "ИЗМЕНЕНИЯ"]] for current_market, row in df_filtered.iterrows(): volume, change = (row['volume'], row['change']) values = [] values.append(current_market) values.append(volume) values.append(str(change) + "%") out.append(values) if current_market != market._name: test_markets.append(set_market(ctx, current_market, backtrade=True)) table = AsciiTable(out).table print("\n".join(["\nРастущий тренд:", table])) return test_markets def set_market(ctx, market, backtrade): if ctx.exchange.is_valid_market(market): market = Market(ctx.exchange, market, backTrade=backtrade) else: click.echo("Market {} is not available".format(market)) sys.exit(1) return market def set_start_end(): try: now_time = datetime.now() delta = timedelta(days=1.5) date_N_days_ago = now_time - delta start = date_N_days_ago end = now_time except ValueError: click.echo("Days is not valid. Must be in 1 2 34 ...'") sys.exit(1) return start, end main.add_command(start) # Запуск сценария if __name__ == "__main__": main()
StarcoderdataPython
110388
<gh_stars>100-1000 """An implementation of the Python Database API Specification v2.0 using Teradata ODBC.""" # The MIT License (MIT) # # Copyright (c) 2015 by Teradata # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. import atexit import collections import ctypes import platform import re import sys import threading from . import util, datatypes from .api import * # @UnusedWildImport # noqa logger = logging.getLogger(__name__) # ODBC Constants SQL_ATTR_ODBC_VERSION, SQL_OV_ODBC2, SQL_OV_ODBC3 = 200, 2, 3 SQL_ATTR_QUERY_TIMEOUT, SQL_ATTR_AUTOCOMMIT = 0, 102 SQL_NULL_HANDLE, SQL_HANDLE_ENV, SQL_HANDLE_DBC, SQL_HANDLE_STMT = 0, 1, 2, 3 SQL_SUCCESS, SQL_SUCCESS_WITH_INFO = 0, 1, SQL_ERROR, SQL_INVALID_HANDLE = -1, -2 SQL_NEED_DATA, SQL_NO_DATA = 99, 100 SQL_CLOSE, SQL_UNBIND, SQL_RESET_PARAMS = 0, 2, 3 SQL_PARAM_TYPE_UNKNOWN = 0 SQL_PARAM_INPUT, SQL_PARAM_INPUT_OUTPUT, SQL_PARAM_OUTPUT = 1, 2, 4 SQL_ATTR_PARAM_BIND_TYPE = 18 SQL_ATTR_ROWS_FETCHED_PTR, SQL_ATTR_ROW_STATUS_PTR = 26, 25 SQL_ATTR_ROW_ARRAY_SIZE = 27 SQL_ATTR_PARAMS_PROCESSED_PTR, SQL_ATTR_PARAM_STATUS_PTR = 21, 20 SQL_ATTR_PARAMSET_SIZE = 22 SQL_PARAM_BIND_BY_COLUMN = 0 SQL_NULL_DATA, SQL_NTS = -1, -3 SQL_IS_POINTER, SQL_IS_UINTEGER, SQL_IS_INTEGER = -4, -5, -6 SQL_FETCH_NEXT, SQL_FETCH_FIRST, SQL_FETCH_LAST = 1, 2, 4 SQL_SIGNED_OFFSET = -20 SQL_C_BINARY, SQL_BINARY, SQL_VARBINARY, SQL_LONGVARBINARY = -2, -2, -3, -4 SQL_C_WCHAR, SQL_WCHAR, SQL_WVARCHAR, SQL_WLONGVARCHAR = -8, -8, -9, -10 SQL_C_SBIGINT = -5 + SQL_SIGNED_OFFSET SQL_FLOAT = 6 SQL_C_FLOAT = SQL_REAL = 7 SQL_C_DOUBLE = SQL_DOUBLE = 8 SQL_DESC_TYPE_NAME = 14 SQL_COMMIT, SQL_ROLLBACK = 0, 1 SQL_STATE_DATA_TRUNCATED = '01004' SQL_STATE_CONNECTION_NOT_OPEN = '08003' SQL_STATE_INVALID_TRANSACTION_STATE = '25000' SQLLEN = ctypes.c_ssize_t SQLULEN = ctypes.c_size_t SQLUSMALLINT = ctypes.c_ushort SQLSMALLINT = ctypes.c_short SQLINTEGER = ctypes.c_int SQLFLOAT = ctypes.c_float SQLDOUBLE = ctypes.c_double SQLBYTE = ctypes.c_ubyte SQLCHAR = ctypes.c_char SQLWCHAR = ctypes.c_wchar SQLRETURN = SQLSMALLINT SQLPOINTER = ctypes.c_void_p SQLHANDLE = ctypes.c_void_p ADDR = ctypes.byref PTR = ctypes.POINTER ERROR_BUFFER_SIZE = 2 ** 10 SMALL_BUFFER_SIZE = 2 ** 12 LARGE_BUFFER_SIZE = 2 ** 20 TRUE = 1 FALSE = 0 odbc = None hEnv = None drivers = None lock = threading.Lock() pyVer = sys.version_info[0] osType = platform.system() # The amount of seconds to wait when submitting non-user defined SQL (e.g. # set query bands, etc). QUERY_TIMEOUT = 120 if pyVer > 2: unicode = str # @ReservedAssignment # Define OS specific methods for handling buffers and strings. if osType == "Darwin" or osType == "Windows" or osType.startswith('CYGWIN'): # Mac OSx and Windows def _createBuffer(l): return ctypes.create_unicode_buffer(l) def _inputStr(s, l=None): if s is None: return None return ctypes.create_unicode_buffer( (s if util.isString(s) else str(s)), l) def _outputStr(s): return s.value def _convertParam(s): if s is None: return None return s if util.isString(s) else str(s) else: # Unix/Linux # Multiply by 3 as one UTF-16 character can require 3 UTF-8 bytes. def _createBuffer(l): return ctypes.create_string_buffer(l * 3) def _inputStr(s, l=None): if s is None: return None return ctypes.create_string_buffer( (s if util.isString(s) else str(s)).encode('utf8'), l) def _outputStr(s): return unicode(s.raw.partition(b'\00')[0], 'utf8') def _convertParam(s): if s is None: return None return (s if util.isString(s) else str(s)).encode('utf8') SQLWCHAR = ctypes.c_char connections = [] def cleanupConnections(): """Cleanup open connections.""" if connections: logger.warn( "%s open connections found on exit, attempting to close...", len(connections)) for conn in list(connections): conn.close() def getDiagnosticInfo(handle, handleType=SQL_HANDLE_STMT): """Gets diagnostic information associated with ODBC calls, particularly when errors occur.""" info = [] infoNumber = 1 while True: sqlState = _createBuffer(6) nativeError = SQLINTEGER() messageBuffer = _createBuffer(ERROR_BUFFER_SIZE) messageLength = SQLSMALLINT() rc = odbc.SQLGetDiagRecW(handleType, handle, infoNumber, sqlState, ADDR(nativeError), messageBuffer, len(messageBuffer), ADDR(messageLength)) if rc == SQL_SUCCESS_WITH_INFO and \ messageLength.value > ctypes.sizeof(messageBuffer): # Resize buffer to fit entire message. messageBuffer = _createBuffer(messageLength.value) continue if rc == SQL_SUCCESS or rc == SQL_SUCCESS_WITH_INFO: info.append( (_outputStr(sqlState), _outputStr(messageBuffer), abs(nativeError.value))) infoNumber += 1 elif rc == SQL_NO_DATA: return info elif rc == SQL_INVALID_HANDLE: raise InterfaceError( 'SQL_INVALID_HANDLE', "Invalid handle passed to SQLGetDiagRecW.") elif rc == SQL_ERROR: if infoNumber > 1: return info raise InterfaceError( "SQL_ERROR", "SQL_ERROR returned from SQLGetDiagRecW.") else: raise InterfaceError( "UNKNOWN_RETURN_CODE", "SQLGetDiagRecW returned an unknown return code: %s", rc) def checkStatus(rc, hEnv=SQL_NULL_HANDLE, hDbc=SQL_NULL_HANDLE, hStmt=SQL_NULL_HANDLE, method="Method", ignore=None): """ Check return status code and log any information or error messages. If error is returned, raise exception.""" sqlState = [] logger.trace("%s returned status code %s", method, rc) if rc not in (SQL_SUCCESS, SQL_NO_DATA): if hStmt != SQL_NULL_HANDLE: info = getDiagnosticInfo(hStmt, SQL_HANDLE_STMT) elif hDbc != SQL_NULL_HANDLE: info = getDiagnosticInfo(hDbc, SQL_HANDLE_DBC) else: info = getDiagnosticInfo(hEnv, SQL_HANDLE_ENV) for i in info: sqlState.append(i[0]) if rc == SQL_SUCCESS_WITH_INFO: logger.debug( u"{} succeeded with info: [{}] {}".format(method, i[0], i[1])) elif not ignore or i[0] not in ignore: logger.debug((u"{} returned non-successful error code " u"{}: [{}] {}").format(method, rc, i[0], i[1])) msg = ", ".join(map(lambda m: m[1], info)) if re.search(r'[^0-9\s]', msg) is None or i[0] == 'I': msg = msg + (". Check that the ODBC driver is installed " "and the ODBCINI or ODBCINST environment " "variables are correctly set.") raise DatabaseError(i[2], u"[{}] {}".format(i[0], msg), i[0]) else: logger.debug( u"Ignoring return of {} from {}: [{}] {}".format(rc, method, i[0], i[1])) # Breaking here because this error is ignored and info could # contain older error messages. # E.g. if error was SQL_STATE_CONNECTION_NOT_OPEN, the next # error would be the original connection error. break if not info: logger.info( "No information associated with return code %s from %s", rc, method) return sqlState def prototype(func, *args): """Setup function prototype""" func.restype = SQLRETURN func.argtypes = args def initFunctionPrototypes(): """Initialize function prototypes for ODBC calls.""" prototype(odbc.SQLAllocHandle, SQLSMALLINT, SQLHANDLE, PTR(SQLHANDLE)) prototype(odbc.SQLGetDiagRecW, SQLSMALLINT, SQLHANDLE, SQLSMALLINT, PTR(SQLWCHAR), PTR(SQLINTEGER), PTR(SQLWCHAR), SQLSMALLINT, PTR(SQLSMALLINT)) prototype(odbc.SQLSetEnvAttr, SQLHANDLE, SQLINTEGER, SQLPOINTER, SQLINTEGER) prototype(odbc.SQLDriverConnectW, SQLHANDLE, SQLHANDLE, PTR(SQLWCHAR), SQLSMALLINT, PTR(SQLWCHAR), SQLSMALLINT, PTR(SQLSMALLINT), SQLUSMALLINT) prototype(odbc.SQLFreeHandle, SQLSMALLINT, SQLHANDLE) prototype(odbc.SQLExecDirectW, SQLHANDLE, PTR(SQLWCHAR), SQLINTEGER) prototype(odbc.SQLNumResultCols, SQLHANDLE, PTR(SQLSMALLINT)) prototype(odbc.SQLDescribeColW, SQLHANDLE, SQLUSMALLINT, PTR(SQLWCHAR), SQLSMALLINT, PTR(SQLSMALLINT), PTR(SQLSMALLINT), PTR(SQLULEN), PTR(SQLSMALLINT), PTR(SQLSMALLINT)) prototype(odbc.SQLColAttributeW, SQLHANDLE, SQLUSMALLINT, SQLUSMALLINT, SQLPOINTER, SQLSMALLINT, PTR(SQLSMALLINT), PTR(SQLLEN)) prototype(odbc.SQLFetch, SQLHANDLE) prototype(odbc.SQLGetData, SQLHANDLE, SQLUSMALLINT, SQLSMALLINT, SQLPOINTER, SQLLEN, PTR(SQLLEN)) prototype(odbc.SQLFreeStmt, SQLHANDLE, SQLUSMALLINT) prototype(odbc.SQLPrepareW, SQLHANDLE, PTR(SQLWCHAR), SQLINTEGER) prototype(odbc.SQLNumParams, SQLHANDLE, PTR(SQLSMALLINT)) prototype(odbc.SQLDescribeParam, SQLHANDLE, SQLUSMALLINT, PTR( SQLSMALLINT), PTR(SQLULEN), PTR(SQLSMALLINT), PTR(SQLSMALLINT)) prototype(odbc.SQLBindParameter, SQLHANDLE, SQLUSMALLINT, SQLSMALLINT, SQLSMALLINT, SQLSMALLINT, SQLULEN, SQLSMALLINT, SQLPOINTER, SQLLEN, PTR(SQLLEN)) prototype(odbc.SQLExecute, SQLHANDLE) prototype(odbc.SQLSetStmtAttr, SQLHANDLE, SQLINTEGER, SQLPOINTER, SQLINTEGER) prototype(odbc.SQLMoreResults, SQLHANDLE) prototype(odbc.SQLDisconnect, SQLHANDLE) prototype(odbc.SQLSetConnectAttr, SQLHANDLE, SQLINTEGER, SQLPOINTER, SQLINTEGER) prototype(odbc.SQLEndTran, SQLSMALLINT, SQLHANDLE, SQLSMALLINT) prototype(odbc.SQLRowCount, SQLHANDLE, PTR(SQLLEN)) prototype(odbc.SQLBindCol, SQLHANDLE, SQLUSMALLINT, SQLSMALLINT, SQLPOINTER, SQLLEN, PTR(SQLLEN)) prototype(odbc.SQLDrivers, SQLHANDLE, SQLUSMALLINT, PTR(SQLCHAR), SQLSMALLINT, PTR(SQLSMALLINT), PTR(SQLCHAR), SQLSMALLINT, PTR(SQLSMALLINT)) def initOdbcLibrary(odbcLibPath=None): """Initialize the ODBC Library.""" global odbc if odbc is None: if osType == "Windows": odbc = ctypes.windll.odbc32 else: if not odbcLibPath: # If MAC OSx if osType == "Darwin": odbcLibPath = "libiodbc.dylib" elif osType.startswith("CYGWIN"): odbcLibPath = "odbc32.dll" else: odbcLibPath = 'libodbc.so' logger.info("Loading ODBC Library: %s", odbcLibPath) odbc = ctypes.cdll.LoadLibrary(odbcLibPath) def initDriverList(): global drivers if drivers is None: drivers = [] description = ctypes.create_string_buffer(SMALL_BUFFER_SIZE) descriptionLength = SQLSMALLINT() attributesLength = SQLSMALLINT() rc = SQL_SUCCESS direction = SQL_FETCH_FIRST while True: rc = odbc.SQLDrivers(hEnv, direction, description, len(description), ADDR(descriptionLength), None, 0, attributesLength) checkStatus(rc, hEnv=hEnv) if rc == SQL_NO_DATA: break drivers.append(description.value.decode("utf-8")) direction = SQL_FETCH_NEXT logger.info("Available drivers: {}".format(", ".join(drivers))) def initOdbcEnv(): """Initialize ODBC environment handle.""" global hEnv if hEnv is None: hEnv = SQLPOINTER() rc = odbc.SQLAllocHandle(SQL_HANDLE_ENV, SQL_NULL_HANDLE, ADDR(hEnv)) checkStatus(rc, hEnv=hEnv) atexit.register(cleanupOdbcEnv) atexit.register(cleanupConnections) # Set the ODBC environment's compatibility level to ODBC 3.0 rc = odbc.SQLSetEnvAttr(hEnv, SQL_ATTR_ODBC_VERSION, SQL_OV_ODBC3, 0) checkStatus(rc, hEnv=hEnv) def cleanupOdbcEnv(): """Cleanup ODBC environment handle.""" if hEnv: odbc.SQLFreeHandle(SQL_HANDLE_ENV, hEnv) def init(odbcLibPath=None): try: lock.acquire() initOdbcLibrary(odbcLibPath) initFunctionPrototypes() initOdbcEnv() initDriverList() finally: lock.release() def determineDriver(dbType, driver): retval = driver if driver is not None: if driver not in drivers: raise InterfaceError( "DRIVER_NOT_FOUND", "No driver found with name '{}'. " " Available drivers: {}".format(driver, ",".join(drivers))) else: matches = [] for driver in drivers: if dbType in driver: matches.append(driver) if not matches: raise InterfaceError( "DRIVER_NOT_FOUND", "No driver found for '{}'. " "Available drivers: {}".format(dbType, ",".join(drivers))) else: retval = matches[len(matches) - 1] if len(matches) > 1: logger.warning( "More than one driver found " "for '{}'. Using '{}'." " Specify the 'driver' option to " "select a specific driver.".format(dbType, retval)) return retval class OdbcConnection: """Represents a Connection to Teradata using ODBC.""" def __init__(self, dbType="Teradata", system=None, username=None, password=<PASSWORD>, autoCommit=False, transactionMode=None, queryBands=None, odbcLibPath=None, dataTypeConverter=datatypes.DefaultDataTypeConverter(), driver=None, **kwargs): """Creates an ODBC connection.""" self.hDbc = SQLPOINTER() self.cursorCount = 0 self.sessionno = 0 self.cursors = [] self.dbType = dbType self.converter = dataTypeConverter # Initialize connection handle init(odbcLibPath) # Build connect string extraParams = set(k.lower() for k in kwargs) connectParams = collections.OrderedDict() if "dsn" not in extraParams: connectParams["DRIVER"] = determineDriver(dbType, driver) if system: connectParams["DBCNAME"] = system if username: connectParams["UID"] = username if password: connectParams["PWD"] = password if transactionMode: connectParams["SESSIONMODE"] = "Teradata" \ if transactionMode == "TERA" else transactionMode connectParams.update(kwargs) connectString = u";".join(u"{}={}".format(key, value) for key, value in connectParams.items()) rc = odbc.SQLAllocHandle(SQL_HANDLE_DBC, hEnv, ADDR(self.hDbc)) checkStatus(rc, hEnv=hEnv, method="SQLAllocHandle") # Create connection logger.debug("Creating connection using ODBC ConnectString: %s", re.sub("PWD=.*?(;|$)", "PWD=XXX;", connectString)) try: lock.acquire() rc = odbc.SQLDriverConnectW(self.hDbc, 0, _inputStr(connectString), SQL_NTS, None, 0, None, 0) finally: lock.release() try: checkStatus(rc, hDbc=self.hDbc, method="SQLDriverConnectW") except: rc = odbc.SQLFreeHandle(SQL_HANDLE_DBC, self.hDbc) self.hDbc = None raise connections.append(self) # Setup autocommit, query bands, etc. try: logger.debug("Setting AUTOCOMMIT to %s", "True" if util.booleanValue(autoCommit) else "False") rc = odbc.SQLSetConnectAttr( self.hDbc, SQL_ATTR_AUTOCOMMIT, TRUE if util.booleanValue(autoCommit) else FALSE, 0) checkStatus( rc, hDbc=self.hDbc, method="SQLSetConnectAttr - SQL_ATTR_AUTOCOMMIT") if dbType == "Teradata": with self.cursor() as c: self.sessionno = c.execute( "SELECT SESSION", queryTimeout=QUERY_TIMEOUT).fetchone()[0] logger.debug("SELECT SESSION returned %s", self.sessionno) if queryBands: c.execute(u"SET QUERY_BAND = '{};' FOR SESSION".format( u";".join(u"{}={}".format(util.toUnicode(k), util.toUnicode(v)) for k, v in queryBands.items())), queryTimeout=QUERY_TIMEOUT) self.commit() logger.debug("Created session %s.", self.sessionno) except Exception: self.close() raise def close(self): """CLoses an ODBC Connection.""" if self.hDbc: if self.sessionno: logger.debug("Closing session %s...", self.sessionno) for cursor in list(self.cursors): cursor.close() rc = odbc.SQLDisconnect(self.hDbc) sqlState = checkStatus( rc, hDbc=self.hDbc, method="SQLDisconnect", ignore=[SQL_STATE_CONNECTION_NOT_OPEN, SQL_STATE_INVALID_TRANSACTION_STATE]) if SQL_STATE_INVALID_TRANSACTION_STATE in sqlState: logger.warning("Rolling back open transaction for session %s " "so it can be closed.", self.sessionno) rc = odbc.SQLEndTran(SQL_HANDLE_DBC, self.hDbc, SQL_ROLLBACK) checkStatus( rc, hDbc=self.hDbc, method="SQLEndTran - SQL_ROLLBACK - Disconnect") rc = odbc.SQLDisconnect(self.hDbc) checkStatus(rc, hDbc=self.hDbc, method="SQLDisconnect") rc = odbc.SQLFreeHandle(SQL_HANDLE_DBC, self.hDbc) if rc != SQL_INVALID_HANDLE: checkStatus(rc, hDbc=self.hDbc, method="SQLFreeHandle") connections.remove(self) self.hDbc = None if self.sessionno: logger.debug("Session %s closed.", self.sessionno) def commit(self): """Commits a transaction.""" logger.debug("Committing transaction...") rc = odbc.SQLEndTran(SQL_HANDLE_DBC, self.hDbc, SQL_COMMIT) checkStatus(rc, hDbc=self.hDbc, method="SQLEndTran - SQL_COMMIT") def rollback(self): """Rollsback a transaction.""" logger.debug("Rolling back transaction...") rc = odbc.SQLEndTran(SQL_HANDLE_DBC, self.hDbc, SQL_ROLLBACK) checkStatus(rc, hDbc=self.hDbc, method="SQLEndTran - SQL_ROLLBACK") def cursor(self): """Returns a cursor.""" cursor = OdbcCursor( self, self.dbType, self.converter, self.cursorCount) self.cursorCount += 1 return cursor def __del__(self): self.close() def __enter__(self): return self def __exit__(self, t, value, traceback): self.close() def __repr__(self): return "OdbcConnection(sessionno={})".format(self.sessionno) connect = OdbcConnection class OdbcCursor (util.Cursor): """Represents an ODBC Cursor.""" def __init__(self, connection, dbType, converter, num): util.Cursor.__init__(self, connection, dbType, converter) self.num = num self.moreResults = None if num > 0: logger.debug( "Creating cursor %s for session %s.", self.num, self.connection.sessionno) self.hStmt = SQLPOINTER() rc = odbc.SQLAllocHandle( SQL_HANDLE_STMT, connection.hDbc, ADDR(self.hStmt)) checkStatus(rc, hStmt=self.hStmt) connection.cursors.append(self) def callproc(self, procname, params, queryTimeout=0): self._checkClosed() query = "CALL {} (".format(procname) for i in range(0, len(params)): if i > 0: query += ", " query += "?" query += ")" logger.debug("Executing Procedure: %s", query) self.execute(query, params, queryTimeout=queryTimeout) return util.OutParams(params, self.dbType, self.converter) def close(self): if self.hStmt: if self.num > 0: logger.debug( "Closing cursor %s for session %s.", self.num, self.connection.sessionno) rc = odbc.SQLFreeHandle(SQL_HANDLE_STMT, self.hStmt) checkStatus(rc, hStmt=self.hStmt) self.connection.cursors.remove(self) self.hStmt = None def _setQueryTimeout(self, queryTimeout): rc = odbc.SQLSetStmtAttr( self.hStmt, SQL_ATTR_QUERY_TIMEOUT, SQLPOINTER(queryTimeout), SQL_IS_UINTEGER) checkStatus( rc, hStmt=self.hStmt, method="SQLSetStmtStmtAttr - SQL_ATTR_QUERY_TIMEOUT") def execute(self, query, params=None, queryTimeout=0): self._checkClosed() if params: self.executemany(query, [params, ], queryTimeout) else: if self.connection.sessionno: logger.debug( "Executing query on session %s using SQLExecDirectW: %s", self.connection.sessionno, query) self._free() self._setQueryTimeout(queryTimeout) rc = odbc.SQLExecDirectW( self.hStmt, _inputStr(_convertLineFeeds(query)), SQL_NTS) checkStatus(rc, hStmt=self.hStmt, method="SQLExecDirectW") self._handleResults() return self def executemany(self, query, params, batch=False, queryTimeout=0): self._checkClosed() self._free() # Prepare the query rc = odbc.SQLPrepareW( self.hStmt, _inputStr(_convertLineFeeds(query)), SQL_NTS) checkStatus(rc, hStmt=self.hStmt, method="SQLPrepare") self._setQueryTimeout(queryTimeout) # Get the number of parameters in the SQL statement. numParams = SQLSMALLINT() rc = odbc.SQLNumParams(self.hStmt, ADDR(numParams)) checkStatus(rc, hStmt=self.hStmt, method="SQLNumParams") numParams = numParams.value # The argument types. dataTypes = [] for paramNum in range(0, numParams): dataType = SQLSMALLINT() parameterSize = SQLULEN() decimalDigits = SQLSMALLINT() nullable = SQLSMALLINT() rc = odbc.SQLDescribeParam( self.hStmt, paramNum + 1, ADDR(dataType), ADDR(parameterSize), ADDR(decimalDigits), ADDR(nullable)) checkStatus(rc, hStmt=self.hStmt, method="SQLDescribeParams") dataTypes.append(dataType.value) if batch: logger.debug( "Executing query on session %s using batched SQLExecute: %s", self.connection.sessionno, query) self._executeManyBatch(params, numParams, dataTypes) else: logger.debug( "Executing query on session %s using SQLExecute: %s", self.connection.sessionno, query) rc = odbc.SQLSetStmtAttr(self.hStmt, SQL_ATTR_PARAMSET_SIZE, 1, 0) checkStatus(rc, hStmt=self.hStmt, method="SQLSetStmtAttr") paramSetNum = 0 for p in params: paramSetNum += 1 logger.trace("ParamSet %s: %s", paramSetNum, p) if len(p) != numParams: raise InterfaceError( "PARAMS_MISMATCH", "The number of supplied parameters " "({}) does not match the expected number of " "parameters ({}).".format(len(p), numParams)) paramArray = [] lengthArray = [] for paramNum in range(0, numParams): val = p[paramNum] inputOutputType = _getInputOutputType(val) valueType, paramType = _getParamValueType( dataTypes[paramNum]) param, length, null = _getParamValue(val, valueType, False) paramArray.append(param) if param is not None: if valueType == SQL_C_BINARY: bufSize = SQLLEN(length) lengthArray.append(SQLLEN(length)) columnSize = SQLULEN(length) elif valueType == SQL_C_DOUBLE: bufSize = SQLLEN(length) lengthArray.append(SQLLEN(length)) columnSize = SQLULEN(length) param = ADDR(param) else: bufSize = SQLLEN(ctypes.sizeof(param)) lengthArray.append(SQLLEN(SQL_NTS)) columnSize = SQLULEN(length) if null: # Handle INOUT parameter with NULL input value. lengthArray.pop(-1) lengthArray.append(SQLLEN(SQL_NULL_DATA)) else: bufSize = SQLLEN(0) columnSize = SQLULEN(0) lengthArray.append(SQLLEN(SQL_NULL_DATA)) logger.trace("Binding parameter %s...", paramNum + 1) rc = odbc.SQLBindParameter( self.hStmt, paramNum + 1, inputOutputType, valueType, paramType, columnSize, 0, param, bufSize, ADDR(lengthArray[paramNum])) checkStatus( rc, hStmt=self.hStmt, method="SQLBindParameter") logger.debug("Executing prepared statement.") rc = odbc.SQLExecute(self.hStmt) for paramNum in range(0, numParams): val = p[paramNum] if isinstance(val, OutParam): val.size = lengthArray[paramNum].value checkStatus(rc, hStmt=self.hStmt, method="SQLExecute") self._handleResults() return self def _executeManyBatch(self, params, numParams, dataTypes): # Get the number of parameter sets. paramSetSize = len(params) # Set the SQL_ATTR_PARAM_BIND_TYPE statement attribute to use # column-wise binding. rc = odbc.SQLSetStmtAttr( self.hStmt, SQL_ATTR_PARAM_BIND_TYPE, SQL_PARAM_BIND_BY_COLUMN, 0) checkStatus(rc, hStmt=self.hStmt, method="SQLSetStmtAttr") # Specify the number of elements in each parameter array. rc = odbc.SQLSetStmtAttr( self.hStmt, SQL_ATTR_PARAMSET_SIZE, paramSetSize, 0) checkStatus(rc, hStmt=self.hStmt, method="SQLSetStmtAttr") # Specify a PTR to get the number of parameters processed. # paramsProcessed = SQLULEN() # rc = odbc.SQLSetStmtAttr(self.hStmt, SQL_ATTR_PARAMS_PROCESSED_PTR, # ADDR(paramsProcessed), SQL_IS_POINTER) # checkStatus(rc, hStmt=self.hStmt, method="SQLSetStmtAttr") # Specify a PTR to get the status of the parameters processed. # paramsStatus = (SQLUSMALLINT * paramSetSize)() # rc = odbc.SQLSetStmtAttr(self.hStmt, SQL_ATTR_PARAM_STATUS_PTR, # ADDR(paramsStatus), SQL_IS_POINTER) # checkStatus(rc, hStmt=self.hStmt, method="SQLSetStmtAttr") # Bind the parameters. paramArrays = [] lengthArrays = [] paramSetSize = len(params) paramSetNum = 0 debugEnabled = logger.isEnabledFor(logging.DEBUG) for p in params: paramSetNum += 1 if debugEnabled: logger.debug("ParamSet %s: %s", paramSetNum, p) if len(p) != numParams: raise InterfaceError( "PARAMS_MISMATCH", "The number of supplied parameters " "({}) does not match the expected number of parameters " "({}).".format(len(p), numParams)) for paramNum in range(0, numParams): p = [] valueType, paramType = _getParamValueType(dataTypes[paramNum]) maxLen = 0 for paramSetNum in range(0, paramSetSize): param, length, null = _getParamValue( # @UnusedVariable params[paramSetNum][paramNum], valueType, True) if length > maxLen: maxLen = length p.append(param) if debugEnabled: logger.debug("Max length for parameter %s is %s.", paramNum + 1, maxLen) if valueType == SQL_C_BINARY: valueSize = SQLLEN(maxLen) paramArrays.append((SQLBYTE * (paramSetSize * maxLen))()) elif valueType == SQL_C_DOUBLE: valueSize = SQLLEN(maxLen) paramArrays.append((SQLDOUBLE * paramSetSize)()) else: maxLen += 1 valueSize = SQLLEN(ctypes.sizeof(SQLWCHAR) * maxLen) paramArrays.append(_createBuffer(paramSetSize * maxLen)) lengthArrays.append((SQLLEN * paramSetSize)()) for paramSetNum in range(0, paramSetSize): index = paramSetNum * maxLen if p[paramSetNum] is not None: if valueType == SQL_C_DOUBLE: paramArrays[paramNum][paramSetNum] = p[paramSetNum] else: for c in p[paramSetNum]: paramArrays[paramNum][index] = c index += 1 if valueType == SQL_C_BINARY: lengthArrays[paramNum][ paramSetNum] = len(p[paramSetNum]) else: lengthArrays[paramNum][ paramSetNum] = SQLLEN(SQL_NTS) paramArrays[paramNum][ index] = _convertParam("\x00")[0] else: lengthArrays[paramNum][paramSetNum] = SQLLEN(SQL_NULL_DATA) if valueType == SQL_C_WCHAR: paramArrays[paramNum][index] = _convertParam("\x00")[0] if debugEnabled: logger.debug("Binding parameter %s...", paramNum + 1) rc = odbc.SQLBindParameter(self.hStmt, paramNum + 1, SQL_PARAM_INPUT, valueType, paramType, SQLULEN(maxLen), 0, paramArrays[paramNum], valueSize, lengthArrays[paramNum]) checkStatus(rc, hStmt=self.hStmt, method="SQLBindParameter") # Execute the SQL statement. if debugEnabled: logger.debug("Executing prepared statement.") rc = odbc.SQLExecute(self.hStmt) checkStatus(rc, hStmt=self.hStmt, method="SQLExecute") def _handleResults(self): # Rest cursor attributes. self.description = None self.rowcount = -1 self.rownumber = None self.columns = {} self.types = [] self.moreResults = None # Get column count in result set. columnCount = SQLSMALLINT() rc = odbc.SQLNumResultCols(self.hStmt, ADDR(columnCount)) checkStatus(rc, hStmt=self.hStmt, method="SQLNumResultCols") rowCount = SQLLEN() rc = odbc.SQLRowCount(self.hStmt, ADDR(rowCount)) checkStatus(rc, hStmt=self.hStmt, method="SQLRowCount") self.rowcount = rowCount.value # Get column meta data and create row iterator. if columnCount.value > 0: self.description = [] nameBuf = _createBuffer(SMALL_BUFFER_SIZE) nameLength = SQLSMALLINT() dataType = SQLSMALLINT() columnSize = SQLULEN() decimalDigits = SQLSMALLINT() nullable = SQLSMALLINT() for col in range(0, columnCount.value): rc = odbc.SQLDescribeColW( self.hStmt, col + 1, nameBuf, len(nameBuf), ADDR(nameLength), ADDR(dataType), ADDR(columnSize), ADDR(decimalDigits), ADDR(nullable)) checkStatus(rc, hStmt=self.hStmt, method="SQLDescribeColW") columnName = _outputStr(nameBuf) odbc.SQLColAttributeW( self.hStmt, col + 1, SQL_DESC_TYPE_NAME, ADDR(nameBuf), len(nameBuf), None, None) checkStatus(rc, hStmt=self.hStmt, method="SQLColAttributeW") typeName = _outputStr(nameBuf) typeCode = self.converter.convertType(self.dbType, typeName) self.columns[columnName.lower()] = col self.types.append((typeName, typeCode, dataType.value)) self.description.append(( columnName, typeCode, None, columnSize.value, decimalDigits.value, None, nullable.value)) self.iterator = rowIterator(self) def nextset(self): self._checkClosed() if self.moreResults is None: self._checkForMoreResults() if self.moreResults: self._handleResults() return True def _checkForMoreResults(self): rc = odbc.SQLMoreResults(self.hStmt) checkStatus(rc, hStmt=self.hStmt, method="SQLMoreResults") self.moreResults = rc == SQL_SUCCESS or rc == SQL_SUCCESS_WITH_INFO return self.moreResults def _free(self): rc = odbc.SQLFreeStmt(self.hStmt, SQL_CLOSE) checkStatus(rc, hStmt=self.hStmt, method="SQLFreeStmt - SQL_CLOSE") rc = odbc.SQLFreeStmt(self.hStmt, SQL_RESET_PARAMS) checkStatus( rc, hStmt=self.hStmt, method="SQLFreeStmt - SQL_RESET_PARAMS") def _checkClosed(self): if not self.hStmt: raise InterfaceError("CURSOR_CLOSED", "Operations cannot be performed on a " "closed cursor.") def _convertLineFeeds(query): return "\r".join(util.linesplit(query)) def _getInputOutputType(val): inputOutputType = SQL_PARAM_INPUT if isinstance(val, InOutParam): inputOutputType = SQL_PARAM_INPUT_OUTPUT elif isinstance(val, OutParam): inputOutputType = SQL_PARAM_OUTPUT return inputOutputType def _getParamValueType(dataType): valueType = SQL_C_WCHAR paramType = SQL_WVARCHAR if dataType in (SQL_BINARY, SQL_VARBINARY, SQL_LONGVARBINARY): valueType = SQL_C_BINARY paramType = dataType elif dataType == SQL_WLONGVARCHAR: paramType = SQL_WLONGVARCHAR elif dataType in (SQL_FLOAT, SQL_DOUBLE, SQL_REAL): valueType = SQL_C_DOUBLE paramType = SQL_DOUBLE return valueType, paramType def _getParamBufferSize(val): return SMALL_BUFFER_SIZE if val.size is None else val.size def _getParamValue(val, valueType, batch): length = 0 null = False if val is None: param = None elif valueType == SQL_C_BINARY: ba = val if isinstance(val, InOutParam): ba = val.inValue if val.inValue is None: null = True ba = bytearray(_getParamBufferSize(val)) elif isinstance(val, OutParam): ba = bytearray(_getParamBufferSize(val)) if ba is not None and not isinstance(ba, bytearray): raise InterfaceError("Expected bytearray for BINARY parameter.") length = len(ba) if batch: param = ba else: byteArr = SQLBYTE * length param = byteArr.from_buffer(ba) if isinstance(val, OutParam): val.setValueFunc(lambda: ba[:val.size]) elif valueType == SQL_C_DOUBLE: f = val if isinstance(val, InOutParam): f = val.inValue if f is None: null = True f = float(0) elif isinstance(val, OutParam): f = float(0) param = SQLDOUBLE(f if not util.isString(f) else float(f)) length = ctypes.sizeof(param) if isinstance(val, OutParam): val.setValueFunc(lambda: param.value) else: if batch: param = _convertParam(val) length = len(param) elif isinstance(val, InOutParam): length = _getParamBufferSize(val) if val.inValue is not None: param = _inputStr(val.inValue, length) else: param = _createBuffer(length) null = True val.setValueFunc(lambda: _outputStr(param)) elif isinstance(val, OutParam): length = _getParamBufferSize(val) param = _createBuffer(length) val.setValueFunc(lambda: _outputStr(param)) else: param = _inputStr(val) length = len(param) return param, length, null def _getFetchSize(cursor): """Gets the fetch size associated with the cursor.""" fetchSize = cursor.fetchSize for dataType in cursor.types: if dataType[2] in (SQL_LONGVARBINARY, SQL_WLONGVARCHAR): fetchSize = 1 break return fetchSize def _getBufSize(cursor, colIndex): bufSize = cursor.description[colIndex - 1][3] + 1 dataType = cursor.types[colIndex - 1][0] if dataType in datatypes.BINARY_TYPES: pass elif dataType in datatypes.FLOAT_TYPES: bufSize = ctypes.sizeof(ctypes.c_double) elif dataType in datatypes.INT_TYPES: bufSize = 30 elif cursor.types[colIndex - 1][2] in (SQL_WCHAR, SQL_WVARCHAR, SQL_WLONGVARCHAR): pass elif dataType.startswith("DATE"): bufSize = 20 elif dataType.startswith("TIMESTAMP"): bufSize = 40 elif dataType.startswith("TIME"): bufSize = 30 elif dataType.startswith("INTERVAL"): bufSize = 80 elif dataType.startswith("PERIOD"): bufSize = 80 elif dataType.startswith("DECIMAL"): bufSize = 42 else: bufSize = 2 ** 16 + 1 return bufSize def _setupColumnBuffers(cursor, buffers, bufSizes, dataTypes, indicators, lastFetchSize): """Sets up the column buffers for retrieving multiple rows of a result set at a time""" fetchSize = _getFetchSize(cursor) # If the fetchSize hasn't changed since the last time setupBuffers # was called, then we can reuse the previous buffers. if fetchSize != lastFetchSize: logger.debug("FETCH_SIZE: %s" % fetchSize) rc = odbc.SQLSetStmtAttr( cursor.hStmt, SQL_ATTR_ROW_ARRAY_SIZE, fetchSize, 0) checkStatus(rc, hStmt=cursor.hStmt, method="SQLSetStmtAttr - SQL_ATTR_ROW_ARRAY_SIZE") for col in range(1, len(cursor.description) + 1): dataType = SQL_C_WCHAR buffer = None bufSize = _getBufSize(cursor, col) lob = False if cursor.types[col - 1][2] == SQL_LONGVARBINARY: lob = True bufSize = LARGE_BUFFER_SIZE buffer = (ctypes.c_byte * bufSize)() dataType = SQL_LONGVARBINARY elif cursor.types[col - 1][2] == SQL_WLONGVARCHAR: lob = True buffer = _createBuffer(LARGE_BUFFER_SIZE) bufSize = ctypes.sizeof(buffer) dataType = SQL_WLONGVARCHAR elif cursor.description[col - 1][1] == BINARY: dataType = SQL_C_BINARY buffer = (ctypes.c_byte * bufSize * fetchSize)() elif cursor.types[col - 1][0] in datatypes.FLOAT_TYPES: dataType = SQL_C_DOUBLE buffer = (ctypes.c_double * fetchSize)() else: buffer = _createBuffer(bufSize * fetchSize) bufSize = int(ctypes.sizeof(buffer) / fetchSize) dataTypes.append(dataType) buffers.append(buffer) bufSizes.append(bufSize) logger.debug("Buffer size for column %s: %s", col, bufSize) indicators.append((SQLLEN * fetchSize)()) if not lob: rc = odbc.SQLBindCol(cursor.hStmt, col, dataType, buffer, bufSize, indicators[col - 1]) checkStatus(rc, hStmt=cursor.hStmt, method="SQLBindCol") return fetchSize def _getLobData(cursor, colIndex, buf, binary): """ Get LOB Data """ length = SQLLEN() dataType = SQL_C_WCHAR bufSize = ctypes.sizeof(buf) if binary: dataType = SQL_C_BINARY rc = odbc.SQLGetData( cursor.hStmt, colIndex, dataType, buf, bufSize, ADDR(length)) sqlState = checkStatus(rc, hStmt=cursor.hStmt, method="SQLGetData") val = None if length.value != SQL_NULL_DATA: if SQL_STATE_DATA_TRUNCATED in sqlState: logger.debug( "Data truncated. Calling SQLGetData to get next part " "of data for column %s of size %s.", colIndex, length.value) if dataType == SQL_C_BINARY: val = bytearray(length.value) val[0:bufSize] = buf newBufSize = len(val) - bufSize newBuffer = (ctypes.c_byte * newBufSize).from_buffer( val, bufSize) rc = odbc.SQLGetData( cursor.hStmt, colIndex, dataType, newBuffer, newBufSize, ADDR(length)) checkStatus( rc, hStmt=cursor.hStmt, method="SQLGetData2") else: val = [_outputStr(buf), ] while SQL_STATE_DATA_TRUNCATED in sqlState: rc = odbc.SQLGetData( cursor.hStmt, colIndex, dataType, buf, bufSize, ADDR(length)) sqlState = checkStatus( rc, hStmt=cursor.hStmt, method="SQLGetData2") val.append(_outputStr(buf)) val = "".join(val) else: if dataType == SQL_C_BINARY: val = bytearray( (ctypes.c_byte * length.value).from_buffer(buf)) else: val = _outputStr(buf) return val def _getRow(cursor, buffers, bufSizes, dataTypes, indicators, rowIndex): """Reads a row of data from the fetched input buffers. If the column type is a BLOB or CLOB, then that data is obtained via calls to SQLGetData.""" row = [] for col in range(1, len(cursor.description) + 1): val = None buf = buffers[col - 1] bufSize = bufSizes[col - 1] dataType = dataTypes[col - 1] length = indicators[col - 1][rowIndex] if length != SQL_NULL_DATA: if dataType == SQL_C_BINARY: val = bytearray((ctypes.c_byte * length).from_buffer( buf, bufSize * rowIndex)) elif dataType == SQL_C_DOUBLE: val = ctypes.c_double.from_buffer(buf, bufSize * rowIndex).value elif dataType == SQL_WLONGVARCHAR: val = _getLobData(cursor, col, buf, False) elif dataType == SQL_LONGVARBINARY: val = _getLobData(cursor, col, buf, True) else: chLen = (int)(bufSize / ctypes.sizeof(SQLWCHAR)) chBuf = (SQLWCHAR * chLen) val = _outputStr(chBuf.from_buffer(buf, bufSize * rowIndex)) row.append(val) return row def rowIterator(cursor): buffers = [] bufSizes = [] dataTypes = [] indicators = [] rowCount = SQLULEN() lastFetchSize = None rc = odbc.SQLSetStmtAttr( cursor.hStmt, SQL_ATTR_ROWS_FETCHED_PTR, ADDR(rowCount), 0) checkStatus(rc, hStmt=cursor.hStmt, method="SQLSetStmtAttr - SQL_ATTR_ROWS_FETCHED_PTR") while cursor.description is not None: lastFetchSize = _setupColumnBuffers(cursor, buffers, bufSizes, dataTypes, indicators, lastFetchSize) rc = odbc.SQLFetch(cursor.hStmt) checkStatus(rc, hStmt=cursor.hStmt, method="SQLFetch") if rc == SQL_NO_DATA: break for rowIndex in range(0, rowCount.value): yield _getRow(cursor, buffers, bufSizes, dataTypes, indicators, rowIndex) if not cursor._checkForMoreResults(): cursor._free()
StarcoderdataPython
1727044
from pathlib import Path import vtk, qt, ctk, slicer from slicer.ScriptedLoadableModule import ScriptedLoadableModule, ScriptedLoadableModuleWidget from slicer.util import VTKObservationMixin from EPISURGBase import EPISURGBaseLogic # pylint: disable=import-error EPISURG_URL = 'https://s3-eu-west-1.amazonaws.com/pstorage-ucl-2748466690/26153588/EPISURG.zip' EPISURG_CHECKSUM = 'MD5:5ec5831a2c6fbfdc8489ba2910a6504b' class EPISURGBrowser(ScriptedLoadableModule): """Uses ScriptedLoadableModule base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def __init__(self, parent): super().__init__(parent) self.parent.title = "EPISURG Browser" self.parent.categories = ["EPISURG"] self.parent.dependencies = [] self.parent.helpText = """ This module can be used to download and visualize the <a href="https://doi.org/10.5522/04/9996158.v1">EPISURG dataset</a>. See more information in the <a href="https://github.com/fepegar/resseg-ijcars">paper repository</a>. """ self.parent.acknowledgementText = """This file was developed by <NAME> (University College London and King's College London). """ class EPISURGBrowserWidget(ScriptedLoadableModuleWidget, VTKObservationMixin): """Uses ScriptedLoadableModuleWidget base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def __init__(self, parent=None): """ Called when the user opens the module the first time and the widget is initialized. """ ScriptedLoadableModuleWidget.__init__(self, parent) VTKObservationMixin.__init__(self) # needed for parameter node observation self.logic = None self.subjects = None def setup(self): ScriptedLoadableModuleWidget.setup(self) self.logic = EPISURGBrowserLogic() self.makeGUI() slicer.episurgBrowser = self self.addObserver(slicer.mrmlScene, slicer.mrmlScene.StartCloseEvent, self.onSceneStartClose) def makeGUI(self): self.setDirButton = ctk.ctkCollapsibleButton() self.setDirButton.text = 'Select dataset directory' setDirLayout = qt.QFormLayout(self.setDirButton) self.layout.addWidget(self.setDirButton) self.datasetDirEdit = ctk.ctkPathLineEdit() self.datasetDirEdit.filters = ctk.ctkPathLineEdit.Dirs setDirLayout.addRow('EPISURG directory: ', self.datasetDirEdit) self.datasetDirButton = qt.QPushButton('Load subjects') self.datasetDirButton.clicked.connect(self.onLoadSubjectsButton) setDirLayout.addWidget(self.datasetDirButton) self.downloadDatasetButton = qt.QPushButton('Download dataset') self.downloadDatasetButton.clicked.connect(self.onDownloadDatasetButton) setDirLayout.addWidget(self.downloadDatasetButton) self.subjectsButton = ctk.ctkCollapsibleButton() self.subjectsButton.text = 'Select subject to load' self.subjectsButton.setEnabled(False) subjectsLayout = qt.QFormLayout(self.subjectsButton) self.layout.addWidget(self.subjectsButton) self.subjectsComboBox = qt.QComboBox() self.subjectsComboBox.addItem('Select subject ID') self.subjectsComboBox.currentIndexChanged.connect(self.onSubjectsComboBox) subjectsLayout.addWidget(self.subjectsComboBox) self.previousSubjectPushButton = qt.QPushButton('Previous') self.previousSubjectPushButton.clicked.connect(self.onPreviousSubjectButton) subjectsLayout.addWidget(self.previousSubjectPushButton) self.nextSubjectPushButton = qt.QPushButton('Next') self.nextSubjectPushButton.clicked.connect(self.onNextSubjectButton) subjectsLayout.addWidget(self.nextSubjectPushButton) self.layout.addStretch() def getCurrentPath(self): text = self.datasetDirEdit.currentPath if not text: slicer.util.errorDisplay( f'Please enter a directory in the widget') raise return Path(text).expanduser().absolute() def getSubjectsDict(self): datasetDir = self.getCurrentPath() if not datasetDir.is_dir(): slicer.util.errorDisplay(f'{datasetDir} is not a directory') raise subjectsDir = datasetDir / 'subjects' if not subjectsDir.is_dir(): slicer.util.errorDisplay(f'"subjects" directory not found in EPISURG directory "{datasetDir}"') raise pattern = 'sub-*' subjectsDirs = sorted(list(subjectsDir.glob(pattern))) if not subjectsDirs: slicer.util.errorDisplay(f'No directories found in {subjectsDir} with pattern {pattern}') raise subjectsDict = { d.name: Subject(d) for d in subjectsDirs } return subjectsDict def cleanupSubjects(self): for subject in self.subjects.values(): subject.cleanup() def cleanup(self): """Called when the application closes and the module widget is destroyed.""" self.removeObservers() # Slots def onLoadSubjectsButton(self): self.datasetDirEdit.addCurrentPathToHistory() self.subjects = self.getSubjectsDict() self.subjectsComboBox.blockSignals(True) self.subjectsComboBox.addItems(list(self.subjects.keys())) self.subjectsComboBox.setCurrentIndex(0) self.subjectsComboBox.blockSignals(False) self.setDirButton.setEnabled(False) self.subjectsButton.setEnabled(True) def onDownloadDatasetButton(self): episurgDir = self.getCurrentPath() subjectsDir = episurgDir / 'subjects' if not subjectsDir.is_dir(): outputDir = episurgDir.parent outputDir.mkdir(exist_ok=True, parents=True) archiveFilePath = outputDir / 'episurg.zip' try: qt.QApplication.setOverrideCursor(qt.Qt.WaitCursor) success = slicer.util.downloadAndExtractArchive( EPISURG_URL, str(archiveFilePath), str(outputDir), checksum=EPISURG_CHECKSUM, ) if success: archiveFilePath.unlink() else: slicer.util.errorDisplay('Error downloading the dataset') except Exception as e: slicer.util.errorDisplay(str(e)) finally: qt.QApplication.restoreOverrideCursor() self.onLoadSubjectsButton() def onSceneStartClose(self, caller, event): """Called just before the scene is closed.""" self.cleanupSubjects() def onPreviousSubjectButton(self): self.subjectsComboBox.currentIndex -= 1 def onNextSubjectButton(self): self.subjectsComboBox.currentIndex += 1 def onSubjectsComboBox(self): try: subject = self.subjects[self.subjectsComboBox.currentText] except KeyError: return try: self.cleanupSubjects() self.logic.closeScene() subject.load() self.logic.jumpToFirstSegment(subject.rater1SegNode) except Exception as e: slicer.util.errorDisplay(f'Failed to load subject: {e}') import traceback traceback.print_exc() class EPISURGBrowserLogic(EPISURGBaseLogic): def __init__(self): super().__init__() class Subject: RED = 222, 53, 7 GREEN = 116, 191, 23 BLUE = 24, 80, 201 def __init__(self, subjectDir): self.dir = Path(subjectDir) self.id = self.dir.name self.t1PrePath = self.dir / 'preop' / f'{self.id}_preop-t1mri-1.nii.gz' self.t1PostDir = self.dir / 'postop' self.t1PostPath = self.t1PostDir / f'{self.id}_postop-t1mri-1.nii.gz' self.rater1SegPath = self.t1PostDir / f'{self.id}_postop-seg-1.nii.gz' self.rater2SegPath = self.t1PostDir / f'{self.id}_postop-seg-2.nii.gz' self.rater3SegPath = self.t1PostDir / f'{self.id}_postop-seg-3.nii.gz' self.cleanup() def __repr__(self): return f'Subject("{self.id}")' def cleanup(self): self.t1PreNode = None self.t1PostNode = None self.rater1SegNode = None self.rater2SegNode = None self.rater3SegNode = None def loadVolumeIfPresent(self, path): if not path.is_file(): return return slicer.util.loadVolume(str(path)) def loadSegmentationIfPresent(self, path): if not path.is_file(): return segmentationNode = slicer.util.loadSegmentation(str(path)) segmentation = segmentationNode.GetSegmentation() rule = slicer.vtkBinaryLabelmapToClosedSurfaceConversionRule segmentation.SetConversionParameter(rule.GetSmoothingFactorParameterName(), "0.2") segmentationNode.CreateClosedSurfaceRepresentation() displayNode = segmentationNode.GetDisplayNode() displayNode.SetVisibility2DFill(False) displayNode.SetAllSegmentsVisibility(True) displayNode.SetOpacity(0.75) return segmentationNode def load(self): self.t1PreNode = self.loadVolumeIfPresent(self.t1PrePath) self.t1PostNode = self.loadVolumeIfPresent(self.t1PostPath) self.rater1SegNode = self.loadSegmentationIfPresent(self.rater1SegPath) self.rater2SegNode = self.loadSegmentationIfPresent(self.rater2SegPath) self.rater3SegNode = self.loadSegmentationIfPresent(self.rater3SegPath) self.show() def show(self): slicer.util.setSliceViewerLayers(background=self.t1PostNode, foreground=self.t1PreNode) self.showSegment(self.rater1SegNode, self.GREEN) self.showSegment(self.rater2SegNode, self.BLUE) self.showSegment(self.rater3SegNode, self.RED) def showSegment(self, segmentationNode, color): if segmentationNode is None: return color = [c / 255 for c in color] segment = segmentationNode.GetSegmentation().GetSegment('Segment_1') segment.SetName('Resection cavity') segment.SetColor(color)
StarcoderdataPython
11280173
<filename>app_sme12/forms.py from django import forms from django.forms import ModelForm from app_backend.models import Province, Amphur, Tumbol, BusinessModel, BusinessGroup, BusinessType from app_sme12.models import Employment, Revenue, AuthorizeCapital, ProfitPrevious, Promote, FormSiteVisit, FormInterview class RegistrationForm(forms.Form): """ ฟอร์มลงทะเบียนประกวด sme ครั้งที่ 12 """ regis_code = forms.CharField(label='เลขสมัคร', max_length=20) ent_name = forms.CharField(label='ชื่อสถานประกอบการ', max_length=200) ent_establish_date = forms.DateField(label='วันที่จัดตั้งกิจการ') ent_sme_code = forms.CharField( label='รหัสสมาชิก สสว.', max_length=50, required=False) ent_sme_connext_code = forms.CharField( label='รหัสสมาชิก SME CONNEXT', max_length=50, required=False) ent_address_no = forms.CharField(label='เลขที่', max_length=100) ent_mu = forms.CharField(label='หมู่', max_length=100, required=False) ent_soi = forms.CharField(label='ซอย', max_length=100, required=False) ent_street = forms.CharField(label='ถนน', max_length=100, required=False) ent_province = forms.ModelChoiceField( label='จังหวัด', queryset=Province.objects.all(), empty_label='-- โปรดเลือก --') ent_amphur = forms.ModelChoiceField( label='อำเภอ', queryset=Amphur.objects.all(), empty_label='-- โปรดเลือก --') ent_tumbol = forms.ModelChoiceField(label='ตำบล', queryset=Tumbol.objects.all( ), empty_label='---------', required=False) ent_postcode = forms.CharField(label='รหัสไปรษณีย์', max_length=200) ent_tel = forms.CharField(label='โทรศัพท์', max_length=200) ent_fax = forms.CharField(label='โทรสาร', max_length=200, required=False) ent_email = forms.EmailField(label='อีเมล') ent_website = forms.CharField( label='เว็บไซต์', max_length=200, required=False) owner_name = forms.CharField(label='ชื่อ-นามสกุล', max_length=200) owner_card_id = forms.CharField( label='เลขที่บัตรประจำตัวประชาชน', max_length=200) owner_address_no = forms.CharField(label='เลขที่', max_length=100) owner_mu = forms.CharField(label='หมู่', max_length=100, required=False) owner_soi = forms.CharField(label='ซอย', max_length=100, required=False) owner_street = forms.CharField(label='ถนน', max_length=100, required=False) owner_province = forms.ModelChoiceField( label='จังหวัด', queryset=Province.objects.all(), empty_label='-- โปรดเลือก --') owner_amphur = forms.ModelChoiceField( label='อำเภอ', queryset=Amphur.objects.all(), empty_label='-- โปรดเลือก --') owner_tumbol = forms.ModelChoiceField( label='ตำบล', queryset=Tumbol.objects.all(), empty_label='---------', required=False) owner_postcode = forms.CharField(label='รหัสไปรษณีย์', max_length=200) owner_tel = forms.CharField(label='โทรศัพท์', max_length=200) owner_fax = forms.CharField(label='โทรสาร', max_length=200, required=False) owner_mobile = forms.CharField(label='โทรศัพท์มือถือ', max_length=200) owner_email = forms.EmailField(label='อีเมล') business_model = forms.ModelChoiceField(label='รูปแบบการจัดตั้งกิจการ', queryset=BusinessModel.objects.all( ).order_by('model_group'), empty_label='-- โปรดเลือก --', required=False) bus_model_etc1 = forms.CharField( label='นิติบุลคลอื่นๆ', max_length=200, required=False) bus_model_etc2 = forms.CharField( label='ได้รับการจดทะเบียนอื่นๆ', max_length=200, required=False) juristic_id = forms.CharField( label='เลขทะเบียนนิติบุคคล', max_length=20, required=False) card_id = forms.CharField( label='เลขที่บัตรประชาชน', max_length=20, required=False) commercial_regis_number = forms.CharField( label='เลขทะเบียนพาณิชย์', max_length=20, required=False) regis_number = forms.CharField( label='เลขทะเบียน', max_length=20, required=False) contact_name = forms.CharField(label='ชื่อ-นามสกุล', max_length=100) contact_position = forms.CharField(label='ตำแหน่ง', max_length=100) contact_tel = forms.CharField(label='โทรศัพท์มือถือ', max_length=30) contact_email = forms.EmailField(label='อีเมล') business_type = forms.ModelChoiceField( label='ประเภทกิจการ', queryset=BusinessType.objects.all(), empty_label='-- โปรดเลือก --') business_group = forms.ModelChoiceField( label='ประเภทกลุ่มธุรกิจ', queryset=BusinessGroup.objects.all(), empty_label='-- โปรดเลือก --') # business_group_etc = forms.CharField(label='กลุ่มธุรกิจอื่นๆ', max_length=100, required=False) product_info = forms.CharField( label='ระบุสินค้า ยี่ห้อ และบริการโดยละเอียด', widget=forms.Textarea, required=False) material = forms.CharField( label='วัตถุดิบในการผลิต', widget=forms.Textarea, required=False) otop = forms.BooleanField( label='มีการผลิตสินค้า OTOP หรือไม่', required=False) f_employment = forms.ModelChoiceField( label='การจ้างงาน', queryset=Employment.objects.all(), empty_label='-- โปรดเลือก --') f_employment_etc = forms.CharField( label='จำนวนจ้าง(คน)', max_length=10, required=False) f_revenue = forms.ModelChoiceField( label='รายได้ต่อปี', queryset=Revenue.objects.all(), empty_label='-- โปรดเลือก --') f_revenue_etc = forms.CharField( label='รายได้(บาท)', max_length=20, required=False) f_cap = forms.ModelChoiceField(label='ทุนจดทะเบียน', queryset=AuthorizeCapital.objects.all( ).order_by('code'), empty_label='-- โปรดเลือก --') f_profit = forms.ModelChoiceField(label='กำไร(ณ สิ้นปีก่อนหน้า)', queryset=ProfitPrevious.objects.all( ).order_by('code'), empty_label='-- โปรดเลือก --') f_promote = forms.ModelMultipleChoiceField( label='รับข่าวสารจากช่องทาง', queryset=Promote.objects.filter(active=True)) f_promote_etc = forms.CharField( label='รับข่าวสารจากช่องทางอื่นๆ', max_length=100, required=False) # f_join_choice = forms.IntegerField(label='เลือกอบรมหรือประกวด', required=False) # f_training_course = forms.CharField(label='หลักสูตรอบรม', max_length=100, required=False) # f_trainee1_name = forms.CharField(label='ชื่อผู้เข้าอบรมคนที่1', max_length=100, required=False) # f_trainee1_id_card = forms.CharField(label='เลขบัตรประชาชนผู้เข้าอบรมคนที่1', max_length=100, required=False) # f_trainee1_mobile = forms.CharField(label='เบอร์มิอถือผู้เข้าอบรมคนที่1', max_length=100, required=False) # f_trainee1_email = forms.EmailField(label='อีเมลผู้เข้าอบรมคนที่1', required=False) # f_trainee2_name = forms.CharField(label='ชื่อผู้เข้าอบรมคนที่2', max_length=100, required=False) # f_trainee2_id_card = forms.CharField(label='เลขบัตรประชาชนผู้เข้าอบรมคนที่2', max_length=100, required=False) # f_trainee2_mobile = forms.CharField(label='เบอร์มิอถือผู้เข้าอบรมคนที่2', max_length=100, required=False) # f_trainee2_email = forms.EmailField(label='อีเมลผู้เข้าอบรมคนที่2', required=False) # f_agreement = forms.BooleanField(label='ยินยอมข้อตกลง', required=False) # f_tsic_no = forms.CharField(label='เลข tsic', max_length=20, required=False) class SitevisitForm(ModelForm): """ ฟอร์มให้คะแนนสถานประกอบการ Site visit """ class Meta: model = FormSiteVisit fields = '__all__' class InterviewForm(ModelForm): """ ฟอร์มให้คะแนนสถานประกอบการ สัมภาษณ์ """ class Meta: model = FormInterview fields = '__all__'
StarcoderdataPython
172541
"""Initialize cms app""" default_app_config = "cms.apps.CMSConfig"
StarcoderdataPython
143662
<filename>PSCP/analysis-scripts/tossconfigurationsFunc.py # -*- coding: utf-8 -*- """ Created on Tue Jul 7 10:17:49 2015 @author: nps5kd """ from __future__ import print_function import sys import optparse import numpy as np import math import matplotlib # for making plots, version 'matplotlib-1.1.0-1'; errors may pop up when using earlier versions import matplotlib.pyplot as plt import matplotlib.cm as cm from matplotlib.font_manager import FontProperties as FP import pdb def readgro(filename, na, nm, nam): # Read in atom coordinate data (starts on 3rd line of the .gro file) # acoordA and acoordB are the atom coordinates for polymorphs A and B file = open(filename, 'r') lines = file.readlines() #lines = filter(None, (line.rstrip() for line in file)) file.close() ngro = (len(lines)) / (na + 3) line = 2 boxv = np.zeros([3, ngro]) acoord = np.zeros((ngro, nm, 3, nam)) for gro in range(int(ngro)): mol = 0 while mol < nm: acounter = 0 while acounter < nam: acoord[gro, mol, 0, acounter] = float(lines[line].split()[3]) acoord[gro, mol, 1, acounter] = float(lines[line].split()[4]) acoord[gro, mol, 2, acounter] = float(lines[line].split()[5]) line += 1 acounter += 1 mol += 1 boxv[:, gro] = np.array(lines[line].split()).astype(np.float) line += 3 return acoord, boxv, ngro def find_centroids(acoord, ngro, boxv, nm): # ==================================================================== # Calculate the centroid and idealized centroid of each molecule # ==================================================================== all_centroids = np.zeros([ngro, nm, 3, 1]) ideal_centroids = np.zeros([nm, 3, 1]) for mol in range(int(nm)): for gro in range(int(ngro)): all_centroids[gro, mol, :, 0] = np.average(acoord[gro, mol, :, :], axis=1) centroids = np.average(all_centroids, axis=0) # for now, we start with centroids are the averages over all molecules (i.e. the centroids) for mol in range(int(nm)): ideal_centroids[mol, :, 0] = centroids[mol, :, 0].copy() return all_centroids, ideal_centroids def rmscalc(coord, coordPrime, gronum, nm, nam): # Quantify error of mapping (least root mean square) diff = np.zeros((nm, 3, nam)) lrms = np.zeros((nm, nam)) for mol in range(int(nm)): for mole in range(int(nam)): for co in range(3): diff[mol, co, mole] = abs(coord[gronum, mol, co, mole] - coordPrime[gronum, mol, co, mole]) for mol in range(int(nm)): for mole in range(int(nam)): lrms[mol, mole] = math.sqrt(diff[mol, 0, mole] ** 2 + diff[mol, 1, mole] ** 2 + diff[mol, 2, mole] ** 2) return lrms def writegrofile(output, lines, numframe, nm, nam, coord, boxv): outgrofile = open(output, 'w') # Write output .gro file # tacount is the total atom count # mcount is the total molecule count x = np.zeros(3) na = nm * nam molname = 'BNZ' for gro in range(int(numframe)): # outgrofile.write('Converted from ' + sys.argv[1] + ' by ' + sys.argv[2]+', molecule ' + str(gro) + '\n') outgrofile.write('Frame number' + str(gro) + '\n') outgrofile.write(' ' + str(na) + '\n') tacount = 0 mcount = 0 for mol in range(int(nm)): for atom in range(int(nam)): # mcount is the current molecule tracker mcount = mol + 1 tacount += 1 xstr = [] for d in range(3): # x[d] = round(acoordBprime[mol,d,atom],8) x[d] = round(coord[gro, mol, d, atom], 8) xstr.append("%13.8f" % (x[d])) line = str(mcount).rjust(5) + molname + lines[tacount + 1].split()[1].rjust(7) + \ str(tacount).rjust(5) + xstr[0] + xstr[1] + xstr[2] + '\n' outgrofile.write(line) boxvline = '' for d in range(len(boxv)): bline = ("%13.8f" % (round(boxv[d], 8))) boxvline += bline outgrofile.write(boxvline+'\n') # make sure the .gro ends on a newline outgrofile.close() def normalcompare(gro1, gro2): angle = np.zeros([4, ]) for x in range(4): C11 = gro1[x, :, 0] C31 = gro1[x, :, 4] C51 = gro1[x, :, 8] C12 = gro2[x, :, 0] C32 = gro2[x, :, 4] C52 = gro2[x, :, 8] A13 = C31 - C11 A15 = C51 - C11 B13 = C32 - C12 B15 = C52 - C12 gro1vect = np.cross(A13, A15) gro2vect = np.cross(B13, B15) gro1vectnorm = np.linalg.norm(gro1vect) gro2vectnorm = np.linalg.norm(gro2vect) cost = np.dot(gro1vect, gro2vect) / (gro1vectnorm * gro2vectnorm) angle[x] = np.arccos(cost) maxangle = angle return maxangle # MAIN BODY def tossconfigs(inputname, outputname, restraint): file = open(inputname, 'r') lines = file.readlines() #lines = filter(None, (line.rstrip() for line in file)) file.close() nam = 12 nm = 72 # Read in the total number of atoms in the system (should be the only item on the second line of the .gro file) print(lines[1]) if len(lines[1].split()) == 1: # na is the number of total atoms na = int(lines[1].split()[0]) # nm is the number of total molecules nm = na / nam else: sys.exit('Unexpected .gro file format') coord, boxv, ngro = readgro(inputname, na, nm, nam) coord2, boxv, ngro2 = readgro(restraint, na, nm, nam) cshape = np.shape(coord) icoord = np.zeros(cshape) for x in range(0, ngro): icoord[x, :, :, :] = coord2[0, :, :, :] #todel1= [] todel2 = [] allcent, idealcent = find_centroids(coord, ngro, boxv, nm) for x in range(ngro): for mol in range(nam): coord[x, :, :, mol] = coord[x, :, :, mol] - allcent[x, :, :, 0] icoord[x, :, :, mol] = icoord[x, :, :, mol] - allcent[0, :, :, 0] maxangles = np.zeros([ngro, 4]) for x in range(ngro): maxangles[x, :] = normalcompare(coord[x, :, :, :], icoord[x, :, :, :]) * (180 / np.pi) """ fig=plt.figure(0) plt.hist(maxangles[:ngro,0],40,alpha=0.3) plt.show() pdb.set_trace() plt.hist(maxangles[:ngro,1],40,alpha=0.3) plt.show() pdb.set_trace() plt.hist(maxangles[:ngro,2],40,alpha=0.3) plt.show() pdb.set_trace() plt.hist(maxangles[:ngro,3],40,alpha=0.3) plt.show() """ for x in range(ngro): for y in range(4): if maxangles[x, y] < 135 and maxangles[x, y] > 45: if x not in todel2: todel2 = np.append(todel2, x) for x in range(ngro): for mol in range(nam): coord[x, :, :, mol] = coord[x, :, :, mol] + allcent[x, :, :, 0] icoord[x, :, :, mol] = icoord[x, :, :, mol] + allcent[0, :, :, 0] newgro = np.delete(coord, todel2, 0) frames = np.shape(newgro)[0] writegrofile(outputname, lines, frames, nm, nam, newgro, boxv) print(todel2) return todel2
StarcoderdataPython
8110247
<filename>directives.py # Define a new directive `code-block` (aliased as `sourcecode`) that uses the # `pygments` source highlighter to render code in color. # # Incorporates code from the `Pygments`_ documentation for `Using Pygments in # ReST documents`_ and `Octopress`_. # # .. _Pygments: http://pygments.org/ # .. _Using Pygments in ReST documents: http://pygments.org/docs/rstdirective/ # .. _Octopress: http://octopress.org/ from pygments.lexers import get_lexer_by_name, TextLexer from pygments import highlight from docutils.parsers.rst import directives, Directive from docutils import nodes from pygments.formatters import HtmlFormatter import re import os import hashlib import __main__ # Absolute path to pygments cache dir PYGMENTS_CACHE_DIR = os.path.abspath(os.path.join( os.path.dirname(__main__.__file__), '../../.pygments-cache')) # Ensure cache dir exists if not os.path.exists(PYGMENTS_CACHE_DIR): os.makedirs(PYGMENTS_CACHE_DIR) class Pygments(Directive): """ Source code syntax hightlighting. """ required_arguments = 1 optional_arguments = 0 final_argument_whitespace = True string_opts = ['title', 'url', 'caption'] option_spec = dict([(key, directives.unchanged) for key in string_opts]) has_content = True def run(self): self.assert_has_content() try: lexer_name = self.arguments[0] lexer = get_lexer_by_name(lexer_name) except ValueError: # no lexer found - use the text one instead of an exception lexer_name = 'text' lexer = TextLexer() formatter = HtmlFormatter() # Construct cache filename cache_file = None content_text = u'\n'.join(self.content).encode('utf-8') cache_file_name = '%s-%s.html' % (lexer_name, hashlib.md5(content_text).hexdigest()) cached_path = os.path.join(PYGMENTS_CACHE_DIR, cache_file_name) # Look for cached version, otherwise parse if os.path.exists(cached_path): cache_file = open(cached_path, 'r', encoding='utf-8') parsed = cache_file.read() else: parsed = highlight(content_text, lexer, formatter) # Strip pre tag and everything outside it pres = re.compile("<pre>(.+)<\/pre>", re.S) stripped = pres.search(parsed).group(1) # Add wrapper with optional caption and link code = '<figure class="code">' if self.options: caption = ('<span>%s</span>' % self.options['caption']) if 'caption' in self.options else '' title = self.options['title'] if 'title' in self.options else 'link' link = ('<a href="%s">%s</a>' % (self.options['url'], title)) if 'url' in self.options else '' if caption or link: code += '<figcaption>%s %s</figcaption>' % (caption, link) code += f'<pre class="hll">{stripped}</pre></figure>' # Write cache if cache_file is None: cache_file = open(cached_path, 'w', encoding='utf-8') cache_file.write(parsed) cache_file.close() return [nodes.raw('', code, format='html')] directives.register_directive('code-block', Pygments) directives.register_directive('sourcecode', Pygments)
StarcoderdataPython
4895142
<gh_stars>0 import re import numpy as np import networkx as nx from shapely.geometry.polygon import LinearRing import drawSvg as draw #some helper functions def normal_length1(vector, side): """Normal vector which points usually outside of the molecule""" unit_vector = vector/np.linalg.norm(vector) unit_normal = np.array([-1*side*unit_vector[1], side*unit_vector[0]]) return unit_normal def calc_degree(vector1, vector2): """Formula for calculating cosA between to vectors""" cos_alpha = np.dot(vector1, vector2)/(np.linalg.norm(vector1)*np.linalg.norm(vector2)) degree = np.arccos(cos_alpha)*180/np.pi return degree def deg_to_rad(deg): return deg*np.pi/180 #all other main functions def comprehend_string(string, orient): """ string: kernel string orient: on default 1 which is clockwise orientation, but -1 is accepted as ccw Cuts up kernel string with a regex and saves the info into an array. Orientation is saved for each domain. By checking which bracket is paired with which, we save pairedness into a dictionary. A list of list is created which will hold the domain types and will be filled in later. """ #separate domains/count pattern = re.compile('@?-?[0-9]* ?[a-z|A-Z|0-9|\*|\)]+[ \(]? ?\+?|\) ?\+?') dom_raw_list = pattern.findall(string) dom_count = len(dom_raw_list) #create empty data structures struct_info_array = np.zeros((dom_count, 2), dtype = 'int') #3 cols rn, sb not needed here #empty angles indicated by -999 for row in range(dom_count): struct_info_array[row, 0] = -999 struct_info_array[row, 1] = orient name_list1 = [] #loop through the raw domains, extract for dom_i in range(len(dom_raw_list)): dom = dom_raw_list[dom_i] dom = dom.strip() #fill table if re.search("\s", dom): dom_parts = re.split("\s", dom) for segm in dom_parts: if segm[0] == "@": #col0 angle segm = segm.lstrip("@") struct_info_array[dom_i, 0] = int(segm) #col0 to write to #struct_info_array[dom_i, 1] = np.sign(int(segm)) #col1 to write to #elif segm is "+": #col2 strand break # struct_info_array[dom_i, 2] = 1 #col2 to write to elif segm != "+": #else: name_list1.append(segm) #only keep the name part further else: name_list1.append(dom) #pairedness dictionary paired_dict = {} for dom_i2 in range(len(dom_raw_list)): if re.search("\(", dom_raw_list[dom_i2]): bracket_count = 1 for next_dom in range(dom_i2 + 1, len(dom_raw_list)): if re.search("\(", dom_raw_list[next_dom]): bracket_count += 1 elif re.search("\)", dom_raw_list[next_dom]): bracket_count -= 1 if bracket_count == 0: paired_dict[dom_i2] = next_dom break #name list of list / finding hairpin loops #paireds in dict, hairpin loop known, other are unpaired -> substructure from these? name_final_lol = [] for dom_i3 in range(len(name_list1)): #paireds if re.search("\(", name_list1[dom_i3]): typ = "paired" name = name_list1[dom_i3].strip("(+ ") #correcting closing bracket name elif re.search("\)", name_list1[dom_i3]): typ = "paired" index_of_pair = list(paired_dict.keys())[list(paired_dict.values()).index(dom_i3)] if re.search("\*", name_list1[index_of_pair]): name = name_list1[index_of_pair].strip("\(").strip("\*") else: name = name_list1[index_of_pair].strip("\(") + "*" #all other are unpaireds else: typ = "unpaired" name = name_list1[dom_i3].strip("+ ") name_final_lol.append([name, typ]) return dom_raw_list, struct_info_array, paired_dict, name_final_lol def process_length_input(struct_info_array, length_input_dict): """ struct_info_array: from comprehend_string length_input_dict: a dictionary, keys are domain indices, values are lengths Create a new column for struct_array, where lengths are going to be stored. """ zeros_list = [0 for i in range(len(struct_info_array[:,1]))] #put into list format and append list to struct_info_array as new col for length in length_input_dict: zeros_list[length] = length_input_dict[length] zeros_list = np.array(zeros_list).reshape((len(zeros_list), 1)) struct_info_array = np.append(struct_info_array, zeros_list, axis=1) return struct_info_array def create_skeleton(dom_raw_list, paired_dict, name_final_lol): #append edges to graph G = nx.Graph() for dom_to_dom in range(len(name_final_lol)-1): if re.search("\+", dom_raw_list[dom_to_dom]) == None: G.add_edge(dom_to_dom, dom_to_dom+1, color='r') #domains that have a connection point are conn. with red edge for pair in paired_dict: G.add_edge(pair, paired_dict[pair], color='g') #paired domains are connected with green edge return G def find_type_of_unpaired(G, paired_dict, name_final_lol): #index of ununpaireds - these don't need to be checked paired_node_list = [] for node in paired_dict: paired_node_list.append(node) paired_node_list.append(paired_dict[node]) #get unpaired too unpaired_node_list = [] for node_index in range(len(name_final_lol)): if node_index not in paired_node_list: unpaired_node_list.append(node_index) #cycles of the skeleton graph cycle_list_G = nx.cycle_basis(G) #neat! multiloop_list = [] #look through cycles, where 3cycles are hairpin, 5c. are bulge and longer ones nest multiloops for cycle in cycle_list_G: if len(cycle) == 3: #always hairpin for item in cycle: if item in unpaired_node_list: name_final_lol[item][1] = "hairpin loop" #name altering unpaired_node_list.remove(item) #trim unpaired list from known items elif len(cycle) > 3 & len(cycle) % 2 == 1: #current bulge def unpaired_here = [] for item in cycle: if item in unpaired_node_list: unpaired_here.append(item) if len(unpaired_here) == 1: name_final_lol[unpaired_here[0]][1] = "bulgeloop" #name altering unpaired_node_list.remove(unpaired_here[0]) #trim unpaired list from known items #find multiloops, the corresponding domains are their own list item in multiloop_list if len(cycle) >= 6: curr_multiloop = [] for index in range(len(cycle)): if cycle[index] in unpaired_node_list: if cycle[index-3] in unpaired_node_list : connections = [n for n in G.edges.data(nbunch=cycle[index-1])] for edge in connections: #only need to check paired edge between these2 if edge[1] == cycle[index-2] and edge[2]['color'] == 'g': name_final_lol[cycle[index-3]][1] = "multiloop" name_final_lol[cycle[index]][1] = "multiloop" #altering names if cycle[index] not in curr_multiloop: curr_multiloop.append(cycle[index]) if cycle[index-3] not in curr_multiloop: curr_multiloop.append(cycle[index-3]) if len(curr_multiloop) > 0: multiloop_list.append(curr_multiloop) for dom in curr_multiloop: unpaired_node_list.remove(dom) #trim unpaired list from known items #unhinged sequence for node_index in unpaired_node_list: #first neighbors direct_neigh = [n for n in G.neighbors(node_index)] #neighbors of current node #start from unhinged and go until all neighbors are unpaired if len(direct_neigh) == 1: name_final_lol[node_index][1] = "unhinged" next_neigh = direct_neigh before = [node_index] while len(next_neigh) == 1 and next_neigh[0] in unpaired_node_list: name_final_lol[next_neigh[0]][1] = "unhinged sequence" before.append(next_neigh[0]) next_neigh = [n for n in G.neighbors(next_neigh[0])] next_neigh.remove(before[-2]) for step in before: unpaired_node_list.remove(step) #bug with this line, cuts out 20 below, could implement it a bit diff #remaining is unknown but probably linear for remain in unpaired_node_list: name_final_lol[remain][1] = "ambiguous" return name_final_lol, multiloop_list, cycle_list_G def resolve_domains_in_cycles(struct_info_array, paired_dict, skeleton_graph): """ This function handles a lot of stuff, separated in inner functions. We take cycles and assume their geometry with trigonometric rules and fill in the information from the string. """ cycle_list_G = nx.cycle_basis(skeleton_graph) paired_node_list = [] for node in paired_dict: paired_node_list.append(node) paired_node_list.append(paired_dict[node]) def give_pair_of_domain(dom_index, paired_dict): if dom_index in paired_dict: return paired_dict[dom_index] elif dom_index in list(paired_dict.values()): index_of_pair = list(paired_dict.keys())[list(paired_dict.values()).index(dom_index)] return index_of_pair else: raise ValueError('not actually paired') def initiate_polygon_table(cycle, struct_info_array, paired_dict, paired_node_list): """ Create table for said polygon, the angles for the polygon depend only on relative angles from the string """ cycle.sort() polygon_array = np.zeros((int(polygon_sides), 3), dtype='float') paired_dist = 10 #could be changed curr_row = 0 for cyc_index in range(len(cycle)): input_ang = struct_info_array[cycle[cyc_index], 0] #rel. angle side = struct_info_array[cycle[cyc_index], 1] if cycle[cyc_index] not in paired_node_list: #at the start of an unpaired there is always a PA polygon_array[curr_row, 0] = cycle[cyc_index] #remember dom name to write back to polygon_array[curr_row, 2] = struct_info_array[cycle[cyc_index], 2] #dom length curr_row += 1 if cycle[cyc_index-1] not in paired_node_list: #unpaired-unpaired if input_ang == -999: poly_ang = 0 else: poly_ang = 180 + input_ang*side polygon_array[curr_row, 1] = poly_ang else: #unpaired - paired(prev) if input_ang == -999: poly_ang = 0 else: poly_ang = 90 + input_ang*side polygon_array[curr_row, 1] = poly_ang else: pair_of_curr = give_pair_of_domain(cycle[cyc_index], paired_dict) if cycle[cyc_index - 1] not in paired_node_list: #paired-unpaired if input_ang == -999: poly_ang = 0 else: poly_ang = 90 + input_ang*side polygon_array[curr_row, 0] = cycle[cyc_index] #remember dom name to write back to polygon_array[curr_row, 1] = poly_ang polygon_array[curr_row, 2] = paired_dist #dom length curr_row += 1 #update row in polygon_array elif cycle[cyc_index - 1] in paired_node_list and cycle[cyc_index - 1] != pair_of_curr: #paired-paired if input_ang == -999: poly_ang = 0 else: poly_ang = np.abs(input_ang) polygon_array[curr_row, 0] = cycle[cyc_index] #remember dom name to write back to polygon_array[curr_row, 1] = poly_ang polygon_array[curr_row, 2] = paired_dist #dom length curr_row += 1 #update row in polygon_array return polygon_array def indicate_polygon_case(polygon_array): """ Based on arbitrary rules involving properties already in the polygon table, this function determines, in which class the current loop belongs, hence with which algorithm we want to solve it. """ angles_not_given = 0 length_not_given = 0 case1 = False for row in range(len(polygon_array[:,0])): if polygon_array[row-1, 2] == 0 and polygon_array[row-1, 1] == 0 and polygon_array[row, 1] == 0: case1 = True if polygon_array[row, 2] == 0: length_not_given += 1 if polygon_array[row, 1] == 0: angles_not_given += 1 #case1 if case1 == True: return "case 1" else: if length_not_given >= 2: #parallelness needs to be solved in case2calc function return "case 2" elif length_not_given == 1: if angles_not_given >= 2: return "case 3" else: return "case 1" #1l 0-1a else: #all lengths known - like crossroads! return "case 4" def case1calc(polygon_array): """ Calculates points of a vector polygon where at least 1 edge length is unknown, we start drawing from (0, 0) with the next domain after this choosen 'loose edge'. We assume angles and length for every cell other than this loose end. Calculate the vertices and calculate the last edge length and two last angles. """ def resort_list_to_start_by_spec_value(dom_index, list_with_value): index = list_with_value.index(dom_index) sorted_list = [] for i in range(len(list_with_value)): sorted_list.append(list_with_value[index-len(list_with_value)+i]) return sorted_list n_poly = len(polygon_array[:,0]) given_ang_list = [] for row in range(n_poly): if polygon_array[row-1, 2] == 0 and polygon_array[row-1, 1] == 0 and polygon_array[row, 1] == 0: start = row if polygon_array[row, 1] != 0: given_ang_list.append(polygon_array[row, 1]) #distribute remaining angles poly_angles_sum = (n_poly - 2) * 180 remaining_average = (poly_angles_sum - sum(given_ang_list))/(n_poly - len(given_ang_list)) for row in range(n_poly): if polygon_array[row, 1] == 0: polygon_array[row, 1] = remaining_average #set all unknown angles for this mean value #get length/angle mean ratio known_len_angle_sum = [] for row in range(n_poly): if polygon_array[row-1, 2] != 0: #non-null length len_angle_sum_multip_here = (polygon_array[row-1, 1] + polygon_array[row, 1]) * polygon_array[row-1, 2] known_len_angle_sum.append(len_angle_sum_multip_here) len_angle_ratio = np.mean(known_len_angle_sum) #fill length col by using len_angle_ratio for row in range(n_poly): if polygon_array[row-1, 2] == 0: #null length! :) new_len = len_angle_ratio / (polygon_array[row-1, 1] + polygon_array[row, 1]) polygon_array[row-1, 2] = new_len #get drawing order by resorting index list index_list = [n for n in range(n_poly)] resorted_list = resort_list_to_start_by_spec_value(start, index_list) resorted_list.pop() #remove last item which is the 'loose end' domain #the table is filled and we can start calculating coords at domain 'start' coords = np.array([[0, 0]]) for index_in_list in range(len(resorted_list)): ang_here = polygon_array[resorted_list[index_in_list], 1] len_here = polygon_array[resorted_list[index_in_list], 2] if index_in_list == 0: curr_coords = np.array([[len_here, 0]]) abs_ang = 0 else: abs_ang += 180-ang_here #abs angle is the outside angle of the polygon, adding them up curr_coords = coords[-1] + np.array([[np.cos(deg_to_rad(abs_ang)) * len_here, np.sin(deg_to_rad(abs_ang)) * len_here]]) coords = np.append(coords, curr_coords, axis=0) #the last prev_coords we get and [0, 0] adds the last side of the polygon len_last = np.linalg.norm(coords[-1]) polygon_array[start-1, 2] = len_last #angle at start-1 vector1 = coords[-2] - coords[-1] vector2 = coords[0] - coords[-1] angle = calc_degree(vector1, vector2) polygon_array[start-1, 1] = angle #angle at start vector1 = coords[-1] - coords[0] vector2 = coords[1] - coords[0] angle = calc_degree(vector1, vector2) polygon_array[start, 1] = angle return polygon_array def feed_polyarr_to_structarray(struct_info_array, polygon_array, cycle, paired_node_list): """Write back calculated relative angles and domain lengths(if appropriate) to SIA""" for poly_index in range(len(polygon_array[:,0])): curr_dom_index = int(polygon_array[poly_index, 0]) poly_ang = polygon_array[poly_index, 1] poly_len = polygon_array[poly_index, 2] side = struct_info_array[curr_dom_index, 1] cyc_index = cycle.index(curr_dom_index) if curr_dom_index not in paired_node_list: #at the start of an unpaired there is always a polygon angle struct_info_array[curr_dom_index, 2] = poly_len #if unpaired, the length we write over if cycle[cyc_index-1] not in paired_node_list: #unpaired-unpaired rel_angle = (poly_ang - 180) / side struct_info_array[curr_dom_index, 0] = rel_angle else: #unpaired - paired(prev) rel_angle = (poly_ang - 90) / side struct_info_array[curr_dom_index, 0] = rel_angle else: if cycle[cyc_index - 1] not in paired_node_list: #paired-unpaired rel_angle = (poly_ang - 90) / side struct_info_array[curr_dom_index, 0] = rel_angle else: #it is always the right paired-paired, as we only put those in the table rel_angle = poly_ang*side struct_info_array[curr_dom_index, 0] = rel_angle return struct_info_array #MAIN LOOP for cycle in cycle_list_G: #treat hairpin and paired into paired separately ~ no polygon there polygon_sides = 0 for item in cycle: if item in paired_node_list: polygon_sides += 0.5 else: polygon_sides += 1 if polygon_sides == 2: #special cases if len(cycle) == 3: #hairpin, nothing to do here pass elif len(cycle) == 4: #paired into paired, can fill in two 0 angles cycle.sort() #the domains will be after this always the secomd and fourth in cycle struct_info_array[cycle[1], 0] = 0 struct_info_array[cycle[3], 0] = 0 elif polygon_sides >= 3: #has a polygon polygon_array = initiate_polygon_table(cycle, struct_info_array, paired_dict, paired_node_list) if indicate_polygon_case(polygon_array) == "case 1": polygon_array = case1calc(polygon_array) elif indicate_polygon_case(polygon_array) == "case 2": pass elif indicate_polygon_case(polygon_array) == "case 3": pass elif indicate_polygon_case(polygon_array) == "case 4": pass #add calculated info back to SIA struct_info_array = feed_polyarr_to_structarray(struct_info_array, polygon_array, cycle, paired_node_list) return struct_info_array #determine order of traversal (order of domains to build up) def determine_contstruct_order(skeleton_graph, paired_dict): cycle_list_G = nx.cycle_basis(skeleton_graph) paired_node_list = [] for node in paired_dict: paired_node_list.append(node) paired_node_list.append(paired_dict[node]) def find_cycle_where_index_belongs(dom_index, cycle_list_G): #now finds largest cycle found = [] for cycle in cycle_list_G: if dom_index in cycle and len(cycle) > len(found): found = cycle return found def resort_list_to_start_by_spec_value(dom_index, list_with_value): index = list_with_value.index(dom_index) sorted_list = [] for i in range(len(list_with_value)): sorted_list.append(list_with_value[index-len(list_with_value)+i]) return sorted_list def give_pair_of_domain(dom_index, paired_dict): if dom_index in paired_dict: return paired_dict[dom_index] elif dom_index in list(paired_dict.values()): index_of_pair = list(paired_dict.keys())[list(paired_dict.values()).index(dom_index)] return index_of_pair else: raise ValueError('not actually paired') # traverse_order = [0] for node in traverse_order: current_in_travord = traverse_order.index(node) counter = 0 #helps with insert index #pair primary if node in paired_node_list: pair_first = give_pair_of_domain(node, paired_dict) #pair first! if pair_first not in traverse_order: traverse_order.insert(current_in_travord + 1, pair_first) counter += 1 #cycle secondary its_cycle = find_cycle_where_index_belongs(node, cycle_list_G) if len(its_cycle) != 0: #if in cycle its_cycle.sort() #sort it first, bugfix #resort so current is at first place resorted_cycle = resort_list_to_start_by_spec_value(node, its_cycle) for item in resorted_cycle: if item not in traverse_order: traverse_order.insert(current_in_travord + counter + 1, item) counter += 1 #other neighbor tertiary neighbors = skeleton_graph.neighbors(node) for neighbor in neighbors: #other neighbor third! if neighbor not in traverse_order: traverse_order.append(neighbor) return traverse_order def stepwise_buildup(struct_info_array2, paired_dict, traverse_order, skeleton_graph): """ Taking the more-or-less filled SIA, we go along the traversing/drawing order, assume lengths and angles for unpaired, out-of-loop domains and loop starters. """ paired_dist = 10 dom_count = len(traverse_order) coordinate_array = np.zeros((dom_count, 4)) #add a new col for absolute angle values struct_info_array2 = np.append(struct_info_array2, [[0] for i in range(len(struct_info_array2[:,0]))], axis=1) #average over given lengths to get a default unpaired length n_given_len = 0 sum_length = 0 for length in struct_info_array2[:,2]: if length != 0: n_given_len += 1 sum_length += length if n_given_len == 0: default_length = 30 else: default_length = sum_length/n_given_len #paired list as before paired_node_list = [] for node in paired_dict: paired_node_list.append(node) paired_node_list.append(paired_dict[node]) def get_red_neigh(domain_index, skeleton_graph): connections = [n for n in skeleton_graph.edges.data(nbunch=domain_index)] red_neigh = [] for edge in connections: if edge[2]['color'] is 'r': red_neigh.append(edge[1]) return red_neigh def give_pair_of_domain(dom_index, paired_dict): if dom_index in paired_dict: return paired_dict[dom_index] elif dom_index in list(paired_dict.values()): index_of_pair = list(paired_dict.keys())[list(paired_dict.values()).index(dom_index)] return index_of_pair else: raise ValueError('not actually paired') def get_preferred_angle(domain_index, paired_node_list, skeleton_graph, traverse_order): #would be better with name_final neighbors = get_red_neigh(domain_index, skeleton_graph) if min(neighbors) == domain_index-1: #connected to prev dom if traverse_order.index(min(neighbors)) < traverse_order.index(domain_index): if min(neighbors) in paired_node_list and domain_index in paired_node_list: pref_angle = 60 elif min(neighbors) in paired_node_list and domain_index not in paired_node_list: pref_angle = 90 elif min(neighbors) not in paired_node_list and domain_index in paired_node_list: pref_angle = 90 elif min(neighbors) not in paired_node_list and domain_index not in paired_node_list: pref_angle = 0 elif traverse_order.index(min(neighbors)) > traverse_order.index(domain_index): #if backwards (SB case) if max(neighbors) in paired_node_list and domain_index in paired_node_list: pref_angle = 60 elif max(neighbors) in paired_node_list and domain_index not in paired_node_list: pref_angle = 45 elif max(neighbors) not in paired_node_list and domain_index in paired_node_list: pref_angle = 45 elif max(neighbors) not in paired_node_list and domain_index not in paired_node_list: pref_angle = 180 else: #not connected to prev dom, so only to next dom if min(neighbors) in paired_node_list and domain_index in paired_node_list: pref_angle = 60 elif min(neighbors) in paired_node_list and domain_index not in paired_node_list: pref_angle = 45 elif min(neighbors) not in paired_node_list and domain_index in paired_node_list: pref_angle = 45 elif min(neighbors) not in paired_node_list and domain_index not in paired_node_list: pref_angle = 180 return pref_angle def calc_coords_of_paired2(domain_index, struct_info_array2, coordinate_array): side = struct_info_array2[domain_index, 1] x0p, y0p, x1p, y1p = coordinate_array[give_pair_of_domain(domain_index, paired_dict)] pair1vec = np.array([x1p - x0p, y1p - y0p]) #direction of normal_vec has to be opposite of the default normal_vec, as that points outside and this inside x0, y0 = np.array([x1p, y1p]) + normal_length1(pair1vec, side) * paired_dist *-1 x1, y1 = np.array([x0, y0]) + pair1vec * -1 return x0, y0, x1, y1 def calculate_other_two_coords(x, y, abs_angle, length): abs_angle_rad = deg_to_rad(abs_angle) next_x = x + np.cos(abs_angle_rad) * length next_y = y + np.sin(abs_angle_rad) * length return next_x, next_y def take_opposite_angle(angle): if angle > 0: angle -= 180 else: angle += 180 return angle #MAIN LOOP for domain_index in traverse_order: written_rows = traverse_order[0 : traverse_order.index(domain_index)] #rows before current in TO if domain_index == 0: #0th dom if struct_info_array2[0, 0] == -999: abs_angle = 0 else: abs_angle = struct_info_array2[0, 0] struct_info_array2[0, 3] = abs_angle #the absolute angle summation starts here if struct_info_array2[0, 2] == 0: length_here = default_length else: length_here = struct_info_array2[0, 2] x1,y1 = calculate_other_two_coords(0, 0, abs_angle, length_here) coordinate_array[0, 2] = x1 coordinate_array[0, 3] = y1 else: #all other doms #when drawing the second pair, just offset the first if domain_index in paired_node_list and give_pair_of_domain(domain_index, paired_dict) in written_rows: x0, y0, x1, y1 = calc_coords_of_paired2(domain_index, struct_info_array2, coordinate_array) coordinate_array[domain_index, 0] = x0 coordinate_array[domain_index, 1] = y0 coordinate_array[domain_index, 2] = x1 coordinate_array[domain_index, 3] = y1 abs_of_pair = struct_info_array2[give_pair_of_domain(domain_index, paired_dict), 3] abs_here = take_opposite_angle(abs_of_pair) struct_info_array2[domain_index, 3] = abs_here #others: unpaireds, first pairs else: side = struct_info_array2[domain_index, 1] neighbors = get_red_neigh(domain_index, skeleton_graph) #rel_angle cases if struct_info_array2[domain_index, 0] == -999: prefer = get_preferred_angle(domain_index, paired_node_list, skeleton_graph, traverse_order) rel_angle = side * prefer else: rel_angle = struct_info_array2[domain_index, 0] #dom length cases if struct_info_array2[domain_index, 2] == 0: length_here = default_length else: length_here = struct_info_array2[domain_index, 2] #for doms > 0 and previous dom didn't have strand break, x0, y0 is the same as x1, y1 of prev dom if len(neighbors) == 1: if neighbors[0] < domain_index: coordinate_array[domain_index, 0] = coordinate_array[neighbors[0], 2] coordinate_array[domain_index, 1] = coordinate_array[neighbors[0], 3] abs_angle = struct_info_array2[neighbors[0], 3] + rel_angle struct_info_array2[domain_index, 3] = abs_angle #fill out abs angle field x0, y0 = coordinate_array[domain_index, 0], coordinate_array[domain_index, 1] x1, y1 = calculate_other_two_coords(x0, y0, abs_angle, length_here) coordinate_array[domain_index, 2] = x1 coordinate_array[domain_index, 3] = y1 elif neighbors[0] > domain_index: coordinate_array[domain_index, 2] = coordinate_array[neighbors[0], 0] coordinate_array[domain_index, 3] = coordinate_array[neighbors[0], 1] abs_angle = take_opposite_angle(struct_info_array2[neighbors[0], 3]) - rel_angle struct_info_array2[domain_index, 3] = abs_angle #fill out abs angle field x1, y1 = coordinate_array[domain_index, 2], coordinate_array[domain_index, 3] #other way around x0, y0 = calculate_other_two_coords(x1, y1, abs_angle, length_here) coordinate_array[domain_index, 0] = x0 coordinate_array[domain_index, 1] = y0 if len(neighbors) == 2: for neigh in neighbors: if neigh < domain_index: if neigh in written_rows: coordinate_array[domain_index, 0] = coordinate_array[domain_index - 1, 2] coordinate_array[domain_index, 1] = coordinate_array[domain_index - 1, 3] if neigh > domain_index: if neigh in written_rows: coordinate_array[domain_index, 2] = coordinate_array[domain_index + 1, 0] coordinate_array[domain_index, 3] = coordinate_array[domain_index + 1, 1] for neigh in neighbors: if neigh < domain_index: if neigh not in written_rows: abs_angle = take_opposite_angle(struct_info_array2[domain_index + 1, 3]) - rel_angle #take the abs angle of the written neighbor struct_info_array2[domain_index, 3] = abs_angle #fill out abs angle field x1, y1 = coordinate_array[domain_index, 2], coordinate_array[domain_index, 3] x0, y0 = calculate_other_two_coords(x1, y1, abs_angle, length_here) coordinate_array[domain_index, 0] = x0 coordinate_array[domain_index, 1] = y0 if neigh > domain_index: if neigh not in written_rows: abs_angle = struct_info_array2[neighbors[0], 3] + rel_angle struct_info_array2[domain_index, 3] = abs_angle #fill out abs angle field x0, y0 = coordinate_array[domain_index, 0], coordinate_array[domain_index, 1] x1, y1 = calculate_other_two_coords(x0, y0, abs_angle, length_here) coordinate_array[domain_index, 2] = x1 coordinate_array[domain_index, 3] = y1 return coordinate_array def create_color_list(name_final_lol, paired_dict, multiloop_list, palette): """ color list for each domain where: pairs are same color, multiloops are same color, neighbor domains never same color """ if palette is "IBM": colors = ["#648FFF", "#785EF0", "#DC267F", "#FE6100", "#FFB000"] background_cols = ["#BACCFB", "#CAC1F3", "#DC9BBB", "#F1C2A6", "#F9E5B9"] #more 'faded' color for rectangle between pairs elif palette is "Wong": colors = ["#000000", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7"] background_cols = ["#BDBDBD", "#EAC267", "#A5CCE2", "#77A79A", "#E8E4A7", "#6595B1", "#D49E73", "#C7A8BA"] elif palette is "Magma": colors = ["#fcfdbf", "#fe9f6d", "#de4968", "#8c2981", "#3b0f70", "#000004"] background_cols = ["#FFFFE8", "#F7C9B1", "#DCA6B1", "#BBA0B8", "#AA93C5", "#A9A9A9"] elif palette is "Plasma": colors = ["#f0f921", "#fdb42f", "#ed7953", "#cc4778", "#9c179e", "#5c01a6", "#0d0887"] background_cols = ["#EDF194", "#F9DCA8", "#E8AE9B", "#CC91A6", "#AE7FAF", "#9C78B9", "#7E7CC1"] else: print("Palette not yet available") def give_pair_of_domain(dom_index, paired_dict): if dom_index in paired_dict: return paired_dict[dom_index] elif dom_index in list(paired_dict.values()): index_of_pair = list(paired_dict.keys())[list(paired_dict.values()).index(dom_index)] return index_of_pair else: raise ValueError('not actually paired') curr_color_i = 0 for dom_index in range(len(name_final_lol)): color_i = curr_color_i % len(colors) if len(name_final_lol[dom_index]) == 2: name, domtype = name_final_lol[dom_index] if domtype is "paired": pair_index = give_pair_of_domain(dom_index, paired_dict) #index2 is line color name_final_lol[dom_index].append(colors[color_i]) name_final_lol[pair_index].append(colors[color_i]) #index3 is only for paired, the between pair background color name_final_lol[dom_index].append(background_cols[color_i]) name_final_lol[pair_index].append(background_cols[color_i]) curr_color_i += 1 elif domtype is "multiloop": for loop in multiloop_list: if dom_index in loop: for loop_index in loop: name_final_lol[loop_index].append(colors[color_i]) else: name_final_lol[dom_index].append(colors[color_i]) curr_color_i += 1 return name_final_lol def lin_domain(x0, y0, x1, y1, side, name, color): #draw line from 5' to 3' p = draw.Line(x0, y0, x1, y1, stroke = color) offset_len = 7 text_size = 7 #label has to be on its correct side vector = np.array([x1 - x0, y1 - y0]) label_offset = normal_length1(vector, side) * offset_len x_text, y_text = np.array([x0,y0]) + vector/2 + label_offset t = draw.Text(name, text_size, x_text, y_text, fill = color) return p, t def hairpin_loop(x0, y0, x1, y1, side, name, color): offset_len = 7 text_size = 7 #calculate Arc arguments r = np.sqrt((x1-x0)**2 + (y1-y0)**2) #rn radius is the distance between paired regions, will change #vector is pointing from point 0 -> point 1 vector = np.array([x1 - x0, y1 - y0]) vec_len = np.linalg.norm(vector) unit_normal = normal_length1(vector, side) #calculate center and label anchor with r and vector diag = np.sqrt(r**2 - (vec_len/2)**2) cx, cy = np.array([x0,y0])+ vector/2 + diag*unit_normal x_text, y_text = np.array([x0,y0])+ vector/2 + (diag+r+offset_len)*unit_normal vec_center_0 = np.array([x0-cx,y0-cy]) vec_center_1 = np.array([x1-cx,y1-cy]) #correction for 0 angle if np.sign(vec_center_0[1]) == 0: which_side0 = 1 else: which_side0 = np.sign(vec_center_0[1]) if np.sign(vec_center_1[1]) == 0: which_side1 = 1 else: which_side1 = np.sign(vec_center_1[1]) #bit unclear about start/end degrees, but works if side == -1: startdeg = calc_degree(vec_center_0, np.array([1,0]))*which_side0 enddeg = calc_degree(vec_center_1, np.array([1,0]))*which_side1 elif side == 1: enddeg = calc_degree(vec_center_0, np.array([1,0]))*which_side0 startdeg = calc_degree(vec_center_1, np.array([1,0]))*which_side1 #draw p = draw.Arc(cx, cy, r, startdeg, enddeg, stroke=color, stroke_width=0.9, fill="none") #stroke_width will be also important #LABEL - if without name, no label is added t = draw.Text(name, text_size, x_text, y_text, fill=color) #label return p, t def bulgeloop(x0, y0, x1, y1, side, name, color): offset_len = 7 text_size = 7 #calculate Arc arguments r = (np.sqrt((x1 - x0)**2 + (y1 - y0)**2))/2 #rn radius is the distance between paired regions, will change #vector is pointing from point 0 -> point 1 vector = np.array([x1 - x0, y1 - y0]) vec_len = np.linalg.norm(vector) unit_normal = normal_length1(vector, side) #calculate center and label anchor with r and vector cx, cy = np.array([x0, y0])+ vector/2 x_text, y_text = np.array([x0, y0])+ vector/2 + (r + offset_len) * unit_normal vec_center_0 = np.array([x0 - cx, y0 - cy]) vec_center_1 = np.array([x1 - cx, y1 - cy]) #correction for 0 angle if np.sign(vec_center_0[1]) == 0: which_side0 = 1 else: which_side0 = np.sign(vec_center_0[1]) if np.sign(vec_center_1[1]) == 0: which_side1 = 1 else: which_side1 = np.sign(vec_center_1[1]) #bit unclear about start/end degrees, but works if side == -1: startdeg = calc_degree(vec_center_0, np.array([1,0])) * which_side0 enddeg = calc_degree(vec_center_1, np.array([1,0])) * which_side1 elif side == 1: enddeg = calc_degree(vec_center_0, np.array([1,0])) * which_side0 startdeg = calc_degree(vec_center_1, np.array([1,0])) * which_side1 #draw p = draw.Arc(cx, cy, r, startdeg, enddeg, stroke=color, stroke_width=0.9, fill="none") #stroke_width will be also important #LABEL - if without name, no label is added t = draw.Text(name, text_size, x_text, y_text, fill=color) #label return p, t def multiloop(d, ml, coordinate_array, struct_info_array2, name_final_lol): offset_len = 7 text_size = 7 side = struct_info_array2[ml[0], 1] colors = [name_final_lol[i][2] for i in ml] names = [name_final_lol[i][0] for i in ml] #taken from https://stackoverflow.com/a/47198877 def find_center(p_ex1, p_ex2, centroid): x1, y1 = p_ex1 x2, y2 = p_ex2 x3, y3 = centroid dx, dy = x2 - x1, y2 - y1 det = dx * dx + dy * dy a = (dy * (y3 - y1) + dx * (x3 - x1))/det return x1 + a * dx, y1 + a * dy #put points into shapely, get centroid coords = [] for dom in ml: point0 = (coordinate_array[dom, 0], coordinate_array[dom, 1]) point1 = (coordinate_array[dom, 2], coordinate_array[dom, 3]) coords.append(point0) coords.append(point1) centroid = LinearRing(coords).centroid centroid = np.asarray(centroid) #get centerpoint for each arc for dom_i in range(len(ml)): dom = ml[dom_i] x0 = coordinate_array[dom, 0] y0 = coordinate_array[dom, 1] x1 = coordinate_array[dom, 2] y1 = coordinate_array[dom, 3] #vector is pointing from point 0 -> point 1 vector = np.array([x1 - x0, y1 - y0]) unit_normal = normal_length1(vector, side) #this should go to the other side as the hairpin center! p_ex1 = np.array([x0, y0]) + vector/2 p_ex2 = np.array([x0, y0]) + vector/2 + unit_normal * -1 cx, cy = find_center(p_ex1, p_ex2, centroid) radius = np.linalg.norm(np.array([x1 - cx, y1 - cy])) x_text, y_text = np.array([cx, cy]) + unit_normal * (radius + offset_len) vec_center_0 = np.array([x0 - cx, y0 - cy]) vec_center_1 = np.array([x1 - cx, y1 - cy]) #correction for 0 angle if np.sign(vec_center_0[1]) == 0: which_side0 = 1 else: which_side0 = np.sign(vec_center_0[1]) if np.sign(vec_center_1[1]) == 0: which_side1 = 1 else: which_side1 = np.sign(vec_center_1[1]) #bit unclear about start/end degrees, but works if side == -1: startdeg = calc_degree(vec_center_0, np.array([1,0])) * which_side0 enddeg = calc_degree(vec_center_1, np.array([1,0])) * which_side1 elif side == 1: enddeg = calc_degree(vec_center_0, np.array([1,0])) * which_side0 startdeg = calc_degree(vec_center_1, np.array([1,0])) * which_side1 #append to draw object m = draw.Arc(cx, cy, radius, startdeg, enddeg, stroke=colors[dom_i], stroke_width=0.9, fill="none") #stroke_width will be also important #LABEL - if without name, no label is added t = draw.Text(names[dom_i], text_size, x_text, y_text, fill=colors[dom_i]) #label d.append(m) d.append(t) return d def draw_image_from_coords(coordinate_array, struct_info_array2, name_final_lol, multiloop_list, paired_dict): def get_canvas_size(coordinate_array): x_coords = list(coordinate_array[:,0]) + list(coordinate_array[:,2]) y_coords = list(coordinate_array[:,1]) + list(coordinate_array[:,3]) x_len = (max(x_coords) - min(x_coords)) + 65 #canvas 14 incre. larger than max range y_len = (max(y_coords) - min(y_coords)) + 65 origo = [min(x_coords) - 30, min(y_coords) - 30] #origin 7 increment lower - which is the text_offset canvas = [int(x_len), int(y_len)] return canvas, origo #draw process SCALE_METRIC = 3 #? CANVAS_SIZE, ORIGIN = get_canvas_size(coordinate_array) #image instancing d = draw.Drawing(CANVAS_SIZE[0], CANVAS_SIZE[1], origin=ORIGIN, displayInline=False) d.setPixelScale(SCALE_METRIC) for row in range(len(coordinate_array[:,0])): x0 = coordinate_array[row, 0] y0 = coordinate_array[row, 1] x1 = coordinate_array[row, 2] y1 = coordinate_array[row, 3] side = struct_info_array2[row, 1] name = name_final_lol[row][0] color = name_final_lol[row][2] #endings indicated if row == 0: dom1vec = np.array([x0 - x1, y0 - y1]) vec5prime = dom1vec/np.linalg.norm(dom1vec) * 10 t5 = draw.Text("5'", 6, vec5prime[0], vec5prime[1], fill='black') d.append(t5) elif row == len(coordinate_array[:,0])-1: dom_last_vec = np.array([x1 - x0, y1 - y0]) vec3prime = np.array([x1,y1]) + dom_last_vec/np.linalg.norm(dom_last_vec) * 7 t3 = draw.Text("3'", 6, vec3prime[0], vec3prime[1], fill='black') d.append(t3) #some dom types have special functions if name_final_lol[row][1] == "hairpin loop": p, t = hairpin_loop(x0, y0, x1, y1, side, name, color) elif name_final_lol[row][1] == "bulgeloop": p, t = bulgeloop(x0, y0, x1, y1, side, name, color) elif name_final_lol[row][1] != "multiloop": p, t = lin_domain(x0, y0, x1, y1, side, name, color) d.append(p) d.append(t) #multiloops done together for ml in multiloop_list: d = multiloop(d, ml, coordinate_array, struct_info_array2, name_final_lol) #rectangle between paired doms for pair1 in paired_dict: pair2 = paired_dict[pair1] color = name_final_lol[pair1][3] x0, y0, x1, y1 = coordinate_array[pair1] x0p, y0p, x1p, y1p = coordinate_array[pair2] r = draw.Lines(x0, y0, x1, y1, x0p, y0p, x1p, y1p, close = False, fill = color) d.append(r) return d def domain_visualization(string, length_input_dict={}, palette="IBM", filename=None, orient=1): """ Includes all previously defined functions, save intermediate data structures inside as local variables and renders the drawing. """ dom_raw_list, struct_info_array, paired_dict, name_final_lol = comprehend_string(string, orient) struct_info_array = process_length_input(struct_info_array, length_input_dict) skeleton_graph = create_skeleton(dom_raw_list, paired_dict, name_final_lol) name_final_lol, multiloop_list, cycle_list_G = find_type_of_unpaired(skeleton_graph, paired_dict, name_final_lol) #if no cycles skip cycle resolve: if len(cycle_list_G) == 0: struct_info_array2 = struct_info_array else: struct_info_array2 = resolve_domains_in_cycles(struct_info_array, paired_dict, skeleton_graph) traverse_order = determine_contstruct_order(skeleton_graph, paired_dict) coordinate_array = stepwise_buildup(struct_info_array2, paired_dict, traverse_order, skeleton_graph) name_final_lol = create_color_list(name_final_lol, paired_dict, multiloop_list, palette) d = draw_image_from_coords(coordinate_array, struct_info_array2, name_final_lol, multiloop_list, paired_dict) if filename != None: d.saveSvg(filename) return d
StarcoderdataPython
3313574
# -*- coding: utf-8 -*- """ lantz.drivers.newport.fsm300 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Implementation of FSM300 using NI DAQ controller Author: <NAME> Date: 9/27/2016 """ from lantz import Driver from lantz.driver import Feat, DictFeat, Action from lantz.drivers.ni.daqmx import AnalogOutputTask, VoltageOutputChannel from lantz import Q_ import time import numpy as np def enforce_units(val, units): if not isinstance(val, Q_): val = Q_(val, units) else: val = val.to(units) return val def enforce_point_units(point, units='um'): point = enforce_units(point[0], units) , enforce_units(point[1], units) return point class FSM300(Driver): def __init__(self, x_ao_ch, y_ao_ch, ao_smooth_rate=Q_('10 kHz'), ao_smooth_steps=Q_('1000 1/V'), limits=((Q_(-10, 'V'), Q_(10, 'V')), (Q_(-10, 'V'), Q_(10, 'V'))), cal=(Q_(10, 'um/V'), Q_(7.6, 'um/V'))): self.x_limits_mag = tuple(float(val / Q_('1 V')) for val in limits[0]) self.y_limits_mag = tuple(float(val / Q_('1 V')) for val in limits[1]) self.ao_smooth_rate = ao_smooth_rate self.ao_smooth_steps = ao_smooth_steps self.cal = cal self._position = (Q_('0 um'), Q_('0 um')) super().__init__() self.x_ao_ch = x_ao_ch self.y_ao_ch = y_ao_ch return def initialize(self): self.task = AnalogOutputTask('fsm300') VoltageOutputChannel(self.x_ao_ch, name='fsm_x', min_max=self.x_limits_mag, units='volts', task=self.task) VoltageOutputChannel(self.y_ao_ch, name='fsm_y', min_max=self.y_limits_mag, units='volts', task=self.task) super().initialize() def finalize(self): self.task.clear() super().finalize() def ao_smooth_func(self, init_point, final_point): init_x, init_y = init_point final_x, final_y = final_point init_x_voltage, final_x_voltage = init_x / self.cal[0], final_x / self.cal[0] init_y_voltage, final_y_voltage = init_y / self.cal[1], final_y / self.cal[1] diff_x_voltage = final_x_voltage - init_x_voltage diff_y_voltage = final_y_voltage - init_y_voltage diff_voltage = max(abs(diff_x_voltage), abs(diff_y_voltage)) steps = int(np.ceil(diff_voltage * self.ao_smooth_steps)) init = np.array([val.to('V').magnitude for val in [init_x_voltage, init_y_voltage]]) diff = np.array([val.to('V').magnitude for val in [diff_x_voltage, diff_y_voltage]]) versine_steps = (1.0 - np.cos(np.linspace(0.0, np.pi, steps))) / 2.0 step_voltages = np.outer(np.ones(steps), init) + np.outer(versine_steps, diff) return step_voltages def ao_linear_func(self, init_point, final_point, steps): init_x, init_y = init_point final_x, final_y = final_point init_x_voltage, final_x_voltage = init_x / self.cal[0], final_x / self.cal[0] init_y_voltage, final_y_voltage = init_y / self.cal[1], final_y / self.cal[1] diff_x_voltage = final_x_voltage - init_x_voltage diff_y_voltage = final_y_voltage - init_y_voltage diff_voltage = max(abs(diff_x_voltage), abs(diff_y_voltage)) init = np.array([val.to('V').magnitude for val in [init_x_voltage, init_y_voltage]]) diff = np.array([val.to('V').magnitude for val in [diff_x_voltage, diff_y_voltage]]) linear_steps = np.linspace(0.0, 1.0, steps) step_voltages = np.outer(np.ones(steps), init) + np.outer(linear_steps, diff) return step_voltages @Feat() def abs_position(self): return self._position @abs_position.setter def abs_position(self, point): point = enforce_point_units(point) step_voltages = self.ao_smooth_func(self._position, point) if step_voltages.size: steps = step_voltages.shape[0] clock_config = { 'source': 'OnboardClock', 'rate': self.ao_smooth_rate.to('Hz').magnitude, 'sample_mode': 'finite', 'samples_per_channel': steps, } self.task.configure_timing_sample_clock(**clock_config) self.task.configure_trigger_disable_start() task_config = { 'data': step_voltages, 'auto_start': False, 'timeout': Q_(0,'s'), 'group_by': 'scan', } self.task.write(**task_config) self.task.start() time.sleep((steps / self.ao_smooth_rate).to('s').magnitude) self.task.stop() self._position = point @Action() def line_scan(self, init_point, final_point, steps, acq_task, acq_rate=Q_('20 kHz'), pts_per_pos=100): init_point = enforce_point_units(init_point) final_point = enforce_point_units(final_point) timeout = enforce_units(1.5*(pts_per_pos*steps/acq_rate), units='s') # AO smooth move to initial point self.abs_position = init_point step_voltages = self.ao_linear_func(init_point, final_point, steps) if acq_task.IO_TYPE == 'CI': chs = list(acq_task.channels.keys()) if not chs: raise ValueError('acquisition task must have at least one channel') ch = chs[0] dev = ch.split('/')[0] step_voltages = np.repeat(step_voltages, pts_per_pos + 1, axis=0) clock_config = { 'rate': acq_rate.to('Hz').magnitude, 'sample_mode': 'finite', 'samples_per_channel': len(step_voltages), } self.task.configure_timing_sample_clock(**clock_config) clock_config = { 'source': '/{}/ao/SampleClock'.format(dev), 'rate': acq_rate.to('Hz').magnitude, 'sample_mode': 'finite', 'samples_per_channel': len(step_voltages), } acq_task.configure_timing_sample_clock(**clock_config) task_config = { 'data': step_voltages, 'auto_start': False, 'timeout': Q_('0 s'), 'group_by': 'scan', } self.task.write(**task_config) acq_task.arm_start_trigger_source = 'ao/StartTrigger'.format(dev) acq_task.arm_start_trigger_type = 'digital_edge' acq_task.start() self.task.start() scanned = acq_task.read(samples_per_channel=len(step_voltages), timeout=timeout) acq_task.stop() self.task.stop() scanned = scanned.reshape((steps, pts_per_pos + 1)) averaged = np.diff(scanned).mean(axis=1) return averaged*acq_rate.to('Hz').magnitude elif acq_task.IO_TYPE == 'AI': step_voltages = np.repeat(step_voltages, pts_per_pos, axis=0) clock_config = { 'source': 'OnboardClock', 'rate': acq_rate.to('Hz').magnitude, 'sample_mode': 'finite', 'samples_per_channel': len(step_voltages), } self.task.configure_timing_sample_clock(**clock_config) acq_task.configure_timing_sample_clock(**clock_config) task_config = { 'data': step_voltages, 'auto_start': False, 'timeout': Q_('0 s'), 'group_by': 'scan', } self.task.write(**task_config) self.task.configure_trigger_digital_edge_start('ai/StartTrigger') self.task.start() acq_task.start() scanned = acq_task.read(samples_per_channel=len(step_voltages), timeout=timeout) acq_task.stop() self.task.stop() scanned = scanned.reshape((steps, pts_per_pos)) averaged = scanned.mean(axis=1) return averaged else: pass
StarcoderdataPython
11290418
<filename>CurationEngine/src/createNewEventRule.py import traceback import os import json import logging import boto3 import botocore from boto3.dynamodb.types import TypeDeserializer logger = logging.getLogger() class CreateNewEventRuleException(Exception): pass # Subclass of boto's TypeDeserializer for DynamoDB to adjust # for DynamoDB Stream format. class StreamTypeDeserializer(TypeDeserializer): def _deserialize_n(self, value): return float(value) def _deserialize_b(self, value): return value # Already in Base64 def lambda_handler(event, context): ''' lambda_handler Top level lambda handler ensuring all exceptions are caught and logged. :param event: AWS Lambda uses this to pass in event data. :type event: Python type - Dict / list / int / string / float / None :param context: AWS Lambda uses this to pass in runtime information. :type context: LambdaContext :return: The event object passed into the method :rtype: Python type - Dict / list / int / string / float / None :raises CreateNewEventRuleException: On any error or exception ''' try: return create_new_event_rule(event, context) except CreateNewEventRuleException: raise except Exception as e: traceback.print_exc() raise CreateNewEventRuleException(e) def create_new_event_rule(event, context): """ create_new_event_rule Creates a new event rule and event target in event bridge to be used in the accelerated data pipelines. :param event: AWS Lambda uses this to pass in event data. :type event: Python type - Dict / list / int / string / float / None :param context: AWS Lambda uses this to pass in runtime information. :type context: LambdaContext :return: The event object passed into the method :rtype: Python type - Dict / list / int / string / float / None """ ddb_deserializer = StreamTypeDeserializer() records = event['Records'] start_curation_process_function_arn = os.environ['START_CURATION_PROCESS_FUNCTION_ARN'] for record in records: ddb = record['dynamodb'] # Get the event type and curation type for the record event_name = record['eventName'].upper() # INSERT, MODIFY, REMOVE if (event_name == 'INSERT') or (event_name == 'MODIFY'): if 'NewImage' not in ddb: logger.warning( 'Cannot process stream if it does not contain NewImage') continue doc_fields = ddb_deserializer.deserialize({'M': ddb['NewImage']}) curation_type = doc_fields['curationType'] print(f'Creating or modifying event for curationType {curation_type}') put_rule(curation_type, doc_fields['cronExpression']) put_target(curation_type, start_curation_process_function_arn) elif event_name == 'REMOVE': doc_fields = ddb_deserializer.deserialize({'M': ddb['Keys']}) curation_type = doc_fields['curationType'] print(f'Removing event for curationType {curation_type}') remove_targets(curation_type) delete_rule(curation_type) return 'Success' def put_rule(curation_type, schedule_expression): client = boto3.client('events') response = client.put_rule( Name=f'{curation_type}-scheduled-curation', ScheduleExpression=schedule_expression, State='ENABLED', Description=f'Event rule for curation type {curation_type}' ) def delete_rule(curation_type): client = boto3.client('events') response = client.delete_rule( Name=f'{curation_type}-scheduled-curation' ) def put_target(curation_type, function_arn): client = boto3.client('events') input = {"curationType": curation_type} response = client.put_targets( Rule=f'{curation_type}-scheduled-curation', Targets=[ { 'Id': f'{curation_type}-event-target', 'Arn': function_arn, 'Input': json.dumps(input) } ] ) def remove_targets(curation_type): client = boto3.client('events') response = client.remove_targets( Rule=f'{curation_type}-scheduled-curation', Ids=[ f'{curation_type}-event-target', ] )
StarcoderdataPython
6562089
print("Hello World") print("My name is <NAME>.") print("Testing") print(" /|") print(" / |") print(" / |") print("/___|") age = ("14") print("My name is <NAME> and I'm " + age + "-years-old.") name = ("<NAME>") print("I'm " + name + " and I live in California") location = ("California") year = ("2005") print("I'm " + name + " and was born in " + year + ". I live currently live in " + location + ".") print(name.upper()) print(name.lower()) print(name.isupper()) print(name[0]) print(name[1]) print(name[2]) print(name[3]) print(name[4]) print(name[5]) print(name[6]) print(name[7]) print(name + " was born in 2005.") print(name) print(name.index("V")) print(name.index("i")) print(name.index("c")) print(name.index("t")) print(name.index("o")) print(name.index("r")) print(name.index("y")) print(name.index(" ")) print(name.index("T")) print(name.index("a")) print(name.index("m")) print(name.index("a")) print(name.index("n")) print(name.index("g")) my_num = -5 print(abs(my_num)) print(pow(3, 5)) print(min(3, 5)) print(max(3, 5)) print(round(3.14156)) print(round(3.7)) from math import* print(max(3.7, pow(3.7, 20))) print(floor(3.7)) print(ceil(3.7)) print(sqrt(36)) print(sqrt (pow(36, 6))) friends = ["Kevin", "Karen", "Jim"] friends[1] = "Mike" print(friends[1:]) lucky_numbers = [4,8,15,16,23,42] friends1 = ["Kevin", "Karen", "Jim", "Oscar", "Toby"] friends1.append("Creed") friends1.insert(1, "Kelly") friends1.reverse() print(friends1) print(friends1.index("Karen")) friends2 = friends1.copy() print(friends2) coordinates = [(4, 5), (6, 7), (80, 34)] coordinates[1] = 10 print(coordinates[0]) def say_hi(name, age): print("Hello " +name+ "you are are " +str(age)+ ".") print("Top") say_hi("Mike", 35) say_hi("Steve", 70) print("Bottom") color = input("Enter a color: ") plural_noun = input("Enter a plural noun: ") celebrity = input("Enter a celebrity: ") print("Roses are " +color) print(plural_noun+ " are blue") print("I love " +celebrity) name = input("Enter your name: ") age = input("Enter your age: ") print("Hello " + name + "! You're " + age + "!") num1 = input("Enter a number: ") num2 = input("Enter another a number: ") result = int(num1) + int(num2) print(result) num1 = input("Enter a number with a decimal: ") num2 = input("Enter another a number with a decimal: ") result = float(num1) + float(num2) print(result)
StarcoderdataPython
348517
<filename>gcal_notifier/main.py #!/usr/bin/env python from datetime import datetime from typing import Any, Dict, Tuple from gcal_notifier.cli import cli from gcal_notifier.config_reader import init_config from gcal_notifier.event_getter import SimpleGCalendarGetter from gcal_notifier.event_loader import load_saved_events from gcal_notifier.event_printer import SimpleGCalendarPrinter from gcal_notifier.event_reminder import SimpleGCalendarNotifier from gcal_notifier.event_saver import save_events from gcal_notifier.globals import CACHE from gcal_notifier.utils import define_period def run_getter( general_params: Dict[str, Any], calendar_params: Dict[str, Any], ) -> None: """Run SimpleGCalendarGetter with user configs. Args: general_params (Dict[str, Any]): General params calendar_params (Dict[str, Any]): Calendar params """ getter = SimpleGCalendarGetter(general_params, calendar_params) getter.load_calendars(define_period("day")) getter.load_events() save_events(getter.events, file_path=CACHE / "events_notify.json") getter.load_calendars(define_period("month")) getter.load_events() save_events(getter.events, file_path=CACHE / "events_print.json") def run_notifier( general_params: Dict[str, Any], calendar_params: Dict[str, Any] ) -> None: """Run SimpleGCalendarNotifier with user configs. Args: general_params (Dict[str, Any]): General params calendar_params (Dict[str, Any]): Calendar params """ saved_events = load_saved_events(CACHE / "events_notify.json") notifier = SimpleGCalendarNotifier( saved_events, general_params, calendar_params ) notifier.search_reminders() def run_printer( general_params: Dict[str, Any], calendar_params: Dict[str, Any], period: Tuple[datetime, datetime], format: str = "day", ) -> None: """Run SimpleGCalendarPrinter with user configs. Args: general_params (Dict[str, Any]): General params calendar_params (Dict[str, Any]): Calendar params format (str): Format to use when printing events """ saved_events = load_saved_events(CACHE / "events_print.json") printer = SimpleGCalendarPrinter( saved_events, general_params, calendar_params, period, format=format ) printer.print_events(format) def gcal_notifier() -> None: """Run gcal_notifier cli.""" args = cli() general_params, calendar_params = init_config() if args.command == "get": run_getter(general_params, calendar_params) elif args.command == "notify": run_notifier(general_params, calendar_params) elif args.command == "print": period = define_period(args.period) run_printer(general_params, calendar_params, period, args.period)
StarcoderdataPython
11324685
<reponame>danielsnider/ecosystem-project-website-template import logging import socket from skyline.io.connection import Connection, ConnectionState from skyline.exceptions import NoConnectionError logger = logging.getLogger(__name__) class ConnectionManager: def __init__(self, message_handler, closed_handler): self._connections = {} self._message_handler = message_handler self._closed_handler = closed_handler def register_connection(self, opened_socket, address): self._connections[address] = ( Connection( opened_socket, address, self._message_handler, self._closed_handler, ), ConnectionState(), ) self._connections[address][0].start() def remove_connection(self, address): connection, state = self.get_connection_tuple(address) connection.stop() state.connected = False del self._connections[address] logger.debug("Removed connection to (%s:%d).", *address) def get_connection(self, address): return self.get_connection_tuple(address)[0] def get_connection_state(self, address): return self.get_connection_tuple(address)[1] def get_connection_tuple(self, address): if address not in self._connections: host, port = address raise NoConnectionError( "Connection to ({}:{}) does not exist.".format(host, port)) return self._connections[address] def broadcast(self, string_message): for _, (connection, _) in self._connections.items(): connection.write_string_message(string_message) def connect_to(self, host, port): new_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) new_socket.connect((host, port)) self.register_connection(new_socket, (host, port)) def stop(self): for _, (connection, state) in self._connections.items(): connection.stop() state.connected = False self._connections.clear()
StarcoderdataPython
391840
<reponame>logic-and-learning-lab/Popper-experiments import json import inspect class ExperimentResult: def __init__(self, problem_name, system_name, trial, solution, total_exec_time, conf_matrix, extra_stats): self.problem_name = problem_name self.system_name = system_name self.trial = trial self.solution = solution self.total_exec_time = total_exec_time self.extra_stats = extra_stats self.conf_matrix = conf_matrix def __str__(self): return f'{self.problem_name}__{self.system_name} :: {self.total_exec_time:.2f}s :: {self.accuracy}' @property def accuracy(self): if self.conf_matrix: tp, fn, tn, fp = self.conf_matrix return (tp + tn) / (tp+fn+tn+fp) return .5 # TODO(Brad): I copied all this from my Popper code and it's still a pretty lazy way to do JSON. TYPE = '__typ__' WRITABLE_CLASSES = {ExperimentResult} NAME_TO_CLASS = {clz.__name__:clz for clz in WRITABLE_CLASSES} class ResultEncoder(json.JSONEncoder): def default(self, obj): if obj.__class__ in WRITABLE_CLASSES: init_vars = inspect.getfullargspec(obj.__init__)[0] all_vars = vars(obj) final_dict = {key:all_vars[key] for key in init_vars if key in all_vars} final_dict[TYPE] = obj.__class__.__name__ return final_dict else: return super().default(obj) def write_result(file, out): with open(file, "w") as f: f.write(json.dumps(out, cls=ResultEncoder)) # To use: stats = json.loads(s, object_hook=decode_stats) def decode_result(dct): if TYPE in dct: clazz = NAME_TO_CLASS[dct[TYPE]] init_vars = inspect.getfullargspec(clazz.__init__)[0] final_dict = {key:dct[key] for key in init_vars if key in dct} return clazz(**final_dict) return dct
StarcoderdataPython
170399
import json import logging import os from unittest import mock from elastic.cobalt_strike_extractor.extractor import CSBeaconExtractor logger = logging.getLogger() def test_transform_beacon(shared_datadir): with mock.patch.dict( os.environ, { "INPUT_ELASTICSEARCH_ENABLED": "False", "OUTPUT_ELASTICSEARCH_ENABLED": "False", "OUTPUT_CONSOLE_ENABLED": "True", }, ): _extractor = CSBeaconExtractor() _docs = (shared_datadir / "sample_raw_docs.ndjson").read_text().strip() _control_docs = ( (shared_datadir / "sample_transformed_docs.ndjson").read_text().strip() ) _data = [] for item in _docs.split("\n"): _data.append(json.loads(item)) _control_data = [] for item in _control_docs.split("\n"): _control_data.append(json.loads(item)) _results = _extractor.transform(_data) _results = list(_results) assert len(_results) == len(_control_data) _zip = zip(_results, _control_data) for item1, item2 in _zip: assert item1 == item2
StarcoderdataPython
6542315
<reponame>Mithzyl/Master-college-selecting-api<gh_stars>0 # Generated by Django 3.1.5 on 2021-02-05 12:14 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Colleges', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=40)), ('province', models.CharField(max_length=10)), ('is_211', models.BooleanField(default=False)), ('is_985', models.BooleanField(default=False)), ], options={ 'verbose_name': 'College', 'verbose_name_plural': 'Colleges', }, ), ]
StarcoderdataPython
4942850
<reponame>hughpyle/GW-BASIC<filename>conv/z80conv/conv.py<gh_stars>10-100 #!/usr/bin/python # Copyright (c) 2020 <NAME> <<EMAIL>> # Licensed under GPLv2. import sys import traceback from .lexer import Lexer from .parser import Parser from .transformer import Transformer from .writer import PasmoWriter def main(): lexer = Lexer(sys.stdin) parser = Parser(lexer) transformer = Transformer(parser) writer = PasmoWriter(transformer) try: for line in writer.lines(): print(line) except SyntaxError as e: print("Exception: %s" % e) traceback.print_exc(file=sys.stdout) if __name__ == '__main__': main()
StarcoderdataPython
8120412
from django.db import models from django.db.models import DO_NOTHING from django.urls import reverse from apps.courses.models import Course, LessonScript from apps.users.models import Student, Teacher # Archwizacja grupy? # from django.core.exceptions import ValidationError class Group(models.Model): teacher = models.ForeignKey( Teacher, on_delete=models.SET_NULL, blank=True, null=True ) students = models.ManyToManyField(Student, blank=True) course = models.ForeignKey(Course, on_delete=models.SET_NULL, blank=True, null=True) # school MONDAY = 1 TUESDAY = 2 WEDNESDAY = 3 THURSDAY = 4 FRIDAY = 5 SATURDAY = 6 WEEK_DAY_CHOICES = ( (MONDAY, "Monday"), (TUESDAY, "Tuesday"), (WEDNESDAY, "Wednesday"), (THURSDAY, "Thursday"), (FRIDAY, "Friday"), (SATURDAY, "Saturday"), ) week_day = models.SmallIntegerField(choices=WEEK_DAY_CHOICES) start_time = models.TimeField() end_time = models.TimeField() class Meta: ordering = ("week_day",) def get_absolute_url(self): return reverse("groups:group-detail", kwargs={"pk": self.id}) def __str__(self): return f"{self.get_week_day_display()} / {self.course} / {self.start_time} - {self.end_time} " class Lesson(models.Model): group = models.ForeignKey(Group, on_delete=models.CASCADE, unique=False) number = models.SmallIntegerField(default=None) teacher = models.ForeignKey( Teacher, on_delete=models.SET_NULL, blank=True, null=True, unique=False ) lesson_script = models.ForeignKey( LessonScript, on_delete=models.SET_NULL, blank=True, null=True ) date = models.DateField(blank=True, null=True) start_time = models.TimeField(blank=True, null=True) end_time = models.TimeField(blank=True, null=True) is_started = models.BooleanField(default=False) is_ended = models.BooleanField(default=False) class Meta: ordering = ("number",) def __str__(self): return f"{self.group} / {self.number}" def get_absolute_url(self): group_id = self.group.pk return reverse( "groups:lesson-detail", kwargs={"pk": self.pk, "group_id": group_id} ) # dodać walidacje czasu # def clean(self): # if self.start_date >= self.end_date: # raise ValidationError("End date cannot be before start date") class StudentPresence(models.Model): student = models.ForeignKey( Student, on_delete=DO_NOTHING, ) lesson = models.ForeignKey(Lesson, on_delete=models.CASCADE) is_present = models.BooleanField(default=False)
StarcoderdataPython
8054278
n1 = int(input('Digite um número para calcular o fatorial dele:\n')) c = n1 mult = 1 while c > 0: print('{}'.format(c), end='') mult = mult * c c -= 1 print('x' if c >= 1 else '=', end='') print(mult)
StarcoderdataPython
6406549
from flask import render_template, request import os import nltk import re import pandas as pd import numpy as np import csv from sentipt.sentipt import SentimentIntensityAnalyzer import plotly.express as px def init_app(app): @app.route("/process") def result(): training_set = [] with open('./query.csv') as csvfile: reader = csv.DictReader(csvfile) for row in reader: training_set.append((row['text'])) os.remove('./query.csv') s = SentimentIntensityAnalyzer() def classificate(training_set): df = pd.DataFrame(columns=["neg", "neu", "pos", "compound"]) for i in range(len(training_set)): e = s.polarity_scores(training_set[i]) df = df.append(e, ignore_index=True) return df data = classificate(training_set) labels = ["Positivos","Negativos"] # ,"Neutros"] cmap = pd.Series(["blue","red"]) #neutro = data["neu"].astype(np.float16).sum() positivo = data["pos"].astype(np.float16).sum() negativo = data["neg"].astype(np.float16).sum() values = [positivo, negativo]#, neutro] fig = px.pie(data, values=values, names=labels, color=cmap, width=800, height=800, hole=.3) fig.write_html('tcrawler/templates/plot.html', auto_open=False) return render_template("result.html")
StarcoderdataPython
8033752
<filename>chatette/modifiers/__init__.py """ Module `chatette.modifiers` Contains everything that is related to modifiers (at the moment only their representation and not generation behavior). """
StarcoderdataPython
8124454
<filename>mundo-1/usando-modulos/ex018.py from math import sin, cos, tan, radians ang = int(input('Insira um ângulo aqui: ')) print('Funções trigonométricas resultantes', end=' --> ') print('Seno: {:.2f}, cosseno: {:.2f} e tangente {:.2f}'.format(sin(radians(ang)), cos(radians(ang)), tan(radians(ang))))
StarcoderdataPython
9675052
def foo(a, b): return a - b + 2 * 42
StarcoderdataPython
9694986
#! /usr/bin/env python3 # Copyright (C) 2017 <NAME>. All Rights Reserved. import unittest from pyparsing import * def get_grammar(debug=False): grammar = Forward() identifier = Word( alphas ) bools = Word("false").setParseAction(lambda s,l,t: False) \ | Word("true").setParseAction(lambda s,l,t: True) integer = Word( nums ).setParseAction(lambda s,l,t: int(t[0])) special = "$eot" lp = Suppress(Literal("(")) rp = Suppress(Literal(")")) ListItem = Literal("ListItem") + lp + grammar + rp ListItem = ListItem.setParseAction(lambda s,l,t: [t[1:len(t)]]) ListEmpty = Literal(".List") ListEmpty = ListEmpty.setParseAction(lambda s,l,t: []) List = (ListEmpty | OneOrMore(ListItem)) List = List.setParseAction(lambda s,l,t: [[i for sublist in t for i in sublist]]) SetItem = Literal("SetItem") + lp + grammar + rp SetItem = SetItem.setParseAction(lambda s,l,t: set(t[1:len(t)])) SetEmpty = Literal(".Set") SetEmpty = SetEmpty.setParseAction(lambda s,l,t: set()) Set = (SetEmpty | OneOrMore(SetItem)) Set = Set.setParseAction(lambda s,l,t: {i for Set in t for i in Set}) MapEmpty = Literal(".Map") MapEmpty = MapEmpty.setParseAction(lambda s,l,t: {}) MapArrow = Literal("|->") MapKey = integer | identifier MapItem = MapKey + MapArrow + grammar MapItem = MapItem.setParseAction(lambda s,l,t: {t[0]:t[2]}) Map = (MapEmpty | OneOrMore(MapItem)) Map = Map.setParseAction(lambda s, l, t: {k: v for d in t for k, v in d.items()}) grammar << (List | Set | Map | integer | bools | special | identifier | lp + grammar + rp ) return grammar def translate(kstr, grammar=None): if grammar == None: grammar = get_grammar() return grammar.parseString(kstr).asList()[0] class test(unittest.TestCase): def test_list(self): kstr = "ListItem(1)" self.assertEqual(translate(kstr), [1]) kstr = "ListItem(1) ListItem(2)" self.assertEqual(translate(kstr), [1, 2]) kstr = "ListItem(ListItem(ListItem ( ListItem ( 42 ) ListItem ( .Map ) ListItem ( .Set ) )))" self.assertEqual(translate(kstr), [[[[42, {}, set()]]]]) kstr = "ListItem(ListItem ( ListItem ( 42 ) ListItem ( .Map ) ListItem ( .Set ) )))" self.assertEqual(translate(kstr), [[[42, {}, set()]]]) pass def test_map(self): kstr = "x |-> ( 2 |-> 0 6 |-> 42 10 |-> 0 ) y |-> ( 9 |-> 24 3 |-> 0)" self.assertEqual(translate(kstr), {'x': {2: 0, 6: 42, 10: 0}, 'y': {9: 24, 3: 0}}) pass def test_set(self): kstr = "x |-> ( SetItem ( 2 ) SetItem ( 6 ) SetItem ( 10 ) ) y |-> ( SetItem ( 3 ) SetItem ( 9 ) )" self.assertEqual(translate(kstr), {'x' : {2, 6, 10}, 'y' : {3, 9}}) pass def test_eot(self): kstr = "ListItem ( ListItem ( $eot ) ListItem ( .Map ) ListItem ( .Set ) ) ListItem ( ListItem ( 10 ) ListItem ( .Map ) ListItem ( .Set ) )" self.assertEqual(translate(kstr), [['$eot', {}, set()], [10, {}, set()]]) pass def test_bools(self): self.assertEqual(translate("false"), False) self.assertEqual(translate("true"), True) pass if __name__ == "__main__": unittest.main()
StarcoderdataPython
1966810
<filename>ccut/tests/dimension_test.py from ..main.dimension import DimensionVector def test(): assert DimensionVector().set_dimensions("M1.1").raise_to_power(2).get_abbr() == 'M2.2' assert DimensionVector().set_dimensions("M1.1 L-1.2").raise_to_power(2).get_abbr() == 'M2.2 L-2.4' assert DimensionVector().set_dimensions("M").raise_to_power(1).get_abbr() == 'M' assert DimensionVector().set_dimensions("M L T").raise_to_power(2).get_abbr() == 'M2 L2 T2' assert str((DimensionVector().set_dimensions("M L2 D2") + DimensionVector().set_dimensions( "L3 Te-1 D-3")).get_dimension_vector()) == "[M 1.0, L 5.0, T 0, I 0, Te -1.0, N 0, J 0, D -1.0, C 0, B 0, U 0]" assert str(DimensionVector().set_dimensions( "M L2 Te-1").get_dimension_vector()) == "[M 1.0, L 2.0, T 0, I 0, Te -1.0, N 0, J 0, D 0, C 0, B 0, U 0]" assert DimensionVector().set_dimensions("M").get_abbr() == "M" assert DimensionVector().set_dimensions("L2").get_abbr() == "L2" assert DimensionVector().set_dimensions("L2 T-2").get_abbr() == "L2 T-2" assert DimensionVector().set_dimensions("T-2 L2").get_abbr() == "L2 T-2" assert DimensionVector().set_dimensions("T-2.0 L2.1").get_abbr() == "L2.1 T-2" assert DimensionVector().set_dimensions("C D J N Te I T L M").get_abbr() == "M L T I Te N J D C" assert DimensionVector().set_dimensions("T2.0 L2.1").get_abbr() == "L2.1 T2" assert DimensionVector().set_dimensions("Te3 T3").get_abbr() == "T3 Te3"
StarcoderdataPython
1912517
"""Sample script to demonstrate usage of the DataAcquisitionClient.""" def main(): """Creates a sample client that reads data from a TCP server (see demo/server.py). Data is written to a rawdata.csv file, as well as a buffer.db sqlite3 database. These files are written in whichever directory the script was run. The client can be stopped with a Keyboard Interrupt (Ctl-C).""" import time import sys from psychopy import clock # Allow the script to be run from the bci root, acquisition dir, or # demo dir. sys.path.append('.') sys.path.append('..') sys.path.append('../..') from bcipy.acquisition.client import DataAcquisitionClient from bcipy.acquisition.devices import supported_device from bcipy.acquisition.protocols.dsi.dsi_connector import DsiConnector # Start the server with the command: # python bcipy/acquisition/datastream/tcp_server.py --name DSI --port 9000 device_spec = supported_device('DSI') connection_params = {'host': '127.0.0.1', 'port': 9000} connector = DsiConnector(connection_params=connection_params, device_spec=device_spec) # Use default processor (FileWriter), buffer, and clock. client = DataAcquisitionClient(connector=connector, clock=clock.Clock()) try: client.start_acquisition() print("\nCollecting data for 3s... (Interrupt [Ctl-C] to stop)\n") while True: time.sleep(3) print(f"Number of samples: {client.get_data_len()}") client.stop_acquisition() client.cleanup() break except IOError as e: print(f'{e.strerror}; make sure you started the server.') except KeyboardInterrupt: print("Keyboard Interrupt") client.stop_acquisition() client.cleanup() if __name__ == '__main__': main()
StarcoderdataPython
6564178
<gh_stars>0 from django.conf import settings from django_pgpy.defaults import get_default_restorers DJANGO_PGPY_DEFAULT_RESTORERS = getattr(settings, 'DJANGO_PGPY_DEFAULT_RESTORERS', get_default_restorers) DJANGO_PGPY_AES_KEY_LENGTH = 32 DJANGO_PGPY_RSA_KEY_LENGTH = 2048
StarcoderdataPython
93679
<reponame>elwoodxblues/saleor<gh_stars>1000+ # -*- coding: utf-8 -*- # Generated by Django 1.10.5 on 2017-02-06 10:07 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [("account", "0008_auto_20161115_1011")] replaces = [("userprofile", "0009_auto_20170206_0407")] operations = [ migrations.AlterModelOptions( name="address", options={"verbose_name": "address", "verbose_name_plural": "addresses"}, ), migrations.AlterModelOptions( name="user", options={"verbose_name": "user", "verbose_name_plural": "users"}, ), migrations.AlterField( model_name="user", name="addresses", field=models.ManyToManyField( blank=True, to="account.Address", verbose_name="addresses" ), ), migrations.AlterField( model_name="user", name="email", field=models.EmailField(max_length=254, unique=True, verbose_name="email"), ), ]
StarcoderdataPython
9758319
x = [int(i) for i in input().split()] if x[0] % x[1] == 0 or x[1] % x[0] == 0: print("Sao Multiplos") else: print("Nao sao Multiplos")
StarcoderdataPython
11288887
<reponame>carlio/pep8 #: E401 import os, sys #: Okay import os import sys from subprocess import Popen, PIPE from myclass import MyClass from foo.bar.yourclass import YourClass import myclass import foo.bar.yourclass #: E402 __all__ = ['abc'] import foo #: Okay try: import foo except: pass else: print('imported foo') finally: print('made attempt to import foo') import bar #: E402 VERSION = '1.2.3' import foo #: E402 import foo a = 1 import bar
StarcoderdataPython
3491014
# vim: tabstop=4 shiftwidth=4 softtabstop=4 # Copyright 2010 United States Government as represented by the # Administrator of the National Aeronautics and Space Administration. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import unittest import webob from nova import context from nova import flags from nova import test from nova.api import ec2 from nova.auth import manager FLAGS = flags.FLAGS class FakeControllerClass(object): pass class FakeApiRequest(object): def __init__(self, action): self.controller = FakeControllerClass() self.action = action class AccessTestCase(test.TestCase): def _env_for(self, ctxt, action): env = {} env['ec2.context'] = ctxt env['ec2.request'] = FakeApiRequest(action) return env def setUp(self): super(AccessTestCase, self).setUp() um = manager.AuthManager() self.context = context.get_admin_context() # Make test users self.testadmin = um.create_user('testadmin') self.testpmsys = um.create_user('testpmsys') self.testnet = um.create_user('testnet') self.testsys = um.create_user('testsys') # Assign some rules um.add_role('testadmin', 'cloudadmin') um.add_role('testpmsys', 'sysadmin') um.add_role('testnet', 'netadmin') um.add_role('testsys', 'sysadmin') # Make a test project self.project = um.create_project('testproj', 'testpmsys', 'a test project', ['testpmsys', 'testnet', 'testsys']) self.project.add_role(self.testnet, 'netadmin') self.project.add_role(self.testsys, 'sysadmin') #user is set in each test def noopWSGIApp(environ, start_response): start_response('200 OK', []) return [''] self.mw = ec2.Authorizer(noopWSGIApp) self.mw.action_roles = {'FakeControllerClass': { '_allow_all': ['all'], '_allow_none': [], '_allow_project_manager': ['projectmanager'], '_allow_sys_and_net': ['sysadmin', 'netadmin'], '_allow_sysadmin': ['sysadmin']}} def tearDown(self): um = manager.AuthManager() # Delete the test project um.delete_project('testproj') # Delete the test user um.delete_user('testadmin') um.delete_user('testpmsys') um.delete_user('testnet') um.delete_user('testsys') super(AccessTestCase, self).tearDown() def response_status(self, user, methodName): ctxt = context.RequestContext(user, self.project) environ = self._env_for(ctxt, methodName) req = webob.Request.blank('/', environ) resp = req.get_response(self.mw) return resp.status_int def shouldAllow(self, user, methodName): self.assertEqual(200, self.response_status(user, methodName)) def shouldDeny(self, user, methodName): self.assertEqual(401, self.response_status(user, methodName)) def test_001_allow_all(self): users = [self.testadmin, self.testpmsys, self.testnet, self.testsys] for user in users: self.shouldAllow(user, '_allow_all') def test_002_allow_none(self): self.shouldAllow(self.testadmin, '_allow_none') users = [self.testpmsys, self.testnet, self.testsys] for user in users: self.shouldDeny(user, '_allow_none') def test_003_allow_project_manager(self): for user in [self.testadmin, self.testpmsys]: self.shouldAllow(user, '_allow_project_manager') for user in [self.testnet, self.testsys]: self.shouldDeny(user, '_allow_project_manager') def test_004_allow_sys_and_net(self): for user in [self.testadmin, self.testnet, self.testsys]: self.shouldAllow(user, '_allow_sys_and_net') # denied because it doesn't have the per project sysadmin for user in [self.testpmsys]: self.shouldDeny(user, '_allow_sys_and_net') if __name__ == "__main__": # TODO: Implement use_fake as an option unittest.main()
StarcoderdataPython
281550
<reponame>Nova-Noir/novabot_v2 from nonebot import get_driver global_config = get_driver().config # nickname: str = list(global_config.nickname)[-1] # Yet this will return a randomly one. nickname: str = "伊蕾娜"
StarcoderdataPython
1972267
from datek_jaipur.domain.compound_types.goods import GoodsType from datek_jaipur.errors import EventValidationError class GoodsBoughtValidationError(EventValidationError): pass class TooMuchCardsInHandError(GoodsBoughtValidationError): pass class CardNotOnDeckError(GoodsBoughtValidationError): def __init__(self, goods_type: GoodsType): self.goods_type = goods_type
StarcoderdataPython
3285979
<gh_stars>1-10 """Rest API for Demo.""" from chalice import Chalice from chalice import Response from demo_dao import DemoDao from util.logger_utility import LoggerUtility APP = Chalice(app_name='ramit-test') APP.debug = True @APP.route('/info', methods=['POST']) def info(): """Info on user.""" # Set log level LoggerUtility.set_level() try: request = APP.current_request demo_dao = DemoDao(request.json_body) response = demo_dao.info() LoggerUtility.log_info('API Invoke sucessfully!') return Response(response, status_code=200) except UserNotFoundException as user_not_found_exception: body = {'Code': '404 - UserNotFound', 'Message': str(user_not_found_exception)} return Response(body, status_code=404) except Exception as exception: body = {'Code': '500- InternalServerError', 'Message': str(exception)} return Response(body, status_code=500) @APP.route('/favorite-shows', methods=['GET']) def favorite_shows(): """My Favourite Shows.""" # Set log level LoggerUtility.set_level() try: request = APP.current_request demo_dao = DemoDao(request.json_body) response = demo_dao.favorite_shows() return Response(response, status_code=200) except Exception as exception: body = {'Code': '500- InternalServerError', 'Message': str(exception)} return Response(body, status_code=500)
StarcoderdataPython
4928948
import logging from multiprocessing import Manager import pytest from tx.readable_log import getLogger, format_message from tx.parallex.objectstore import PlasmaStore, SimpleStore logger = getLogger(__name__, logging.INFO) @pytest.fixture def manager(): with Manager() as manager: yield manager @pytest.fixture(params=[lambda manager: PlasmaStore(manager, 100000), SimpleStore]) def object_store(manager, request): p = request.param(manager) try: p.init() yield p except: p.shutdown()
StarcoderdataPython
3332082
from github import Github import argparse import os import requests import json import re from difflib import get_close_matches from urllib.parse import urlparse def setup_args(): parser = argparse.ArgumentParser() parser.add_argument("--token", help="A GitHub token for the repo") return parser.parse_args() def fuzzy_review_comment_check(comment_body): first_word = comment_body.split()[0] if first_word != "⚠️": first_word = re.sub('[^A-Za-z0-9]+', '', first_word) #removing special character match = get_close_matches(first_word, pref_list, cutoff=0.8) if not match: return False else: return True def parse_review_comment(data, github): for comment in data: if "in_reply_to_id" not in comment: if not fuzzy_review_comment_check(comment["body"]): review_comment_edit(comment["id"], github, comment["body"]) def review_comment_edit(id, github, body): url = "https://api.github.com/repos/{}/pulls/comments/{}".format( repository_name, id ) headers = { "Accept": "application/vnd.github.v3+json", "Authorization": "Bearer " + str(github), } print(headers) payload = { "body": "⚠️ " + str(body) + " \n\n⚠️ [PR Comment Etiquette](https://github.com/HomeXLabs/reviewington/blob/main/docs/pr_etiquette.md) not followed on above comment ⚠️" } resp = requests.patch(url=url, headers=headers, data=json.dumps(payload)) def main(): global repository_name global pref_list global pr job_name = os.environ["GITHUB_WORKFLOW"] repository_name = os.environ["GITHUB_REPOSITORY"] git_ref = os.environ["GITHUB_REF"] # setup arguments args = setup_args() github = args.token pref_list = [ "Change", "Question", "Concern", "Discussion", "Praise", "Suggestion", "Nitpick", "Guide", "⚠️ ", ] pr = git_ref.split("/")[2] url = "https://api.github.com/repos/{}/pulls/{}/comments".format( repository_name, pr ) headers = { "Accept": "application/vnd.github.v3+json", "Authorization": "Bearer " + str(github), } resp = requests.get(url=url, headers=headers) data = resp.json() parse_review_comment(data, github) if __name__ == "__main__": main()
StarcoderdataPython
9658639
<gh_stars>10-100 # Copyright (c) 2012-2015 Netforce Co. Ltd. # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. # IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, # DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR # OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE # OR OTHER DEALINGS IN THE SOFTWARE. from .field import * from .char import * from .float import * from .integer import * from .boolean import * from .text import * from .selection import * from .date import * from .datetime import * from .time import * from .binary import * from .many2one import * from .one2many import * from .many2many import * from .reference import * from .file import * from .json import * from .reference import * from .decimal import *
StarcoderdataPython
5194504
import numpy as np from scipy.signal import stft SOUND_SPEED = 340 # [m/s] # Steering vectors def compute_steering_vectors_single_frequency(array_geometry, frequency, theta_grid, phi_grid): # wave number k = 2*np.pi*frequency/SOUND_SPEED n_mics = len(array_geometry[0]) theta_grid = theta_grid * np.pi/180 # [degree] to [radian] phi_grid = phi_grid * np.pi/180 # [degree] to [radian] u = np.sin(theta_grid.reshape(-1, 1)).dot(np.cos(phi_grid).reshape(1, -1)) v = np.sin(theta_grid.reshape(-1, 1)).dot(np.sin(phi_grid).reshape(1, -1)) w = np.tile(np.cos(theta_grid.reshape(-1, 1)), (1, phi_grid.shape[0])) x = u.reshape(u.shape[0], u.shape[1], 1)*array_geometry[0].reshape(1, 1, n_mics) y = v.reshape(v.shape[0], v.shape[1], 1)*array_geometry[1].reshape(1, 1, n_mics) z = w.reshape(w.shape[0], w.shape[1], 1)*array_geometry[2].reshape(1, 1, n_mics) return np.exp( -1j*k*(x + y + z)) def compute_steering_vectors(array_geometry, sampling_frequency, n_fft, theta_grid, phi_grid): n_thetas = len(theta_grid) n_phis = len(phi_grid) n_mics = len(array_geometry[0]) steering_vectors = np.zeros((n_fft, n_thetas, n_phis, n_mics), dtype=np.complex64) for i_fft in range(n_fft): frequency = (i_fft / n_fft) * (sampling_frequency/2) steering_vectors[i_fft] = compute_steering_vectors_single_frequency(array_geometry, frequency, theta_grid, phi_grid) return steering_vectors def compute_sinr_2(source_tf_multichannel, interference_tf_multichannel): source_power = 0 interference_power = 0 n_fft_bins = source_tf_multichannel.shape[0] for i_f in range(n_fft_bins): source_power += np.trace(source_stft_multichannel[i_f].dot(source_stft_multichannel[i_f].transpose().conjugate())) interference_power += np.trace(interference_stft_multichannel[i_f].dot(interference_stft_multichannel[i_f].transpose().conjugate())) return 10*np.log10(np.abs(source_power/interference_power)) def compute_sinr(source_tf_multichannel, interference_tf_multichannel, weights=None): n_fft_bins, n_mics, _ = source_tf_multichannel.shape source_power = 0 interference_power = 0 if weights is not None: for i_f in range(n_fft_bins): source_power += weights[i_f].reshape(n_mics, 1).transpose().conjugate().dot( source_tf_multichannel[i_f].dot( source_tf_multichannel[i_f].transpose().conjugate())).dot( weights[i_f].reshape(n_mics, 1)) interference_power += weights[i_f].transpose().conjugate().dot( interference_tf_multichannel[i_f].dot( interference_tf_multichannel[i_f].transpose().conjugate())).dot( weights[i_f]) else: for i_f in range(n_fft_bins): source_power += np.trace(source_tf_multichannel[i_f].dot(source_tf_multichannel[i_f].transpose().conjugate())) interference_power += np.trace(interference_tf_multichannel[i_f].dot(interference_tf_multichannel[i_f].transpose().conjugate())) return 10*np.log10(np.abs(source_power/interference_power)) def compute_mvdr_tf_beamformers(source_steering_vectors, tf_frames_multichannel, diagonal_loading_param=1): n_fft_bins, n_mics = source_steering_vectors.shape mvdr_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): n_frames = tf_frames_multichannel.shape[1] R = 1./n_frames * tf_frames_multichannel[i_fft_bin].dot(tf_frames_multichannel[i_fft_bin].transpose().conjugate()) \ + diagonal_loading_param*np.identity(n_mics, dtype=np.complex64) invR = np.linalg.inv(R) normalization_factor = source_steering_vectors[i_fft_bin, :].transpose().conjugate().dot(invR).dot(source_steering_vectors[i_fft_bin, :]) mvdr_tf_beamformers[i_fft_bin] = invR.dot(source_steering_vectors[i_fft_bin, :]) / (normalization_factor) return mvdr_tf_beamformers def compute_mvndr_tf_beamformers(source_steering_vectors, tf_frames_multichannel, regularization_param=1): # Minimum variance near-distortless response beamformers # w = argmin w^H*R*w + \lambda * (v_s^H*w - 1)^2 n_fft_bins, n_mics = source_steering_vectors.shape mvndr_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): # R = tf_frames_multichannel[i_fft_bin].dot(tf_frames_multichannel[i_fft_bin].transpose().conjugate()) + np.identity(n_mics) # invR = np.linalg.inv(R) # normalization_factor = source_steering_vectors[i_fft_bin, :].transpose().conjugate().dot(invR).dot(source_steering_vectors[i_fft_bin, :]) # regularization_param = 1/normalization_factor R = tf_frames_multichannel[i_fft_bin].dot(tf_frames_multichannel[i_fft_bin].transpose().conjugate())\ + np.identity(n_mics)\ + regularization_param*source_steering_vectors[i_fft_bin, :]*source_steering_vectors[i_fft_bin, :].transpose().conjugate() invR = np.linalg.inv(R) mvndr_tf_beamformers[i_fft_bin] = regularization_param*invR.dot(source_steering_vectors[i_fft_bin, :]) return mvndr_tf_beamformers def compute_lcmv_tf_beamformers(steering_vectors, tf_frames_multichannel, constraint_vector): n_fft_bins, n_mics, n_steering_vectors = steering_vectors.shape lcmv_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): n_samples = len(tf_frames_multichannel[i_fft_bin]) R = 1./n_samples * (tf_frames_multichannel[i_fft_bin].dot( tf_frames_multichannel[i_fft_bin].transpose().conjugate()) \ + np.identity(n_mics) ) invR = np.linalg.inv(R) normalization_matrix = steering_vectors[i_fft_bin].transpose().conjugate().dot( invR).dot(steering_vectors[i_fft_bin]) normalization_matrix = (1 - 1e-3)*normalization_matrix \ + 1e-3*np.trace(normalization_matrix)/n_steering_vectors * 1*np.identity(n_steering_vectors) inverse_normalization_matrix = np.linalg.inv(normalization_matrix) lcmv_tf_beamformers[i_fft_bin] = invR.dot(steering_vectors[i_fft_bin]).dot( inverse_normalization_matrix).dot(constraint_vector) return lcmv_tf_beamformers def compute_null_controlling_tf_beamformers(source_steering_vectors, null_steering_vectors, tf_frames_multichannel, null_constraint_threshold, eigenvalue_percentage_threshold=0.99): n_fft_bins, n_mics, n_null_steering_vectors = null_steering_vectors.shape nc_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): null_steering_correlation_matrix = null_steering_vectors[i_fft_bin].dot( null_steering_vectors[i_fft_bin].transpose().conjugate()) eigenvalues, eigenvectors = np.linalg.eigh(null_steering_correlation_matrix) running_sums = np.cumsum(np.abs(eigenvalues[-1::-1])) cutoff_index = np.searchsorted(running_sums, eigenvalue_percentage_threshold * running_sums[-1]) eigenvectors = eigenvectors[:, len(eigenvalues)-cutoff_index-1:] steering_vectors = np.hstack((source_steering_vectors[i_fft_bin].reshape(-1, 1), eigenvectors)) n_samples = len(tf_frames_multichannel[i_fft_bin]) R = 1./n_samples * (tf_frames_multichannel[i_fft_bin].dot( tf_frames_multichannel[i_fft_bin].transpose().conjugate()) \ + np.identity(n_mics) ) invR = np.linalg.inv(R) normalization_matrix = steering_vectors.transpose().conjugate().dot( invR).dot(steering_vectors) """ Regularization for dealing with ill-conditionaed normalization matrix Ref: <NAME>, <NAME>, "Source reconstruction of broadband EEG/MEG data using the frequency-adaptive broadband (FAB) beamformer", bioRxiv Equation (12) in https://www.biorxiv.org/content/biorxiv/early/2018/12/20/502690.full.pdf """ normalization_matrix = (1 - 1e-3)*normalization_matrix \ + 1e-3*np.trace(normalization_matrix)/steering_vectors.shape[1] * 10*np.identity(steering_vectors.shape[1]) inverse_normalization_matrix = np.linalg.inv(normalization_matrix) constraint_vector = null_constraint_threshold*np.ones(steering_vectors.shape[1]) constraint_vector[0] = 1 nc_tf_beamformers[i_fft_bin] = invR.dot(steering_vectors).dot( inverse_normalization_matrix).dot(constraint_vector) return nc_tf_beamformers def compute_null_controlling_tf_beamformers_2(source_steering_vectors, null_steering_vectors, tf_sample_covariance_batch, null_constraint_threshold, eigenvalue_percentage_threshold=0.99, diagonal_loading_param=1): n_fft_bins, n_mics, n_null_steering_vectors = null_steering_vectors.shape nc_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): null_steering_correlation_matrix = null_steering_vectors[i_fft_bin].dot( null_steering_vectors[i_fft_bin].transpose().conjugate()) eigenvalues, eigenvectors = np.linalg.eigh(null_steering_correlation_matrix) running_sums = np.cumsum(np.abs(eigenvalues[-1::-1])) cutoff_index = np.searchsorted(running_sums, eigenvalue_percentage_threshold * running_sums[-1]) eigenvectors = eigenvectors[:, len(eigenvalues)-cutoff_index-1:] steering_vectors = np.hstack((source_steering_vectors[i_fft_bin].reshape(-1, 1), eigenvectors)) R = np.sum(tf_sample_covariance_batch[:, i_fft_bin, :, :], axis=0) / len(tf_sample_covariance_batch) + diagonal_loading_param*np.identity(n_mics) invR = np.linalg.inv(R) normalization_matrix = steering_vectors.transpose().conjugate().dot( invR).dot(steering_vectors) """ Regularization for dealing with ill-conditionaed normalization matrix Ref: <NAME>, <NAME>, "Source reconstruction of broadband EEG/MEG data using the frequency-adaptive broadband (FAB) beamformer", bioRxiv Equation (12) in https://www.biorxiv.org/content/biorxiv/early/2018/12/20/502690.full.pdf """ normalization_matrix = (1 - 1e-3)*normalization_matrix \ + 1e-3*np.trace(normalization_matrix)/steering_vectors.shape[1] * 10*np.identity(steering_vectors.shape[1]) inverse_normalization_matrix = np.linalg.inv(normalization_matrix) constraint_vector = null_constraint_threshold*np.ones(steering_vectors.shape[1]) constraint_vector[0] = 1 nc_tf_beamformers[i_fft_bin] = invR.dot(steering_vectors).dot( inverse_normalization_matrix).dot(constraint_vector) return nc_tf_beamformers def compute_null_controlling_minibatch_tf_beamformers(source_steering_vectors, null_steering_vectors, tf_frames_multichannel_batch, null_constraint_threshold, eigenvalue_percentage_threshold=0.99): n_fft_bins, n_mics, n_null_steering_vectors = null_steering_vectors.shape nc_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): null_steering_correlation_matrix = null_steering_vectors[i_fft_bin].dot( null_steering_vectors[i_fft_bin].transpose().conjugate()) eigenvalues, eigenvectors = np.linalg.eigh(null_steering_correlation_matrix) running_sums = np.cumsum(np.abs(eigenvalues[-1::-1])) cutoff_index = np.searchsorted(running_sums, eigenvalue_percentage_threshold * running_sums[-1]) eigenvectors = eigenvectors[:, len(eigenvalues)-cutoff_index-1:] steering_vectors = np.hstack((source_steering_vectors[i_fft_bin].reshape(-1, 1), eigenvectors)) R = np.zeros((n_mics, n_mics), dtype=np.complex64) for tf_frames_multichannel in tf_frames_multichannel_batch: n_samples = len(tf_frames_multichannel[i_fft_bin]) R += 1./n_samples * (tf_frames_multichannel[i_fft_bin].dot( tf_frames_multichannel[i_fft_bin].transpose().conjugate())) R = R / len(tf_frames_multichannel_batch) R += 20*np.identity(n_mics) # To prevent singularity of R invR = np.linalg.inv(R) normalization_matrix = steering_vectors.transpose().conjugate().dot( invR).dot(steering_vectors) """ Regularization for dealing with ill-conditionaed normalization matrix Ref: <NAME>, <NAME>, "Source reconstruction of broadband EEG/MEG data using the frequency-adaptive broadband (FAB) beamformer", bioRxiv Equation (12) in https://www.biorxiv.org/content/biorxiv/early/2018/12/20/502690.full.pdf """ normalization_matrix = (1 - 1e-3)*normalization_matrix \ + 1e-3*np.trace(normalization_matrix)/steering_vectors.shape[1] * 10*np.identity(steering_vectors.shape[1]) inverse_normalization_matrix = np.linalg.inv(normalization_matrix) constraint_vector = null_constraint_threshold*np.ones(steering_vectors.shape[1]) constraint_vector[0] = 1 nc_tf_beamformers[i_fft_bin] = invR.dot(steering_vectors).dot( inverse_normalization_matrix).dot(constraint_vector) return nc_tf_beamformers def simulate_multichannel_tf(array_geometry, signal, theta, phi, sampling_frequency, stft_params): n_mics = len(array_geometry[0]) n_samples_per_frame = stft_params["n_samples_per_frame"] n_fft_bins = stft_params["n_fft_bins"] hop_size = stft_params["hop_size"] stft_window = stft_params["window"] steering_vector = ( compute_steering_vectors(array_geometry, sampling_frequency, n_fft_bins, theta, phi) )[:, 0, 0, :] _, _, tf_frames = stft(signal.reshape(-1), fs=sampling_frequency, window=stft_window, nperseg=n_samples_per_frame, noverlap=n_samples_per_frame-hop_size, nfft=n_samples_per_frame, padded=True) tf_frames = tf_frames[:-1, 1:-1] tf_frames_multichannel = steering_vector.reshape(n_fft_bins, n_mics, 1)\ * tf_frames.reshape(tf_frames.shape[0], 1, tf_frames.shape[1]) return tf_frames_multichannel def simulate_multichannel_tf_circular(array_geometry, signal, azimuth, sampling_frequency, stft_params): n_mics = len(array_geometry[0]) n_samples_per_frame = stft_params["n_samples_per_frame"] n_fft_bins = stft_params["n_fft_bins"] hop_size = stft_params["hop_size"] stft_window = stft_params["window"] steering_vector = ( compute_steering_vectors_circular(array_geometry, sampling_frequency, stft_params, azimuth) )[:, 0, :] _, _, tf_frames = stft(signal.reshape(-1), fs=sampling_frequency, window=stft_window, nperseg=n_samples_per_frame, noverlap=n_samples_per_frame-hop_size, nfft=n_samples_per_frame, padded=True) tf_frames = tf_frames[:-1, 1:-1] tf_frames_multichannel = steering_vector.reshape(n_fft_bins, n_mics, 1)\ * tf_frames.reshape(tf_frames.shape[0], 1, tf_frames.shape[1]) return tf_frames_multichannel def check_distortless_constraint(weight, source_steering_vector, tolerance=1e-9): assert(np.abs(weight.transpose().conjugate().dot(source_steering_vector)) - 1 < tolerance) def compute_steering_vectors_circular(array_geometry, sampling_frequency, stft_params, azimuth_grid): n_mics = len(array_geometry[0]) n_azimuths = len(azimuth_grid) delay = np.zeros((n_azimuths, n_mics), dtype=np.float32) n_samples_per_frame = stft_params["n_samples_per_frame"] n_fft_bins = stft_params["n_fft_bins"] for m in range(n_mics): pos_x = array_geometry[0][m] pos_y = array_geometry[1][m] radius = np.sqrt(pos_x*pos_x + pos_y*pos_y) mic_azimuth = np.arctan2(pos_y, pos_x) for k in range(n_azimuths): azimuth = 2 * np.pi * azimuth_grid[k]/360 delay[k][m] = - radius * np.cos(mic_azimuth - azimuth) * sampling_frequency / SOUND_SPEED steering_vectors = np.zeros((n_fft_bins, n_azimuths, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): v = 2 * np.pi * (i_fft_bin / n_samples_per_frame) * delay; steering_vectors[i_fft_bin] = np.cos(v) - np.sin(v) * 1j return steering_vectors def compute_minimum_variance_tf_beamformers(source_steering_vectors, tf_frames_multichannel=None, diagonal_loading_param=1): n_fft_bins, n_mics = source_steering_vectors.shape mvdr_tf_beamformers = np.zeros((n_fft_bins, n_mics), dtype=np.complex64) for i_fft_bin in range(n_fft_bins): R = diagonal_loading_param*np.identity(n_mics, dtype=np.complex64) if tf_frames_multichannel is not None: n_frames = tf_frames_multichannel.shape[1] R += 1./n_frames * tf_frames_multichannel[i_fft_bin].dot(tf_frames_multichannel[i_fft_bin].transpose().conjugate()) invR = np.linalg.inv(R) normalization_factor = source_steering_vectors[i_fft_bin].transpose().conjugate().dot( invR).dot(source_steering_vectors[i_fft_bin]) mvdr_tf_beamformers[i_fft_bin] = invR.dot(source_steering_vectors[i_fft_bin]) / normalization_factor return mvdr_tf_beamformers
StarcoderdataPython
5189612
<reponame>kloper/pato # -*- python -*- """@file @brief I2C-serial transport for pato Copyright (c) 2014-2015 <NAME> <<EMAIL>>. All rights reserved. @page License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. The views and conclusions contained in the software and documentation are those of the authors and should not be interpreted as representing official policies, either expressed or implied, of the Pato Project. """ from __future__ import absolute_import import serial import time from util.protocol import ProtocolException from bridge import Bridge as BridgeProtocol from bridge.protocol import Cmd class Bridge(object): """ @brief Communication transport using Pato's UART-TWI bridge A simple transport that allows python code running on PC to talk with Pato via UART, while Pato is compiled with TWI (I2C) interface only. This requires python pyserial package to be installed. The main purpose of this transport is automatic E2D testing of various features. """ def __init__(self, slave_addr, timeout=0.3, serial_timeout=10, *args, **kwargs): """ @brief Constructor @param[in] slave_addr TWI address of target Pato device @param[in] timeout timeout value in time.clock() units for the query sequence to be completed. @param[in] serial_timeout timeout value for pyserial communication. @param[in] args extra arguments for pyserial @param[in] kwargs extra keyword arguments for pyserial """ self.serial = serial.Serial(timeout=serial_timeout, *args, **kwargs) self.slave_addr = slave_addr self.bridge = BridgeProtocol(self.serial) self.timeout = timeout def query(self, request): """ @brief Generic query (request/reply) method for UART-TWI bridge. Schedule TWI Write of request packet supplied as a parameter. The write is performed without stop condition. Then, TWI Read for a single reply packet is scheduled. If send and/or receive return unexpected result, the function will retry both send and receive pair until timeout specified in constructor is reached. If during the timeout period send and receive didn't succeeded, @ref ProtocolException is thrown. @param[in] request regular list of bytes representing packet to be sent via the bridge. @returns Received reply packet @throws ProtocolException upon send or receive timeout """ now = time.monotonic() elapsed = now while elapsed - now < self.timeout: (send_status, send_remaining) = \ self.bridge.execute(Cmd.TWI_MASTER_SEND, self.slave_addr, request, 0) (recv_status, recv_remaining, reply) = \ self.bridge.execute( Cmd.TWI_MASTER_RECV, self.slave_addr, 5, 1, 1) elapsed = time.monotonic() if send_remaining + recv_remaining != 0: print("send_remaining: {} status {:02x}".\ format(send_remaining, send_status)) print("recv_remaining: {} status {:02x}".\ format(recv_remaining, recv_status)) continue return reply raise ProtocolException("Failed to query") def close(self): """ @brief Close serial line to bridge """ self.serial.close()
StarcoderdataPython
11245112
<filename>chapter2/2_1_2.py # Calculating the classification result using sample dataset import kNN if __name__ == "__main__": group, labels = kNN.createDataSet() print(group) print(labels) result = kNN.classify0([0, 0], group, labels, 3) print(result)
StarcoderdataPython
3264786
<reponame>kiteco/intellij-plugin from definition import myFunction <caret>myFunction()
StarcoderdataPython
8063079
#!/bin/python3 # Our first python module from gpiozero import Robot import time robby = Robot(left=(7,8), right=(9,10)) robby.backward() time.sleep(20) robby.stop()
StarcoderdataPython
109704
# A simple simulator for SHA+XRAM from mmio import mmiodev, NOP, RD, WR import sha as SHAFunc def as_chars(s, n): b = [] for i in xrange(n): byte = s & 0xff s >>= 8 b.append(byte) return [chr(i) for i in b] def to_num(s, n): num = 0 for i in xrange(n): num |= (ord(s[i]) << (i * 8)) return num class SHA(mmiodev): SHA_IDLE = 0 SHA_RD = 1 SHA_OP1 = 2 SHA_OP2 = 3 SHA_WR = 4 def __init__(self): mmiodev.__init__(self) self.addReg('sha_start', 0xfe00, 1, readonly=True) self.addReg('sha_state', 0xfe01, 1, readonly=True) self.addReg('sha_rdaddr', 0xfe02, 2) self.addReg('sha_wraddr', 0xfe04, 2) self.addReg('sha_len', 0xfe06, 2) self.bytes_read = 0 self.rd_data = [0] * 64 self.hs_data = [0] * 20 self.sha = SHAFunc.new() # Create easy access properties. sha_state = property(lambda s: s.getRegI('sha_state'), lambda s, v: s.setRegI('sha_state', v)) sha_rdaddr = property(lambda s: s.getRegI('sha_rdaddr'), lambda s, v: s.setRegI('sha_rdaddr', v)) sha_wraddr = property(lambda s: s.getRegI('sha_wraddr'), lambda s, v: s.setRegI('sha_wraddr', v)) sha_len = property(lambda s: s.getRegI('sha_len'), lambda s, v: s.setRegI('sha_len', v)) def simulate(self, s_in): cmd = s_in['cmd'] cmdaddr = s_in['cmdaddr'] cmddata = s_in['cmddata'] self.sha_state = s_in['sha_state'] self.sha_rdaddr = s_in['sha_rdaddr'] self.sha_wraddr = s_in['sha_wraddr'] self.sha_len = s_in['sha_len'] self.bytes_read = s_in['sha_bytes_read'] self.rd_data = s_in['sha_rd_data'] self.hs_data = s_in['sha_hs_data'] self.xram = s_in['XRAM'] # default dataout. dataout = 0; # execute command. started = False if cmd == RD: found, data = self.read(cmdaddr) if found: dataout = data s_out = self.s_dict() s_out['dataout'] = dataout return s_out elif cmd == WR and self.sha_state == self.SHA_IDLE: if cmdaddr == 0xfe00: if cmddata == 1: self.sha_state = self.SHA_RD self.bytes_read = 0 started = True else: self.write(cmdaddr, cmddata) # do the operations. if not started and self.sha_state == self.SHA_RD: self.rd_data = 0 for i in xrange(64): addr = (self.sha_rdaddr + self.bytes_read + 63 - i) & 0xffff byte = self.xram[addr] self.rd_data |= byte << (i*8) self.bytes_read = self.bytes_read + 64 self.sha_state = self.SHA_OP1 elif not started and self.sha_state == self.SHA_OP1: self.sha_state = self.SHA_OP2 elif not started and self.sha_state == self.SHA_OP2: if self.bytes_read < self.sha_len: # Need more blk self.sha_state = self.SHA_RD else: self.sha_state = self.SHA_WR bytes_in = bytes(''.join(as_chars(self.rd_data, 64))) self.sha.update(bytes_in) res = self.sha.digest() self.hs_data = to_num(res, 20) elif not started and self.sha_state == self.SHA_WR: for i in xrange(20): addr = (self.sha_wraddr + 19 - i) & 0xffff byte = (self.hs_data >> (i*8)) & 0xff self.xram[addr] = byte self.sha_state = self.SHA_IDLE s_out = self.s_dict() s_out['dataout'] = dataout return s_out def s_dict(self): return { 'sha_state' : self.sha_state, 'sha_rdaddr' : self.sha_rdaddr, 'sha_wraddr' : self.sha_wraddr, 'sha_len' : self.sha_len, 'sha_bytes_read': self.bytes_read, 'sha_rd_data' : self.rd_data, 'sha_hs_data' : self.hs_data, 'XRAM' : self.xram } def testSHA(): sha = SHA() sha.sha_state = 0 assert sha.sha_state == 0 s_in = sha.s_dict() s_in['cmd'] = WR s_in['cmdaddr'] = 0xfe06 s_in['cmddata'] = 128 s_out = sha.simulate(s_in) assert s_out['sha_len'] == 128 s_in = sha.s_dict() s_in['cmd'] = RD s_in['cmdaddr'] = 0xfe06 s_in['cmddata'] = 3 s_out = sha.simulate(s_in) assert s_out['dataout'] == 128 if __name__ == '__main__': testSHA()
StarcoderdataPython
4979343
# Copyright 2021 Seek Thermal Inc. # # Original author: <NAME> <<EMAIL>> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. class SeekCameraVersion: """Version of the seekcamera-python library. The version number scheme is [MAJOR].[MINOR].[PATCH]. Attributes ---------- MAJOR: int Major version number of the library. MINOR: int Minor version number of the library. PATCH: int Patch version number of the library. """ MAJOR = 1 MINOR = 1 PATCH = 1 def __str__(self): return "{}.{}.{}".format(self.MAJOR, self.MINOR, self.PATCH) def __repr__(self): return "SeekCameraVersion({}, {}, {})".format( self.MAJOR, self.MINOR, self.PATCH )
StarcoderdataPython
205661
<gh_stars>1-10 import cv2 import depthai import numpy as np _conf_threshold = 0.5 def get_cv_rotated_rect(bbox, angle): x0, y0, x1, y1 = bbox width = abs(x0 - x1) height = abs(y0 - y1) x = x0 + width * 0.5 y = y0 + height * 0.5 return ((x, y), (width, height), np.rad2deg(angle)) def rotated_Rectangle(bbox, angle): X0, Y0, X1, Y1 = bbox width = abs(X0 - X1) height = abs(Y0 - Y1) x = int(X0 + width * 0.5) y = int(Y0 + height * 0.5) pt1_1 = (int(x + width / 2), int(y + height / 2)) pt2_1 = (int(x + width / 2), int(y - height / 2)) pt3_1 = (int(x - width / 2), int(y - height / 2)) pt4_1 = (int(x - width / 2), int(y + height / 2)) t = np.array([[np.cos(angle), -np.sin(angle), x - x * np.cos(angle) + y * np.sin(angle)], [np.sin(angle), np.cos(angle), y - x * np.sin(angle) - y * np.cos(angle)], [0, 0, 1]]) tmp_pt1_1 = np.array([[pt1_1[0]], [pt1_1[1]], [1]]) tmp_pt1_2 = np.dot(t, tmp_pt1_1) pt1_2 = (int(tmp_pt1_2[0][0]), int(tmp_pt1_2[1][0])) tmp_pt2_1 = np.array([[pt2_1[0]], [pt2_1[1]], [1]]) tmp_pt2_2 = np.dot(t, tmp_pt2_1) pt2_2 = (int(tmp_pt2_2[0][0]), int(tmp_pt2_2[1][0])) tmp_pt3_1 = np.array([[pt3_1[0]], [pt3_1[1]], [1]]) tmp_pt3_2 = np.dot(t, tmp_pt3_1) pt3_2 = (int(tmp_pt3_2[0][0]), int(tmp_pt3_2[1][0])) tmp_pt4_1 = np.array([[pt4_1[0]], [pt4_1[1]], [1]]) tmp_pt4_2 = np.dot(t, tmp_pt4_1) pt4_2 = (int(tmp_pt4_2[0][0]), int(tmp_pt4_2[1][0])) points = np.array([pt1_2, pt2_2, pt3_2, pt4_2]) return points def non_max_suppression(boxes, probs=None, angles=None, overlapThresh=0.3): # if there are no boxes, return an empty list if len(boxes) == 0: return [], [] # if the bounding boxes are integers, convert them to floats -- this # is important since we'll be doing a bunch of divisions if boxes.dtype.kind == "i": boxes = boxes.astype("float") # initialize the list of picked indexes pick = [] # grab the coordinates of the bounding boxes x1 = boxes[:, 0] y1 = boxes[:, 1] x2 = boxes[:, 2] y2 = boxes[:, 3] # compute the area of the bounding boxes and grab the indexes to sort # (in the case that no probabilities are provided, simply sort on the bottom-left y-coordinate) area = (x2 - x1 + 1) * (y2 - y1 + 1) idxs = y2 # if probabilities are provided, sort on them instead if probs is not None: idxs = probs # sort the indexes idxs = np.argsort(idxs) # keep looping while some indexes still remain in the indexes list while len(idxs) > 0: # grab the last index in the indexes list and add the index value to the list of picked indexes last = len(idxs) - 1 i = idxs[last] pick.append(i) # find the largest (x, y) coordinates for the start of the bounding box and the smallest (x, y) coordinates for the end of the bounding box xx1 = np.maximum(x1[i], x1[idxs[:last]]) yy1 = np.maximum(y1[i], y1[idxs[:last]]) xx2 = np.minimum(x2[i], x2[idxs[:last]]) yy2 = np.minimum(y2[i], y2[idxs[:last]]) # compute the width and height of the bounding box w = np.maximum(0, xx2 - xx1 + 1) h = np.maximum(0, yy2 - yy1 + 1) # compute the ratio of overlap overlap = (w * h) / area[idxs[:last]] # delete all indexes from the index list that have overlap greater than the provided overlap threshold idxs = np.delete(idxs, np.concatenate(([last], np.where(overlap > overlapThresh)[0]))) # return only the bounding boxes that were picked return boxes[pick].astype("int"), angles[pick] def decode_predictions(scores, geometry1, geometry2): # grab the number of rows and columns from the scores volume, then # initialize our set of bounding box rectangles and corresponding # confidence scores (numRows, numCols) = scores.shape[2:4] rects = [] confidences = [] angles = [] # loop over the number of rows for y in range(0, numRows): # extract the scores (probabilities), followed by the # geometrical data used to derive potential bounding box # coordinates that surround text scoresData = scores[0, 0, y] xData0 = geometry1[0, 0, y] xData1 = geometry1[0, 1, y] xData2 = geometry1[0, 2, y] xData3 = geometry1[0, 3, y] anglesData = geometry2[0, 0, y] # loop over the number of columns for x in range(0, numCols): # if our score does not have sufficient probability, # ignore it if scoresData[x] < _conf_threshold: continue # compute the offset factor as our resulting feature # maps will be 4x smaller than the input image (offsetX, offsetY) = (x * 4.0, y * 4.0) # extract the rotation angle for the prediction and # then compute the sin and cosine angle = anglesData[x] cos = np.cos(angle) sin = np.sin(angle) # use the geometry volume to derive the width and height # of the bounding box h = xData0[x] + xData2[x] w = xData1[x] + xData3[x] # compute both the starting and ending (x, y)-coordinates # for the text prediction bounding box endX = int(offsetX + (cos * xData1[x]) + (sin * xData2[x])) endY = int(offsetY - (sin * xData1[x]) + (cos * xData2[x])) startX = int(endX - w) startY = int(endY - h) # add the bounding box coordinates and probability score # to our respective lists rects.append((startX, startY, endX, endY)) confidences.append(scoresData[x]) angles.append(angle) # return a tuple of the bounding boxes and associated confidences return (rects, confidences, angles) def decode_east(nnet_packet, **kwargs): scores = nnet_packet.get_tensor(0) geometry1 = nnet_packet.get_tensor(1) geometry2 = nnet_packet.get_tensor(2) bboxes, confs, angles = decode_predictions(scores, geometry1, geometry2 ) boxes, angles = non_max_suppression(np.array(bboxes), probs=confs, angles=np.array(angles)) boxesangles = (boxes, angles) return boxesangles def show_east(boxesangles, frame, **kwargs): bboxes = boxesangles[0] angles = boxesangles[1] for ((X0, Y0, X1, Y1), angle) in zip(bboxes, angles): width = abs(X0 - X1) height = abs(Y0 - Y1) cX = int(X0 + width * 0.5) cY = int(Y0 + height * 0.5) rotRect = ((cX, cY), ((X1 - X0), (Y1 - Y0)), angle * (-1)) points = rotated_Rectangle(frame, rotRect, color=(255, 0, 0), thickness=1) cv2.polylines(frame, [points], isClosed=True, color=(255, 0, 0), thickness=1, lineType=cv2.LINE_8) return frame def order_points(pts): rect = np.zeros((4, 2), dtype="float32") s = pts.sum(axis=1) rect[0] = pts[np.argmin(s)] rect[2] = pts[np.argmax(s)] diff = np.diff(pts, axis=1) rect[1] = pts[np.argmin(diff)] rect[3] = pts[np.argmax(diff)] return rect def four_point_transform(image, pts): rect = order_points(pts) (tl, tr, br, bl) = rect widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2)) widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2)) maxWidth = max(int(widthA), int(widthB)) heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2)) heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2)) maxHeight = max(int(heightA), int(heightB)) dst = np.array([ [0, 0], [maxWidth - 1, 0], [maxWidth - 1, maxHeight - 1], [0, maxHeight - 1]], dtype="float32") M = cv2.getPerspectiveTransform(rect, dst) warped = cv2.warpPerspective(image, M, (maxWidth, maxHeight)) return warped
StarcoderdataPython
3213723
#!/usr/bin/env python # -*- coding: utf-8 -*- # filename = __init__ # author=KGerring # date = 4/15/21 # project poetryproj # docs root """ poetryproj """ from __future__ import annotations import os import sys __all__ = [] __all__ = sorted( [ getattr(v, "__name__", k) for k, v in list(globals().items()) # export if ( (callable(v) and getattr(v, "__module__", "") == __name__ or k.isupper()) # callables from this module and not str(getattr(v, "__name__", k)).startswith("__") # or CONSTANTS ) ] ) # neither marked internal if __name__ == "__main__": print(__file__)
StarcoderdataPython
5023143
#!/usr/bin/env python """ Unit test suite for the betr regression test manager """ from __future__ import print_function import logging import os import sys import unittest if sys.version_info[0] == 2: # pragma: no coverage from ConfigParser import SafeConfigParser as config_parser else: from configparser import ConfigParser as config_parser from rtest_betr import main class BeTR_suite(unittest.TestCase): """ """ _LOG_FILENAME = 'dummy.testlog' def setUp(self): """ """ logging.basicConfig(filename=self._LOG_FILENAME, filemode='w', level=logging.INFO, format='%(message)s') logging.info('mtest {0} unit test log.'.format(__name__)) def tearDown(self): """ """ logging.shutdown() if os.path.isfile(self._LOG_FILENAME): os.remove(self._LOG_FILENAME) # pragma: no coverage # ------------------------------------------------------ def test_example_default(self): """A working example test default value. """ expected = True received = True self.assertEqual(expected, received) if __name__ == '__main__': # unittest.main(buffer=True) unittest.main() # pragma: no coverage
StarcoderdataPython
6598196
<filename>devilry/apps/core/devilry_core_mommy_factories.py<gh_stars>0 from django.conf import settings from model_mommy import mommy def examiner(group=None, shortname=None, fullname=None, automatic_anonymous_id=None): """ Creates an Examiner using ``mommy.make('core.Examiner', ...)``. Args: group: The AssignmentGroup to add the examiner to (optional). shortname: The ``shortname`` of the user (optional). fullname: The ``fullname`` of the user (optional). automatic_anonymous_id: The ``automatic_anonymous_id`` of the RelatedExaminer (optional). Returns: Examiner: The created examiner. """ user_kwargs = {} if shortname: user_kwargs['shortname'] = shortname if fullname: user_kwargs['fullname'] = fullname relatedexaminer_kwargs = {} if automatic_anonymous_id: relatedexaminer_kwargs['automatic_anonymous_id'] = automatic_anonymous_id return mommy.make( 'core.Examiner', assignmentgroup=group, relatedexaminer=mommy.make('core.RelatedExaminer', user=mommy.make(settings.AUTH_USER_MODEL, **user_kwargs), **relatedexaminer_kwargs) ) def candidate(group=None, shortname=None, fullname=None, automatic_anonymous_id=None, relatedstudents_candidate_id=None, candidates_candidate_id=None): """ Creates a Candidate using ``mommy.make('core.Candidate', ...)``. Args: group: The AssignmentGroup to add the candidate to (optional). shortname: The ``shortname`` of the user (optional). fullname: The ``fullname`` of the user (optional). automatic_anonymous_id: The ``automatic_anonymous_id`` of the RelatedStudent (optional). relatedstudents_candidate_id: The ``candidate_id`` of the RelatedStudent (optional). candidates_candidate_id: The ``candidate_id`` of the Candidate (optional). Returns: Candidate: The created candidate. """ user_kwargs = {} if shortname: user_kwargs['shortname'] = shortname if fullname: user_kwargs['fullname'] = fullname relatedstudent_kwargs = {} if automatic_anonymous_id: relatedstudent_kwargs['automatic_anonymous_id'] = automatic_anonymous_id if relatedstudents_candidate_id: relatedstudent_kwargs['candidate_id'] = relatedstudents_candidate_id candidate_kwargs = {} if candidates_candidate_id: candidate_kwargs['candidate_id'] = candidates_candidate_id return mommy.make( 'core.Candidate', assignment_group=group, relatedstudent=mommy.make('core.RelatedStudent', user=mommy.make(settings.AUTH_USER_MODEL, **user_kwargs), **relatedstudent_kwargs) )
StarcoderdataPython
246874
def convert2meter(s, input_unit="in"): ''' Function to convert inches, feet and cubic feet to meters and cubic meters ''' if input_unit == "in": return s*0.0254 elif input_unit == "ft": return s*0.3048 elif input_unit == "cft": return s*0.0283168 else: print("Error: Input unit is unknown.") ## Apply function measurement_unit = {"Girth":"in", "Height":"ft", "Volume":"cft"} trees = trees_raw.copy() for feature in ["Girth", "Height", "Volume"]: trees[feature] = trees_raw[feature].apply(lambda x: convert2meter(s=x, input_unit=measurement_unit.get(feature)))
StarcoderdataPython
9717025
# This file is part of QuTiP: Quantum Toolbox in Python. # # Copyright (c) 2011 and later, <NAME> and <NAME>. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # # 3. Neither the name of the QuTiP: Quantum Toolbox in Python nor the names # of its contributors may be used to endorse or promote products derived # from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A # PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ############################################################################### import numpy as np from numpy.testing import assert_, run_module_suite from qutip import ssesolve, destroy, coherent, mesolve, parallel_map def test_ssesolve_photocurrent(): "Stochastic: ssesolve: photo-current" tol = 0.01 N = 4 gamma = 0.25 ntraj = 25 nsubsteps = 100 a = destroy(N) H = a.dag() * a psi0 = coherent(N, 0.5) sc_ops = [np.sqrt(gamma) * a] e_ops = [a.dag() * a, a + a.dag(), (-1j)*(a - a.dag())] times = np.linspace(0, 2.5, 50) res_ref = mesolve(H, psi0, times, sc_ops, e_ops) res = ssesolve(H, psi0, times, sc_ops, e_ops, ntraj=ntraj, nsubsteps=nsubsteps, method='photocurrent', store_measurement=True, map_func=parallel_map) assert_(all([np.mean(abs(res.expect[idx] - res_ref.expect[idx])) < tol for idx in range(len(e_ops))])) assert_(len(res.measurement) == ntraj) assert_(all([m.shape == (len(times), len(sc_ops)) for m in res.measurement])) def test_ssesolve_homodyne(): "Stochastic: ssesolve: homodyne" tol = 0.01 N = 4 gamma = 0.25 ntraj = 25 nsubsteps = 100 a = destroy(N) H = a.dag() * a psi0 = coherent(N, 0.5) sc_ops = [np.sqrt(gamma) * a] e_ops = [a.dag() * a, a + a.dag(), (-1j)*(a - a.dag())] times = np.linspace(0, 2.5, 50) res_ref = mesolve(H, psi0, times, sc_ops, e_ops) res = ssesolve(H, psi0, times, sc_ops, e_ops, ntraj=ntraj, nsubsteps=nsubsteps, method='homodyne', store_measurement=True, map_func=parallel_map) assert_(all([np.mean(abs(res.expect[idx] - res_ref.expect[idx])) < tol for idx in range(len(e_ops))])) assert_(len(res.measurement) == ntraj) assert_(all([m.shape == (len(times), len(sc_ops)) for m in res.measurement])) def test_ssesolve_heterodyne(): "Stochastic: ssesolve: heterodyne" tol = 0.01 N = 4 gamma = 0.25 ntraj = 25 nsubsteps = 100 a = destroy(N) H = a.dag() * a psi0 = coherent(N, 0.5) sc_ops = [np.sqrt(gamma) * a] e_ops = [a.dag() * a, a + a.dag(), (-1j)*(a - a.dag())] times = np.linspace(0, 2.5, 50) res_ref = mesolve(H, psi0, times, sc_ops, e_ops) res = ssesolve(H, psi0, times, sc_ops, e_ops, ntraj=ntraj, nsubsteps=nsubsteps, method='heterodyne', store_measurement=True, map_func=parallel_map) assert_(all([np.mean(abs(res.expect[idx] - res_ref.expect[idx])) < tol for idx in range(len(e_ops))])) assert_(len(res.measurement) == ntraj) assert_(all([m.shape == (len(times), len(sc_ops), 2) for m in res.measurement])) if __name__ == "__main__": run_module_suite()
StarcoderdataPython
11348996
## # File: testGitUtils.py # Author: jdw # Date: 18-Jul-2021 # # Updates: # ## """ Test utilities """ __docformat__ = "google en" __author__ = "<NAME>" __email__ = "<EMAIL>" __license__ = "Apache 2.0" import os.path import time import random import string import unittest import logging # from rcsb.utils.io import __version__ from rcsb.utils.io.FileUtil import FileUtil from rcsb.utils.io.GitUtil import GitUtil HERE = os.path.abspath(os.path.dirname(__file__)) TOPDIR = os.path.dirname(os.path.dirname(os.path.dirname(HERE))) logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s]-%(module)s.%(funcName)s: %(message)s") logger = logging.getLogger() logger.setLevel(logging.INFO) class GitUtilTests(unittest.TestCase): def setUp(self): self.__workPath = os.path.join(HERE, "test-output") self.__startTime = time.time() logger.debug("Running tests on version %s", __version__) logger.debug("Starting %s at %s", self.id(), time.strftime("%Y %m %d %H:%M:%S", time.localtime())) def tearDown(self): endTime = time.time() logger.debug("Completed %s at %s (%.4f seconds)", self.id(), time.strftime("%Y %m %d %H:%M:%S", time.localtime()), endTime - self.__startTime) def testGitOps(self): """Test case - git clone""" try: branch = "test-branch" repositoryPath = "rcsb/py-rcsb_exdb_assets_stash_test.git" localRepositoryPath = os.path.join(self.__workPath, "test-stash") fU = FileUtil() fU.remove(localRepositoryPath) gitToken = None gU = GitUtil(gitToken) ok = gU.clone(repositoryPath, localRepositoryPath, branch=branch) self.assertTrue(ok) logger.info("status %r", gU.status(localRepositoryPath)) # gU.pull(localRepositoryPath, branch=branch) self.assertTrue(ok) logger.info("status %r", gU.status(localRepositoryPath)) # testPath = os.path.join(localRepositoryPath, "stash", "TESTFILE.txt") self.__makeFile(testPath, 10) # ok = gU.addAll(localRepositoryPath, branch=branch) self.assertTrue(ok) logger.info("status %r", gU.status(localRepositoryPath, branch=branch)) # ok = gU.commit(localRepositoryPath, branch=branch) self.assertTrue(ok) logger.info("status %r", gU.status(localRepositoryPath, branch=branch)) # if gitToken: gU.push(localRepositoryPath, branch=branch) self.assertTrue(ok) logger.info("status %r", gU.status(localRepositoryPath, branch=branch)) # gU.pull(localRepositoryPath, branch=branch) self.assertTrue(ok) logger.info("status %r", gU.status(localRepositoryPath, branch=branch)) # except Exception as e: logger.exception("Failing with %s", str(e)) self.fail() def __makeFile(self, fp, count): sLen = 50 with open(fp, "w") as ofh: for ii in range(count): tS = "".join(random.choices(string.ascii_uppercase + string.digits, k=sLen)) ofh.write("%d %s\n" % (ii, tS)) def suiteGitTests(): suiteSelect = unittest.TestSuite() suiteSelect.addTest(GitUtilTests("testGitOps")) return suiteSelect if __name__ == "__main__": mySuite = suiteGitTests() unittest.TextTestRunner(verbosity=2).run(mySuite) #
StarcoderdataPython