sentence1
stringlengths
52
3.87M
sentence2
stringlengths
1
47.2k
label
stringclasses
1 value
def _change_bios_setting(self, properties): """Change the bios settings to specified values.""" keys = properties.keys() # Check if the BIOS resource/property exists. headers, bios_uri, settings = self._check_bios_resource(keys) if not self._operation_allowed(headers, 'PATCH'): headers, bios_uri, _ = self._get_bios_settings_resource(settings) self._validate_if_patch_supported(headers, bios_uri) request_headers = self._get_bios_hash_password(self.bios_password) status, headers, response = self._rest_patch(bios_uri, request_headers, properties) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Change the bios settings to specified values.
entailment
def _get_iscsi_settings_resource(self, data): """Get the iscsi settings resoure. :param data: Existing iscsi settings of the server. :returns: headers, iscsi_settings url and iscsi settings as a dictionary. :raises: IloCommandNotSupportedError, if resource is not found. :raises: IloError, on an error from iLO. """ try: iscsi_settings_uri = data['links']['Settings']['href'] except KeyError: msg = ('iscsi settings resource not found.') raise exception.IloCommandNotSupportedError(msg) status, headers, iscsi_settings = self._rest_get(iscsi_settings_uri) if status != 200: msg = self._get_extended_error(iscsi_settings) raise exception.IloError(msg) return headers, iscsi_settings_uri, iscsi_settings
Get the iscsi settings resoure. :param data: Existing iscsi settings of the server. :returns: headers, iscsi_settings url and iscsi settings as a dictionary. :raises: IloCommandNotSupportedError, if resource is not found. :raises: IloError, on an error from iLO.
entailment
def _get_bios_boot_resource(self, data): """Get the Boot resource like BootSources. :param data: Existing Bios settings of the server. :returns: boot settings. :raises: IloCommandNotSupportedError, if resource is not found. :raises: IloError, on an error from iLO. """ try: boot_uri = data['links']['Boot']['href'] except KeyError: msg = ('Boot resource not found.') raise exception.IloCommandNotSupportedError(msg) status, headers, boot_settings = self._rest_get(boot_uri) if status != 200: msg = self._get_extended_error(boot_settings) raise exception.IloError(msg) return boot_settings
Get the Boot resource like BootSources. :param data: Existing Bios settings of the server. :returns: boot settings. :raises: IloCommandNotSupportedError, if resource is not found. :raises: IloError, on an error from iLO.
entailment
def _get_bios_mappings_resource(self, data): """Get the Mappings resource. :param data: Existing Bios settings of the server. :returns: mappings settings. :raises: IloCommandNotSupportedError, if resource is not found. :raises: IloError, on an error from iLO. """ try: map_uri = data['links']['Mappings']['href'] except KeyError: msg = ('Mappings resource not found.') raise exception.IloCommandNotSupportedError(msg) status, headers, map_settings = self._rest_get(map_uri) if status != 200: msg = self._get_extended_error(map_settings) raise exception.IloError(msg) return map_settings
Get the Mappings resource. :param data: Existing Bios settings of the server. :returns: mappings settings. :raises: IloCommandNotSupportedError, if resource is not found. :raises: IloError, on an error from iLO.
entailment
def _check_iscsi_rest_patch_allowed(self): """Checks if patch is supported on iscsi. :returns: iscsi url. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ headers, bios_uri, bios_settings = self._check_bios_resource() # Check if the bios resource exists. if('links' in bios_settings and 'iScsi' in bios_settings['links']): iscsi_uri = bios_settings['links']['iScsi']['href'] status, headers, settings = self._rest_get(iscsi_uri) if status != 200: msg = self._get_extended_error(settings) raise exception.IloError(msg) if not self._operation_allowed(headers, 'PATCH'): headers, iscsi_uri, settings = ( self._get_iscsi_settings_resource(settings)) self._validate_if_patch_supported(headers, iscsi_uri) return iscsi_uri else: msg = ('"links/iScsi" section in bios' ' does not exist') raise exception.IloCommandNotSupportedError(msg)
Checks if patch is supported on iscsi. :returns: iscsi url. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _change_iscsi_settings(self, iscsi_info): """Change iSCSI settings. :param iscsi_info: A dictionary that contains information of iSCSI target like target_name, lun, ip_address, port etc. :raises: IloError, on an error from iLO. """ headers, bios_uri, bios_settings = self._check_bios_resource() # Get the Mappings resource. map_settings = self._get_bios_mappings_resource(bios_settings) nics = [] for mapping in map_settings['BiosPciSettingsMappings']: for subinstance in mapping['Subinstances']: for association in subinstance['Associations']: if 'NicBoot' in association: nics.append(association) if not nics: msg = ('No nics found') raise exception.IloError(msg) iscsi_uri = self._check_iscsi_rest_patch_allowed() # Set iSCSI info to all nics iscsi_infos = [] for nic in nics: data = iscsi_info.copy() data['iSCSIBootAttemptName'] = nic data['iSCSINicSource'] = nic data['iSCSIBootAttemptInstance'] = nics.index(nic) + 1 iscsi_infos.append(data) patch_data = {'iSCSIBootSources': iscsi_infos} status, headers, response = self._rest_patch(iscsi_uri, None, patch_data) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Change iSCSI settings. :param iscsi_info: A dictionary that contains information of iSCSI target like target_name, lun, ip_address, port etc. :raises: IloError, on an error from iLO.
entailment
def _change_secure_boot_settings(self, property, value): """Change secure boot settings on the server.""" system = self._get_host_details() # find the BIOS URI if ('links' not in system['Oem']['Hp'] or 'SecureBoot' not in system['Oem']['Hp']['links']): msg = (' "SecureBoot" resource or feature is not ' 'supported on this system') raise exception.IloCommandNotSupportedError(msg) secure_boot_uri = system['Oem']['Hp']['links']['SecureBoot']['href'] # Change the property required new_secure_boot_settings = {} new_secure_boot_settings[property] = value # perform the patch status, headers, response = self._rest_patch( secure_boot_uri, None, new_secure_boot_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg) # Change the bios setting as a workaround to enable secure boot # Can be removed when fixed for Gen9 snap2 val = self._get_bios_setting('CustomPostMessage') val = val.rstrip() if val.endswith(" ") else val+" " self._change_bios_setting({'CustomPostMessage': val})
Change secure boot settings on the server.
entailment
def get_secure_boot_mode(self): """Get the status of secure boot. :returns: True, if enabled, else False :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ system = self._get_host_details() if ('links' not in system['Oem']['Hp'] or 'SecureBoot' not in system['Oem']['Hp']['links']): msg = ('"SecureBoot" resource or feature is not supported' ' on this system') raise exception.IloCommandNotSupportedError(msg) secure_boot_uri = system['Oem']['Hp']['links']['SecureBoot']['href'] # get the Secure Boot object status, headers, secure_boot_settings = self._rest_get(secure_boot_uri) if status >= 300: msg = self._get_extended_error(secure_boot_settings) raise exception.IloError(msg) return secure_boot_settings['SecureBootCurrentState']
Get the status of secure boot. :returns: True, if enabled, else False :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def set_secure_boot_mode(self, secure_boot_enable): """Enable/Disable secure boot on the server. :param secure_boot_enable: True, if secure boot needs to be enabled for next boot, else False. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ if self._is_boot_mode_uefi(): self._change_secure_boot_settings('SecureBootEnable', secure_boot_enable) else: msg = ('System is not in UEFI boot mode. "SecureBoot" related ' 'resources cannot be changed.') raise exception.IloCommandNotSupportedInBiosError(msg)
Enable/Disable secure boot on the server. :param secure_boot_enable: True, if secure boot needs to be enabled for next boot, else False. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def reset_secure_boot_keys(self): """Reset secure boot keys to manufacturing defaults. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ if self._is_boot_mode_uefi(): self._change_secure_boot_settings('ResetToDefaultKeys', True) else: msg = ('System is not in UEFI boot mode. "SecureBoot" related ' 'resources cannot be changed.') raise exception.IloCommandNotSupportedInBiosError(msg)
Reset secure boot keys to manufacturing defaults. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def clear_secure_boot_keys(self): """Reset all keys. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ if self._is_boot_mode_uefi(): self._change_secure_boot_settings('ResetAllKeys', True) else: msg = ('System is not in UEFI boot mode. "SecureBoot" related ' 'resources cannot be changed.') raise exception.IloCommandNotSupportedInBiosError(msg)
Reset all keys. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _perform_power_op(self, oper): """Perform requested power operation. :param oper: Type of power button press to simulate. Supported values: 'ON', 'ForceOff', 'ForceRestart' and 'Nmi' :raises: IloError, on an error from iLO. """ power_settings = {"Action": "Reset", "ResetType": oper} systems_uri = "/rest/v1/Systems/1" status, headers, response = self._rest_post(systems_uri, None, power_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Perform requested power operation. :param oper: Type of power button press to simulate. Supported values: 'ON', 'ForceOff', 'ForceRestart' and 'Nmi' :raises: IloError, on an error from iLO.
entailment
def _press_pwr_btn(self, pushType="Press"): """Simulates a physical press of the server power button. :param pushType: Type of power button press to simulate Supported values are: 'Press' and 'PressAndHold' :raises: IloError, on an error from iLO. """ power_settings = {"Action": "PowerButton", "Target": "/Oem/Hp", "PushType": pushType} systems_uri = "/rest/v1/Systems/1" status, headers, response = self._rest_post(systems_uri, None, power_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Simulates a physical press of the server power button. :param pushType: Type of power button press to simulate Supported values are: 'Press' and 'PressAndHold' :raises: IloError, on an error from iLO.
entailment
def _retry_until_powered_on(self, power): """This method retries power on operation. :param: power : target power state """ # If the system is in the same power state as # requested by the user, it gives the error # InvalidOperationForSystemState. To avoid this error # the power state is checked before power on # operation is performed. status = self.get_host_power_status() if (status != power): self._perform_power_op(POWER_STATE[power]) return self.get_host_power_status() else: return status
This method retries power on operation. :param: power : target power state
entailment
def set_host_power(self, power): """Toggle the power button of server. :param power: 'ON' or 'OFF' :raises: IloError, on an error from iLO. """ power = power.upper() if (power is not None) and (power not in POWER_STATE): msg = ("Invalid input '%(pow)s'. " "The expected input is ON or OFF." % {'pow': power}) raise exception.IloInvalidInputError(msg) # Check current power status, do not act if it's in requested state. cur_status = self.get_host_power_status() if cur_status == power: LOG.debug(self._("Node is already in '%(power)s' power state."), {'power': power}) return if power == 'ON' and 'PROLIANT BL' in self.get_product_name().upper(): self._retry_until_powered_on(power) else: self._perform_power_op(POWER_STATE[power])
Toggle the power button of server. :param power: 'ON' or 'OFF' :raises: IloError, on an error from iLO.
entailment
def get_http_boot_url(self): """Request the http boot url from system in uefi boot mode. :returns: URL for http boot :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedInBiosError, if the system is in the bios boot mode. """ if(self._is_boot_mode_uefi() is True): return self._get_bios_setting('UefiShellStartupUrl') else: msg = 'get_http_boot_url is not supported in the BIOS boot mode' raise exception.IloCommandNotSupportedInBiosError(msg)
Request the http boot url from system in uefi boot mode. :returns: URL for http boot :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedInBiosError, if the system is in the bios boot mode.
entailment
def set_http_boot_url(self, url): """Set url to the UefiShellStartupUrl to the system in uefi boot mode. :param url: URL for http boot :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedInBiosError, if the system is in the bios boot mode. """ if(self._is_boot_mode_uefi() is True): self._change_bios_setting({'UefiShellStartupUrl': url}) else: msg = 'set_http_boot_url is not supported in the BIOS boot mode' raise exception.IloCommandNotSupportedInBiosError(msg)
Set url to the UefiShellStartupUrl to the system in uefi boot mode. :param url: URL for http boot :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedInBiosError, if the system is in the bios boot mode.
entailment
def unset_iscsi_info(self): """Disable iSCSI boot option in UEFI boot mode. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedInBiosError, if the system is in the BIOS boot mode. """ if(self._is_boot_mode_uefi() is True): iscsi_info = {'iSCSIBootEnable': 'Disabled'} self._change_iscsi_settings(iscsi_info) else: msg = 'iSCSI boot is not supported in the BIOS boot mode' raise exception.IloCommandNotSupportedInBiosError(msg)
Disable iSCSI boot option in UEFI boot mode. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedInBiosError, if the system is in the BIOS boot mode.
entailment
def get_iscsi_initiator_info(self): """Give iSCSI initiator information of iLO. :returns: iSCSI initiator information. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the system is in the bios boot mode. """ headers, bios_uri, bios_settings = self._check_bios_resource() if('links' in bios_settings and 'iScsi' in bios_settings['links']): iscsi_uri = bios_settings['links']['iScsi']['href'] status, headers, iscsi_settings = self._rest_get(iscsi_uri) if status != 200: msg = self._get_extended_error(iscsi_settings) raise exception.IloError(msg) return iscsi_settings['iSCSIInitiatorName'] else: msg = ('"links/iScsi" section in bios ' 'does not exist') raise exception.IloCommandNotSupportedError(msg)
Give iSCSI initiator information of iLO. :returns: iSCSI initiator information. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the system is in the bios boot mode.
entailment
def set_iscsi_initiator_info(self, initiator_iqn): """Set iSCSI initiator information in iLO. :param initiator_iqn: Initiator iqn for iLO. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the system is in the bios boot mode. """ if(self._is_boot_mode_uefi() is True): iscsi_uri = self._check_iscsi_rest_patch_allowed() initiator_info = {'iSCSIInitiatorName': initiator_iqn} status, headers, response = self._rest_patch(iscsi_uri, None, initiator_info) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg) else: msg = 'iSCSI initiator cannot be set in the BIOS boot mode' raise exception.IloCommandNotSupportedError(msg)
Set iSCSI initiator information in iLO. :param initiator_iqn: Initiator iqn for iLO. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the system is in the bios boot mode.
entailment
def get_pending_boot_mode(self): """Retrieves the pending boot mode of the server. Gets the boot mode to be set on next reset. :returns: either LEGACY or UEFI. :raises: IloError, on an error from iLO. """ headers, uri, bios_settings = self._check_bios_resource(['BootMode']) _, _, settings = self._get_bios_settings_resource(bios_settings) boot_mode = settings.get('BootMode') if boot_mode == 'LegacyBios': boot_mode = 'legacy' return boot_mode.upper()
Retrieves the pending boot mode of the server. Gets the boot mode to be set on next reset. :returns: either LEGACY or UEFI. :raises: IloError, on an error from iLO.
entailment
def set_pending_boot_mode(self, boot_mode): """Sets the boot mode of the system for next boot. :param boot_mode: either 'uefi' or 'legacy'. :raises: IloInvalidInputError, on an invalid input. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ boot_mode = boot_mode.lower() if boot_mode not in ['uefi', 'legacy']: msg = 'Invalid Boot mode specified' raise exception.IloInvalidInputError(msg) boot_properties = {'BootMode': boot_mode} if boot_mode == 'legacy': boot_properties['BootMode'] = 'LegacyBios' else: # If Boot Mode is 'Uefi' set the UEFIOptimizedBoot first. boot_properties['UefiOptimizedBoot'] = "Enabled" # Change the Boot Mode self._change_bios_setting(boot_properties)
Sets the boot mode of the system for next boot. :param boot_mode: either 'uefi' or 'legacy'. :raises: IloInvalidInputError, on an invalid input. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_supported_boot_mode(self): """Retrieves the supported boot mode. :returns: any one of the following proliantutils.ilo.constants: SUPPORTED_BOOT_MODE_LEGACY_BIOS_ONLY, SUPPORTED_BOOT_MODE_UEFI_ONLY, SUPPORTED_BOOT_MODE_LEGACY_BIOS_AND_UEFI """ system = self._get_host_details() bios_uefi_class_val = 0 # value for bios_only boot mode if ('Bios' in system['Oem']['Hp'] and 'UefiClass' in system['Oem']['Hp']['Bios']): bios_uefi_class_val = (system['Oem']['Hp'] ['Bios']['UefiClass']) return mappings.GET_SUPPORTED_BOOT_MODE_RIS_MAP.get( bios_uefi_class_val)
Retrieves the supported boot mode. :returns: any one of the following proliantutils.ilo.constants: SUPPORTED_BOOT_MODE_LEGACY_BIOS_ONLY, SUPPORTED_BOOT_MODE_UEFI_ONLY, SUPPORTED_BOOT_MODE_LEGACY_BIOS_AND_UEFI
entailment
def reset_ilo_credential(self, password): """Resets the iLO password. :param password: The password to be set. :raises: IloError, if account not found or on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ acc_uri = '/rest/v1/AccountService/Accounts' for status, hds, account, memberuri in self._get_collection(acc_uri): if account['UserName'] == self.login: mod_user = {} mod_user['Password'] = password status, headers, response = self._rest_patch(memberuri, None, mod_user) if status != 200: msg = self._get_extended_error(response) raise exception.IloError(msg) return msg = "iLO Account with specified username is not found." raise exception.IloError(msg)
Resets the iLO password. :param password: The password to be set. :raises: IloError, if account not found or on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _get_ilo_details(self): """Gets iLO details :raises: IloError, on an error from iLO. :raises: IloConnectionError, if iLO is not up after reset. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ manager_uri = '/rest/v1/Managers/1' status, headers, manager = self._rest_get(manager_uri) if status != 200: msg = self._get_extended_error(manager) raise exception.IloError(msg) # verify expected type mtype = self._get_type(manager) if (mtype not in ['Manager.0', 'Manager.1']): msg = "%s is not a valid Manager type " % mtype raise exception.IloError(msg) return manager, manager_uri
Gets iLO details :raises: IloError, on an error from iLO. :raises: IloConnectionError, if iLO is not up after reset. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def reset_ilo(self): """Resets the iLO. :raises: IloError, on an error from iLO. :raises: IloConnectionError, if iLO is not up after reset. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ manager, reset_uri = self._get_ilo_details() action = {'Action': 'Reset'} # perform the POST status, headers, response = self._rest_post(reset_uri, None, action) if(status != 200): msg = self._get_extended_error(response) raise exception.IloError(msg) # Check if the iLO is up again. common.wait_for_ilo_after_reset(self)
Resets the iLO. :raises: IloError, on an error from iLO. :raises: IloConnectionError, if iLO is not up after reset. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def reset_bios_to_default(self): """Resets the BIOS settings to default values. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ # Check if the BIOS resource if exists. headers_bios, bios_uri, bios_settings = self._check_bios_resource() # Get the BaseConfig resource. try: base_config_uri = bios_settings['links']['BaseConfigs']['href'] except KeyError: msg = ("BaseConfigs resource not found. Couldn't apply the BIOS " "Settings.") raise exception.IloCommandNotSupportedError(msg) # Check if BIOS resource supports patch, else get the settings if not self._operation_allowed(headers_bios, 'PATCH'): headers, bios_uri, _ = self._get_bios_settings_resource( bios_settings) self._validate_if_patch_supported(headers, bios_uri) status, headers, config = self._rest_get(base_config_uri) if status != 200: msg = self._get_extended_error(config) raise exception.IloError(msg) new_bios_settings = {} for cfg in config['BaseConfigs']: default_settings = cfg.get('default', None) if default_settings is not None: new_bios_settings = default_settings break else: msg = ("Default Settings not found in 'BaseConfigs' resource.") raise exception.IloCommandNotSupportedError(msg) request_headers = self._get_bios_hash_password(self.bios_password) status, headers, response = self._rest_patch(bios_uri, request_headers, new_bios_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Resets the BIOS settings to default values. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_ilo_firmware_version_as_major_minor(self): """Gets the ilo firmware version for server capabilities :returns: String with the format "<major>.<minor>" or None. """ try: manager, reset_uri = self._get_ilo_details() ilo_fw_ver_str = ( manager['Oem']['Hp']['Firmware']['Current']['VersionString'] ) return common.get_major_minor(ilo_fw_ver_str) except Exception: return None
Gets the ilo firmware version for server capabilities :returns: String with the format "<major>.<minor>" or None.
entailment
def get_server_capabilities(self): """Gets server properties which can be used for scheduling :returns: a dictionary of hardware properties like firmware versions, server model. :raises: IloError, if iLO returns an error in command execution. """ capabilities = {} system = self._get_host_details() capabilities['server_model'] = system['Model'] rom_firmware_version = ( system['Oem']['Hp']['Bios']['Current']['VersionString']) capabilities['rom_firmware_version'] = rom_firmware_version capabilities.update(self._get_ilo_firmware_version()) capabilities.update(self._get_number_of_gpu_devices_connected()) drive_details = self._get_drive_type_and_speed() if drive_details is not None: capabilities.update(drive_details) raid_details = self._get_logical_raid_levels() if raid_details is not None: capabilities.update(raid_details) if self._is_raid_supported(): capabilities['hardware_supports_raid'] = 'true' boot_modes = common.get_supported_boot_modes( self.get_supported_boot_mode()) capabilities.update({ 'boot_mode_bios': boot_modes.boot_mode_bios, 'boot_mode_uefi': boot_modes.boot_mode_uefi}) if self._get_tpm_capability(): capabilities['trusted_boot'] = 'true' if self._get_cpu_virtualization(): capabilities['cpu_vt'] = 'true' if self._get_nvdimm_n_status(): capabilities['nvdimm_n'] = 'true' try: self._check_iscsi_rest_patch_allowed() capabilities['iscsi_boot'] = 'true' except exception.IloError: # If an error is raised dont populate the capability # iscsi_boot pass try: self.get_secure_boot_mode() capabilities['secure_boot'] = 'true' except exception.IloCommandNotSupportedError: # If an error is raised dont populate the capability # secure_boot pass if self._is_sriov_enabled(): capabilities['sriov_enabled'] = 'true' return capabilities
Gets server properties which can be used for scheduling :returns: a dictionary of hardware properties like firmware versions, server model. :raises: IloError, if iLO returns an error in command execution.
entailment
def activate_license(self, key): """Activates iLO license. :param key: iLO license key. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ manager, uri = self._get_ilo_details() try: lic_uri = manager['Oem']['Hp']['links']['LicenseService']['href'] except KeyError: msg = ('"LicenseService" section in Manager/Oem/Hp does not exist') raise exception.IloCommandNotSupportedError(msg) lic_key = {} lic_key['LicenseKey'] = key # Perform POST to activate license status, headers, response = self._rest_post(lic_uri, None, lic_key) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Activates iLO license. :param key: iLO license key. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _get_vm_device_status(self, device='FLOPPY'): """Returns the given virtual media device status and device URI :param device: virtual media device to be queried :returns json format virtual media device status and its URI :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ valid_devices = {'FLOPPY': 'floppy', 'CDROM': 'cd'} # Check if the input is valid if device not in valid_devices: raise exception.IloInvalidInputError( "Invalid device. Valid devices: FLOPPY or CDROM.") manager, uri = self._get_ilo_details() try: vmedia_uri = manager['links']['VirtualMedia']['href'] except KeyError: msg = ('"VirtualMedia" section in Manager/links does not exist') raise exception.IloCommandNotSupportedError(msg) for status, hds, vmed, memberuri in self._get_collection(vmedia_uri): status, headers, response = self._rest_get(memberuri) if status != 200: msg = self._get_extended_error(response) raise exception.IloError(msg) if (valid_devices[device] in [item.lower() for item in response['MediaTypes']]): vm_device_uri = response['links']['self']['href'] return response, vm_device_uri # Requested device not found msg = ('Virtualmedia device "' + device + '" is not' ' found on this system.') raise exception.IloError(msg)
Returns the given virtual media device status and device URI :param device: virtual media device to be queried :returns json format virtual media device status and its URI :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_vm_status(self, device='FLOPPY'): """Returns the virtual media drive status. :param device: virtual media device to be queried :returns device status in dictionary form :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ response, vm_device_uri = self._get_vm_device_status(device) # Create RIBCL equivalent response # RIBCL provides this data in VM status # VM_APPLET = CONNECTED | DISCONNECTED # DEVICE = FLOPPY | CDROM # BOOT_OPTION = BOOT_ALWAYS | BOOT_ONCE | NO_BOOT # WRITE_PROTECT = YES | NO # IMAGE_INSERTED = YES | NO response_data = {} if response.get('WriteProtected', False): response_data['WRITE_PROTECT'] = 'YES' else: response_data['WRITE_PROTECT'] = 'NO' if response.get('BootOnNextServerReset', False): response_data['BOOT_OPTION'] = 'BOOT_ONCE' else: response_data['BOOT_OPTION'] = 'BOOT_ALWAYS' if response.get('Inserted', False): response_data['IMAGE_INSERTED'] = 'YES' else: response_data['IMAGE_INSERTED'] = 'NO' if response.get('ConnectedVia') == 'NotConnected': response_data['VM_APPLET'] = 'DISCONNECTED' # When media is not connected, it's NO_BOOT response_data['BOOT_OPTION'] = 'NO_BOOT' else: response_data['VM_APPLET'] = 'CONNECTED' response_data['IMAGE_URL'] = response['Image'] response_data['DEVICE'] = device # FLOPPY cannot be a boot device if ((response_data['BOOT_OPTION'] == 'BOOT_ONCE') and (response_data['DEVICE'] == 'FLOPPY')): response_data['BOOT_OPTION'] = 'NO_BOOT' return response_data
Returns the virtual media drive status. :param device: virtual media device to be queried :returns device status in dictionary form :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def set_vm_status(self, device='FLOPPY', boot_option='BOOT_ONCE', write_protect='YES'): """Sets the Virtual Media drive status It sets the boot option for virtual media device. Note: boot option can be set only for CD device. :param device: virual media device :param boot_option: boot option to set on the virtual media device :param write_protect: set the write protect flag on the vmedia device Note: It's ignored. In RIS it is read-only. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ # CONNECT is a RIBCL call. There is no such property to set in RIS. if boot_option == 'CONNECT': return boot_option_map = {'BOOT_ONCE': True, 'BOOT_ALWAYS': False, 'NO_BOOT': False } if boot_option not in boot_option_map: msg = ('Virtualmedia boot option "' + boot_option + '" is ' 'invalid.') raise exception.IloInvalidInputError(msg) response, vm_device_uri = self._get_vm_device_status(device) # Update required property vm_settings = {} vm_settings['Oem'] = ( {'Hp': {'BootOnNextServerReset': boot_option_map[boot_option]}}) # perform the patch operation status, headers, response = self._rest_patch( vm_device_uri, None, vm_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Sets the Virtual Media drive status It sets the boot option for virtual media device. Note: boot option can be set only for CD device. :param device: virual media device :param boot_option: boot option to set on the virtual media device :param write_protect: set the write protect flag on the vmedia device Note: It's ignored. In RIS it is read-only. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def insert_virtual_media(self, url, device='FLOPPY'): """Notifies iLO of the location of a virtual media diskette image. :param url: URL to image :param device: virual media device :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ response, vm_device_uri = self._get_vm_device_status(device) # Eject media if there is one. RIBCL was tolerant enough to overwrite # existing media, RIS is not. This check is to take care of that # assumption. if response.get('Inserted', False): self.eject_virtual_media(device) # Update required property vm_settings = {} vm_settings['Image'] = url # Perform the patch operation status, headers, response = self._rest_patch( vm_device_uri, None, vm_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Notifies iLO of the location of a virtual media diskette image. :param url: URL to image :param device: virual media device :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _get_persistent_boot_devices(self): """Get details of persistent boot devices, its order :returns: List of dictionary of boot sources and list of boot device order :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ # Check if the BIOS resource if exists. headers_bios, bios_uri, bios_settings = self._check_bios_resource() # Get the Boot resource. boot_settings = self._get_bios_boot_resource(bios_settings) # Get the BootSources resource try: boot_sources = boot_settings['BootSources'] except KeyError: msg = ("BootSources resource not found.") raise exception.IloError(msg) try: boot_order = boot_settings['PersistentBootConfigOrder'] except KeyError: msg = ("PersistentBootConfigOrder resource not found.") raise exception.IloCommandNotSupportedError(msg) return boot_sources, boot_order
Get details of persistent boot devices, its order :returns: List of dictionary of boot sources and list of boot device order :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_persistent_boot_device(self): """Get current persistent boot device set for the host :returns: persistent boot device for the system :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ system = self._get_host_details() try: # Return boot device if it is persistent. if system['Boot']['BootSourceOverrideEnabled'] == 'Continuous': device = system['Boot']['BootSourceOverrideTarget'] if device in DEVICE_RIS_TO_COMMON: return DEVICE_RIS_TO_COMMON[device] return device except KeyError as e: msg = "get_persistent_boot_device failed with the KeyError:%s" raise exception.IloError((msg) % e) # Check if we are in BIOS boot mode. # There is no resource to fetch boot device order for BIOS boot mode if not self._is_boot_mode_uefi(): return None # Get persistent boot device order for UEFI boot_sources, boot_devices = self._get_persistent_boot_devices() boot_string = "" try: for source in boot_sources: if (source["StructuredBootString"] == boot_devices[0]): boot_string = source["BootString"] break except KeyError as e: msg = "get_persistent_boot_device failed with the KeyError:%s" raise exception.IloError((msg) % e) if 'HP iLO Virtual USB CD' in boot_string: return 'CDROM' elif ('NIC' in boot_string or 'PXE' in boot_string or "iSCSI" in boot_string): return 'NETWORK' elif common.isDisk(boot_string): return 'HDD' else: return None
Get current persistent boot device set for the host :returns: persistent boot device for the system :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _update_persistent_boot(self, device_type=[], persistent=False): """Changes the persistent boot device order in BIOS boot mode for host Note: It uses first boot device from the device_type and ignores rest. :param device_type: ordered list of boot devices :param persistent: Boolean flag to indicate if the device to be set as a persistent boot device :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ tenure = 'Once' new_device = device_type[0] # If it is a standard device, we need to convert in RIS convention if device_type[0].upper() in DEVICE_COMMON_TO_RIS: new_device = DEVICE_COMMON_TO_RIS[device_type[0].upper()] if persistent: tenure = 'Continuous' systems_uri = "/rest/v1/Systems/1" # Need to set this option first if device is 'UefiTarget' if new_device is 'UefiTarget': system = self._get_host_details() uefi_devices = ( system['Boot']['UefiTargetBootSourceOverrideSupported']) iscsi_device = None for device in uefi_devices: if device is not None and 'iSCSI' in device: iscsi_device = device break if iscsi_device is None: msg = 'No UEFI iSCSI bootable device found' raise exception.IloError(msg) new_boot_settings = {} new_boot_settings['Boot'] = {'UefiTargetBootSourceOverride': iscsi_device} status, headers, response = self._rest_patch(systems_uri, None, new_boot_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg) new_boot_settings = {} new_boot_settings['Boot'] = {'BootSourceOverrideEnabled': tenure, 'BootSourceOverrideTarget': new_device} status, headers, response = self._rest_patch(systems_uri, None, new_boot_settings) if status >= 300: msg = self._get_extended_error(response) raise exception.IloError(msg)
Changes the persistent boot device order in BIOS boot mode for host Note: It uses first boot device from the device_type and ignores rest. :param device_type: ordered list of boot devices :param persistent: Boolean flag to indicate if the device to be set as a persistent boot device :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def update_persistent_boot(self, device_type=[]): """Changes the persistent boot device order for the host :param device_type: ordered list of boot devices :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ # Check if the input is valid for item in device_type: if item.upper() not in DEVICE_COMMON_TO_RIS: raise exception.IloInvalidInputError("Invalid input. Valid " "devices: NETWORK, HDD," " ISCSI or CDROM.") self._update_persistent_boot(device_type, persistent=True)
Changes the persistent boot device order for the host :param device_type: ordered list of boot devices :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_one_time_boot(self): """Retrieves the current setting for the one time boot. :returns: Returns the first boot device that would be used in next boot. Returns 'Normal' is no device is set. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ system = self._get_host_details() try: if system['Boot']['BootSourceOverrideEnabled'] == 'Once': device = system['Boot']['BootSourceOverrideTarget'] if device in DEVICE_RIS_TO_COMMON: return DEVICE_RIS_TO_COMMON[device] return device else: # value returned by RIBCL if one-time boot setting are absent return 'Normal' except KeyError as e: msg = "get_one_time_boot failed with the KeyError:%s" raise exception.IloError((msg) % e)
Retrieves the current setting for the one time boot. :returns: Returns the first boot device that would be used in next boot. Returns 'Normal' is no device is set. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _get_firmware_update_service_resource(self): """Gets the firmware update service uri. :returns: firmware update service uri :raises: IloError, on an error from iLO. :raises: IloConnectionError, if not able to reach iLO. :raises: IloCommandNotSupportedError, for not finding the uri """ manager, uri = self._get_ilo_details() try: fw_uri = manager['Oem']['Hp']['links']['UpdateService']['href'] except KeyError: msg = ("Firmware Update Service resource not found.") raise exception.IloCommandNotSupportedError(msg) return fw_uri
Gets the firmware update service uri. :returns: firmware update service uri :raises: IloError, on an error from iLO. :raises: IloConnectionError, if not able to reach iLO. :raises: IloCommandNotSupportedError, for not finding the uri
entailment
def update_firmware(self, file_url, component_type): """Updates the given firmware on the server for the given component. :param file_url: location of the raw firmware file. Extraction of the firmware file (if in compact format) is expected to happen prior to this invocation. :param component_type: Type of component to be applied to. :raises: InvalidInputError, if the validation of the input fails :raises: IloError, on an error from iLO :raises: IloConnectionError, if not able to reach iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server """ fw_update_uri = self._get_firmware_update_service_resource() action_data = { 'Action': 'InstallFromURI', 'FirmwareURI': file_url, } # perform the POST LOG.debug(self._('Flashing firmware file: %s ...'), file_url) status, headers, response = self._rest_post( fw_update_uri, None, action_data) if status != 200: msg = self._get_extended_error(response) raise exception.IloError(msg) # wait till the firmware update completes. common.wait_for_ris_firmware_update_to_complete(self) try: state, percent = self.get_firmware_update_progress() except exception.IloError: msg = 'Status of firmware update not known' LOG.debug(self._(msg)) # noqa return if state == "ERROR": msg = 'Unable to update firmware' LOG.debug(self._(msg)) # noqa raise exception.IloError(msg) elif state == "UNKNOWN": msg = 'Status of firmware update not known' LOG.debug(self._(msg)) # noqa else: # "COMPLETED" | "IDLE" LOG.info(self._('Flashing firmware file: %s ... done'), file_url)
Updates the given firmware on the server for the given component. :param file_url: location of the raw firmware file. Extraction of the firmware file (if in compact format) is expected to happen prior to this invocation. :param component_type: Type of component to be applied to. :raises: InvalidInputError, if the validation of the input fails :raises: IloError, on an error from iLO :raises: IloConnectionError, if not able to reach iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server
entailment
def get_firmware_update_progress(self): """Get the progress of the firmware update. :returns: firmware update state, one of the following values: "IDLE", "UPLOADING", "PROGRESSING", "COMPLETED", "ERROR". If the update resource is not found, then "UNKNOWN". :returns: firmware update progress percent :raises: IloError, on an error from iLO. :raises: IloConnectionError, if not able to reach iLO. """ try: fw_update_uri = self._get_firmware_update_service_resource() except exception.IloError as e: LOG.debug(self._('Progress of firmware update not known: %s'), str(e)) return "UNKNOWN", "UNKNOWN" # perform the GET status, headers, response = self._rest_get(fw_update_uri) if status != 200: msg = self._get_extended_error(response) raise exception.IloError(msg) fw_update_state = response.get('State') fw_update_progress_percent = response.get('ProgressPercent') LOG.debug(self._('Flashing firmware file ... in progress %d%%'), fw_update_progress_percent) return fw_update_state, fw_update_progress_percent
Get the progress of the firmware update. :returns: firmware update state, one of the following values: "IDLE", "UPLOADING", "PROGRESSING", "COMPLETED", "ERROR". If the update resource is not found, then "UNKNOWN". :returns: firmware update progress percent :raises: IloError, on an error from iLO. :raises: IloConnectionError, if not able to reach iLO.
entailment
def _get_tpm_capability(self): """Retrieves if server is TPM capable or not. :returns True if TPM is Present else False """ tpm_values = {"NotPresent": False, "PresentDisabled": True, "PresentEnabled": True} try: tpm_state = self._get_bios_setting('TpmState') except exception.IloCommandNotSupportedError: tpm_state = "NotPresent" tpm_result = tpm_values[tpm_state] return tpm_result
Retrieves if server is TPM capable or not. :returns True if TPM is Present else False
entailment
def _get_cpu_virtualization(self): """get cpu virtualization status.""" try: cpu_vt = self._get_bios_setting('ProcVirtualization') except exception.IloCommandNotSupportedError: return False if cpu_vt == 'Enabled': vt_status = True else: vt_status = False return vt_status
get cpu virtualization status.
entailment
def _get_nvdimm_n_status(self): """Get status of NVDIMM_N. :returns: True if NVDIMM_N is present and enabled, False otherwise. """ try: nvdimm_n_status = self._get_bios_setting('NvDimmNMemFunctionality') if nvdimm_n_status == 'Enabled': nvn_status = True else: nvn_status = False except exception.IloCommandNotSupportedError: nvn_status = False return nvn_status
Get status of NVDIMM_N. :returns: True if NVDIMM_N is present and enabled, False otherwise.
entailment
def inject_nmi(self): """Inject NMI, Non Maskable Interrupt. Inject NMI (Non Maskable Interrupt) for a node immediately. :raises: IloError, on an error from iLO """ cur_status = self.get_host_power_status() if cur_status != 'ON': raise exception.IloError("Server is not in powered on state.") self._perform_power_op("Nmi")
Inject NMI, Non Maskable Interrupt. Inject NMI (Non Maskable Interrupt) for a node immediately. :raises: IloError, on an error from iLO
entailment
def get_current_bios_settings(self, only_allowed_settings=True): """Get current BIOS settings. :param: only_allowed_settings: True when only allowed BIOS settings are to be returned. If False, All the BIOS settings supported by iLO are returned. :return: a dictionary of current BIOS settings is returned. Depending on the 'only_allowed_settings', either only the allowed settings are returned or all the supported settings are returned. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ headers, bios_uri, bios_settings = self._check_bios_resource() # Remove the "links" section bios_settings.pop("links", None) if only_allowed_settings: return utils.apply_bios_properties_filter( bios_settings, constants.SUPPORTED_BIOS_PROPERTIES) return bios_settings
Get current BIOS settings. :param: only_allowed_settings: True when only allowed BIOS settings are to be returned. If False, All the BIOS settings supported by iLO are returned. :return: a dictionary of current BIOS settings is returned. Depending on the 'only_allowed_settings', either only the allowed settings are returned or all the supported settings are returned. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_pending_bios_settings(self, only_allowed_settings=True): """Get current BIOS settings. :param: only_allowed_settings: True when only allowed BIOS settings are to be returned. If False, All the BIOS settings supported by iLO are returned. :return: a dictionary of pending BIOS settings. Depending on the 'only_allowed_settings', either only the allowed settings are returned or all the supported settings are returned. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ headers, bios_uri, bios_settings = self._check_bios_resource() try: settings_config_uri = bios_settings['links']['Settings']['href'] except KeyError: msg = ("Settings resource not found. Couldn't get pending BIOS " "Settings.") raise exception.IloCommandNotSupportedError(msg) status, headers, config = self._rest_get(settings_config_uri) if status != 200: msg = self._get_extended_error(config) raise exception.IloError(msg) # Remove the "links" section config.pop("links", None) if only_allowed_settings: return utils.apply_bios_properties_filter( config, constants.SUPPORTED_BIOS_PROPERTIES) return config
Get current BIOS settings. :param: only_allowed_settings: True when only allowed BIOS settings are to be returned. If False, All the BIOS settings supported by iLO are returned. :return: a dictionary of pending BIOS settings. Depending on the 'only_allowed_settings', either only the allowed settings are returned or all the supported settings are returned. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def set_bios_settings(self, data=None, only_allowed_settings=True): """Sets current BIOS settings to the provided data. :param: only_allowed_settings: True when only allowed BIOS settings are to be set. If False, all the BIOS settings supported by iLO and present in the 'data' are set. :param: data: a dictionary of BIOS settings to be applied. Depending on the 'only_allowed_settings', either only the allowed settings are set or all the supported settings that are in the 'data' are set. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ if not data: raise exception.IloError("Could not apply settings with" " empty data") if only_allowed_settings: unsupported_settings = [key for key in data if key not in ( constants.SUPPORTED_BIOS_PROPERTIES)] if unsupported_settings: msg = ("Could not apply settings as one or more settings are" " not supported. Unsupported settings are %s." " Supported settings are %s." % ( unsupported_settings, constants.SUPPORTED_BIOS_PROPERTIES)) raise exception.IloError(msg) self._change_bios_setting(data)
Sets current BIOS settings to the provided data. :param: only_allowed_settings: True when only allowed BIOS settings are to be set. If False, all the BIOS settings supported by iLO and present in the 'data' are set. :param: data: a dictionary of BIOS settings to be applied. Depending on the 'only_allowed_settings', either only the allowed settings are set or all the supported settings that are in the 'data' are set. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_default_bios_settings(self, only_allowed_settings=True): """Get default BIOS settings. :param: only_allowed_settings: True when only allowed BIOS settings are to be returned. If False, All the BIOS settings supported by iLO are returned. :return: a dictionary of default BIOS settings(factory settings). Depending on the 'only_allowed_settings', either only the allowed settings are returned or all the supported settings are returned. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ headers_bios, bios_uri, bios_settings = self._check_bios_resource() # Get the BaseConfig resource. try: base_config_uri = bios_settings['links']['BaseConfigs']['href'] except KeyError: msg = ("BaseConfigs resource not found. Couldn't apply the BIOS " "Settings.") raise exception.IloCommandNotSupportedError(msg) status, headers, config = self._rest_get(base_config_uri) if status != 200: msg = self._get_extended_error(config) raise exception.IloError(msg) for cfg in config['BaseConfigs']: default_settings = cfg.get('default') if default_settings: break else: msg = ("Default BIOS Settings not found in 'BaseConfigs' " "resource.") raise exception.IloCommandNotSupportedError(msg) if only_allowed_settings: return utils.apply_bios_properties_filter( default_settings, constants.SUPPORTED_BIOS_PROPERTIES) return default_settings
Get default BIOS settings. :param: only_allowed_settings: True when only allowed BIOS settings are to be returned. If False, All the BIOS settings supported by iLO are returned. :return: a dictionary of default BIOS settings(factory settings). Depending on the 'only_allowed_settings', either only the allowed settings are returned or all the supported settings are returned. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def get_bios_settings_result(self): """Gets the result of the bios settings applied :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ headers, bios_uri, bios_settings = self._check_bios_resource() settings_result = bios_settings.get("SettingsResult").get("Messages") status = "failed" if len(settings_result) > 1 else "success" return {"status": status, "results": settings_result}
Gets the result of the bios settings applied :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
entailment
def _obsolete_plot_iso_abund_marco(directory, name_h5_file, mass_range, cycle, logic_stable, i_decay, file_solar, solar_factor): """ Interface to plot average over mass_range. Parameters ---------- directory : string Location of h5 file to plot. Needed for plot_tools. name_h5_file : string Name of h5 file. Needed for plot_tools. mass_range : list A 1x2 array required to plot data in a certain mass range. Needed for _read_iso_abund_marco. cycle : integer which cycle from the h5 file?. Needed for _read_iso_abund_marco. logic_stable : boolean Do you want to plot only stable or not. i_decay : integer If i_decay is 1, then plot not decayed. If i_decay is 2, then plot decayed. Make sense only if stable is true. file_solar : string File where to take solar abundances. solar_factor : float value to correct initial abundances to solar, e.g. for Z=0.01 and AG89 solar_factor = 2. See Also -------- se._read_iso_abund_marco() """ # provide library for Z versus element names, and Z for elements u.give_zip_element_z_and_names() # solar abundances are read here u.solar(file_solar,solar_factor) # from here I have average abundances in mass_range to plot average_iso_abund_marco(mass_range,cycle,logic_stable,i_decay) fig = pl.figure() # Figure object ax = fig.add_subplot(1,1,1) # Axes object: one row, one column, first plot (one plot!) # Tick marks xminorlocator = MultipleLocator(1) xmajorlocator = MultipleLocator(10) ax.xaxis.set_major_locator(xmajorlocator) ax.xaxis.set_minor_locator(xminorlocator) yminorlocator = MultipleLocator(0.1) ymajorlocator = MultipleLocator(1) ax.yaxis.set_major_locator(ymajorlocator) ax.yaxis.set_minor_locator(yminorlocator) ax.set_yscale('log') if not logic_stable: for i in range(len(u.spe)): pl.plot(amass_int[u.cl[spe[i]]],average_mass_frac[u.cl[spe[i]]],'ko') pl.xlabel('$Mass$ $number$', fontsize=20) pl.ylabel('$X_{i}$', fontsize=20) pl.ylim(1.0e-10,10.) pl.xlim(55,110) elif logic_stable: # plot stable #for i in range(len(stable)): # pl.plot(amass_int[cl[stable[i].capitalize()]],average_mass_frac[cl[stable[i].capitalize()]]/u.solar_abundance[stable[i].lower()],'ko') if i_decay == 2: for j in range(len(stable)): #print cl[stable[j].capitalize()],stable[j].capitalize(),amass_int[cl[stable[j].capitalize()]] pl.plot(amass_int[u.cl[stable[j].capitalize()]],old_div(u.mass_fractions_array_decayed[u.back_ind[stable[j]]],u.solar_abundance[stable[j].lower()]),'Dk') for i in range(len(stable)): for j in range(len(stable)): if stable[i][:2] == stable[j][:2]: if stable[i] == stable[j-1]: adum =[amass_int[u.cl[stable[i].capitalize()]],amass_int[u.cl[stable[j].capitalize()]]] mfdum =[old_div(float(average_mass_frac[u.cl[stable[i].capitalize()]]),float(u.solar_abundance[stable[i].lower()])),old_div(float(average_mass_frac[u.cl[stable[j].capitalize()]]),float(u.solar_abundance[stable[j].lower()]))] mfddum=[old_div(float(u.average_mass_frac_decay[u.back_ind[stable[i]]]),float(u.solar_abundance[stable[i].lower()])),old_div(float(u.average_mass_frac_decay[u.back_ind[stable[j]]]),float(u.solar_abundance[stable[j].lower()]))] #pl.plot(adum,mfdum,'k-') # I had to add this try/except...why? I guess is someone related to H2, that I spotted that was wrong in stable_raw... # should deal without this. Have to be solved when I have time Marco (June 7 2011) if i_decay == 2: try: pl.plot(adum,mfddum,'k-') except UnboundLocalError: continue pl.xlabel('$Mass$ $number$', fontsize=20) pl.ylabel('$X_{i}/X_{sun}$', fontsize=20) pl.ylim(1.0e-3,5000.) pl.xlim(55,210) pl.grid() pl.show()
Interface to plot average over mass_range. Parameters ---------- directory : string Location of h5 file to plot. Needed for plot_tools. name_h5_file : string Name of h5 file. Needed for plot_tools. mass_range : list A 1x2 array required to plot data in a certain mass range. Needed for _read_iso_abund_marco. cycle : integer which cycle from the h5 file?. Needed for _read_iso_abund_marco. logic_stable : boolean Do you want to plot only stable or not. i_decay : integer If i_decay is 1, then plot not decayed. If i_decay is 2, then plot decayed. Make sense only if stable is true. file_solar : string File where to take solar abundances. solar_factor : float value to correct initial abundances to solar, e.g. for Z=0.01 and AG89 solar_factor = 2. See Also -------- se._read_iso_abund_marco()
entailment
def _obsolete_plot_el_abund_marco(directory,name_h5_file,mass_range,cycle,logic_stable,i_decay,file_solar,solar_factor,symbol='ko'): """ Interface to plot elements abundances averaged over mass_range. Parameters ---------- directory : string Location of h5 file to plot. Needed for plot_tools. name_h5_file : string Name of h5 file. Needed for plot_tools. mass_range : list A 1x2 array required to plot data in a certain mass range. Needed for _read_iso_abund_marco. cycle : integer which cycle from the h5 file?. Needed for _read_iso_abund_marco. logic_stable : boolean Do you want to plot only stable or not. i_decay : integer If i_decay is 1, then plot not decayed. If i_decay is 2, then plot decayed. Make sense only if stable is true. file_solar : string File where to take solar abundances. solar_factor : float value to correct initial abundances to solar, e.g. for Z=0.01 and AG89 solar_factor = 2. See Also -------- se._read_iso_abund_marco() """ # provide library for Z versus element names, and Z for elements u.give_zip_element_z_and_names() # solar abundances are read here u.solar(file_solar,solar_factor) # from here I have average abundances in mass_range to plot average_iso_abund_marco(mass_range,cycle,logic_stable,i_decay) # element abundances are calculated here mass_fractions_array_decayed = average_mass_frac_decay mass_fractions_array_not_decayed = average_mass_frac u.element_abund_marco(i_decay,stable,jjdum,mass_fractions_array_not_decayed,mass_fractions_array_decayed) fig = pl.figure() # Figure object ax = fig.add_subplot(1,1,1) # Axes object: one row, one column, first plot (one plot!) # Tick marks xminorlocator = MultipleLocator(1) xmajorlocator = MultipleLocator(10) ax.xaxis.set_major_locator(xmajorlocator) ax.xaxis.set_minor_locator(xminorlocator) yminorlocator = MultipleLocator(0.1) ymajorlocator = MultipleLocator(1) ax.yaxis.set_major_locator(ymajorlocator) ax.yaxis.set_minor_locator(yminorlocator) ax.set_yscale('log') if not logic_stable: for i in range(u.z_bismuth): pl.plot(z_for_elem[i],elem_prod_fac[i],symbol,markersize=10.) pl.xlabel('$Atomic$ $number$', fontsize=20) pl.ylabel('$X_{i}/X_{sun}$', fontsize=20) pl.ylim(1.0e-2,1000.) pl.xlim(0,95) elif logic_stable: for i in range(u.z_bismuth): if index_stable[i] == 1: continue #pl.plot(z_for_elem[i],elem_prod_fac[i],'ko') if i_decay == 2: for i in range(u.z_bismuth): if index_stable[i] == 1: pl.plot(z_for_elem[i],elem_prod_fac_decayed[i],symbol,markersize=10.) pl.xlabel('$Atomic$ $number$', fontsize=20) pl.ylabel('$X_{i}/X_{sun}$', fontsize=20) pl.ylim(1.0e-2,1000.) pl.xlim(0,95) pl.grid() pl.show()
Interface to plot elements abundances averaged over mass_range. Parameters ---------- directory : string Location of h5 file to plot. Needed for plot_tools. name_h5_file : string Name of h5 file. Needed for plot_tools. mass_range : list A 1x2 array required to plot data in a certain mass range. Needed for _read_iso_abund_marco. cycle : integer which cycle from the h5 file?. Needed for _read_iso_abund_marco. logic_stable : boolean Do you want to plot only stable or not. i_decay : integer If i_decay is 1, then plot not decayed. If i_decay is 2, then plot decayed. Make sense only if stable is true. file_solar : string File where to take solar abundances. solar_factor : float value to correct initial abundances to solar, e.g. for Z=0.01 and AG89 solar_factor = 2. See Also -------- se._read_iso_abund_marco()
entailment
def get(self, cycle_list, dataitem=None, isotope=None, sparse=1): """ Simple function that simply calls h5T.py get method. There are three ways to call this function. Parameters ---------- cycle_list : string, list If cycle_list is a string, then get interpates the argument cycle_list as a dataitem and fetches the dataitem for all cycles. If cycle_list is a list, then get fetches the dataitem for the cycles in the list. dataitem : string, optional fetches the dataitem from the list of cycles. If dataitem is None, then cycle_list must be a string and will be used as dataitem. If dataitem is an isotope in the form 'H-2', it then returns the result of, >>> self.get(cycle_list,'iso_massf',dataitem) The default is None. isotope : string, optional The name of the isotope to fetch, it must be in the form 'H-2'. If isotope is None, then cycle_list or dataitem must be a string. The default is None. sparse : integer, optional Implements a sparsity factor on the fetched data. The default is 1. Notes ----- Calling the get method directly in the form, >>> self.get(cycle_list,'iso_massf',dataitem) is depricated, and only included for compatibility. """ return self.se.get(cycle_list,dataitem,isotope,sparse)
Simple function that simply calls h5T.py get method. There are three ways to call this function. Parameters ---------- cycle_list : string, list If cycle_list is a string, then get interpates the argument cycle_list as a dataitem and fetches the dataitem for all cycles. If cycle_list is a list, then get fetches the dataitem for the cycles in the list. dataitem : string, optional fetches the dataitem from the list of cycles. If dataitem is None, then cycle_list must be a string and will be used as dataitem. If dataitem is an isotope in the form 'H-2', it then returns the result of, >>> self.get(cycle_list,'iso_massf',dataitem) The default is None. isotope : string, optional The name of the isotope to fetch, it must be in the form 'H-2'. If isotope is None, then cycle_list or dataitem must be a string. The default is None. sparse : integer, optional Implements a sparsity factor on the fetched data. The default is 1. Notes ----- Calling the get method directly in the form, >>> self.get(cycle_list,'iso_massf',dataitem) is depricated, and only included for compatibility.
entailment
def get_elemental_abunds(self,cycle,index=None): """ returns the elemental abundances for one cycle, either for the whole star or a specific zone depending upon the value of 'index'. Parameters ---------- cycle : string or integer Model to get the abundances for. index : integer or list, optional zone number for which to get elemental abundances. If None the entire abundance profile is returned. If a 1x2 list, the abundances are returned between indices of index[0] and index[1]. The default is None. """ isoabunds=self.se.get(cycle,'iso_massf') A=array(self.se.A) Z=array(self.se.Z) names=self.se.isos Zuq=list(set(Z)) # list of unique Zs Zuq.sort() if index==None: index=[0,len(isoabunds)] if type(index)==list: elemabunds=[] for zone in range(index[0],index[1]): percent=int((zone-index[0])*100./(index[1]-index[0])) sys.stdout.flush() sys.stdout.write("\rgetting elemental abundances " + "...%d%%" % percent) elemabunds.append([sum(isoabunds[zone][where(Z==iZ)]) for iZ in Zuq]) else: elemabunds=[sum(isoabunds[index][where(Z==iZ)]) for iZ in Zuq] return elemabunds
returns the elemental abundances for one cycle, either for the whole star or a specific zone depending upon the value of 'index'. Parameters ---------- cycle : string or integer Model to get the abundances for. index : integer or list, optional zone number for which to get elemental abundances. If None the entire abundance profile is returned. If a 1x2 list, the abundances are returned between indices of index[0] and index[1]. The default is None.
entailment
def plot_prof_1(self, mod, species, xlim1, xlim2, ylim1, ylim2, symbol=None): """ plot one species for cycle between xlim1 and xlim2 Parameters ---------- mod : string or integer Model to plot, same as cycle number. species : list Which species to plot. xlim1, xlim2 : float Mass coordinate range. ylim1, ylim2 : float Mass fraction coordinate range. symbol : string, optional Which symbol you want to use. If None symbol is set to '-'. The default is None. """ DataPlot.plot_prof_1(self,species,mod,xlim1,xlim2,ylim1,ylim2,symbol) """ tot_mass=self.se.get(mod,'total_mass') age=self.se.get(mod,'age') mass=self.se.get(mod,'mass') Xspecies=self.se.get(mod,'iso_massf',species) pyl.plot(mass,np.log10(Xspecies),'-',label=species) pyl.xlim(xlim1,xlim2) pyl.ylim(ylim1,ylim2) pyl.legend() pl.xlabel('$Mass$ $coordinate$', fontsize=20) pl.ylabel('$X_{i}$', fontsize=20) pl.title('Mass='+str(tot_mass)+', Time='+str(age)+' years, cycle='+str(mod)) """
plot one species for cycle between xlim1 and xlim2 Parameters ---------- mod : string or integer Model to plot, same as cycle number. species : list Which species to plot. xlim1, xlim2 : float Mass coordinate range. ylim1, ylim2 : float Mass fraction coordinate range. symbol : string, optional Which symbol you want to use. If None symbol is set to '-'. The default is None.
entailment
def plot_prof_2(self, mod, species, xlim1, xlim2): """ Plot one species for cycle between xlim1 and xlim2 Parameters ---------- mod : string or integer Model to plot, same as cycle number. species : list Which species to plot. xlim1, xlim2 : float Mass coordinate range. """ mass=self.se.get(mod,'mass') Xspecies=self.se.get(mod,'yps',species) pyl.plot(mass,Xspecies,'-',label=str(mod)+', '+species) pyl.xlim(xlim1,xlim2) pyl.legend()
Plot one species for cycle between xlim1 and xlim2 Parameters ---------- mod : string or integer Model to plot, same as cycle number. species : list Which species to plot. xlim1, xlim2 : float Mass coordinate range.
entailment
def write_deltatable(self, filename='default', decayed=True, dcycle=500, iniabufile='../../frames/mppnp/USEEPP/iniab2.0E-02GN93.ppn'): """ This subroutine is to write out tables with delta values for cosmochemists to use in comparison with their data. No options are necessarily needed to load this routine, however, it might be useful to specify a filename. This file furthermore searches for thermal pulses, hence, it's only useful for non-explosive TP-AGB stars! Parameters ---------- filename : string, optional Choose the filename you want. The default is "default". decayed : boolean, optional Value if decayed massfractions of isotope should be taken or not. The default is False. dcycle : integer, optional Difference between cycles to search for thermal pulses. The default is 500. iniabufile : string, optional File with initial abundances. As a standard value, the GN93 file is used (in USEEPP folder). Important, input file has to be USEEPP conforming, see NuGrid book! The default is '../../frames/mppnp/USEEPP/iniab2.0E-02GN93.ppn'. Notes ----- Regardless of what value is used as filename it will be replaced with 'delta_outfile.txt'. """ print('This is a preliminary version - contact Reto for more information!') # make filename filename = 'delta_outfile.txt' # which iso_massmf? if decayed: isomassmf = 'iso_massf_decay' else: isomassmf = 'iso_massf' # read in thermal pulse position and co_ratio (from private routine) tp_pos, co_return = self._tp_finder(dcycle) # define isotopes to read out and calculate delta values noele = 1 # there is at least one element available elelist = list() isolisttmp = list() isolist = list() isoabulist = list() isoabulisttmp = list() # load file w/ initial abundances inut = iniabu(iniabufile) # list of elements: itmp = inut.names[0][0:2].replace(' ','') elelist.append([itmp, inut.z[0]]) isolisttmp.append(inut.a[0]) isoabulisttmp.append(inut.abu[0]) for i in range(1,len(inut.names)): if inut.names[i][0:2].replace(' ','') != itmp: # add to elelist itmp = inut.names[i][0:2].replace(' ','') elelist.append([itmp, inut.z[i]]) # append to isolist isolist.append(isolisttmp) isolisttmp = list() isolisttmp.append(inut.a[i]) # append to isoabulist isoabulist.append(isoabulisttmp) isoabulisttmp = list() isoabulisttmp.append(inut.abu[i]) # increase number of elements noele += 1 else: # add to isolisttmp isolisttmp.append(inut.a[i]) isoabulisttmp.append(inut.abu[i]) isolist.append(isolisttmp) isoabulist.append(isoabulisttmp) ### CHOP TEMPORARILY ### elelist = elelist[5:len(elelist)-2] isolist = isolist[5:len(elelist)-2] isoabulist = isoabulist[5:len(elelist)-2] # make an index vector for at which position for each line the most abundand isotope is isoabuindex = zeros(len(isoabulist),dtype=int) # as integer! for i in range(len(isoabulist)): tmp = 0 for j in range(len(isoabulist[i])): if isoabulist[i][j] > tmp: isoabuindex[i] = j tmp = isoabulist[i][j] # and now - finally - make a list with all delta values that need to be calculated # 0: isotope name, 1: nominator isotope, 2: denominator isotope # also make solar system ratios list deltalist = list() solsysratio = list() for i in range(len(isolist)): if len(isolist[i]) > 1: for j in range(len(isolist[i])): if j != isoabuindex[i]: deltalist.append([elelist[i][0], isolist[i][j], isolist[i][isoabuindex[i]]]) solsysratio.append(old_div(isoabulist[i][j], isoabulist[i][isoabuindex[i]])) solsysratio = array(solsysratio) # Make an array to write all data into. first column, cycle number, second column, co ratio, then all delta values write_out = zeros((len(tp_pos), len(deltalist) + 2)) # now add first three columns to write_out for i in range(len(write_out)): write_out[i][0] = tp_pos[i] write_out[i][1] = co_return[i] # header for delta values deltaheader = list() ### BIG DELTA LOOP ### for deli in range(len(deltalist)): ## read in the two isotopes of interest, iso1 and iso2 (iso1 as nominator) iso1 = zeros(len(tp_pos)) iso2 = zeros(len(tp_pos)) # isotope names: if len(deltalist[deli][0]) == 1: iso1name = deltalist[deli][0].upper() + '-' + str(int(deltalist[deli][1])) iso2name = deltalist[deli][0].upper() + '-' + str(int(deltalist[deli][2])) else: iso1name = deltalist[deli][0][0].upper() + deltalist[deli][0][1] + '-' + str(int(deltalist[deli][1])) iso2name = deltalist[deli][0][0].upper() + deltalist[deli][0][1] + '-' + str(int(deltalist[deli][2])) # read in iso_data = self.get(tp_pos,isomassmf,[iso1name,iso2name]) iso1 = np.zeros(len(iso_data)) iso2 = np.zeros(len(iso_data)) for i in range(len(iso_data)): iso1[i] = iso_data[i][0] iso2[i] = iso_data[i][1] # readin loop # for i in range(len(tp_pos)): # iso1[i] = self.get(int(tp_pos[i]),isomassmf,iso1name) # iso2[i] = self.get(int(tp_pos[i]),isomassmf,iso2name) ## calculate deltavalue array deltavalues = (iso1/iso2 / solsysratio[deli] - 1.) * 1000. ## append values to write_out for i in range(len(deltavalues)): write_out[i][deli+2] = deltavalues[i] ## header deltaheader.append('del_' + deltalist[deli][0] + str(int(deltalist[deli][1])) + '_' + deltalist[deli][0] + str(int(deltalist[deli][2]))) ### WRITE OUT DATAFILE ### outf = open(filename,'w') # write header outf.writelines('cycle_no,'.ljust(18) + 'c_o_ratio,'.ljust(18)) for i in range(len(deltaheader)): if i != len(deltaheader)-1: outfstr = deltaheader[i] + ',' else: outfstr = deltaheader[i] outf.writelines(outfstr.ljust(18)) outf.writelines('\n') # write data for i in range(len(write_out)): for j in range(len(write_out[i])): if j != len(write_out[i])-1: outfstr = format(write_out[i][j],'.7E') + ',' else: outfstr = format(write_out[i][j],'.7E') outf.writelines(outfstr.ljust(18)) outf.writelines('\n') # close file outf.close()
This subroutine is to write out tables with delta values for cosmochemists to use in comparison with their data. No options are necessarily needed to load this routine, however, it might be useful to specify a filename. This file furthermore searches for thermal pulses, hence, it's only useful for non-explosive TP-AGB stars! Parameters ---------- filename : string, optional Choose the filename you want. The default is "default". decayed : boolean, optional Value if decayed massfractions of isotope should be taken or not. The default is False. dcycle : integer, optional Difference between cycles to search for thermal pulses. The default is 500. iniabufile : string, optional File with initial abundances. As a standard value, the GN93 file is used (in USEEPP folder). Important, input file has to be USEEPP conforming, see NuGrid book! The default is '../../frames/mppnp/USEEPP/iniab2.0E-02GN93.ppn'. Notes ----- Regardless of what value is used as filename it will be replaced with 'delta_outfile.txt'.
entailment
def _tp_finder(self, dcycle): # Private routine """ Routine to find thermal pulses in given star and returns an index vector that gives the cycle number in which the thermal pulse occure. The routine looks for the C/O ratio jumping up and up, so only useful in TP-AGB star. A vector is given back that indicates the position of the cycle that is at 95% of the thermal pulse (to make sure it's not in the next one and that most of the processing is done). The script also returns the co_ratio vector - the C/O ratio (number fraction) at the given thermal pulse. """ # read in c and o isotopes for all cycles, regarding deltacycle last_cycle = int(self.se.cycles[len(self.se.cycles)-1]) cyc_tp = list(range(1,last_cycle + dcycle, dcycle)) all_data = array(self.get(cyc_tp,['C-12','C-13','O-16','O-17','O-18'])) c_nf = np.zeros(len(all_data)) o_nf = np.zeros(len(all_data)) for i in range(len(all_data)): c_nf[i] = all_data[i][0] + all_data[i][1] o_nf[i] = all_data[i][2] + all_data[i][3] + all_data[i][4] # search for thermal pulses co_ratio = (old_div(c_nf, o_nf)) * 15.9994 / 12.0107 tp_guess = 200 # this should be an upper limit! tp_guess_max = 200 # to through an error # guess variables, i is the actual break criterion, n a max counter gi = 0 gn = 0 while gi != 1 and gn < 10000: tp_ind = list() i = 0 while i < len(co_ratio)-2: gcompar= old_div(1., (dcycle*tp_guess*100.)) slope1 = old_div((co_ratio[i+1]-co_ratio[i]),(dcycle)) slope2 = old_div((co_ratio[i+2]-co_ratio[i+1]),dcycle) if slope1 > gcompar and slope2 < gcompar and co_ratio[i+1] > co_ratio[i]: tp_ind.append(i+1) i += 3 # jump three cycles to avoid defining a single cycle twice! else: i += 1 if abs(len(tp_ind) - tp_guess) < old_div(tp_guess,2): # gotta be within factor two of guess gi = 1 else: gn += 1 tp_guess /= 2 # check w/ maximum of thermal pulses allowed if len(tp_ind) > tp_guess_max: print('Problem detected with number of pulses') # create thermal pulse vector tp_startf = zeros(len(tp_ind)) # found start for i in range(len(tp_startf)): tp_startf[i] = cyc_tp[tp_ind[i]] # read out isotopic composition at 95% of the thermal pulse and the initial of the star # set up thermal pulse positions tp_limits = zeros(len(tp_startf)+1) for i in range(len(tp_startf)): tp_limits[i] = tp_startf[i] tp_limits[len(tp_limits)-1] = int(self.se.cycles[len(self.se.cycles)-1]) # thermal pulse position (where to read the isotope ratio) tp_pos = list() for i in range(len(tp_startf)): tp_pos.append(int(tp_limits[i] + 0.95 * (tp_limits[i+1] - tp_limits[i]))) # create co_ret vector to return c/o ratio vector co_return = zeros(len(tp_pos)) for i in range(len(tp_pos)): co_return[i] = co_ratio[tp_ind[i]] # return the two vectors return tp_pos,co_return
Routine to find thermal pulses in given star and returns an index vector that gives the cycle number in which the thermal pulse occure. The routine looks for the C/O ratio jumping up and up, so only useful in TP-AGB star. A vector is given back that indicates the position of the cycle that is at 95% of the thermal pulse (to make sure it's not in the next one and that most of the processing is done). The script also returns the co_ratio vector - the C/O ratio (number fraction) at the given thermal pulse.
entailment
def ernst_table_exporter(self, cycle, outfname='table_out', sheetname='Sheet 1'): """ This routine takes NuGrid data (model output) for a given cycle and writes it into an Excel sheet. This is one format as requested by Ernst Zinner in June 2013 (through Marco). If you want all radioactive isotopes, start from the restart file. Empty columns are not written out and you will get a message how many were empty. Please note that only one cycle is written out. Parameters ---------- cycle : integer Number of the cycle to consider. outfname : string, optional File name to write it to, .xlsx is appended automatically. The default is 'table_out'. sheetname : string, optional Name of the sheet in the excel file. The default is 'Sheet 1'. """ from xlsxwriter.workbook import Workbook # https://xlsxwriter.readthedocs.org/ Note: We neex xlswriter. Please meake sure it is installed. Run pip install xlsxwriter to install it using pip. If pip is not installed, install it via easy_install pip. Depending on the system you are on, you might need sudo rights for thesethings.' # isotopes and data all_data = np.array(self.get(cycle,'iso_massf')) header_data = self.se.isotopes # get mass data mass_data = np.array(self.get(cycle,'mass'))[np.newaxis] # stack mass data and header together header_data = np.hstack((['Mass'],header_data)) all_data = np.hstack((mass_data.transpose(),all_data)) # zero the cells with 1.e-99 entry for i in range(len(all_data)): for j in range(len(all_data[i])): if all_data[i][j] == 1.e-99: all_data[i][j] = 0. # check how many columns have all zeros in the file colzero = 0 all_sum = all_data.sum(0) for i in range(len(all_sum)): if all_sum[i] == 0.: colzero += 1 print(str(colzero) + ' columns are empty. Skipping them.') # now filter data all_data_fil = np.zeros((len(all_data),len(all_data[0])-colzero)) header_data_fil = np.zeros((len(header_data)-colzero),dtype='|S9') k = 0 for j in range(len(all_data[0])): if all_sum[j] != 0: for i in range(len(all_data)): all_data_fil[i][k] = all_data[i][j] header_data_fil[k] = header_data[j] k += 1 # write to excel file excelfile = Workbook(outfname + '.xlsx') wsh = excelfile.add_worksheet(sheetname) print('If you run from a restart file, this might take a little bit. Be patient!') for i in range(len(all_data_fil)): for j in range(len(all_data_fil[i])): if i == 0: wsh.write(0,j,header_data_fil[j]) wsh.write(i+1,j,all_data_fil[i][j]) excelfile.close() return None
This routine takes NuGrid data (model output) for a given cycle and writes it into an Excel sheet. This is one format as requested by Ernst Zinner in June 2013 (through Marco). If you want all radioactive isotopes, start from the restart file. Empty columns are not written out and you will get a message how many were empty. Please note that only one cycle is written out. Parameters ---------- cycle : integer Number of the cycle to consider. outfname : string, optional File name to write it to, .xlsx is appended automatically. The default is 'table_out'. sheetname : string, optional Name of the sheet in the excel file. The default is 'Sheet 1'.
entailment
def plot4(self, num): """ Plots the abundances of H-1, He-4, C-12 and O-16. """ self.plot_prof_1(num,'H-1',0.,5.,-5,0.) self.plot_prof_1(num,'He-4',0.,5.,-5,0.) self.plot_prof_1(num,'C-12',0.,5.,-5,0.) self.plot_prof_1(num,'O-16',0.,5.,-5,0.) pyl.legend(loc=3)
Plots the abundances of H-1, He-4, C-12 and O-16.
entailment
def plot4_nolog(self, num): """ Plots the abundances of H-1, He-4, C-12 and O-16. """ self.plot_prof_2(num,'H-1',0.,5.) self.plot_prof_2(num,'He-4',0.,5.) self.plot_prof_2(num,'C-12',0.,5.) self.plot_prof_2(num,'O-16',0.,5.) pyl.legend(loc=3)
Plots the abundances of H-1, He-4, C-12 and O-16.
entailment
def plot_prof_sparse(self, mod, species, xlim1, xlim2, ylim1, ylim2, sparse, symbol): """ plot one species for cycle between xlim1 and xlim2. Parameters ---------- species : list which species to plot. mod : string or integer Model (cycle) to plot. xlim1, xlim2 : float Mass coordinate range. ylim1, ylim2 : float Mass fraction coordinate range. sparse : integer Sparsity factor for points. symbol : string which symbol you want to use? """ mass=self.se.get(mod,'mass') Xspecies=self.se.get(mod,'yps',species) pyl.plot(mass[0:len(mass):sparse],np.log10(Xspecies[0:len(Xspecies):sparse]),symbol) pyl.xlim(xlim1,xlim2) pyl.ylim(ylim1,ylim2) pyl.legend()
plot one species for cycle between xlim1 and xlim2. Parameters ---------- species : list which species to plot. mod : string or integer Model (cycle) to plot. xlim1, xlim2 : float Mass coordinate range. ylim1, ylim2 : float Mass fraction coordinate range. sparse : integer Sparsity factor for points. symbol : string which symbol you want to use?
entailment
def trajectory(self, ini, end, delta, mass_coo, age_in_sec=False, online=False): """ create a trajectory out of a stellar model Parameters ---------- ini : integer Initial model, inital cycle number. end : integer Final model, final cycle number. delta : integer Sparsity factor of the frames. mass_coo : float Mass coordinate for the traj. age_in_sec : boolean, optional Set to True if age in se file is in seconds (like in MESA). The default is False. Returns -------- float radius_at_mass_coo, density_at_mass_coo, temperature_at_mass_coo, age_all Notes ----- plus writes a file with the trajectory information to be used with ppn. Warning: remove the old trajectory, if you have any for the same mass coordinate. You are appending data, not overwriting. Update: this method works for output types with indexes going from the outside in (MESA) or the other way around. Also the requested quantities are linearly interpolated in the mass shell. online: boolean, optional are you working online in the ipython notebook? If so, you will be given an HTML link to download the file. """ filename='traj_'+str(mass_coo)+'.dat' f = open(filename,'a') radius_at_mass_coo=[] density_at_mass_coo=[] temperature_at_mass_coo=[] masses=self.se.get(list(range(ini,end+1,delta)),'mass') temps=self.se.get(list(range(ini,end+1,delta)),'temperature') rhos=self.se.get(list(range(ini,end+1,delta)),'rho') radii=self.se.get(list(range(ini,end+1,delta)),'radius') ages=self.se.get(list(range(ini,end+1,delta)),'age') cycs=list(range(ini,end+1,delta)) age_all=[] for i in range(len(ages)): age=ages[i] if age_in_sec: age /= constants.one_year mass=masses[i] temperature=temps[i] rho=rhos[i] radius=radii[i] my_things=[temperature,rho,radius] if mass[0]>mass[len(mass)-1]: zone_above=where(mass>mass_coo)[0][-1] zone_below=zone_above+1 else: zone_above=where(mass>mass_coo)[0][0] zone_below=zone_above-1 if mass[zone_below]>mass[zone_above]: sys.exit("ERROR: finding of zone index confused") all_things_interplt=[] for thing in my_things: thing_interplt=thing[zone_below]+(mass_coo-mass[zone_below])* \ (thing[zone_above]-thing[zone_below])/(mass[zone_above]-mass[zone_below]) all_things_interplt.append(thing_interplt) this_temperature,this_rho,this_radius=all_things_interplt string = str(cycs[i])+' '+str(age)+' '+str(this_temperature)+' '+str(this_rho) f.write(string+"\n") radius_at_mass_coo.append(this_radius) density_at_mass_coo.append(this_rho) temperature_at_mass_coo.append(this_temperature) age_all.append(age) f.close() if online: return FileLink(filename) return radius_at_mass_coo, density_at_mass_coo, temperature_at_mass_coo, age_all
create a trajectory out of a stellar model Parameters ---------- ini : integer Initial model, inital cycle number. end : integer Final model, final cycle number. delta : integer Sparsity factor of the frames. mass_coo : float Mass coordinate for the traj. age_in_sec : boolean, optional Set to True if age in se file is in seconds (like in MESA). The default is False. Returns -------- float radius_at_mass_coo, density_at_mass_coo, temperature_at_mass_coo, age_all Notes ----- plus writes a file with the trajectory information to be used with ppn. Warning: remove the old trajectory, if you have any for the same mass coordinate. You are appending data, not overwriting. Update: this method works for output types with indexes going from the outside in (MESA) or the other way around. Also the requested quantities are linearly interpolated in the mass shell. online: boolean, optional are you working online in the ipython notebook? If so, you will be given an HTML link to download the file.
entailment
def abund_at_masscoordinate(self, ini, mass_coo, online=False): """ Create a file with distribution at a given mass coord, and at a given time step. This for instance may be used as intial distribution for function trajectory, to reproduce local conditions in ppn. Parameters ---------- ini : integer Initial model, inital cycle number. mass_coo : float or 1x2 list Mass coordinate for the traj. If list, return mass-averaged abundances for the region spanned by the list. online: boolean, optional are you working online in the ipython notebook? If so, you will be given an HTML link to download the file. """ age=self.se.get(ini,'age') mass=self.se.get(ini,'mass') temperature=self.se.get(ini,'temperature') rho=self.se.get(ini,'rho') abund_string = self.se.dcols[5] print(abund_string) if online: from IPython.display import FileLink, FileLinks tm=type(mass_coo) if tm is not list: filename='massf_'+str(mass_coo)+'.dat' f = open(filename,'w') zone=np.abs(mass-mass_coo).argmin() abunds=self.se.get(ini,abund_string)[zone] mass_coo_new=mass[zone] else: filename='massf_'+str(mass_coo[0])+'_'+str(mass_coo[1])+'.dat' f = open(filename,'w') idx1=np.abs(mass-mass_coo[0]).argmin() idx2=np.abs(mass-mass_coo[1]).argmin() dm=np.diff(np.insert(mass,0,0.)) dm=dm[idx1:idx2] #average abundances: totmass=sum(dm) abunds=self.se.get(ini,abund_string)[idx1:idx2] dmabunds=[abunds[i]*dm[i] for i in range(len(dm))] abundsum=np.zeros(len(self.se.isotopes)) for i in range(len(abundsum)): abundsum[i]=sum([vec[i] for vec in dmabunds]) abunds=old_div(abundsum, totmass) # for i in range(len(mass)): # if mass_coo == mass[i]: # mass_coo_new = mass[i] # zone = int(i) # elif mass_coo > mass[i]: # try: # dum = mass[i+1] # if mass_coo <= mass[i+1]: # mass_coo_new = mass[i+1] # zone = int(i+1) # except IndexError: # mass_coo_new = mass[i] # zone = int(i) if tm is not list: string = 'C Model number | time (yr) | Temperature (GK) | density (cm^-3) ' f.write(string+"\n") string = 'C '+str(ini)+' '+str(age)+' '+str(temperature[zone])+' '+str(rho[zone]) f.write(string+"\n") string = 'C Mass coordinate that is really used' f.write(string+"\n") string = 'C '+str(mass_coo_new) f.write(string+"\n") else: string = 'C Model number | time (yr)' f.write(string+"\n") string = 'C '+str(ini)+' '+str(age) f.write(string+"\n") string = 'C Mass coordinate range' f.write(string+"\n") string = 'C '+str(mass_coo[0])+', '+str(mass_coo[1]) f.write(string+"\n") # the for loop below maybe optimized, I believe # defining before isotopes and abundances. Marco 13 Jannuary 2011 for i in range(len(self.se.isotopes)): if str(self.se.isotopes[i].split('-')[1][-2:]).upper() != 'M1': string = 'D '+str(self.se.isotopes[i].split('-')[0]).upper()+' '+str(self.se.isotopes[i].split('-')[1]).upper()+' '+str(abunds[i]) f.write(string+"\n") f.close() if online: return FileLink(filename)
Create a file with distribution at a given mass coord, and at a given time step. This for instance may be used as intial distribution for function trajectory, to reproduce local conditions in ppn. Parameters ---------- ini : integer Initial model, inital cycle number. mass_coo : float or 1x2 list Mass coordinate for the traj. If list, return mass-averaged abundances for the region spanned by the list. online: boolean, optional are you working online in the ipython notebook? If so, you will be given an HTML link to download the file.
entailment
def _kip(self, cycle_end, mix_thresh, xaxis, sparse): """ *** Should be used with care, therefore has been flagged as a private routine *** This function uses a threshold diffusion coefficient, above which the the shell is considered to be convective, to plot a Kippenhahn diagram. Parameters ---------- cycle_end : integer The final cycle number. mix_thresh : float The threshold diffusion coefficient. xaxis : string Choose one of 'age', 'cycle', 'log_age' or 'log_time_left'. sparse : integer Sparsity factor when plotting from cyclelist. Examples -------- >>> pt=mp.se('/ngpod1/swj/see/mppnp_out/scratch_data/M25.0Z1e-02','.h5') >>> pt.kip(10000,'log_time_left',100) """ original_cyclelist = self.se.cycles cyclelist = original_cyclelist[0:cycle_end:sparse] xx = self.se.ages[:cycle_end:sparse] totalmass = [] m_ini = float(self.se.get('mini')) fig = pl.figure(1) ax = pl.subplot(1,1,1) fsize = 12 def getlims(d_coeff, massco): """ This function returns the convective boundaries for a cycle, given the cycle's dcoeff and massco columns, taking into account whether surface or centre are at the top. """ plotlims = [] if massco[0] > massco[-1]: for j in range(-1,-len(d_coeff)-1,-1): if j == -1: if d_coeff[j] >= mix_thresh: plotlims.append(massco[j]) else: pass elif (d_coeff[j]-mix_thresh)*(d_coeff[j+1]-mix_thresh) < 0: plotlims.append(massco[j]) if j == -len(d_coeff): if d_coeff[j] >= mix_thresh: plotlims.append(massco[j]) return plotlims else: for j in range(len(d_coeff)): if j == 0: if d_coeff[j] >= mix_thresh: plotlims.append(massco[j]) else: pass elif (d_coeff[j]-mix_thresh)*(d_coeff[j-1]-mix_thresh) < 0: plotlims.append(massco[j]) if j == len(d_coeff)-1: if d_coeff[j] >= mix_thresh: plotlims.append(massco[j]) return plotlims if xaxis == 'age': ax.set_xlabel('Age [yr]',fontsize=fsize) elif xaxis == 'cycle': xx = cyclelist ax.set_xlabel('Cycle',fontsize=fsize) elif xaxis == 'log_age': for i in range(len(xx)): xx[i] = np.log10(xx[i]) ax.set_xlabel('log$_{10}$(age) [yr]',fontsize=fsize) elif xaxis == 'log_time_left': for i in range(len(xx)): xx[i] = np.log10(max(xx)-xx[i]) xx[-2] = xx[-3]-abs(xx[-4]-xx[-3]) xx[-1] = xx[-2]-abs(xx[-3]-xx[-2]) ax.set_xlabel('log$_{10}$(time until collapse) [yr]',fontsize=fsize) #centre-surface flag: flag = False if self.se.get(cyclelist[1],'mass')[0] > self.se.get(cyclelist[1],'mass')[-1]: flag = True for i in range(len(cyclelist)): if flag == True: totalmass.append(self.se.get(cyclelist[i],'mass')[0]) else: totalmass.append(self.se.get(cyclelist[i],'mass')[-1]) percent = int(i*100/len(cyclelist)) sys.stdout.flush() sys.stdout.write("\rcreating color map " + "...%d%%" % percent) d_coeff = self.se.get(cyclelist[i],'dcoeff') massco = self.se.get(cyclelist[i],'mass') plotlims = getlims(d_coeff,massco) for k in range(0,len(plotlims),2): ax.axvline(xx[i],ymin=old_div(plotlims[k],m_ini),ymax=old_div(plotlims[k+1],m_ini),color='b',linewidth=0.5) ax.plot(xx, totalmass, color='black', linewidth=1) if xaxis == 'log_time_left': ax.axis([xx[0],xx[-1],0.,m_ini]) else: ax.axis([min(xx),max(xx),0.,m_ini]) ax.set_ylabel('Mass [$M_{\odot}$]',fontsize=fsize) pl.show()
*** Should be used with care, therefore has been flagged as a private routine *** This function uses a threshold diffusion coefficient, above which the the shell is considered to be convective, to plot a Kippenhahn diagram. Parameters ---------- cycle_end : integer The final cycle number. mix_thresh : float The threshold diffusion coefficient. xaxis : string Choose one of 'age', 'cycle', 'log_age' or 'log_time_left'. sparse : integer Sparsity factor when plotting from cyclelist. Examples -------- >>> pt=mp.se('/ngpod1/swj/see/mppnp_out/scratch_data/M25.0Z1e-02','.h5') >>> pt.kip(10000,'log_time_left',100)
entailment
def kip_cont(self, modstart, modstop, dcoeff_thresh=1.e12, xres=1000, ylims=[0., 0.], xlims=[0., 0.], yres=2000, ixaxis='log_time_left', outfile='', landscape_plot=False, codev='KEP', kepswitch=12555, outlines=False, write_preproc=False, hatching=False): """ This function creates a Kippenhahn diagram as a contour plot of the se output using a convection flag or diffusion coefficient threshold. Parameters ---------- modstart, modstop : integer First and last cycle numbers to plot. dcoeff_thresh : float, optional Diffusion coefficient threshold, above which assume convection is present (only for MESA, where convection_indicator is not there)). The default is 1.e12. xres, yres : integer, optional x and y resolution. The default for xres is 1000, the default for yres is 2000. xlims, ylims : list, optional x and y plot limits. The default is [0., 0.]. ixaxis : string, optional Choose one of 'age', 'model_number' or 'log_time_left'. The default is 'log_time_left'. outfile : string, optional Name of output file including extension, which will be saved in 300 dpi. The default is ''. landscape_plot : boolean, optional For a landscape plot. The default is False. codev : string, optional Coose one of 'KEP', 'MES' or 'GNV'. The default is 'KEP'. kepswitch : integer, optional The default is 12555. outlines : boolean, optional The default is False. write_preproc : boolean, optional The default is False. hatching : boolean, optional The default if False. Examples -------- >>> pt.kip_cont(0, -1, xres=1000, yres=1000, ixaxis='log_time_left') Notes ----- Unfortunately, although the implicit do loops are faster, I cannot implement a % bar, but this example call should not take more than 1 minute. """ tmp_cycles=self.se.cycles original_cyclelist = [int(tmp_cycles[i]) for i in range(len(tmp_cycles))] nmodels=len(self.se.cycles[modstart:modstop]) print('nmodels = ', nmodels) sparse = int(max(1,old_div(nmodels,xres))) cyclelist = original_cyclelist[modstart:modstop:sparse] age_unit=self.get('age_unit') if codev == 'KEP': oneyear = 365.*24.*3600. elif codev == 'MES': oneyear=self.get('one_year') elif codev == 'GNV': oneyear=1.e0 m_min=ylims[0] m_max=ylims[1] if m_min==0.: m_min=0. ylims[0] = m_min if m_max==0.: m_max=float(self.se.get('mini')) ylims[1] = m_max dy = old_div((m_max-m_min),float(yres)) y = np.arange(m_min, m_max, dy) Z = np.zeros([len(y),len(cyclelist)],float) datatype='convection' if 'convection_indicator' not in self.se.dcols: datatype='dcoeff' def list_to_string(array): string='' for el in array: string+=' '+str(el)+' ' string+='\n' return string if write_preproc==True: if os.path.exists(self.sedir+'/conv_data_preproc.txt'): print('Preprocessor already exists (conv_data_preproc.txt).') print('Please remove this file if you want to create a new preprocessor file') sys.exit() print('write_preproc=True') print('getting complete dataset') print('getting mass coordinates') allcycs=[int(self.se.cycles[i]) for i in range(len(self.se.cycles))] mass=self.se.get(allcycs,'mass') print('getting conv') if datatype=='dcoeff': conv=se.f.se.get(allcycs,'dcoeff') else: conv=self.se.get(allcycs,'convection_indicator') print('getting cycles') models=self.se.cycles print('getting ages') if codev=='KEP': deltat=self.se.get(allcycs,'deltat') ages=np.cumsum(deltat) else: ages=self.se.ages print('writing preprocessor file') f=open(self.sedir+'/conv_data_preproc.txt','w') #f=open('./conv_data_preproc.txt','w') f.write('FORMAT OF THIS FILE:\n') f.write('model_number\n') f.write('star_age/yr\n') f.write('mass/Mo\n') f.write('convection_indicator or dcoeff if unavailable \n') f.write('*************************************************************\n') for i in range(len(models)): percent = int(i*100/len(self.se.cycles)) sys.stdout.flush() sys.stdout.write("\rprogress " + "...%d%%" % percent) f.write(str(models[i])+'\n') f.write(str(ages[i])+'\n') f.write(list_to_string(mass[i])) f.write(list_to_string(conv[i])) f.close() print('preprocessor file written') sys.exit() def realarray(array): """ Parameters ---------- array : list Takes array of strings Returns -------- list array of floats """ floatarray=np.array([float(el) for el in array]) return floatarray print('getting data...') if os.path.exists(self.sedir+'/conv_data_preproc.txt'): print('... from preprocessor file ...') lines=open(self.sedir+'/conv_data_preproc.txt','r').readlines() #lines=open('./conv_data_preproc.txt','r').readlines() lines=lines[6:] mod=np.array([float(line.split()[0]) for line in lines[::4]]) age=old_div(np.array([float(line.split()[0]) for line in lines[1::4]]),oneyear) # masses and mix types will be read just as an array of strings (each string is a profile) # to be extracted later masses=lines[2::4] conv=lines[3::4] tmp=[realarray(massco.split()) for massco in masses] masses=tmp tmp=[realarray(mixvec.split()) for mixvec in conv] conv=tmp print(len(age),len(mod),len(masses),len(conv)) else: print('... from HDF5 data ...') masses=self.se.get(cyclelist,'mass') mod=cyclelist if self.deltat == None: print('getting deltat since not initialised') self.deltat = self.se.get(self.se.cycles,'deltat') age=old_div(np.cumsum(self.deltat), (3600.*24.*365.)) if datatype=='convection': conv=self.se.get(cyclelist,'convection_indicator') else: conv=self.se.get(cyclelist,'dcoeff') print('calculating convection matrix... ') print(len(masses)) conv_i_vec_matrix=np.zeros([len(y),len(masses)],float) for i in range(len(masses)): percent = int(i*100/len(masses)) sys.stdout.flush() sys.stdout.write("\rcreating color map mix " + "...%d%%" % percent) mass = masses[i] mix = conv[i] # print i, len(mass),len(mix) # rearrange centre to surface: if mass[-1]<mass[0]: mass=np.append(mass,[0.])[::-1] mix=np.append(mix,[0.])[::-1] else: mass=np.append(mass[::-1],[0.])[::-1] mix=np.append(mix[::-1],[0.])[::-1] f = interpolate.interp1d(mass, mix, bounds_error=False, fill_value=0.) mixnew = f(y) for j in range(len(mixnew)): conv_i_vec_matrix[j,i] = mixnew[j] print('getting stellar mass...') mtot = np.array([np.max(m) for m in masses]) ######################################################################### # PLOT: fsize=20 params = {'axes.labelsize': fsize, 'text.fontsize': fsize, 'legend.fontsize': fsize, 'xtick.labelsize': fsize*0.8, 'ytick.labelsize': fsize*0.8, 'xtick.major.pad': 8, # distance to major tick label in points 'ytick.major.pad': 6, # distance to major tick label in points 'text.usetex': False} pl.rcParams.update(params) fig = pl.figure(1) ax = pl.axes() if landscape_plot == True: fig.set_size_inches(9,4) fsize=20 pl.gcf().subplots_adjust(bottom=0.15) pl.gcf().subplots_adjust(right=0.85) ax.set_ylabel('$\mathrm{Mass }(M_\odot)$',fontsize=fsize) xxx=[] age_array = age if ixaxis == 'log_time_left': # log of time left until core collapse gage= np.array(age_array) lage=np.zeros(len(gage)) agemin = max(old_div(abs(gage[-1]-gage[-2]),5.),1.e-10) for i in np.arange(len(gage)): if gage[-1]-gage[i]>agemin: lage[i]=np.log10(gage[-1]-gage[i]+agemin) else : lage[i]=np.log10(agemin) xxx = np.array([lage[int(i)] for i in cyclelist]) # np.array([lage[i] for i in cyclelist]) print(len(xxx)) print('plot versus time left') ax.set_xlabel('$\mathrm{log}_{10}(t^*/\mathrm{yr})$',fontsize=fsize) if xlims == [0.,0.]: xlims = [xxx[0],xxx[-1]] elif ixaxis =='model_number': cyclelist=mod[modstart:modstop:sparse] # np.array([int(cycle) for cycle in cyclelist]) xxx= cyclelist print('plot versus model number') ax.set_xlabel('Model number',fontsize=fsize) if xlims == [0.,0.]: xlims = [cyclelist[0],cyclelist[-1]] elif ixaxis =='age': xxx = old_div(np.array([age_array[int(i)] for i in cyclelist]),1.e6) print('plot versus age') ax.set_xlabel('Age [Myr]',fontsize=fsize) if xlims == [0.,0.]: xlims = [xxx[0],xxx[-1]] #cmapMIX=mpl.colors.ListedColormap(['w','#8B8386']) # rose grey cmapMIX = mpl.colors.ListedColormap(['#C4C4C4']) # grey77 #cmap = mpl.colors.ListedColormap(['w','b']) # some stuff for rasterizing only the contour part of the plot, for nice, but light, eps: class ListCollection(Collection): def __init__(self, collections, **kwargs): Collection.__init__(self, **kwargs) self.set_collections(collections) def set_collections(self, collections): self._collections = collections def get_collections(self): return self._collections @allow_rasterization def draw(self, renderer): for _c in self._collections: _c.draw(renderer) def insert_rasterized_contour_plot(c): collections = c.collections for _c in collections: _c.remove() cc = ListCollection(collections, rasterized=True) ax = pl.gca() ax.add_artist(cc) return cc print('plotting contours') ax.autoscale(False) low_level = dcoeff_thresh - old_div(dcoeff_thresh,10) high_level= dcoeff_thresh + old_div(dcoeff_thresh,10) if datatype=='dcoeff': low_level = dcoeff_thresh - old_div(dcoeff_thresh,10) high_level= dcoeff_thresh + old_div(dcoeff_thresh,10) CMIX=ax.contourf(xxx,y,conv_i_vec_matrix, cmap=cmapMIX, alpha=1.0,levels=[low_level,1.e99]) else: CMIX=ax.contourf(xxx,y,conv_i_vec_matrix, cmap=cmapMIX, alpha=1.0,levels=[0.5,1.5]) if outlines == True: if datatype=='dcoeff': CMIXoutlines=ax.contour(xxx,y,conv_i_vec_matrix, cmap=cmapMIX,levels=[low_level,high_level]) else: CMIX_outlines=ax.contour(xxx,y,conv_i_vec_matrix, cmap=cmapMIX,levels=[0.5,1.5]) ax.plot(xxx,mtot,color='k') ax.axis([xlims[0],xlims[-1],ylims[0],ylims[1]]) def contour_to_hatched_patches(cntrset, hatch_colors, hatch_patterns, remove_contour=True): from itertools import cycle patches_list = [] for pathcollection in cntrset.collections: patches_list.append([PathPatch(p1) for p1 in pathcollection.get_paths()]) if remove_contour: pathcollection.remove() for patches, hc, hp in zip(patches_list, cycle(hatch_colors), cycle(hatch_patterns)): for p in patches: p.set_fc("none") p.set_ec("k") p.set_hatch(hp) ax.add_patch(p) hatch_colors = "k" hatch_patterns = "/\|-+xoO.*" if hatching==True: contour_to_hatched_patches(CMIX, hatch_colors, hatch_patterns, remove_contour=True) # uncomment or rasterizing the contour - for making nice eps figures that aren't huge files: #insert_rasterized_contour_plot(CMIX) #if outlines==True: # insert_rasterized_contour_plot(CMIXoutlines) if outfile!='': if outfile[-4:] == '.png': fig.savefig(outfile,dpi=300) elif outfile[-4:] == '.eps': fig.savefig(outfile,format='eps') elif outfile[-3:] == '.ps': fig.savefig(outfile,format='ps') elif outfile[-4:] == '.pdf': fig.savefig(outfile,format='pdf') else: print('file format not specified as .eps or .png, saving as eps:') print(outfile+'.eps') fig.savefig(outfile+'.eps',format='eps') pl.show()
This function creates a Kippenhahn diagram as a contour plot of the se output using a convection flag or diffusion coefficient threshold. Parameters ---------- modstart, modstop : integer First and last cycle numbers to plot. dcoeff_thresh : float, optional Diffusion coefficient threshold, above which assume convection is present (only for MESA, where convection_indicator is not there)). The default is 1.e12. xres, yres : integer, optional x and y resolution. The default for xres is 1000, the default for yres is 2000. xlims, ylims : list, optional x and y plot limits. The default is [0., 0.]. ixaxis : string, optional Choose one of 'age', 'model_number' or 'log_time_left'. The default is 'log_time_left'. outfile : string, optional Name of output file including extension, which will be saved in 300 dpi. The default is ''. landscape_plot : boolean, optional For a landscape plot. The default is False. codev : string, optional Coose one of 'KEP', 'MES' or 'GNV'. The default is 'KEP'. kepswitch : integer, optional The default is 12555. outlines : boolean, optional The default is False. write_preproc : boolean, optional The default is False. hatching : boolean, optional The default if False. Examples -------- >>> pt.kip_cont(0, -1, xres=1000, yres=1000, ixaxis='log_time_left') Notes ----- Unfortunately, although the implicit do loops are faster, I cannot implement a % bar, but this example call should not take more than 1 minute.
entailment
def _kip_cont2(self, sparse, cycle_start=0, cycle_end=0, plot=['dcoeff'], thresholds=[1.0E+12], xax='log_time_left', alphas=[1.0], yllim=0., yulim=0., y_res=2000, xllim=0., xulim=0., age='seconds', sparse_intrinsic=20, engen=False, netnuc_name='eps_nuc', engenalpha=0.6, outfile='plot.pdf', annotation='', KEPLER=False): """ !! EXPERIMENTAL FEATURE (flagged as private) !! This function creates a Kippenhahn diagram as a contour plot of the .se.h5 or .out.h5 files using any continuous variable (columns in the hdf5 cycle data). Multiple columns may be plotted, their name indicated in the list "plot", and their thresholds in the list "thresholds". Currently, this is only designed to take one threshold for each variable but future versions will hopefully be able to plot with multiple thresholds, however you may circumvent this issue by repeating the variable in "plots" and entering a second threshold for it in "thresholds". Parameters ---------- sparse : integer x-axis (timestep) sparsity. The true sparsity is sparse*sparse_intrinsic. Try 100 or 500 for .se.h5 and 20 for .out.h5 files and for preliminaxllimry plots. cycle_start : integer, optional Cycle from which you wish to plot. The default is 0. cycle_end : integer, optional Maximum cycle that you wish to plot. If cycle_end is 0, then it will plot up to the last cycle available. The default is 0. plot : list, optional 1-D array containing the variables to be plotted (as strings, e.g. plots=['dcoeff','C-13']. I recommend always plotting 'dcoeff' as plots[0]). The default is ['dcoeff']. thresholds : list, optional 1-D array containing the thresholds corresponding to the variables in "plots". The default is [1.0E+12]. xax : string, optional x-axis quantity; either 'log_time_left' or 'cycles'. The default is 'log_time_left'. alphas : list, optional Array containing the opacity (0 to 1) of the contour for each variable. The default is [1.0]. yllim : float, optional Lower plot limit for y-axis (mass co-ordinate). The default is 0.. yulim : float, optional Upper plot limit for y-axis (mass co-ordinate). The default is 0.. y_res : integer, optional y-axis resolution. Defaults to 2000 but increasing to as much as 10000 does not significantly affect the plotting time. The default is 2000. xllim : float, optional Lower plot limit for x-axis. The default is 0.. xulim : float, optional Upper plot limit for x-axis. The default is 0.. age : string, optional Either 'years' or 'seconds', depending on the data. The default is 'seconds'. sparse_intrinsic : integer, optional Sparsity of timesteps in the data provided (usually 20 for .out.h5 files and 1 for .se.h5 files). The default is 20. engen : boolean, optional Whether the user would like to plot Kippenhahn of convective zones and energy generation. If True, please still include plots=['dcoeff'] and thresholds=[1.0E+12'] in your call. This will require the data to have an 'eps_nuc' column, so the plot is only working for .se.h5 files from MESA in the current se library. This is the most recent addition, so probably the most buggy. The plot script will automatically calculate and assign multiple thresholds according to the model. The default is False. netnuc_name : string, optional The name of the column containing (eps_nuc-eps_neu). If you do not have available eps_neu, then you can give netnuc_name="eps_nuc" to just plot energy generation. The default is "eps_nuc". engenalpha : float, optional Opacity of the energy generation contours. The default is 0.6. outfile : string, optional The name to save the plot as. The default is 'plot.pdf'. annotation : string, optional Some optional annotation to add to the plot. The default is ''. KEPLER : boolean, optional The default is False. """ # Organize cycles and ages: original_cyclelist = self.se.cycles if cycle_end==0.: cycle_end = original_cyclelist[-1] cycle_end = old_div(int(cycle_end),sparse_intrinsic) - 1 if cycle_start==0: pass else: cycle_start = old_div(int(cycle_start),sparse_intrinsic) - 1 cyclelist = original_cyclelist[cycle_start:cycle_end:sparse] # fix for KEPLER restart counting at O burning: original_ages= self.se.ages age_at_restart = 0. age_at_restart_idx = 0 if KEPLER == True: for i in range(1,len(original_ages)): if (original_ages[i]-original_ages[i-1]) < 0.: age_at_restart_idx = i-1 age_at_restart = original_ages[i-1] print('age restart found at cycle = '+str(age_at_restart_idx)+', age = '+str(age_at_restart)) KEPLER = True break for i in range(age_at_restart_idx+1,len(original_ages)): original_ages[i] = original_ages[i] + age_at_restart # Figure: fig = pl.figure() ax = pl.axes() params = {'axes.labelsize': 15, 'text.fontsize': 15, 'legend.fontsize': 15, 'xtick.labelsize': 15, 'ytick.labelsize': 15, 'text.usetex': False} fsize=18 pl.rcParams.update(params) # X-axis: if xax == 'log_time_left': if KEPLER == True: xxtmp = original_ages[cycle_start:cycle_end:sparse] else: xxtmp = self.se.ages[cycle_start:cycle_end:sparse] if age == 'years': if KEPLER == True: pass else: xxtmp = self.se.ages[cycle_start:cycle_end:sparse] elif age == 'seconds': if KEPLER == True: for i in range(len(cyclelist)): xxtmp[i] = old_div(original_ages[cycle_start:cycle_end:sparse][i],31558149.984) else: for i in range(len(cyclelist)): xxtmp[i] = old_div(self.se.ages[cycle_start:cycle_end:sparse][i],31558149.984) if xax == 'cycles': xx = cyclelist xxtmp = cyclelist # Set up x-axis according to whether ages are in years or seconds and # re-write as log(time left). The last entry will always be -inf in this # way so we calculate it by extrapolating the anti-penultimate and # penultimate entries. # Modified from the GENEC gdic (R. Hirschi) if xax == 'log_time_left': xx=np.zeros(len(xxtmp)) agemin = max(old_div(abs(xxtmp[-1]-xxtmp[-2]),5.),1.e-10) for i in np.arange(len(xxtmp)): if xxtmp[-1]-xxtmp[i]>agemin: xx[i]=np.log10(xxtmp[-1]-xxtmp[i]+agemin) else : xx[i]=np.log10(agemin) ax.set_xlabel('$log_\mathrm{10}(t_\mathrm{end}-t)\;[\mathrm{yr}]$',fontsize=fsize-1) if xax == 'cycles': ax.set_xlabel('$\mathrm{CYCLE}$',fontsize=fsize-1) # Y-axis limits and resolution: totalmass = [] try: m_ini = float(self.se.get('mini')) except: mini=m.se.get(0,'total_mass') mini=old_div(mini,constants.mass_sun) print('getting Mini from 1st cycle') if yulim==0.: yulim = m_ini dy = old_div(m_ini,float(y_res)) vlinetol = 1.0E-8 # Set up (y-axis) vector and a 3-D (hist) array to store all of the # contours. y = np.arange(0., m_ini, dy) if engen == True: Z = np.zeros([len(y),len(xxtmp),len(plot)+2],float) else: Z = np.zeros([len(y),len(xxtmp),len(plot)],float) # Define function extracting the contour boundaries which will be # called for every cycle in cyclelist, for every variable to be plotted # along with its corresponding threshold(s). def getlims(variable_array,thresh,massco_array): """This function returns the variable boundaries (in mass) for a cycle, given the cycle's variable and mass columns, ensuring that the boundaries are ordered centre to surface (as some .se.h5 files are the opposite).""" plotlims = [] # Just a fix for some get problem I was having: if len(massco_array) == 2: massco_array = massco_array[0] if len(variable_array) == 2: variable_array = variable_array[0] if massco_array[0] > massco_array[-1]: for j in range(-1,-len(variable_array)-1,-1): if j == -1: if variable_array[j] >= thresh: plotlims.append(massco_array[j]) else: pass elif (variable_array[j]-thresh)*(variable_array[j+1]-thresh) < 0: plotlims.append(massco_array[j]) if j == -len(variable_array): if variable_array[j] >= thresh: plotlims.append(massco_array[j]) return plotlims else: for j in range(len(variable_array)): if j == 0: if variable_array[j] >= thresh: plotlims.append(massco_array[j]) else: pass elif (variable_array[j]-thresh)*(variable_array[j-1]-thresh) < 0: plotlims.append(massco_array[j]) if j == len(variable_array)-1: if variable_array[j] >= thresh: plotlims.append(massco_array[j]) return plotlims # Flag preventing plotting any other variables on an energy generation # Kippenhahn plot: if engen == True: plot = ['dcoeff'] # This loop gets the mass co-ordinate array and the variable arrays, # calls to get the boundaries in order, and populates the contour array. ypscoeff = [-1,-1,-1] # this should have same length as plot - quick fix for yps. total_massco = [] for i in range(len(cyclelist)): # print 'CYCLE: ', cyclelist[i] massco = self.se.get(cyclelist[i],'mass') total_massco.append(max(massco)) plotlimits=[] for j in range(len(plot)): if plot[j][1] == '-' or plot[j][2] == '-': # Assume file has yps, not iso_massf ypsthere = True try: variables = self.se.get(cyclelist[i],'yps') # If this is not the case, do the usual se calls for iso_massf except KeyError: variables = self.se.get(cyclelist[i],plot[j]) ypsthere = False # If yps is there, ask which indices correspond to the # elements that are to be plotted, one by one. if ypsthere == True: if ypscoeff[j] == -1: ypscoeff[j] = int(input("What integer is your element "+str(plot[j])+" in the 'yps' array? ")) else: pass variables = self.se.get(cyclelist[i],'yps')[:,ypscoeff[j]] else: variables = self.se.get(cyclelist[i],plot[j]) plotlims = getlims(variables,thresholds[j],massco) plotlimits.append(plotlims) percent = int(i*100/len(cyclelist)) sys.stdout.flush() sys.stdout.write("\rcreating color map " + "...%d%%" % percent) for g in range(len(plot)): for k in range(0,len(plotlimits[g]),2): llimit = plotlimits[g][k] ulimit = plotlimits[g][k+1] #if xx[i] >= 0: for f in range(y_res): if llimit<=y[f] and ulimit>y[f]: Z[f,i,g]=1. #else: # ax.axvline(xx[i],ymin=llimit/m_ini,ymax=ulimit/m_ini,color='#8B8386',alpha=alphas[0],linewidth=0.5) # This function determines the adjacent two mass cells to a point in the # y-vector (which contains mass co-ordinates centre to surface, split into # y_res chunks), returning their index in the mass co-ordinate vector for # that timestep/cycle. def find_nearest(array,value): """ Returns [lower,upper] indexes locating adjacent mass cells (in the massco vector) around y-value (one of y_res points equally spaced between centre and surface). """ idx=(np.abs(array-value)).argmin() lims=np.zeros([2],int) if idx == len(array)-1: # SJONES post-mod lims[0] = idx - 1 # SJONES post-mod lims[1] = idx # SJONES post-mod return lims if array[idx] < value: if array[idx]-array[idx+1] < 0.: lims[0] = idx lims[1] = idx-1 return lims else: lims[0] = idx lims[1] = idx+1 return lims elif array[idx] > value: if array[idx]-array[idx+1] < 0.: lims[0] = idx+1 lims[1] = idx return lims else: lims[0] = idx-1 lims[1] = idx return lims # This flag enebles the loop below it to populate the contour array for # energy generation. It does not take threshold arguments, as the array # contains the log of the energy generation rather than "above" or "below". # Because of this, contour boundaries are automatically calculated # according to the max energy generation in the model. dummy_engen=[] engen_signs = [] if engen == True: # Requires eps_nuc array in the data. Produces energy generation contour # by linearly interpolating eps_nuc between mass co-ordinates according # to the y-resolution: for i in range(len(cyclelist)): # print 'CYCLE: ', cyclelist[i] max_energy_gen = 0. min_energy_gen = 0. massco = self.se.get(cyclelist[i],'mass') if len(massco) <= 10: massco=massco[0] dummy_engen = self.se.get(cyclelist[i],netnuc_name) if len(dummy_engen) <= 10: dummy_engen = dummy_engen[0] for f in range(len(dummy_engen)): # make all values absolute, but note in engen_signs which were negative: if dummy_engen[f] == 0.: engen_signs.append(1.) else: engen_signs.append(old_div(dummy_engen[f],abs(dummy_engen[f]))) if abs(engen_signs[f]) != 1.: print('engen sign not +/- 1!!') print('engen_signs['+str(f)+'] = ',engen_signs[f]) print('dummy_engen[f] = ', dummy_engen[f]) sys.exit() dummy_engen[f] = abs(dummy_engen[f]) log_epsnuc = np.log10(dummy_engen) # now insert the correct signs again: for f in range(len(log_epsnuc)): log_epsnuc[f] = log_epsnuc[f]*engen_signs[f] #for f in range(len(log_epsnuc)): #if str(log_epsnuc[f]) == 'nan': log_epsnuc[f] = 0. # print log_epsnuc percent = int(i*100/len(cyclelist)) sys.stdout.flush() sys.stdout.write("\rcreating color map " + "...%d%%" % percent) for j in range(len(y)): if j == len(y)-1: energy_here = 0. elif j == 0: energy_here = log_epsnuc[-1] elif y[j] > max(massco): energy_here = 0. else: lims = find_nearest(massco,y[j]) frac = old_div((y[j]-massco[lims[0]]),(massco[lims[1]]-massco[lims[0]])) energy_here = frac*(log_epsnuc[lims[1]]-log_epsnuc[lims[0]]) + log_epsnuc[lims[0]] if energy_here > max_energy_gen: max_energy_gen = energy_here if energy_here < min_energy_gen: min_energy_gen = energy_here if abs(max_energy_gen) > 100.: print(y[j]) print(engen_signs[f], log_epsnuc[f], frac, lims[0], lims[1], massco[lims[0]], massco[lims[1]]) print((massco[lims[1]]-massco[lims[0]]), (y[j]-massco[lims[0]])) print(max_energy_gen) print('exit due to energy generation > 100') sys.exit() # print energy_here # print max_energy_gen # if energy_here >= 0.: #Z[j,i,1] = 10**energy_here #SJONES comment if energy_here < 0.: energy_here = 0. Z[j,i,1] = energy_here # if energy_here < 0.: # Z[j,i,2] = 10**energy_here # Here we define the colourmap for the energy generation and an array # containing a list of colours in which to plot each variable (in the # order that the variables appear in "plots") iso_colours is obsolete # but was for when we tried plotting isotopes with just their boundary # lines as opposed to shading (for clarity). Colourmaps of these choices # are written to cmap (array). engen_cmap=mpl.cm.get_cmap('Blues') engen_cmap.set_under(color='w',alpha=engenalpha) enloss_cmap=mpl.cm.get_cmap('Reds') colours = ['#8B8386','m','g','b'] iso_colours = ['b','r','y'] cmap = [] for i in range(len(plot)): cmap.append(mpl.colors.ListedColormap(['w',colours[i]])) print('plotting contours') if xllim==0. and xulim==0.: ax.axis([float(xx[0]),float(xx[-1]),yllim,yulim]) else: ax.axis([xllim,xulim,yllim,yulim]) # Plot all of the contours. Levels indicates to only plot the shaded # regions and not plot the white regions, so that they are essentially # transparent. If engen=True, then the energy generation levels # (boundary values) are calculated (in dex) from 2 to the maximum in # steps of 2. for i in range(len(plot)): ax.contourf(xx,y,Z[:,:,i],levels=[0.5,1.5],colors=colours[i], alpha=alphas[i]) if engen == True: #ceiling = int(max_energy_gen+1) #floor = int(min_energy_gen+1) #cburn = ax.contourf(xx,y,Z[:,:,1],cmap=engen_cmap,locator=mpl.ticker.LogLocator(),alpha=engenalpha) # SJONES comment cburn = ax.contourf(xx,y,Z[:,:,1],cmap=engen_cmap,alpha=engenalpha,levels=list(range(5,32,5))) cbarburn = pl.colorbar(cburn) # if min_energy_gen != 0: # closs = ax.contourf(xx,y,Z[:,:,2],cmap=enloss_cmap,locator=mpl.ticker.LogLocator(),alpha=engenalpha) # cbarloss = pl.colorbar(closs) # cbarburn.set_label('$\epsilon_\mathrm{nuc}-\epsilon_{\\nu} \; (\mathrm{erg\,g}^{-1}\mathrm{\,s}^{-1})$, > 0',fontsize=fsize) cbarburn.set_label('$log_{10}(\epsilon_\mathrm{nuc}) \; (\mathrm{erg\,g}^{-1}\mathrm{\,s}^{-1})$, > 0',fontsize=fsize) pl.plot(xx,total_massco,color='k') pl.text(0.9,0.9,annotation,horizontalalignment='right',transform = ax.transAxes,fontsize=fsize) pl.ylabel('$\mathrm{Mass}\;[M_\odot]$',fontsize=fsize-1) pl.savefig(outfile) print(outfile+' is done.') pl.show()
!! EXPERIMENTAL FEATURE (flagged as private) !! This function creates a Kippenhahn diagram as a contour plot of the .se.h5 or .out.h5 files using any continuous variable (columns in the hdf5 cycle data). Multiple columns may be plotted, their name indicated in the list "plot", and their thresholds in the list "thresholds". Currently, this is only designed to take one threshold for each variable but future versions will hopefully be able to plot with multiple thresholds, however you may circumvent this issue by repeating the variable in "plots" and entering a second threshold for it in "thresholds". Parameters ---------- sparse : integer x-axis (timestep) sparsity. The true sparsity is sparse*sparse_intrinsic. Try 100 or 500 for .se.h5 and 20 for .out.h5 files and for preliminaxllimry plots. cycle_start : integer, optional Cycle from which you wish to plot. The default is 0. cycle_end : integer, optional Maximum cycle that you wish to plot. If cycle_end is 0, then it will plot up to the last cycle available. The default is 0. plot : list, optional 1-D array containing the variables to be plotted (as strings, e.g. plots=['dcoeff','C-13']. I recommend always plotting 'dcoeff' as plots[0]). The default is ['dcoeff']. thresholds : list, optional 1-D array containing the thresholds corresponding to the variables in "plots". The default is [1.0E+12]. xax : string, optional x-axis quantity; either 'log_time_left' or 'cycles'. The default is 'log_time_left'. alphas : list, optional Array containing the opacity (0 to 1) of the contour for each variable. The default is [1.0]. yllim : float, optional Lower plot limit for y-axis (mass co-ordinate). The default is 0.. yulim : float, optional Upper plot limit for y-axis (mass co-ordinate). The default is 0.. y_res : integer, optional y-axis resolution. Defaults to 2000 but increasing to as much as 10000 does not significantly affect the plotting time. The default is 2000. xllim : float, optional Lower plot limit for x-axis. The default is 0.. xulim : float, optional Upper plot limit for x-axis. The default is 0.. age : string, optional Either 'years' or 'seconds', depending on the data. The default is 'seconds'. sparse_intrinsic : integer, optional Sparsity of timesteps in the data provided (usually 20 for .out.h5 files and 1 for .se.h5 files). The default is 20. engen : boolean, optional Whether the user would like to plot Kippenhahn of convective zones and energy generation. If True, please still include plots=['dcoeff'] and thresholds=[1.0E+12'] in your call. This will require the data to have an 'eps_nuc' column, so the plot is only working for .se.h5 files from MESA in the current se library. This is the most recent addition, so probably the most buggy. The plot script will automatically calculate and assign multiple thresholds according to the model. The default is False. netnuc_name : string, optional The name of the column containing (eps_nuc-eps_neu). If you do not have available eps_neu, then you can give netnuc_name="eps_nuc" to just plot energy generation. The default is "eps_nuc". engenalpha : float, optional Opacity of the energy generation contours. The default is 0.6. outfile : string, optional The name to save the plot as. The default is 'plot.pdf'. annotation : string, optional Some optional annotation to add to the plot. The default is ''. KEPLER : boolean, optional The default is False.
entailment
def abup_se_plot(mod,species): """ plot species from one ABUPP file and the se file. You must use this function in the directory where the ABP files are and an ABUP file for model mod must exist. Parameters ---------- mod : integer Model to plot, you need to have an ABUPP file for that model. species : string The species to plot. Notes ----- The species is set to 'C-12'. """ # Marco, you have already implemented finding headers and columns in # ABUP files. You may want to transplant that into here? species='C-12' filename = 'ABUPP%07d0000.DAT' % mod print(filename) mass,c12=np.loadtxt(filename,skiprows=4,usecols=[1,18],unpack=True) c12_se=self.se.get(mod,'iso_massf','C-12') mass_se=self.se.get(mod,'mass') pyl.plot(mass,c12) pyl.plot(mass_se,c12_se,'o',label='cycle '+str(mod)) pyl.legend()
plot species from one ABUPP file and the se file. You must use this function in the directory where the ABP files are and an ABUP file for model mod must exist. Parameters ---------- mod : integer Model to plot, you need to have an ABUPP file for that model. species : string The species to plot. Notes ----- The species is set to 'C-12'.
entailment
def _read_iso_abund_marco(self, mass_range, cycle): """ plot the abundance of all the chemical species Parameters ---------- mass_range : list A 1x2 array containing the lower and upper mass range. If None, it will plot over the entire range. cycle : string or integer A string/integer of the cycle of interest. """ import nuutils as u masses = [] # Check the inputs #if not self.se.cycles.count(str(cycle)): # print 'You entered an cycle that doesn\'t exist in this dataset:', cycle # print 'I will try and correct your format.' # cyc_len = len(self.se.cycles[-1]) # print cyc_len, len(str(cycle)) # # while len(str(cycle)) < cyc_len: # cycle = '0'+str(cycle) # print cycle # if not self.se.cycles.count(str(cycle)): # print 'I was unable to correct your cycle. Please check that it exists in your dataset.' masses = self.se.get(cycle,'mass') if mass_range == None: print('Using default mass range') mass_range = [min(masses),max(masses)] # what this was for??? Marco #masses.sort() #mass_range.sort() print('Using The following conditions:') print('\tmass_range:', mass_range[0], mass_range[1]) print('\tcycle:', cycle) isotope_names = self.se.isotopes u.convert_specie_naming_from_h5_to_ppn(isotope_names) names_ppn_world = u.spe number_names_ppn_world = u.n_array u.define_zip_index_for_species(names_ppn_world,number_names_ppn_world) # from here below I read the abundance. #name_specie_in_file=self.se.dcols[5] # I am using directly 'iso_massf' only because somehow m20 explosive do not have dcols.... name_specie_in_file='iso_massf' abunds=self.se.get(cycle,name_specie_in_file) global used_masses used_masses = [] self.mass_frac = [] for i in range(len(masses)): if mass_range[0] <= masses[i] and mass_range[1] >= masses[i] : used_masses.append(masses[i]) self.mass_frac.append(abunds[i])
plot the abundance of all the chemical species Parameters ---------- mass_range : list A 1x2 array containing the lower and upper mass range. If None, it will plot over the entire range. cycle : string or integer A string/integer of the cycle of interest.
entailment
def decay(self, mass_frac): """ this module simply calculate abundances of isotopes after decay. It requires that before it is used a call is made to _read_iso_abund_marco and _stable_species. Parameters ---------- mass_frac : list alist of mass_frac dicts. See Also -------- _read_iso_abund_marco(), nuutils.Utils._stable_species() """ import nuutils as u global decayed_multi_d decayed_multi_d=[] #print len(mass_frac) #print len(decay_raw) for iii in range(len(mass_frac)): jj=-1 decayed=[] for i in range(len(u.decay_raw)): if u.jdum[i] > 0.5: jj=jj+1 dummy=0. for j in range(len(u.decay_raw[i])): try: dum_str = u.decay_raw[i][j] dummy = dummy + float(self.mass_frac[iii][u.cl[dum_str.lower().capitalize()]]) #print cl[dum_str.lower().capitalize()] #print dum_str, mass_frac[iii][cl[dum_str.capitalize()]] except KeyError: None #print 'I am not in the network:',decay_raw[i][j] except IndexError: None #print 'I am not read',cl[decay_raw[i][j].lower().capitalize()],decay_raw[i][j] decayed.append(dummy) decayed_multi_d.append(decayed)
this module simply calculate abundances of isotopes after decay. It requires that before it is used a call is made to _read_iso_abund_marco and _stable_species. Parameters ---------- mass_frac : list alist of mass_frac dicts. See Also -------- _read_iso_abund_marco(), nuutils.Utils._stable_species()
entailment
def burnstage(self, **keyw): """ This function calculates the presence of burning stages and outputs the ages when key isotopes are depleted and uses them to calculate burning lifetimes. Parameters ---------- keyw : dict A dict of key word arguments. Returns ------- list A list containing the following information: burn_cycles, burn_ages, burn_abun, burn_type and burn_lifetime. Notes ----- The following keywords can also be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | isoa | "A" | +------------------+---------------+ | isoz | "Z" | +------------------+---------------+ | mass | "mass" | +------------------+---------------+ | cycle | "cycle" | +------------------+---------------+ | cyclefin | 0 | +------------------+---------------+ All arguments change the name of fields used to read data from HDF5 files, other than cyclefin. Cyclefin is the last timestep to use when reading files. Cycles contain the cycle numbers for the various points where the abundance is abun. The age of the star at each point and the type of burning is indicated by those arrays. The lifetimes are calculated by. """ if ("isoa" in keyw) == False: keyw["isoa"] = "A" if ("isoz" in keyw) == False: keyw["isoz"] = "Z" if ("mass" in keyw) == False: keyw["mass"] = "mass" if ("age" in keyw) == False: keyw["age"] = "age" if ("abund" in keyw) == False: keyw["abund"] = "iso_massf" if ("cycle" in keyw) == False: keyw["cycle"] = "cycle" if ("cyclefin" in keyw) == False: cyclefin = 1.e99 else: cyclefin = keyw["cyclefin"] burn_cycles = [] burn_ages = [] burn_abun = [] burn_type = [] burn_lifetime = [] firstfile = True hemax, cmax, nemax, omax = 0, 0, 0, 0 cycles_list = self.se.cycles xm_list = self.se.get(keyw["mass"]) age_list = self.se.get(keyw["age"]) abund_list = self.se.get(keyw["abund"]) tables = self.se.Tables() isoa_list = tables[0] isoz_list = tables[1] # Check the order of the input data xm_init = xm_list[0] centre = 0 if isinstance(xm_init, list) == True: if xm_init[0] > xm_init[1]: # mass is descending with shell number and the centre of the star # is the last shell centre = -1 # Determine yps indices for certain abundances for i in range(len(isoa_list)): try: A = int(isoa_list[i]) Z = int(isoz_list[i]) except TypeError: A = int(isoa_list[i][0]) Z = int(isoz_list[i][0]) if A == 1 and Z == 1: h1index = i elif A == 4 and Z == 2: he4index = i elif A == 12 and Z == 6: c12index = i elif A == 16 and Z == 8: o16index = i elif A == 20 and Z == 10: ne20index = i elif A == 28 and Z == 14: si28index = i if firstfile == True: hmax = abund_list[0][centre][h1index] firstfile = False # Try and determine the location of a convective core using the central and # next from central shells for i in range(1, len(cycles_list)-1): if cycles_list[i] > cyclefin and cyclefin != 0: pair = False age1 = -1 for i in range(len(burn_type)): if 'start' in burn_type[i] and pair == False: age1 = burn_ages[i] pair = True elif 'end' in burn_type[i] and pair == True: age2 = burn_ages[i] pair = False if age1 != -1: burn_lifetime.append(age2 - age1) age1 = -1 return [burn_cycles, burn_ages, burn_abun, burn_type, burn_lifetime] # H-burning hcen = abund_list[i][centre][h1index] hcennext = abund_list[i+1][centre][h1index] if hcen >1.e-10: if hcennext < hmax-0.003 and hcen >= hmax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(hcen) burn_type.append('H_start') if hcennext < 1.e-1 and hcen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('H') if hcennext < 1.e-2 and hcen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('H') if hcennext < 1.e-3 and hcen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('H') if hcennext < 1.e-4 and hcen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('H') if hcennext < 1.e-5 and hcen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('H_end') hemax = abund_list[i][centre][he4index] if hcennext < 1.e-6 and hcen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('H') if hcennext < 1.e-9 and hcen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('H') # He-burning hecen = abund_list[i][centre][he4index] hecennext = abund_list[i+1][centre][he4index] if hcen < 1.e-5 and hecen > 1.e-10: if hecennext < hemax-0.003 and hecen >= hemax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(hecen) burn_type.append('He_start') if hecennext < 1.e-1 and hecen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('He') if hecennext < 1.e-2 and hecen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('He') if hecennext < 1.e-3 and hecen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('He') if hecennext < 1.e-4 and hecen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('He') if hecennext < 1.e-5 and hecen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('He_end') cmax = abund_list[i][centre][c12index] if hecennext < 1.e-6 and hecen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('He') if hecennext < 1.e-9 and hecen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('He') # C-burning ccen = abund_list[i][centre][c12index] ccennext = abund_list[i+1][centre][c12index] if hcen < 1.e-5 and hecen < 1.e-5 and ccen > 1.e-10: if ccennext < cmax-0.003 and ccen >= cmax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(ccen) burn_type.append('C_start') if ccennext < 1.e-1 and ccen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('C') if ccennext < 1.e-2 and ccen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('C') if ccennext < 1.e-3 and ccen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('C') if ccennext < 1.e-4 and ccen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('C') if ccennext < 1.e-5 and ccen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('C_end') nemax = abund_list[i][centre][ne20index] if ccennext < 1.e-6 and ccen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('C') if ccennext < 1.e-9 and ccen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('C') # Ne-burning necen = abund_list[i][centre][ne20index] necennext = abund_list[i+1][centre][ne20index] if hcen < 1.e-5 and hecen < 1.e-5 and ccen < 1.e-3 and necen > 1.e-10: if necennext < nemax-0.003 and necen >= nemax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(necen) burn_type.append('Ne_start') if necennext < 1.e-1 and necen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('Ne') if necennext < 1.e-2 and necen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('Ne') if necennext < 1.e-3 and necen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('Ne_end') omax = abund_list[i][centre][o16index] if necennext < 1.e-4 and necen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('Ne') if necennext < 1.e-5 and necen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('Ne') if necennext < 1.e-6 and necen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('Ne') if necennext < 1.e-9 and necen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('Ne') # O-burning ocen = abund_list[i][centre][o16index] ocennext = abund_list[i+1][centre][o16index] if hcen < 1.e-5 and hecen < 1.e-5 and ccen < 1.e-3 and ocen > 1.e-10: if ocennext < omax-0.003 and ocen >= omax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(ccen) burn_type.append('O_start') if ocennext < 1.e-1 and ocen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('O') if ocennext < 1.e-2 and ocen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('O') if ocennext < 1.e-3 and ocen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('O') if ocennext < 1.e-4 and ocen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('O') if ocennext < 1.e-5 and ocen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('O_end') if ocennext < 1.e-6 and ocen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('O') if ocennext < 1.e-9 and ocen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('O') pair = False age1 = -1 for i in range(len(burn_type)): if 'start' in burn_type[i] and pair == False: age1 = burn_ages[i] pair = True elif 'end' in burn_type[i] and pair == True: age2 = burn_ages[i] pair = False if age1 != -1: burn_lifetime.append(age2 - age1) age1 = -1 return [burn_cycles, burn_ages, burn_abun, burn_type, burn_lifetime]
This function calculates the presence of burning stages and outputs the ages when key isotopes are depleted and uses them to calculate burning lifetimes. Parameters ---------- keyw : dict A dict of key word arguments. Returns ------- list A list containing the following information: burn_cycles, burn_ages, burn_abun, burn_type and burn_lifetime. Notes ----- The following keywords can also be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | isoa | "A" | +------------------+---------------+ | isoz | "Z" | +------------------+---------------+ | mass | "mass" | +------------------+---------------+ | cycle | "cycle" | +------------------+---------------+ | cyclefin | 0 | +------------------+---------------+ All arguments change the name of fields used to read data from HDF5 files, other than cyclefin. Cyclefin is the last timestep to use when reading files. Cycles contain the cycle numbers for the various points where the abundance is abun. The age of the star at each point and the type of burning is indicated by those arrays. The lifetimes are calculated by.
entailment
def burnstage_upgrade(self, **keyw): """ This function calculates the presence of burning stages and outputs the ages when key isotopes are depleted and uses them to calculate burning lifetimes. Parameters ---------- keyw : dict A dict of key word arguments. Returns ------- list A list containing the following information: burn_cycles, burn_ages, burn_abun, burn_type and burn_lifetime. Notes ----- The following keywords can also be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | isoa | "A" | +------------------+---------------+ | isoz | "Z" | +------------------+---------------+ | mass | "mass" | +------------------+---------------+ | cycle | "cycle" | +------------------+---------------+ | cyclefin | 0 | +------------------+---------------+ All arguments change the name of fields used to read data from HDF5 files, other than cyclefin. Cyclefin is the last timestep to use when reading files. Cycles contain the cycle numbers for the various points where the abundance is abun. The age of the star at each point and the type of burning is indicated by those arrays. The lifetimes are calculated by. """ if ("isoa" in keyw) == False: keyw["isoa"] = "A" if ("isoz" in keyw) == False: keyw["isoz"] = "Z" if ("mass" in keyw) == False: keyw["mass"] = "mass" if ("age" in keyw) == False: keyw["age"] = "age" if ("abund" in keyw) == False: keyw["abund"] = "iso_massf" if ("cycle" in keyw) == False: keyw["cycle"] = "cycle" if ("cyclefin" in keyw) == False: cyclefin = 1.e99 else: cyclefin = keyw["cyclefin"] burn_cycles = [] burn_ages = [] burn_abun = [] burn_type = [] burn_lifetime = [] firstfile = True hemax, cmax, nemax, omax = 0., 0., 0., 0. hburn_logic = True heburn_logic = True cburn_logic = True neburn_logic = True oburn_logic = True hburn_start_logic = False heburn_start_logic = False cburn_start_logic = False neburn_start_logic = False oburn_start_logic = False #cycles_list = self.se.cycles cyc = self.se.cycles sparsity_factor = int(1) cycles_list = list(range(int(cyc[0]),int(cyc[len(cyc)-1]),((int(cyc[1])-int(cyc[0])))*sparsity_factor)) age_list = self.se.get(keyw["age"]) # I want to read only the isotopes I need to identify the burning stages. all_isos=self.se.isotopes #list_all_isos=all_isos.tolist() useful_species = species_list("burn_stages") useful_index = [] for iso in useful_species: #useful_index.append(all_isos.index(iso)) useful_index.append(useful_species.index(iso)) specie_index={} for a,b in zip(useful_species,useful_index): specie_index[a] = b # Check the order of the input data xm_init = self.se.get(0,keyw["mass"]) central_zone = 0 external_zone = -1 if isinstance(xm_init, list) == True: if xm_init[0] > xm_init[1]: # mass is descending with shell number and the centre of the star # is the last shell central_zone = -1 external_zone = 0 # central zone first zone = 0 xm_cyc=[] xm_list=[] for i in cycles_list: xm_cyc = self.se.get(i,keyw["mass"])[central_zone] xm_list.append(xm_cyc) abund_list = [] for i in cycles_list: abund_tmp = [] for iso in useful_species: abund_cyc = self.se.get(i,keyw["abund"],iso)[central_zone] abund_tmp.append(abund_cyc) abund_list.append(abund_tmp) if firstfile == True: hsurf = self.se.get(0,keyw["abund"],'H-1')[external_zone] #hesurf = self.se.get(0,keyw["abund"],'He-4')[external_zone] firstfile = False # Try and determine the location of a convective core using the central and # next from central shells for i in range(1, len(cycles_list)-1): if cycles_list[i] > cyclefin and cyclefin != 0: pair = False age1 = -1 for i in range(len(burn_type)): if 'start' in burn_type[i] and pair == False: age1 = burn_ages[i] pair = True elif 'end' in burn_type[i] and pair == True: age2 = burn_ages[i] pair = False if age1 != -1: burn_lifetime.append(age2 - age1) age1 = -1 return [burn_cycles, burn_ages, burn_abun, burn_type, burn_lifetime] print('passa 3') # H-burning if hburn_logic: hcen = abund_list[i][specie_index['H-1']] hcennext = abund_list[i+1][specie_index['H-1']] if hcen >1.e-10: if hcennext < hsurf-0.003 and hcen >= hsurf-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(hcen) burn_type.append('H_start') hburn_start_logic = True if hcennext < 1.e-1 and hcen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('H') if hcennext < 1.e-2 and hcen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('H') if hcennext < 1.e-3 and hcen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('H') if hcennext < 1.e-4 and hcen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('H') if hcennext < 1.e-5 and hcen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('H_end') hemax = abund_list[i][specie_index['He-4']] if hburn_start_logic: hburn_logic == False if hcennext < 1.e-6 and hcen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('H') #if hcennext < 1.e-9 and hcen >= 1.e-9: # burn_cycles.append(cycles_list[i]) # burn_ages.append(age_list[i]) # burn_abun.append(1.e-9) # burn_type.append('H') # He-burning hecen = abund_list[i][specie_index['He-4']] hecennext = abund_list[i+1][specie_index['He-4']] if hcen < 1.e-5 and hecen > 1.e-10: if hecennext < hemax-0.003 and hecen >= hemax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(hecen) burn_type.append('He_start') if hecennext < 1.e-1 and hecen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('He') if hecennext < 1.e-2 and hecen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('He') if hecennext < 1.e-3 and hecen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('He') if hecennext < 1.e-4 and hecen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('He') if hecennext < 1.e-5 and hecen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('He_end') cmax = abund_list[i][specie_index['C-12']] if hecennext < 1.e-6 and hecen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('He') if hecennext < 1.e-9 and hecen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('He') # C-burning ccen = abund_list[i][specie_index['C-12']] ccennext = abund_list[i+1][specie_index['C-12']] if hcen < 1.e-5 and hecen < 1.e-5 and ccen > 1.e-10: if ccennext < cmax-0.003 and ccen >= cmax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(ccen) burn_type.append('C_start') if ccennext < 1.e-1 and ccen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('C') if ccennext < 1.e-2 and ccen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('C') if ccennext < 1.e-3 and ccen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('C') if ccennext < 1.e-4 and ccen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('C') if ccennext < 1.e-5 and ccen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('C_end') nemax = abund_list[i][specie_index['Ne-20']] if ccennext < 1.e-6 and ccen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('C') if ccennext < 1.e-9 and ccen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('C') # Ne-burning necen = abund_list[i][specie_index['Ne-20']] necennext = abund_list[i+1][specie_index['Ne-20']] if hcen < 1.e-5 and hecen < 1.e-5 and ccen < 1.e-3 and necen > 1.e-10: if necennext < nemax-0.003 and necen >= nemax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(necen) burn_type.append('Ne_start') if necennext < 1.e-1 and necen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('Ne') if necennext < 1.e-2 and necen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('Ne') if necennext < 1.e-3 and necen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('Ne_end') omax = abund_list[i][specie_index['O-16']] if necennext < 1.e-4 and necen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('Ne') if necennext < 1.e-5 and necen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('Ne') if necennext < 1.e-6 and necen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('Ne') if necennext < 1.e-9 and necen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('Ne') # O-burning ocen = abund_list[i][specie_index['O-16']] ocennext = abund_list[i+1][specie_index['O-16']] if hcen < 1.e-5 and hecen < 1.e-5 and ccen < 1.e-3 and ocen > 1.e-10: if ocennext < omax-0.003 and ocen >= omax-0.003: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(ccen) burn_type.append('O_start') if ocennext < 1.e-1 and ocen >= 1.e-1: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-1) burn_type.append('O') if ocennext < 1.e-2 and ocen >= 1.e-2: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-2) burn_type.append('O') if ocennext < 1.e-3 and ocen >= 1.e-3: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-3) burn_type.append('O') if ocennext < 1.e-4 and ocen >= 1.e-4: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-4) burn_type.append('O') if ocennext < 1.e-5 and ocen >= 1.e-5: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-5) burn_type.append('O_end') if ocennext < 1.e-6 and ocen >= 1.e-6: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-6) burn_type.append('O') if ocennext < 1.e-9 and ocen >= 1.e-9: burn_cycles.append(cycles_list[i]) burn_ages.append(age_list[i]) burn_abun.append(1.e-9) burn_type.append('O') print('passa 4') pair = False age1 = -1 for i in range(len(burn_type)): if 'start' in burn_type[i] and pair == False: age1 = burn_ages[i] pair = True elif 'end' in burn_type[i] and pair == True: age2 = burn_ages[i] pair = False if age1 != -1: burn_lifetime.append(age2 - age1) age1 = -1 return [burn_cycles, burn_ages, burn_abun, burn_type, burn_lifetime]
This function calculates the presence of burning stages and outputs the ages when key isotopes are depleted and uses them to calculate burning lifetimes. Parameters ---------- keyw : dict A dict of key word arguments. Returns ------- list A list containing the following information: burn_cycles, burn_ages, burn_abun, burn_type and burn_lifetime. Notes ----- The following keywords can also be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | isoa | "A" | +------------------+---------------+ | isoz | "Z" | +------------------+---------------+ | mass | "mass" | +------------------+---------------+ | cycle | "cycle" | +------------------+---------------+ | cyclefin | 0 | +------------------+---------------+ All arguments change the name of fields used to read data from HDF5 files, other than cyclefin. Cyclefin is the last timestep to use when reading files. Cycles contain the cycle numbers for the various points where the abundance is abun. The age of the star at each point and the type of burning is indicated by those arrays. The lifetimes are calculated by.
entailment
def cores(self, incycle, **keyw): """ This function uses the abundances as a function of time to return core masses. Parameters ---------- incycle : integer incycle is the cycle to choose where to take the core masses. keyw : dict A dict of key word arguments. Returns ------- list [cores, core_type, core_info] cores contains the core masses for the types found in core_type. Core_info stores a variety of information about the abundances at certain mass coordinates. Notes ----- These core masses are: +----------+-----------------------------------------+ | M_alpha | mass of the helium core | +----------+-----------------------------------------+ | M_CO | mass of the carbon-oxygen core | +----------+-----------------------------------------+ | M_si | mass of the silicon core | +----------+-----------------------------------------+ | M_fe | mass of the iron core | +----------+-----------------------------------------+ | M_rem | mass of the remnant star post-supernova | +----------+-----------------------------------------+ The following keywords can also be used: +------------------+------------------+ | Keyword Argument | Default Value | +==================+==================+ | abund | "iso_massf" | +------------------+------------------+ | isoa | "A" | +------------------+------------------+ | isom | "isomeric_state" | +------------------+------------------+ | isoz | "Z" | +------------------+------------------+ | mass | "mass" | +------------------+------------------+ | core_opt | 1 | +------------------+------------------+ All arguments change the name of fields used to read data from HDF5 files, other than core_opt. core_opt controls which scheme to use for calculating the core masses. If core_opt is 0, then cores uses alpha-isotopes to calculate the silicon and iron cores. Use this for stellar evolution output. Si_core = Si28+S32+Ar36+Ca40+Ti44 Fe_core = Cr48+Fe52+Ni56 If core_opt is 1, then cores uses all elements in a network with proton number Z=23 as a boundary. Use this for MPPNP output. Si_core = Sum of all isotopes with 14 <= Z <= 22 Fe_core = Sum of all isotopes with 23 <= Z <= 28 """ def infomod(core_opt, *inp): """ This calls the correct infomod function depending on the value of core_opt. """ if core_opt == 0: return infomod1(inp[0], inp[1], inp[2]) elif core_opt == 1: return infomod2(inp[0], inp[1], inp[2], inp[3], inp[4]) def infomod1(shell, yps, isoindex): """ Function for defining data to print into a string. This is used for the case of core_opt = 0. """ xh = yps[shell][isoindex[0]] xhe = yps[shell][isoindex[1]] xc = yps[shell][isoindex[2]] xo = yps[shell][isoindex[3]] xsi = yps[shell][isoindex[4]] xs = yps[shell][isoindex[5]] xa = yps[shell][isoindex[6]] xca = yps[shell][isoindex[7]] xti = yps[shell][isoindex[8]] xcr = yps[shell][isoindex[9]] xfe = yps[shell][isoindex[10]] xni = yps[shell][isoindex[11]] xsicore = xsi + xs + xa + xca + xti xfecore = xcr + xfe + xni return ' h=' + "%12.4e"%(xh) + ' he=' + "%12.4e"%(xhe) + \ ' c=' + "%12.4e"%(xc) + ' o=' + "%12.4e"%(xo) + \ ' si=' + "%12.4e"%(xsicore) + ' fe=' + "%12.4e"%(xfecore) def infomod2(shell, yps, isoindex, xsicore, xfecore): """ Function for defining data to print into a string. This is used for the case of core_opt = 1. """ xsicore = 0. xsicoren = 0. xfecore = 0. xfecoren = 0. xh = yps[shell][isoindex[0]] xhe = yps[shell][isoindex[1]] xc = yps[shell][isoindex[2]] xo = yps[shell][isoindex[3]] for j in iso_si: xsicore += yps[i][j] xsicoren += yps[i+iter][j] for j in iso_fe: xfecore += yps[i][j] xfecoren += yps[i+iter][j] return 'shellnb = ' + str(shell) + ' h=' + "%12.4e"%(xh) + \ ' he=' + "%12.4e"%(xhe) + ' c=' + "%12.4e"%(xc) + \ ' o=' + "%12.4e"%(xo) + ' si=' + "%12.4e"%(xsicore) + \ ' fe=' + "%12.4e"%(xfecore) if ("isoa" in keyw) == False: keyw["isoa"] = "A" if ("isoz" in keyw) == False: keyw["isoz"] = "Z" if ("mass" in keyw) == False: keyw["mass"] = "mass" if ("abund" in keyw) == False: keyw["abund"] = "iso_massf" if ("coreopt" in keyw) == False: core_opt = 1 else: core_opt = keyw["coreopt"] cores = [0,0,0,0,0,0] core_type = ["","","","","",""] core_info = [] iso_si = [] iso_fe = [] first = True xm_list = self.se.get(incycle, keyw["mass"]) abund_list = self.se.get(incycle, keyw["abund"]) tables = self.se.Tables isoa_list = tables[0] isoz_list = tables[1] # Check the order of the input data xmass = xm_list yps = abund_list centre = 0 surface = len(xmass)-1 iter = -1 if isinstance(xmass, list) == True: if xmass[0] > xmass[1]: # mass is descending with shell number and the centre of the star # is the last shell centre = len(xmass)-1 surface = 0 iter = 1 mco01 = 0. na = 0 nco = 0 h1index = -1 he4index = -1 c12index = -1 o16index = -1 si28index = -1 s32index = -1 a36index = -1 ca40index = -1 ti44index = -1 cr48index = -1 fe52index = -1 ni56index = -1 # Determine yps indices for certain abundances for i in range(len(isoa_list)): try: A = int(isoa_list[i]) Z = int(isoz_list[i]) except TypeError: A = int(isoa_list[i][0]) Z = int(isoz_list[i][0]) if A == 1 and Z == 1: h1index = i elif A == 4 and Z == 2: he4index = i elif A == 12 and Z == 6: c12index = i elif A == 16 and Z == 8: o16index = i if core_opt == 0: if A == 28 and Z == 14: si28index = i elif A == 32 and Z == 16: s32index = i elif A == 36 and Z == 18: a36index = i elif A == 40 and Z == 20: ca40index = i elif A == 44 and Z == 22: ti44index = i elif A == 48 and Z == 24: cr48index = i elif A == 52 and Z == 26: fe52index = i elif A == 56 and Z == 38: ni56index = i if h1index == -1 or he4index == -1 or c12index == -1 or o16index == -1: print("A key isotope(s) is not found in network! Please check for the \ presence of H1, He4, C12 and O16.") os.sys.exit() # Si_core = Si28+S32+Ar36+Ca40+Ti44 # Fe_core = Cr48+Fe52+Ni56 if core_opt == 0: if si28index == -1 or s32index == -1 or a36index == -1 or ca40index == -1 \ or ti44index == -1 or cr48index == -1 or fe52index == -1 or ni56index == -1: print("Key isotopes for measuring the core mass with core_opt = 0 \ are missing. Setting core_opt = 1.") core_opt = 1 # Si_core = Sum of all isotopes with 14 <= Z <= 22 # Fe_core = Sum of all isotopes with 23 <= Z <= 28 if core_opt == 1: for i in range(len(isoa_list)): try: A = int(isoa_list[i]) Z = int(isoz_list[i]) except TypeError: A = int(isoa_list[i][0]) Z = int(isoz_list[i][0]) if Z >= 14 and Z <= 22: iso_si.append(i) if Z >= 23 and Z <= 28: iso_fe.append(i) isoindex = [h1index, he4index, c12index, o16index] if core_opt == 0: isoindex.extend([si28index, s32index, a36index, ca40index, ti44index, cr48index, fe52index, ni56index]) if first == True: first = False cores[0] = xmass[surface] core_type[0] = "Final" core_info.append(infomod(core_opt, surface, yps, isoindex, iso_si, iso_fe)) # Iterate over shells to determine the core masses for i in np.arange(surface, centre, iter): xsicore = 0. xfecore = 0. xsicoren = 0. xfecoren = 0. # Abundances of key isotopes at this shell (and the next one) xh = yps[i][h1index] xhe = yps[i][he4index] xc = yps[i][c12index] xo = yps[i][o16index] xhn = yps[i+iter][h1index] xhen = yps[i+iter][he4index] xcn = yps[i+iter][c12index] xon = yps[i+iter][o16index] xcocore = xc + xo xcocoren = xcn + xon if core_opt == 0: xsi = yps[i][si28index] xs = yps[i][s32index] xa = yps[i][a36index] xca = yps[i][ca40index] xti = yps[i][ti44index] xcr = yps[i][cr48index] xfe = yps[i][fe52index] xni = yps[i][ni56index] xsin = yps[i+iter][si28index] xsn = yps[i+iter][s32index] xan = yps[i+iter][a36index] xcan = yps[i+iter][ca40index] xtin = yps[i+iter][ti44index] xcrn = yps[i+iter][cr48index] xfen = yps[i+iter][fe52index] xnin = yps[i+iter][ni56index] xsicore = xsi + xs + xa + xca + xti xfecore = xcr + xfe + xni xsicoren = xsin + xsn + xan + xcan + xtin xfecoren = xcrn + xfen + xnin elif core_opt == 1: for j in iso_si: xsicore += yps[i][j] xsicoren += yps[i+iter][j] for j in iso_fe: xfecore += yps[i][j] xfecoren += yps[i+iter][j] # M_alpha: if xh >= 1.e-9: if xhen > 0.75 and xhe <= 0.75: if cores[1] == 0: cores[1] = xmass[i] core_type[1] = 'Malpha 75%' core_info.append('Malpha 75% '+str(xmass[i-iter])+ \ infomod(core_opt, i-iter, yps, isoindex, iso_si, iso_fe)) core_info.append('Malpha 75% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) core_info.append('Malpha 75% '+str(xmass[i+iter])+ \ infomod(core_opt, i+iter, yps, isoindex, iso_si, iso_fe)) if xhen > 0.5 and xhe <= 0.5: core_info.append('Malpha 50% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xhn < 1.e-2 and xh >= 1.e-2: na=i core_info.append('Malpha 1.e-2 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xhn < 1.e-4 and xh >= 1.e-4: core_info.append('Malpha 1.e-4 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xhn < 1.e-5 and xh >= 1.e-5: core_info.append('Malpha 1.e-5 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) # M_CO: if xhe >= 1.e-9 and xh < 1.e-9: if xcocoren > 0.5 and xcocore <= 0.5: core_info.append('Mco 50% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xcocoren > 0.75 and xcocore <= 0.75: core_info.append('Mco 75% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xhen < 1.e-2 and xhe >= 1.e-2: if cores[2] == 0: mco01=xmass[i] nco=i cores[2] = xmass[i] core_type[2] = 'Mco' core_info.append('Mco 1.e-2 '+str(xmass[i-iter])+ \ infomod(core_opt, i-iter, yps, isoindex, iso_si, iso_fe)) core_info.append('Mco 1.e-2 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) core_info.append('Mco 1.e-2 '+str(xmass[i+iter])+ \ infomod(core_opt, i+iter, yps, isoindex, iso_si, iso_fe)) if xhen < 1.e-4 and xhe >= 1.e-4: core_info.append('Mco 1.e-4 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xhen < 1.e-5 and xhe >= 1.e-5: core_info.append('Mco 1.e-5 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) # M_Si: if xcocore >= 1.e-7: if xsicoren > 0.5 and xsicore <= 0.5: if cores[3] == 0: core_info.append('Msi 50% '+str(xmass[i-iter])+ \ infomod(core_opt, i-iter, yps, isoindex, iso_si, iso_fe)) core_info.append('Msi 50% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) core_info.append('Msi 50% '+str(xmass[i+iter])+ \ infomod(core_opt, i+iter, yps, isoindex, iso_si, iso_fe)) cores[3] = xmass[i] core_type[3] = 'Msi 50%' if xsicoren > 0.75 and xsicore <= 0.75: core_info.append('Msi 75% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xcocoren > 1.e-2 and xcocore <= 1.e-2: core_info.append('Msi 1.e-2 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) # M_fe: if xfecoren > 0.5 and xfecore <= 0.5: if cores[4] == 0: core_info.append('Mfe 50% '+str(xmass[i-iter])+ \ infomod(core_opt, i-iter, yps, isoindex, iso_si, iso_fe)) core_info.append('Mfe 50% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) core_info.append('Mfe 50% '+str(xmass[i+iter])+ \ infomod(core_opt, i+iter, yps, isoindex, iso_si, iso_fe)) cores[4] = xmass[i] core_type[4] = 'Mfe 50%' if xfecoren > 0.75 and xfecore <= 0.75: core_info.append('Mfe 75% '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) if xsicoren > 1.e-2 and xsicore <= 1.e-2: core_info.append('Mfe 1.e-2 '+str(xmass[i])+ \ infomod(core_opt, i, yps, isoindex, iso_si, iso_fe)) mcof=mco01 i=na while i < nco: i+=1 xco = yps[i][c12index] + yps[i][o16index] xcop = yps[i-iter][c12index] + yps[i-iter][o16index] mcof+=(xco+xcop)/2.*(xmass[i-iter]-xmass[i]) cores[2] = mcof core_type[2] = 'Mco int' # M_rem vs M_CO relationship xmco = np.array([0.72,1.01,1.38,2.10,2.97,4.94,7.20,13.88,24.75,38.12,58.73]) xmre = np.array([0.72,1.01,1.23,1.42,1.65,2.15,2.72,4.3,7.6,11.4,17.1]) if 'Mco' in core_type: for i in np.arange(len(xmco)): if cores[2] < xmco[i]: xco = yps[i][c12index] + yps[i][o16index] xcop = yps[i-iter][c12index] + yps[i-iter][o16index] cores[5] = xmre[i-1]+(xmre[i]-xmre[i-1])*(cores[j]-xmco[i-1])/(xmco[i]-xmco[i-1]) core_type[5] = 'Mrem' break return [cores, core_type, core_info]
This function uses the abundances as a function of time to return core masses. Parameters ---------- incycle : integer incycle is the cycle to choose where to take the core masses. keyw : dict A dict of key word arguments. Returns ------- list [cores, core_type, core_info] cores contains the core masses for the types found in core_type. Core_info stores a variety of information about the abundances at certain mass coordinates. Notes ----- These core masses are: +----------+-----------------------------------------+ | M_alpha | mass of the helium core | +----------+-----------------------------------------+ | M_CO | mass of the carbon-oxygen core | +----------+-----------------------------------------+ | M_si | mass of the silicon core | +----------+-----------------------------------------+ | M_fe | mass of the iron core | +----------+-----------------------------------------+ | M_rem | mass of the remnant star post-supernova | +----------+-----------------------------------------+ The following keywords can also be used: +------------------+------------------+ | Keyword Argument | Default Value | +==================+==================+ | abund | "iso_massf" | +------------------+------------------+ | isoa | "A" | +------------------+------------------+ | isom | "isomeric_state" | +------------------+------------------+ | isoz | "Z" | +------------------+------------------+ | mass | "mass" | +------------------+------------------+ | core_opt | 1 | +------------------+------------------+ All arguments change the name of fields used to read data from HDF5 files, other than core_opt. core_opt controls which scheme to use for calculating the core masses. If core_opt is 0, then cores uses alpha-isotopes to calculate the silicon and iron cores. Use this for stellar evolution output. Si_core = Si28+S32+Ar36+Ca40+Ti44 Fe_core = Cr48+Fe52+Ni56 If core_opt is 1, then cores uses all elements in a network with proton number Z=23 as a boundary. Use this for MPPNP output. Si_core = Sum of all isotopes with 14 <= Z <= 22 Fe_core = Sum of all isotopes with 23 <= Z <= 28
entailment
def presnyields(self, *cycles, **keyw): """ This function calculates the presupernova yields of a full structure profile from a remnant mass, mrem, to the surface. Parameters ---------- cycles : variadic tuple cycle[0] is the cycle to perform the presupernova yields calculations on. If cycle[1] is also specified, the yields are outputted using 'initial' abundances from cycle[1], otherwise the ejected masses are outputted. keyw : dict A dict of key word arguments. Notes ----- The following keywords can be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | xm | "mass" | +------------------+---------------+ | mrem | 0 | +------------------+---------------+ abund and xm are used when the variables within the input file differ in their names. The default values are set to the output typically found in an MPPNP output file. For example, if the table for the abundances is called "abundances" instead of the default value, use abund = "abundances" as a keyword argument. mrem is specified using a keyword argument and tells the program where to begin integrating. """ abund_list = [] xm_list = [] if ("xm" in keyw) == False: keyw["xm"] = "mass" if ("abund" in keyw) == False: keyw["abund"] = "iso_massf" if ("mrem" in keyw) == False: mrem = 0. else: mrem = keyw["mrem"] # Only two cycles are required in this program. # Any more will be ignored cylen = len(cycles) if cylen > 2: cylen = 2 for i in range(cylen): cycle = cycles[i] abund_list.append(self.se.get(cycle, keyw['abund'])) xm_list.append(self.se.get(cycle, keyw['xm'])) isoX = abund_list[0] xm = xm_list[0] if cylen == 2: isoXini = abund_list[1] # initial abundances niso = len(isoX[0,:]) nshells = len(xm) X_i = np.zeros([niso], float) ybound = np.zeros([niso], float) xarray = np.zeros([nshells+1], float) yarray = np.zeros([nshells+1], float) # This part determines the index of the mass coordinate array which # is closest to the specified remnant mass. This is used in the next # part, which is used to interpolate the abundances at the remnant mass for k in range(nshells): k1 = k if mrem<=xm[k]: break # This part is the interpolation of the isotopes found at the remnant # mass. for i in range(niso): if k1>=1: if isoX[k1-1,i]!=0.0: m=old_div((isoX[k1,i]-isoX[k1-1,i]),(xm[k1]-xm[k1-1])) ybound[i] = isoX[k1-1,i] +m*(mrem-xm[k1-1]) else: ybound[i]=1.e-99 if k1==0: if isoX[k1,i]!=0.0: ybound[i]=isoX[k1,i] else: ybound[i]=1.e-99 # This part merges the interpolated data and the existing arrays into # the arrays xarray and yarray. Once this is done, the summation is # made. xarray[0] = mrem xarray[1:nshells-k1+1] = xm[k1:nshells] for i in range(niso): yarray[0] = ybound[i] for j in range(nshells-k1): if isoX[k1+j,i] != 0.0: yarray[j+1] = isoX[k1+j,i] else: yarray[j+1] = 1.e-99 if cylen == 1: # Calculate the ejected masses for j in range(nshells-k1): X_i[i] = X_i[i] + ((0.5*(yarray[j+1] + yarray[j])) * \ (xarray[j+1] - xarray[j])) elif cylen == 2: # Calculate the SN yield. for j in range(nshells-k1): X_i[i] = X_i[i] + ((0.5*(yarray[j+1] + yarray[j]) - isoXini[-1,i]) * \ (xarray[j+1] - xarray[j])) return X_i
This function calculates the presupernova yields of a full structure profile from a remnant mass, mrem, to the surface. Parameters ---------- cycles : variadic tuple cycle[0] is the cycle to perform the presupernova yields calculations on. If cycle[1] is also specified, the yields are outputted using 'initial' abundances from cycle[1], otherwise the ejected masses are outputted. keyw : dict A dict of key word arguments. Notes ----- The following keywords can be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | xm | "mass" | +------------------+---------------+ | mrem | 0 | +------------------+---------------+ abund and xm are used when the variables within the input file differ in their names. The default values are set to the output typically found in an MPPNP output file. For example, if the table for the abundances is called "abundances" instead of the default value, use abund = "abundances" as a keyword argument. mrem is specified using a keyword argument and tells the program where to begin integrating.
entailment
def windyields(self, ini, end, delta, **keyw): """ This function returns the wind yields and ejected masses. X_i, E_i = data.windyields(ini, end, delta) Parameters ---------- ini : integer The starting cycle. end : integer The finishing cycle. delta : integer The cycle interval. keyw : dict A dict of key word arguments. Returns ------- list The function returns a list of the wind yields(X_i) and a list of the ejected masses(E_i) in the mass units that were used (usually solar masses). Notes ----- The following keywords cand also be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | tmass | "mass" | +------------------+---------------+ | cycle | "cycle" | +------------------+---------------+ The keyword arguments are used when the variables within the input file differ in name from their default values typically found in an MPPNP output file. If the data table differs in name, use these keywords. For example, if the table for the abundances is called "abundances" instead of "iso_massf", then use abund = "abundances" as a keyword argument. """ if ("tmass" in keyw) == False: keyw["tmass"] = "mass" if ("abund" in keyw) == False: keyw["abund"] = "iso_massf" if ("cycle" in keyw) == False: keyw["cycle"] = "cycle" print("Windyields() initialised. Reading files...") ypsinit = [] niso = 0 X_i = [] E_i = [] totalmass = [] ypssurf = [] cycles = [] first = True # The following statements copy global functions into local memory, # which is called faster, speeding up the code slightly wc = self._windcalc cycleret = self.se.cycles retrieve = self.se.get capp = cycles.extend tapp = totalmass.extend yapp = ypssurf.extend # Retrieve the data from the files for i in range(ini,end+1,delta): step = int(i) capp([int(cycleret[i-ini])]) tapp([retrieve(step,keyw["tmass"])]) yapp([retrieve(step,keyw["abund"])]) print("Reading complete. Calculating yields and ejected masses...") nsteps = len(cycles)-1 niso = len(ypssurf[0]) X_i = np.zeros([niso], float) E_i = np.zeros([niso], float) # Call the windyields calculator X_i, E_i = wc(first, totalmass, nsteps, niso, ypssurf, \ ypsinit, X_i, E_i, cycles) return X_i, E_i
This function returns the wind yields and ejected masses. X_i, E_i = data.windyields(ini, end, delta) Parameters ---------- ini : integer The starting cycle. end : integer The finishing cycle. delta : integer The cycle interval. keyw : dict A dict of key word arguments. Returns ------- list The function returns a list of the wind yields(X_i) and a list of the ejected masses(E_i) in the mass units that were used (usually solar masses). Notes ----- The following keywords cand also be used: +------------------+---------------+ | Keyword Argument | Default Value | +==================+===============+ | abund | "iso_massf" | +------------------+---------------+ | tmass | "mass" | +------------------+---------------+ | cycle | "cycle" | +------------------+---------------+ The keyword arguments are used when the variables within the input file differ in name from their default values typically found in an MPPNP output file. If the data table differs in name, use these keywords. For example, if the table for the abundances is called "abundances" instead of "iso_massf", then use abund = "abundances" as a keyword argument.
entailment
def _windcalc(self, first, totalmass, nsteps, niso, ypssurf, ypsinit, \ X_i, E_i, cycles): """ This function calculates the windyields and ejected masses as called from windyields(). It uses a summation version of the formulae used in Hirschi et al. 2005, "Yields of rotating stars at solar metallicity". If it is the first file, the arrays need to be created and the initial abundances set """ if first == True: X_i = np.zeros([niso], float) E_i = np.zeros([niso], float) ypsinit = ypssurf[0] for m in range(niso): for n in range(nsteps): X_i[m] = X_i[m] + ((totalmass[n] - totalmass[n+1]) * \ (0.5 * (ypssurf[n][m] + ypssurf[n+1][m]) - ypsinit[m])) E_i[m] = E_i[m] + ((totalmass[n] - totalmass[n+1]) * \ (0.5 * (ypssurf[n][m] + ypssurf[n+1][m]))) else: for m in range(niso): for n in range(nsteps): X_i[m] = X_i[m] + ((totalmass[n] - totalmass[n+1]) * \ (0.5 * (ypssurf[n][m] + ypssurf[n+1][m]) - ypsinit[m])) E_i[m] = E_i[m] + ((totalmass[n] - totalmass[n+1]) * \ (0.5 * (ypssurf[n][m] + ypssurf[n+1][m]))) return X_i, E_i
This function calculates the windyields and ejected masses as called from windyields(). It uses a summation version of the formulae used in Hirschi et al. 2005, "Yields of rotating stars at solar metallicity". If it is the first file, the arrays need to be created and the initial abundances set
entailment
def average_iso_abund_marco(self,mass_range,cycle,stable,i_decay): """ Interface to average over mass_range. Parameters ---------- mass_range : list A 1x2 array required to plot data in a certain mass range. Needed for _read_iso_abund_marco. cycle : integer which cycle from the h5 file?. Needed for _read_iso_abund_marco stable : boolean Do you want to plot only stable or not. i_decay : integer If i_decay is 1, then plot not decayed. If i_decay is 2, then plot decayed. Make sense only if stable is true. See Also -------- _read_iso_abund_marco() """ import nuutils as u if not stable and i_decay == 2: print('ERROR: choose i_decay = 1') return #data=mp.se(directory,name_h5_file) self._read_iso_abund_marco(mass_range,cycle) #print spe if i_decay == 2: u.stable_specie() self.decay(self.mass_frac) # here I am calculating average mass fraction for all isotopes in given mass range, and then # if needed calculating average over decayed. # warning: mass_range is bigger than used_masses range, by definition. Should I use it? print('average over used_masses range, not over original mass_range') print(used_masses[0],used_masses[len(used_masses)-1],'instead of',mass_range[0],mass_range[1]) global average_mass_frac average_mass_frac = [] if len(used_masses) >= 2: dm_tot = abs(used_masses[len(used_masses)-1]-used_masses[0]) for j in range(len(u.spe)-1): temp = 0. for i in range(len(used_masses)-1): dm_i = abs(used_masses[i+1]-used_masses[i]) temp = float(self.mass_frac[i][j]*dm_i/dm_tot) + temp average_mass_frac.append(temp) #print average_mass_frac elif len(used_masses) == 1: print('case with 1 mass zone only, not implemented yet') somma = 0. somma = sum(average_mass_frac) print('departure from 1 of sum of average_mass_frac=',abs(1. - somma)) # not let's do it over decayed also, if i_decay = 2 if i_decay == 2: global average_mass_frac_decay average_mass_frac_decay = [] dm_tot = abs(used_masses[len(used_masses)-1]-used_masses[0]) # #print len(decayed_multi_d[0]),decayed_multi_d[0] for j in range(len(u.back_ind)): temp = 0. for i in range(len(used_masses)-1): dm_i = abs(used_masses[i+1]-used_masses[i]) temp = float(decayed_multi_d[i][j]*dm_i/dm_tot) + temp average_mass_frac_decay.append(temp) somma = 0. somma = sum(average_mass_frac_decay) print('departure from 1 of sum of average_mass_frac_decay=',abs(1. - somma))
Interface to average over mass_range. Parameters ---------- mass_range : list A 1x2 array required to plot data in a certain mass range. Needed for _read_iso_abund_marco. cycle : integer which cycle from the h5 file?. Needed for _read_iso_abund_marco stable : boolean Do you want to plot only stable or not. i_decay : integer If i_decay is 1, then plot not decayed. If i_decay is 2, then plot decayed. Make sense only if stable is true. See Also -------- _read_iso_abund_marco()
entailment
def _get_elem_names(self): """ returns for one cycle an element name dictionary.""" import nuutils as u # provide library for Z versus element names, and Z for elements #element_name = self.se.elements element_name = self.elements_names u.give_zip_element_z_and_names(element_name) self.z_of_element_name = u.index_z_for_elements
returns for one cycle an element name dictionary.
entailment
def get_abundance_iso_decay(self,cycle): """ returns the decayed stable isotopes. Parameters ---------- cycle : integer The cycle. """ import nuutils as u masses_for_this_cycle = self.se.get(cycle,'mass') self._read_iso_abund_marco([min(masses_for_this_cycle),max(masses_for_this_cycle)],cycle) u.stable_specie() self.decay(self.mass_frac) self.index_for_all_species = u.cl self.index_for_stable_species = u.back_ind self.decayed_stable_isotopes_per_cycle = decayed_multi_d # from here read solar abundances solar_factor = 2. u.solar('iniab1.0E-02.ppn_GN93',solar_factor) self.stable_isotope_identifier=u.jjdum self.stable_isotope_list=u.stable self.isotopic_production_factors=[] for i in range(len(masses_for_this_cycle)): pf_dum=[] jj=0 for j in range(len(self.stable_isotope_identifier)): if self.stable_isotope_identifier[j] == 1: pf_dum.append(float(old_div(self.mass_frac[i][self.index_for_all_species[self.stable_isotope_list [jj].capitalize()]],u.solar_abundance[self.stable_isotope_list[jj].lower()]))) jj=jj+1 #elif self.stable_isotope_identifier[j] == 0: # pf_dum.append(float(0.)) self.isotopic_production_factors.append(pf_dum) self.isotopic_production_factors_decayed=[] for i in range(len(masses_for_this_cycle)): pf_dum_d=[] jj=0 for j in range(len(self.stable_isotope_identifier)): if self.stable_isotope_identifier[j] == 1: pf_dum_d.append(float(old_div(self.decayed_stable_isotopes_per_cycle[i][self.index_for_stable_species[self.stable_isotope_list [jj].upper()]],u.solar_abundance[self.stable_isotope_list[jj].lower()]))) jj=jj+1 self.isotopic_production_factors_decayed.append(pf_dum_d)
returns the decayed stable isotopes. Parameters ---------- cycle : integer The cycle.
entailment
def get_abundance_elem(self,cycle): """ returns the undecayed element profile (all elements that are in elem_names). Parameters ---------- cycle : integer The cycle number """ import nuutils as u masses_for_this_cycle = self.se.get(cycle,'mass') self._read_iso_abund_marco([min(masses_for_this_cycle),max(masses_for_this_cycle)],cycle) u.stable_specie() self.decay(self.mass_frac) # provide library for Z versus element names, and Z for elements element_name = self.se.elements u.give_zip_element_z_and_names(element_name) # from here read solar abundances solar_factor = 2. u.solar('iniab1.0E-02.ppn_GN93',solar_factor) self.stable_isotope_identifier=u.jjdum self.stable_isotope_list=u.stable self.element_abundance_not_decayed=[] self.element_abundance_decayed =[] self.element_production_factors=[] self.element_production_factors_decayed=[] for i in range(len(masses_for_this_cycle)): mass_fractions_array_decayed = decayed_multi_d[i] mass_fractions_array_not_decayed = self.mass_frac[i] u.element_abund_marco(2,self.stable_isotope_list,self.stable_isotope_identifier,mass_fractions_array_not_decayed,mass_fractions_array_decayed) self.element_abundance_not_decayed.append(u.elem_abund) self.element_abundance_decayed.append(u.elem_abund_decayed) self.element_production_factors.append(u.elem_prod_fac) self.element_production_factors_decayed.append(u.elem_prod_fac_decayed)
returns the undecayed element profile (all elements that are in elem_names). Parameters ---------- cycle : integer The cycle number
entailment
def maximum_size_bytes(self): """Gets the biggest disk drive :returns size in bytes. """ return utils.max_safe( [device.get('CapacityBytes') for device in self.devices if device.get('CapacityBytes') is not None])
Gets the biggest disk drive :returns size in bytes.
entailment
def generate_account_shared_access_signature(self, resource_types, permission, expiry, start=None, ip=None, protocol=None): ''' Generates a shared access signature for the table service. Use the returned signature with the sas_token parameter of TableService. :param ResourceTypes resource_types: Specifies the resource types that are accessible with the account SAS. :param AccountPermissions permission: The permissions associated with the shared access signature. The user is restricted to operations allowed by the permissions. Required unless an id is given referencing a stored access policy which contains this field. This field must be omitted if it has been specified in an associated stored access policy. :param expiry: The time at which the shared access signature becomes invalid. Required unless an id is given referencing a stored access policy which contains this field. This field must be omitted if it has been specified in an associated stored access policy. Azure will always convert values to UTC. If a date is passed in without timezone info, it is assumed to be UTC. :type expiry: date or str :param start: The time at which the shared access signature becomes valid. If omitted, start time for this call is assumed to be the time when the storage service receives the request. Azure will always convert values to UTC. If a date is passed in without timezone info, it is assumed to be UTC. :type start: date or str :param str ip: Specifies an IP address or a range of IP addresses from which to accept requests. If the IP address from which the request originates does not match the IP address or address range specified on the SAS token, the request is not authenticated. For example, specifying sip=168.1.5.65 or sip=168.1.5.60-168.1.5.70 on the SAS restricts the request to those IP addresses. :param str protocol: Specifies the protocol permitted for a request made. The default value is https,http. See :class:`~azure.storage.models.Protocol` for possible values. :return: A Shared Access Signature (sas) token. :rtype: str ''' _validate_not_none('self.account_name', self.account_name) _validate_not_none('self.account_key', self.account_key) sas = SharedAccessSignature(self.account_name, self.account_key) return sas.generate_account(Services.TABLE, resource_types, permission, expiry, start=start, ip=ip, protocol=protocol)
Generates a shared access signature for the table service. Use the returned signature with the sas_token parameter of TableService. :param ResourceTypes resource_types: Specifies the resource types that are accessible with the account SAS. :param AccountPermissions permission: The permissions associated with the shared access signature. The user is restricted to operations allowed by the permissions. Required unless an id is given referencing a stored access policy which contains this field. This field must be omitted if it has been specified in an associated stored access policy. :param expiry: The time at which the shared access signature becomes invalid. Required unless an id is given referencing a stored access policy which contains this field. This field must be omitted if it has been specified in an associated stored access policy. Azure will always convert values to UTC. If a date is passed in without timezone info, it is assumed to be UTC. :type expiry: date or str :param start: The time at which the shared access signature becomes valid. If omitted, start time for this call is assumed to be the time when the storage service receives the request. Azure will always convert values to UTC. If a date is passed in without timezone info, it is assumed to be UTC. :type start: date or str :param str ip: Specifies an IP address or a range of IP addresses from which to accept requests. If the IP address from which the request originates does not match the IP address or address range specified on the SAS token, the request is not authenticated. For example, specifying sip=168.1.5.65 or sip=168.1.5.60-168.1.5.70 on the SAS restricts the request to those IP addresses. :param str protocol: Specifies the protocol permitted for a request made. The default value is https,http. See :class:`~azure.storage.models.Protocol` for possible values. :return: A Shared Access Signature (sas) token. :rtype: str
entailment
def push_power_button(self, target_value): """Reset the system in hpe exclusive manner. :param target_value: The target value to be set. :raises: InvalidInputError, if the target value is not allowed. :raises: SushyError, on an error from iLO. """ if target_value not in mappings.PUSH_POWER_BUTTON_VALUE_MAP_REV: msg = ('The parameter "%(parameter)s" value "%(target_value)s" is ' 'invalid. Valid values are: %(valid_power_values)s' % {'parameter': 'target_value', 'target_value': target_value, 'valid_power_values': ( mappings.PUSH_POWER_BUTTON_VALUE_MAP_REV.keys())}) raise exception.InvalidInputError(msg) value = mappings.PUSH_POWER_BUTTON_VALUE_MAP_REV[target_value] target_uri = ( self._get_hpe_push_power_button_action_element().target_uri) self._conn.post(target_uri, data={'PushType': value})
Reset the system in hpe exclusive manner. :param target_value: The target value to be set. :raises: InvalidInputError, if the target value is not allowed. :raises: SushyError, on an error from iLO.
entailment
def bios_settings(self): """Property to provide reference to `BIOSSettings` instance It is calculated once when the first time it is queried. On refresh, this property gets reset. """ return bios.BIOSSettings( self._conn, utils.get_subresource_path_by(self, 'Bios'), redfish_version=self.redfish_version)
Property to provide reference to `BIOSSettings` instance It is calculated once when the first time it is queried. On refresh, this property gets reset.
entailment
def update_persistent_boot(self, devices=[], persistent=False): """Changes the persistent boot device order in BIOS boot mode for host Note: It uses first boot device from the devices and ignores rest. :param devices: ordered list of boot devices :param persistent: Boolean flag to indicate if the device to be set as a persistent boot device :raises: IloError, on an error from iLO. :raises: IloInvalidInputError, if the given input is not valid. """ device = PERSISTENT_BOOT_DEVICE_MAP.get(devices[0].upper()) if device == sushy.BOOT_SOURCE_TARGET_UEFI_TARGET: try: uefi_devices = self.uefi_target_override_devices iscsi_device = None for uefi_device in uefi_devices: if uefi_device is not None and 'iSCSI' in uefi_device: iscsi_device = uefi_device break if iscsi_device is None: msg = 'No UEFI iSCSI bootable device found on system.' raise exception.IloError(msg) except sushy.exceptions.SushyError as e: msg = ('Unable to get uefi target override devices. ' 'Error %s') % (str(e)) raise exception.IloError(msg) uefi_boot_settings = { 'Boot': {'UefiTargetBootSourceOverride': iscsi_device} } self._conn.patch(self.path, data=uefi_boot_settings) elif device is None: device = sushy.BOOT_SOURCE_TARGET_NONE tenure = (sushy.BOOT_SOURCE_ENABLED_CONTINUOUS if persistent else sushy.BOOT_SOURCE_ENABLED_ONCE) self.set_system_boot_source(device, enabled=tenure)
Changes the persistent boot device order in BIOS boot mode for host Note: It uses first boot device from the devices and ignores rest. :param devices: ordered list of boot devices :param persistent: Boolean flag to indicate if the device to be set as a persistent boot device :raises: IloError, on an error from iLO. :raises: IloInvalidInputError, if the given input is not valid.
entailment
def secure_boot(self): """Property to provide reference to `SecureBoot` instance It is calculated once when the first time it is queried. On refresh, this property gets reset. """ return secure_boot.SecureBoot( self._conn, utils.get_subresource_path_by(self, 'SecureBoot'), redfish_version=self.redfish_version)
Property to provide reference to `SecureBoot` instance It is calculated once when the first time it is queried. On refresh, this property gets reset.
entailment
def ethernet_interfaces(self): """Provide reference to EthernetInterfacesCollection instance""" return ethernet_interface.EthernetInterfaceCollection( self._conn, self._get_hpe_sub_resource_collection_path('EthernetInterfaces'), redfish_version=self.redfish_version)
Provide reference to EthernetInterfacesCollection instance
entailment
def smart_storage(self): """This property gets the object for smart storage. This property gets the object for smart storage. There is no collection for smart storages. :returns: an instance of smart storage """ return hpe_smart_storage.HPESmartStorage( self._conn, utils.get_subresource_path_by( self, ['Oem', 'Hpe', 'Links', 'SmartStorage']), redfish_version=self.redfish_version)
This property gets the object for smart storage. This property gets the object for smart storage. There is no collection for smart storages. :returns: an instance of smart storage
entailment
def storages(self): """This property gets the list of instances for Storages This property gets the list of instances for Storages :returns: a list of instances of Storages """ return storage.StorageCollection( self._conn, utils.get_subresource_path_by(self, 'Storage'), redfish_version=self.redfish_version)
This property gets the list of instances for Storages This property gets the list of instances for Storages :returns: a list of instances of Storages
entailment
def simple_storages(self): """This property gets the list of instances for SimpleStorages :returns: a list of instances of SimpleStorages """ return simple_storage.SimpleStorageCollection( self._conn, utils.get_subresource_path_by(self, 'SimpleStorage'), redfish_version=self.redfish_version)
This property gets the list of instances for SimpleStorages :returns: a list of instances of SimpleStorages
entailment
def memory(self): """Property to provide reference to `MemoryCollection` instance It is calculated once when the first time it is queried. On refresh, this property gets reset. """ return memory.MemoryCollection( self._conn, utils.get_subresource_path_by(self, 'Memory'), redfish_version=self.redfish_version)
Property to provide reference to `MemoryCollection` instance It is calculated once when the first time it is queried. On refresh, this property gets reset.
entailment
def get_smart_storage_config(self, smart_storage_config_url): """Returns a SmartStorageConfig Instance for each controller.""" return (smart_storage_config. HPESmartStorageConfig(self._conn, smart_storage_config_url, redfish_version=self.redfish_version))
Returns a SmartStorageConfig Instance for each controller.
entailment
def _get_smart_storage_config_by_controller_model(self, controller_model): """Returns a SmartStorageConfig Instance for controller by model. :returns: SmartStorageConfig Instance for controller """ ac = self.smart_storage.array_controllers.array_controller_by_model( controller_model) if ac: for ssc_id in self.smart_storage_config_identities: ssc_obj = self.get_smart_storage_config(ssc_id) if ac.location == ssc_obj.location: return ssc_obj
Returns a SmartStorageConfig Instance for controller by model. :returns: SmartStorageConfig Instance for controller
entailment
def check_smart_storage_config_ids(self): """Check SmartStorageConfig controllers is there in hardware. :raises: IloError, on an error from iLO. """ if self.smart_storage_config_identities is None: msg = ('The Redfish controller failed to get the ' 'SmartStorageConfig controller configurations.') LOG.debug(msg) raise exception.IloError(msg)
Check SmartStorageConfig controllers is there in hardware. :raises: IloError, on an error from iLO.
entailment
def delete_raid(self): """Delete the raid configuration on the hardware. Loops through each SmartStorageConfig controller and clears the raid configuration. :raises: IloError, on an error from iLO. """ self.check_smart_storage_config_ids() any_exceptions = [] ld_exc_count = 0 for config_id in self.smart_storage_config_identities: try: ssc_obj = self.get_smart_storage_config(config_id) ssc_obj.delete_raid() except exception.IloLogicalDriveNotFoundError as e: ld_exc_count += 1 except sushy.exceptions.SushyError as e: any_exceptions.append((config_id, str(e))) if any_exceptions: msg = ('The Redfish controller failed to delete the ' 'raid configuration in one or more controllers with ' 'Error: %(error)s' % {'error': str(any_exceptions)}) raise exception.IloError(msg) if ld_exc_count == len(self.smart_storage_config_identities): msg = ('No logical drives are found in any controllers. Nothing ' 'to delete.') raise exception.IloLogicalDriveNotFoundError(msg)
Delete the raid configuration on the hardware. Loops through each SmartStorageConfig controller and clears the raid configuration. :raises: IloError, on an error from iLO.
entailment
def _parse_raid_config_data(self, raid_config): """It will parse raid config data based on raid controllers :param raid_config: A dictionary containing target raid configuration data. This data stucture should be as follows: raid_config = {'logical_disks': [{'raid_level': 1, 'size_gb': 100, 'controller': 'HPE Smart Array P408i-a SR Gen10'}, <info-for-logical-disk-2>]} :returns: A dictionary of controllers, each containing list of their respected logical drives. """ default = ( self.smart_storage.array_controllers.get_default_controller.model) controllers = {default: []} for ld in raid_config['logical_disks']: if 'controller' not in ld.keys(): controllers[default].append(ld) else: ctrl = ld['controller'] if ctrl not in controllers: controllers[ctrl] = [] controllers[ctrl].append(ld) return controllers
It will parse raid config data based on raid controllers :param raid_config: A dictionary containing target raid configuration data. This data stucture should be as follows: raid_config = {'logical_disks': [{'raid_level': 1, 'size_gb': 100, 'controller': 'HPE Smart Array P408i-a SR Gen10'}, <info-for-logical-disk-2>]} :returns: A dictionary of controllers, each containing list of their respected logical drives.
entailment
def create_raid(self, raid_config): """Create the raid configuration on the hardware. :param raid_config: A dictionary containing target raid configuration data. This data stucture should be as follows: raid_config = {'logical_disks': [{'raid_level': 1, 'size_gb': 100, 'physical_disks': ['6I:1:5'], 'controller': 'HPE Smart Array P408i-a SR Gen10'}, <info-for-logical-disk-2>]} :raises: IloError, on an error from iLO. """ self.check_smart_storage_config_ids() any_exceptions = [] controllers = self._parse_raid_config_data(raid_config) # Creating raid on rest of the controllers for controller in controllers: try: config = {'logical_disks': controllers[controller]} ssc_obj = ( self._get_smart_storage_config_by_controller_model( controller)) if ssc_obj: ssc_obj.create_raid(config) else: members = ( self.smart_storage.array_controllers.get_members()) models = [member.model for member in members] msg = ('Controller not found. Available controllers are: ' '%(models)s' % {'models': models}) any_exceptions.append((controller, msg)) except sushy.exceptions.SushyError as e: any_exceptions.append((controller, str(e))) if any_exceptions: msg = ('The Redfish controller failed to create the ' 'raid configuration for one or more controllers with ' 'Error: %(error)s' % {'error': str(any_exceptions)}) raise exception.IloError(msg)
Create the raid configuration on the hardware. :param raid_config: A dictionary containing target raid configuration data. This data stucture should be as follows: raid_config = {'logical_disks': [{'raid_level': 1, 'size_gb': 100, 'physical_disks': ['6I:1:5'], 'controller': 'HPE Smart Array P408i-a SR Gen10'}, <info-for-logical-disk-2>]} :raises: IloError, on an error from iLO.
entailment
def _post_create_read_raid(self, raid_config): """Read the logical drives from the system after post-create raid :param raid_config: A dictionary containing target raid configuration data. This data stucture should be as follows: raid_config = {'logical_disks': [{'raid_level': 1, 'size_gb': 100, 'physical_disks': ['6I:1:5'], 'controller': 'HPE Smart Array P408i-a SR Gen10'}, <info-for-logical-disk-2>]} :raises: IloLogicalDriveNotFoundError, if no controllers are configured :raises: IloError, if any error form iLO :returns: A dictionary containing list of logical disks """ controllers = self._parse_raid_config_data(raid_config) ld_exc_count = 0 any_exceptions = [] config = {'logical_disks': []} for controller in controllers: try: ssc_obj = ( self._get_smart_storage_config_by_controller_model( controller)) if ssc_obj: result = ssc_obj.read_raid(controller=controller) config['logical_disks'].extend(result['logical_disks']) except exception.IloLogicalDriveNotFoundError as e: ld_exc_count += 1 except sushy.exceptions.SushyError as e: any_exceptions.append((controller, str(e))) if ld_exc_count == len(controllers): msg = 'No logical drives are found in any controllers.' raise exception.IloLogicalDriveNotFoundError(msg) if any_exceptions: msg = ('The Redfish controller failed to read the ' 'raid configuration in one or more controllers with ' 'Error: %(error)s' % {'error': str(any_exceptions)}) raise exception.IloError(msg) return config
Read the logical drives from the system after post-create raid :param raid_config: A dictionary containing target raid configuration data. This data stucture should be as follows: raid_config = {'logical_disks': [{'raid_level': 1, 'size_gb': 100, 'physical_disks': ['6I:1:5'], 'controller': 'HPE Smart Array P408i-a SR Gen10'}, <info-for-logical-disk-2>]} :raises: IloLogicalDriveNotFoundError, if no controllers are configured :raises: IloError, if any error form iLO :returns: A dictionary containing list of logical disks
entailment
def _post_delete_read_raid(self): """Read the logical drives from the system after post-delete raid :raises: IloError, if any error form iLO :returns: Empty dictionary with format: {'logical_disks': []} """ any_exceptions = [] ssc_ids = self.smart_storage_config_identities config = {'logical_disks': []} for ssc_id in ssc_ids: try: ssc_obj = self.get_smart_storage_config(ssc_id) ac_obj = ( self.smart_storage.array_controllers. array_controller_by_location(ssc_obj.location)) if ac_obj: model = ac_obj.model result = ssc_obj.read_raid() if result: config['logical_disks'].extend(result['logical_disks']) except sushy.exceptions.SushyError as e: any_exceptions.append((model, str(e))) if any_exceptions: msg = ('The Redfish controller failed to read the ' 'raid configuration in one or more controllers with ' 'Error: %(error)s' % {'error': str(any_exceptions)}) raise exception.IloError(msg) return config
Read the logical drives from the system after post-delete raid :raises: IloError, if any error form iLO :returns: Empty dictionary with format: {'logical_disks': []}
entailment