PioApocalypse
74b8c9cfae
now keys with numeric values are sub-dictionaries with a "value" and a "units" key - unitS not unit to comply directly with NeXus format, which turned out to be a good idea to avoid confusion since eLabFTW uses the word "units" for the list of accepted units and "unit" for the selected one... NOTE: UoM = Unit of Measurement
285 lines
13 KiB
Python
285 lines
13 KiB
Python
import os, json, requests, h5py
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from getpass import getpass
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from APIHandler import APIHandler
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from classes import *
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def call_entrypoint_from_elabid(elabid):
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'''
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Calls an entrypoint sample from eLabFTW using its elabid, then returns an object of the Entrypoint class.
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If the entry is not a sample (category_title not matching exactly "Sample") returns ValueError.
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'''
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try:
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sample_data = APIHandler(apikey).get_entry_from_elabid(elabid, entryType="items")
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if not sample_data.get("category_title") == "Sample":
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raise ValueError("The resource you selected is not a sample, therefore it can't be used as an entrypoint.")
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sample_object = Entrypoint(sample_data)
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except ConnectionError as e:
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raise ConnectionError(e)
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return sample_object # Entrypoint-class object
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def call_material_from_elabid(elabid):
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'''
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Calls a material from eLabFTW using its elabid, then returns an object of the Material class.
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If the entry is neither a PLD Target or a Substrate batch returns ValueError. Such entries always have a category_title key with its value matching exactly "PLD Target" or "Substrate".
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Because of an old typo, the value "Subtrate" (second 's' is missing) is also accepted.
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'''
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try:
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material_data = APIHandler(apikey).get_entry_from_elabid(elabid, entryType="items")
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material_category = material_data.get("category_title")
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# TO-DO: correct this typo on elabftw: Subtrate → Substrate.
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if not material_category in ["PLD Target", "Substrate", "Subtrate"]:
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print(f"Category of the resource: {material_category}.")
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raise ValueError(f"The referenced resource (elabid = {elabid}) is not a material.")
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elif material_category == "PLD Target":
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material_object = Target(material_data)
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else:
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material_object = Substrate(material_data)
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except ConnectionError as e:
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raise ConnectionError(e)
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return material_object # Material-class object
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def call_layers_from_list(elabid_list):
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'''
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Calls a list of (PLD deposition) experiments from eLabFTW using their elabid - which means the input must be a list of integers instead of a single one - then returns a list of Layer-class objects.
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If one of the entries is not related to a deposition layer (category_title not matching exactly "PLD Deposition") that entry is skipped, with no error raised.
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'''
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list_of_layers = []
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for elabid in elabid_list:
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try:
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layer_data = APIHandler(apikey).get_entry_from_elabid(elabid, entryType="experiments")
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if not layer_data.get("category_title") == "PLD Deposition":
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continue
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layer_object = Layer(layer_data)
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list_of_layers.append(layer_object)
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except ConnectionError as e:
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nums = [ layer.layer_number for layer in list_of_layers ]
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nums.sort()
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print(f"LIST OF THE LAYERS PROCESSED (unordered):\n" + str(nums))
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raise ConnectionError(f"An error occurred while fetching the experiment with elabid = {elabid}:\n" +
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str(e) + f"\nPlease solve the problem before retrying." + "\n\n" +
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f"Last resource attempted to call: {ELABFTW_API_URL}/experiments/{elabid}"
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)
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return list_of_layers # list of Layer-class objects
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def chain_entrypoint_to_batch(sample_object):
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'''
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Takes an Entrypoint-class object, looks at its .batch_elabid attribute and returns a Material-class object containing data on the substrate batch associated to the starting sample.
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Dependency: call_material_from_elabid.
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'''
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material_elabid = sample_object.batch_elabid
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material_object = call_material_from_elabid(material_elabid)
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return material_object
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def chain_entrypoint_to_layers(sample_object):
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'''
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Takes an Entrypoint-class object, looks at its .linked_experiments_elabid attribute (list) and returns a list of Layer-class objects containing data on the deposition layers associated to the starting sample - using the function call_layers_from_list.
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The list is sorted by progressive layer number (layer_number attribute).
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Dependency: call_layers_from_list.
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'''
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linked_experiments_elabid = sample_object.linked_experiments_elabid # list of elabid
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layer_object_list = call_layers_from_list(linked_experiments_elabid)
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layer_object_list.sort(key=lambda x: x.layer_number)
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return layer_object_list
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def chain_layer_to_target(layer_object):
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'''
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Takes a Layer-class object, looks at its .target_elabid attribute and returns a Material-class object containing data on the PLD target used in the deposition of said layer.
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Dependency: call_material_from_elabid.
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'''
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target_elabid = layer_object.target_elabid
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material_object = call_material_from_elabid(target_elabid)
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return material_object
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def deduplicate_instruments_from_layers(layers):
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'''
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Takes a list of Layer-class objects and for each layer gets the instruments used (laser, depo chamber and RHEED), returns deduplicated list. Ideally, the lists should only contain one element.
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'''
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lasers = []
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chambers = []
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rheeds = []
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for lyr in layers:
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instruments = lyr.get_instruments(apikey)
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lasers.append(instruments["laser_system"])
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chambers.append(instruments["deposition_chamber"])
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rheeds.append(instruments["rheed_system"])
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instruments_used_dict = {
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"laser_system": list( set( lasers ) ),
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"deposition_chamber": list( set( chambers ) ),
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"rheed_system" : list( set( rheeds ) ),
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}
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# lasers = { f"layer_{lyr.layer_number}": lyr.laser_system for lyr in layers }
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# chambers = { f"layer_{lyr.layer_number}": lyr.deposition_chamber for lyr in layers }
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# rheeds = { f"layer_{lyr.layer_number}": lyr.rheed_system for lyr in layers }
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# instruments_used_dict = {
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# "laser_system": lasers,
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# "deposition_chamber": chambers,
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# "rheed_system": rheeds,
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# }
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return instruments_used_dict
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def make_nexus_schema_dictionary(substrate_object, layers):
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'''
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Main function, takes all the other functions to reconstruct the full dataset. Takes a Substrate-class object (output of the chain_entrypoint_to_batch() function) and a list of Layer-class objects (output of the chain_entrypoint_to_layers() function), returns dictionary with the same schema as the NeXus standard for PLD fabrications.
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'''
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pld_fabrication = {
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"sample": {
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"substrate": {
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"name": substrate_object.name,
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"chemical_formula" : substrate_object.get_compound_formula(apikey),
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"orientation" : substrate_object.orientation,
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"miscut_angle" : {
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"value": substrate_object.miscut_angle,
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"units": substrate_object.miscut_angle_unit
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},
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"miscut_direction" : substrate_object.miscut_direction,
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"thickness" : {
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"value": substrate_object.thickness,
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"units": substrate_object.thickness_unit,
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},
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"dimensions" : substrate_object.dimensions,
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"surface_treatment" : substrate_object.surface_treatment,
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"manufacturer" : substrate_object.manufacturer,
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"batch_id" : substrate_object.batch_id,
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},
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"multilayer": {},
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},
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"instruments_used": deduplicate_instruments_from_layers(layers),
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}
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multilayer = pld_fabrication["sample"]["multilayer"]
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for layer in layers:
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name = "layer_" + layer.layer_number
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target_object = chain_layer_to_target(layer)
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target_dict = {
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"name": target_object.name,
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"chemical_formula" : target_object.get_compound_formula(apikey),
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"description" : target_object.description,
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"shape" : target_object.shape,
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"dimensions" : target_object.dimensions,
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"thickness" : {
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"value": target_object.thickness,
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"units": target_object.thickness_unit,
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},
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"solid_form" : target_object.solid_form,
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"manufacturer" : target_object.manufacturer,
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"batch_id" : target_object.name,
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# TO-DO: currently not available:
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}
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multilayer[name] = {
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"target": target_dict,
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"start_time": layer.start_time,
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"operator": layer.operator,
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"description": layer.description,
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"number_of_pulses": layer.number_of_pulses,
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"deposition_time": {
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"value": layer.deposition_time,
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"units": layer.deposition_time_unit,
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},
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"temperature": {
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"value": layer.temperature,
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"units": layer.temperature_unit,
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},
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"heating_method": layer.heating_method,
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"layer_thickness": {
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"value": layer.layer_thickness,
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"units": layer.layer_thickness_unit,
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},
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"buffer_gas": layer.buffer_gas,
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"process_pressure": {
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"value": layer.process_pressure,
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"units": layer.process_pressure_unit,
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},
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"heater_target_distance": {
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"value": layer.heater_target_distance,
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"units": layer.heater_target_distance_unit,
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},
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"repetition_rate": {
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"value": layer.repetition_rate,
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"units": layer.repetition_rate_unit,
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},
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"laser_fluence": {
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"value": layer.laser_fluence,
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"units": layer.laser_fluence_unit,
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},
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"laser_spot_area": {
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"value": layer.laser_spot_area,
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"units": layer.laser_spot_area_unit,
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},
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"laser_energy": {
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"value": layer.laser_energy,
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"units": layer.laser_energy_unit,
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},
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"laser_rastering": {
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"geometry": layer.laser_rastering_geometry,
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"positions": layer.laser_rastering_positions,
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"velocities": layer.laser_rastering_velocities,
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},
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"pre_annealing": {
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"ambient_gas": layer.pre_annealing_ambient_gas,
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"pressure": {
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"value": layer.pre_annealing_pressure,
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"units": layer.pre_annealing_pressure_unit,
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},
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"temperature": {
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"value": layer.pre_annealing_temperature,
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"units": layer.pre_annealing_temperature_unit,
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},
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"duration": {
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"value": layer.pre_annealing_duration,
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"units": layer.pre_annealing_duration_unit,
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},
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},
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"post_annealing": {
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"ambient_gas": layer.post_annealing_ambient_gas,
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"pressure": {
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"value": layer.post_annealing_pressure,
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"units": layer.post_annealing_pressure_unit,
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},
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"temperature": {
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"value": layer.post_annealing_temperature,
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"units": layer.post_annealing_temperature_unit,
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},
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"duration": {
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"value": layer.post_annealing_duration,
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"units": layer.post_annealing_duration_unit,
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},
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},
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}
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return pld_fabrication
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def build_nexus_file(pld_fabrication, output_path):
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# NOTE: look at the mail attachment from Emiliano...
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with h5py.File(output_path, "w") as f:
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nx_pld_entry = f.create_group("pld_fabrication")
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nx_pld_entry.attrs["NX_class"] = "NXentry"
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# Sample section
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nx_sample = nx_pld_entry.create_group("sample")
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nx_sample.attrs["NX_class"] = "NXsample"
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# Substrate section
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nx_substrate = nx_pld_entry.create_group("substrate")
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nx_substrate.attrs["NX_class"] = "NXsubentry"
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pass
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if __name__=="__main__":
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# TO-DO: place the API base URL somewhere else.
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ELABFTW_API_URL = "https://elabftw.fisica.unina.it/api/v2"
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apikey = getpass("Paste API key here: ")
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elabid = input("Enter elabid of your starting sample [default= 1111]: ") or 1111
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data = APIHandler(apikey).get_entry_from_elabid(elabid)
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sample = Entrypoint(data)
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sample_name = sample.name.strip().replace(" ","_")
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substrate_object = chain_entrypoint_to_batch(sample) # Substrate-class object
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layers = chain_entrypoint_to_layers(sample) # list of Layer-class objects
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result = make_nexus_schema_dictionary(substrate_object, layers)
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# print(make_nexus_schema_dictionary(substrate_object, layers)) # debug
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with open (f"output/sample-{sample_name}.json", "w") as f:
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json.dump(result, f, indent=3) |