From 79b77a0cabf8c33be2953f849875a276aeb1bea7 Mon Sep 17 00:00:00 2001 From: AaronH-sys Date: Mon, 9 Mar 2026 14:01:41 +0000 Subject: [PATCH 1/9] added donto flag --- aiidalab_ispg/app/atmospec_steps.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/aiidalab_ispg/app/atmospec_steps.py b/aiidalab_ispg/app/atmospec_steps.py index beb8a6c..9287d77 100644 --- a/aiidalab_ispg/app/atmospec_steps.py +++ b/aiidalab_ispg/app/atmospec_steps.py @@ -280,6 +280,7 @@ def _add_mdci_orca_params(self, orca_parameters, basis, mdci_method, nroots): mdci_params["input_blocks"]["mdci"] = { "nroots": nroots, "maxcore": MEMORY_PER_CPU, + "donto": True, } # TODO: For efficiency reasons, in might not be necessary to calculated left-vectors # to obtain TDM, but we need to benchmark that first. @@ -297,6 +298,7 @@ def _add_tddft_orca_params( tddft_params["input_blocks"]["tddft"] = { "nroots": nroots, "maxcore": MEMORY_PER_CPU, + "donto": True, } if es_method == ExcitedStateMethod.TDDFT: tddft_params["input_blocks"]["tddft"]["tda"] = "false" From 43077129baa985c8cb76522413c91aefffef9feb Mon Sep 17 00:00:00 2001 From: AaronH-sys Date: Mon, 9 Mar 2026 14:18:11 +0000 Subject: [PATCH 2/9] retrieve .nto files --- aiidalab_ispg/app/atmospec_steps.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/aiidalab_ispg/app/atmospec_steps.py b/aiidalab_ispg/app/atmospec_steps.py index 9287d77..5f6952c 100644 --- a/aiidalab_ispg/app/atmospec_steps.py +++ b/aiidalab_ispg/app/atmospec_steps.py @@ -280,6 +280,8 @@ def _add_mdci_orca_params(self, orca_parameters, basis, mdci_method, nroots): mdci_params["input_blocks"]["mdci"] = { "nroots": nroots, "maxcore": MEMORY_PER_CPU, + + # Calculate nto flag "donto": True, } # TODO: For efficiency reasons, in might not be necessary to calculated left-vectors @@ -298,6 +300,8 @@ def _add_tddft_orca_params( tddft_params["input_blocks"]["tddft"] = { "nroots": nroots, "maxcore": MEMORY_PER_CPU, + + # Calculate nto flag "donto": True, } if es_method == ExcitedStateMethod.TDDFT: @@ -380,6 +384,9 @@ def submit(self, _=None): # Fetch GBW file from optimization step, to be used as a guess # for subsequent excited state calculations. builder.opt.orca.metadata.options.additional_retrieve_list = ["aiida.gbw"] + + # Retrieve .nto files + builder.exc.orca.metadata.options.additional_retrieve_list = ["*.nto"] # Clean the remote directory by default, # we're copying back the main output file and gbw file anyway. From 43118f4f3be24fc3f000deec9da5ce724eba906e Mon Sep 17 00:00:00 2001 From: AaronH-sys Date: Wed, 11 Mar 2026 13:51:31 +0000 Subject: [PATCH 3/9] Added NTO calc checkbox and outputs nto files --- aiidalab_ispg/app/atmospec_steps.py | 34 +++++++++++++++++++++++------ aiidalab_ispg/app/input_widgets.py | 28 ++++++++++++++++++++++++ 2 files changed, 55 insertions(+), 7 deletions(-) diff --git a/aiidalab_ispg/app/atmospec_steps.py b/aiidalab_ispg/app/atmospec_steps.py index 5f6952c..9eb5073 100644 --- a/aiidalab_ispg/app/atmospec_steps.py +++ b/aiidalab_ispg/app/atmospec_steps.py @@ -21,6 +21,7 @@ MoleculeSettings, ResourceSelectionWidget, WignerSamplingSettings, + OrbitalSettings, ) from .optimization_steps import OptimizationParameters from .steps import SubmitWorkChainStepBase, ViewWorkChainStatusStep @@ -39,6 +40,8 @@ class AtmospecParameters(OptimizationParameters): tddft_functional: str nwigner: int wigner_low_freq_thr: float + + calculate_orbitals: bool DEFAULT_ATMOSPEC_PARAMETERS = AtmospecParameters( @@ -54,6 +57,8 @@ class AtmospecParameters(OptimizationParameters): tddft_functional="wB97X-D4", nwigner=0, wigner_low_freq_thr=100.0, + + calculate_orbitals=True, ) @@ -81,6 +86,8 @@ def __init__(self, **kwargs): ) self.wigner_settings = WignerSamplingSettings() + + self.orbital_settings = OrbitalSettings() self.codes_selector = CodeSettings() self.resources_settings = ResourceSelectionWidget() @@ -96,6 +103,8 @@ def __init__(self, **kwargs): self.wigner_settings, self.molecule_settings, self.excited_state_settings, + + self.orbital_settings, ] grid_layout = ipw.Layout( width="100%", @@ -188,6 +197,8 @@ def _update_ui_from_parameters(self, parameters: AtmospecParameters) -> None: self.excited_state_settings.basis.value = parameters.es_basis self.wigner_settings.nwigner.value = parameters.nwigner self.wigner_settings.wigner_low_freq_thr.value = parameters.wigner_low_freq_thr + + self.orbital_settings.calculate_orbitals.value = parameters.calculate_orbitals # Infer the value of the gs_sync checkbox if ( @@ -213,6 +224,8 @@ def _get_parameters_from_ui(self) -> AtmospecParameters: nstates=self.excited_state_settings.nstates.value, nwigner=self.wigner_settings.nwigner.value, wigner_low_freq_thr=self.wigner_settings.wigner_low_freq_thr.value, + + calculate_orbitals = self.orbital_settings.calculate_orbitals.value, ) @traitlets.observe("process") @@ -269,7 +282,7 @@ def build_base_orca_params(self, params: AtmospecParameters) -> dict: "input_keywords": input_keywords, } - def _add_mdci_orca_params(self, orca_parameters, basis, mdci_method, nroots): + def _add_mdci_orca_params(self, orca_parameters, basis, mdci_method, nroots, donto): mdci_params = deepcopy(orca_parameters) mdci_params["input_keywords"].append(mdci_method.value) mdci_params["input_keywords"].append(basis) @@ -281,8 +294,8 @@ def _add_mdci_orca_params(self, orca_parameters, basis, mdci_method, nroots): "nroots": nroots, "maxcore": MEMORY_PER_CPU, - # Calculate nto flag - "donto": True, +# Calculate nto flag + "donto": donto, } # TODO: For efficiency reasons, in might not be necessary to calculated left-vectors # to obtain TDM, but we need to benchmark that first. @@ -292,7 +305,7 @@ def _add_mdci_orca_params(self, orca_parameters, basis, mdci_method, nroots): return mdci_params def _add_tddft_orca_params( - self, base_orca_parameters, basis, es_method, functional, nroots + self, base_orca_parameters, basis, es_method, functional, nroots, donto ): tddft_params = deepcopy(base_orca_parameters) tddft_params["input_keywords"].append(functional) @@ -301,9 +314,11 @@ def _add_tddft_orca_params( "nroots": nroots, "maxcore": MEMORY_PER_CPU, - # Calculate nto flag - "donto": True, +# Calculate nto flag + "donto": donto, } + + if es_method == ExcitedStateMethod.TDDFT: tddft_params["input_blocks"]["tddft"]["tda"] = "false" return tddft_params @@ -330,6 +345,7 @@ def submit(self, _=None): builder.code = load_code(self.codes_selector.orca.value) builder.structure = self.input_structure + base_orca_parameters = self.build_base_orca_params(bp) gs_opt_parameters = self._add_optimization_orca_params( base_orca_parameters, basis=bp.basis, gs_method=bp.method @@ -344,6 +360,8 @@ def submit(self, _=None): basis=bp.es_basis, functional=bp.tddft_functional, nroots=bp.nstates, + + donto=bp.calculate_orbitals, ) elif bp.excited_method in ( ExcitedStateMethod.ADC2, @@ -354,6 +372,8 @@ def submit(self, _=None): basis=bp.es_basis, mdci_method=bp.excited_method, nroots=bp.nstates, + + donto=bp.calculate_orbitals, ) else: msg = f"Excited method {bp.excited_method} not implemented" @@ -385,7 +405,7 @@ def submit(self, _=None): # for subsequent excited state calculations. builder.opt.orca.metadata.options.additional_retrieve_list = ["aiida.gbw"] - # Retrieve .nto files + # Retrieve .nto and .cube files builder.exc.orca.metadata.options.additional_retrieve_list = ["*.nto"] # Clean the remote directory by default, diff --git a/aiidalab_ispg/app/input_widgets.py b/aiidalab_ispg/app/input_widgets.py index 99211f9..a33d142 100644 --- a/aiidalab_ispg/app/input_widgets.py +++ b/aiidalab_ispg/app/input_widgets.py @@ -293,6 +293,33 @@ def reset(self): self.wigner_low_freq_thr.value = self._LOW_FREQ_THR_DEFAULT +class OrbitalSettings(ipw.VBox): + title = ipw.HTML( + """
+

Orbital Calculation

+
""" + ) + + _CALCULATE_ORBITALS_DEFAULT = True + + def __init__(self, **kwargs): + style = {"description_width": "initial"} + layout = ipw.Layout(max_width="250px") + + self.calculate_orbitals = ipw.Checkbox( + value=self._CALCULATE_ORBITALS_DEFAULT, + description="Calculate Natural Transition Orbitals", + indent=False, + layout=layout, + ) + + super().__init__( + children=[self.title, self.calculate_orbitals] + ) + + def reset(self): + self.charge.value = self._CALCULATE_ORBITALS_DEFAULT + class CodeSettings(ipw.VBox): codes_title = ipw.HTML( """
@@ -312,6 +339,7 @@ def __init__(self, **kwargs): default_calc_job_plugin="orca.orca", description="ORCA program", ) + super().__init__( children=[ self.codes_title, From b3bea7500556215000a8a2be07399f10a028301c Mon Sep 17 00:00:00 2001 From: AaronH-sys Date: Fri, 13 Mar 2026 23:19:07 +0000 Subject: [PATCH 4/9] Calculation of one specified orbital of s1 nto file --- aiidalab_ispg/app/atmospec_steps.py | 13 +++- aiidalab_ispg/app/input_widgets.py | 24 ++++++- aiidalab_ispg/workflows/atmospec.py | 101 +++++++++++++++++++++++++++- 3 files changed, 132 insertions(+), 6 deletions(-) diff --git a/aiidalab_ispg/app/atmospec_steps.py b/aiidalab_ispg/app/atmospec_steps.py index 9eb5073..9f5ae80 100644 --- a/aiidalab_ispg/app/atmospec_steps.py +++ b/aiidalab_ispg/app/atmospec_steps.py @@ -93,6 +93,8 @@ def __init__(self, **kwargs): self.resources_settings = ResourceSelectionWidget() self.codes_selector.orca.observe(self._update_state, "value") + + self.codes_selector.orca_plot.observe(self._update_state, "value") # Set defaults self._update_ui_from_parameters(DEFAULT_ATMOSPEC_PARAMETERS) @@ -131,6 +133,10 @@ def _validate_input_parameters(self) -> bool: if self.codes_selector.orca.value is None: return False return True + + if self.codes_selector.orca_plot.value is None: + return False + return True def _wigner_allowed(self): # Do not allow Wigner sampling for EOM-CCSD @@ -344,6 +350,9 @@ def submit(self, _=None): builder = AtmospecWorkChain.get_builder() builder.code = load_code(self.codes_selector.orca.value) + + builder.plot_code = load_code(self.codes_selector.orca_plot.value) + builder.structure = self.input_structure base_orca_parameters = self.build_base_orca_params(bp) @@ -381,7 +390,7 @@ def submit(self, _=None): builder.optimize = bp.optimize builder.opt.orca.parameters = gs_opt_parameters - builder.exc.orca.parameters = es_parameters + builder.exc.orca.parameters = es_parameters num_proc = self.resources_settings.num_mpi_tasks.value if num_proc > 1: @@ -406,7 +415,7 @@ def submit(self, _=None): builder.opt.orca.metadata.options.additional_retrieve_list = ["aiida.gbw"] # Retrieve .nto and .cube files - builder.exc.orca.metadata.options.additional_retrieve_list = ["*.nto"] + builder.exc.orca.metadata.options.additional_retrieve_list = ["*.nto", "*.cube"] # Clean the remote directory by default, # we're copying back the main output file and gbw file anyway. diff --git a/aiidalab_ispg/app/input_widgets.py b/aiidalab_ispg/app/input_widgets.py index a33d142..3d7204c 100644 --- a/aiidalab_ispg/app/input_widgets.py +++ b/aiidalab_ispg/app/input_widgets.py @@ -333,18 +333,25 @@ class CodeSettings(ipw.VBox): # In the order of priority, we will select the default ORCA code from these # First, we try to use SLURM on local machine, if available _DEFAULT_ORCA_CODES = ("orca@slurm", "orca@localhost") + _DEFAULT_ORCA_PLOT_CODES = ("orca_plot@localhost") def __init__(self, **kwargs): self.orca = ComputationalResourcesWidget( default_calc_job_plugin="orca.orca", description="ORCA program", ) - + + self.orca_plot = ComputationalResourcesWidget( + default_calc_job_plugin="orca.orca_plot", + description="ORCA plotting program", + ) + super().__init__( children=[ self.codes_title, # self.codes_help, self.orca, + self.orca_plot, ], **kwargs, ) @@ -369,6 +376,21 @@ def _set_default_codes(self, _=None): if not self.orca.value: print("WARNING: ORCA code has not been found locally") + + for code_label in self._DEFAULT_ORCA_PLOT_CODES: + try: + self.orca_plot.value = load_code(code_label).uuid + return + except (NotExistent, ValueError): + pass + except tl.TraitError: + # This can happen if one of the code/computers is not configured/enabled or hidden + # In practice, this happened to me locally when importing from production DB. + # https://github.com/ispg-group/aiidalab-ispg/issues/240 + pass + + if not self.orca_plot.value: + print("WARNING: ORCA_PLOT code has not been found locally") def reset(self): self._set_default_codes() diff --git a/aiidalab_ispg/workflows/atmospec.py b/aiidalab_ispg/workflows/atmospec.py index caab295..53ad497 100644 --- a/aiidalab_ispg/workflows/atmospec.py +++ b/aiidalab_ispg/workflows/atmospec.py @@ -9,6 +9,7 @@ if_, process_handler, run, + CalcJob ) from aiida.orm import ( Bool, @@ -20,6 +21,7 @@ StructureData, TrajectoryData, to_aiida_type, + FolderData, ) from aiida.plugins import CalculationFactory, DataFactory, WorkflowFactory @@ -33,11 +35,63 @@ structures_to_trajectory, ) +from aiida_shell import launch_shell_job + +import tempfile + Code = DataFactory("core.code.installed") OrcaCalculation = CalculationFactory("orca.orca") OrcaBaseWorkChain = WorkflowFactory("orca.base") +from aiida.common import CalcInfo, CodeInfo + + +class OrcaPlotCalculation(CalcJob): + + def _build_process_label(self) -> str: + return "NTO->CUBE workflow" + + @classmethod + def define(cls, spec): + super().define(spec) + + spec.input('code', valid_type=Code) + spec.input('nto_file', valid_type=SinglefileData) + spec.input('plot_input', valid_type=SinglefileData) + + spec.inputs['metadata']['options']['resources'].default = { + "num_machines": 1, + "num_mpiprocs_per_machine": 1, + } + + spec.inputs['metadata']['options']['withmpi'].default = False + + spec.output('retrieved') + + + def prepare_for_submission(self, folder): + + with self.inputs.nto_file.open(mode='rb') as handle: + folder.create_file_from_filelike(handle, 'input.nto') + + with self.inputs.plot_input.open(mode='rb') as handle: + folder.create_file_from_filelike(handle, 'input') + + codeinfo = CodeInfo() + codeinfo.code_uuid = self.inputs.code.uuid + codeinfo.cmdline_params = ['input.nto', '-i'] + codeinfo.stdin_name = 'input' + + calcinfo = CalcInfo() + calcinfo.codes_info = [codeinfo] + + # files to retrieve + calcinfo.retrieve_list = ['*.cube'] + + return calcinfo + + class OrcaExcitationWorkChain(OrcaBaseWorkChain): """A simple shim for UV/vis excitation in ORCA.""" @@ -47,20 +101,24 @@ def _build_process_label(self) -> str: @classmethod def define(cls, spec): super().define(spec) + spec.output( "excitations", valid_type=Dict, required=True, help="Excitation energies and oscillator strengths from a single-point excitations", - ) + ) + def extract_transitions_from_orca_output(self, orca_output_params): + return { "oscillator_strengths": orca_output_params["etoscs"], # Orca returns excited state energies in cm^-1 # Perhaps we should do the conversion here, # to make this less ORCA specific. "excitation_energies_cm": orca_output_params["etenergies"], + } @process_handler(exit_codes=ExitCode(0), priority=600) @@ -71,6 +129,7 @@ def add_excitation_output(self, calculation): ) self.out("excitations", Dict(transitions).store()) + class OrcaWignerSpectrumWorkChain(WorkChain): """Top level workchain for Nuclear Ensemble Approach UV/vis @@ -92,9 +151,14 @@ def define(cls, spec): namespace="exc", exclude=["orca.structure", "orca.code"], ) + spec.input("structure", valid_type=(StructureData, TrajectoryData)) + spec.input("code", valid_type=Code) - + + spec.input("plot_code", valid_type=Code) + + # Whether to perform geometry optimization spec.input( "optimize", @@ -121,6 +185,8 @@ def define(cls, spec): required=True, help="Output parameters from a single-point excitations", ) + + spec.expose_outputs( RobustOptimizationWorkChain, namespace="opt", @@ -142,6 +208,7 @@ def define(cls, spec): ), cls.excite, cls.inspect_excitation, + cls.nto_to_cube, if_(cls.should_run_wigner)( cls.wigner_sampling, cls.wigner_excite, @@ -182,7 +249,30 @@ def excite(self): calc_exc = self.submit(OrcaExcitationWorkChain, **inputs) calc_exc.label = "franck-condon-excitation" - return ToContext(calc_exc=calc_exc) + + return ToContext(calc_exc=calc_exc) + + def nto_to_cube(self): + + with self.ctx.calc_exc.outputs.retrieved.base.repository.open( + "aiida.s1.nto", "rb" + ) as handler: + nto_file = SinglefileData(handler) + + plot_input = SinglefileData.from_string( + "1\n1\n3\n0\n4\n120\n5\n7\n2\n4\n10\n11" + ) + + inputs = { + "code": self.inputs.plot_code, + "nto_file": nto_file, + "plot_input": plot_input, + } + + calc = self.submit(OrcaPlotCalculation, **inputs) + + return ToContext(calc_cube=calc) + def wigner_sampling(self): self.report(f"Generating {self.inputs.nwigner.value} Wigner geometries") @@ -257,6 +347,8 @@ def inspect_excitation(self): self.report("Single point excitation failed :-(") return self.exit_codes.ERROR_EXCITATION_FAILED self.out("franck_condon_excitations", calc.outputs.excitations) + + def inspect_wigner_excitation(self): """Check whether all wigner excitations succeeded""" @@ -315,7 +407,10 @@ def launch(self): ) for conf_id in self.inputs.structure.get_stepids(): inputs.structure = self.inputs.structure.get_step_structure(conf_id) + workflow = self.submit(OrcaWignerSpectrumWorkChain, **inputs) + + workflow.label = f"atmospec-conf-{conf_id}" self.to_context(confs=append_(workflow)) From bbf966ef02338f8a7f70bc71325e318f54fc45e5 Mon Sep 17 00:00:00 2001 From: Hugh Date: Wed, 22 Apr 2026 23:29:29 +0000 Subject: [PATCH 5/9] Added NTO parser, multiple NTO support and cubehandler support from the prototype model. --- aiidalab_ispg/nto/parsercalcfunction.py | 165 ++++++++++++++++++++++++ aiidalab_ispg/nto/subworkchains.py | 148 +++++++++++++++++++++ aiidalab_ispg/workflows/atmospec.py | 139 ++++++++++++-------- 3 files changed, 400 insertions(+), 52 deletions(-) create mode 100644 aiidalab_ispg/nto/parsercalcfunction.py create mode 100644 aiidalab_ispg/nto/subworkchains.py diff --git a/aiidalab_ispg/nto/parsercalcfunction.py b/aiidalab_ispg/nto/parsercalcfunction.py new file mode 100644 index 0000000..05c8ced --- /dev/null +++ b/aiidalab_ispg/nto/parsercalcfunction.py @@ -0,0 +1,165 @@ +from aiida.engine import calcfunction +from aiida.orm import Dict, Float, Str, Bool + +@calcfunction +def parse_orca_output(nto_folder, filename, threshold=0, states="all", nto=True): + # -*- coding: utf-8 -*- + ''' + # orca-st + ''' + + import sys #system + import re #regular expressions + + #remove comment in case you get an encoding error when saving the output to a file with ">" under windows + #alternatively replace 'cm⁻¹' with 'cm-1' in the table header (close to the end of script) + #alternatively you can configure the windows console with "set PYTHONIOENCODING=utf-8" before starting the script + #replace 'cm⁻¹' with 'cm-1' for pdf file conversion with pandoc in case of unicode issues + if hasattr(sys.stdout, 'reconfigure'): + sys.stdout.reconfigure(encoding='utf-8') + + #Convert from Aiida nodes to python datatypes if required. + if hasattr(filename, "value"): + filename = filename.value + if hasattr(threshold, "value"): + threshold = threshold.value + if hasattr(states, "value"): + states = states.value + if hasattr(nto, "value"): + nto = nto.value + + # global constants + found_uv_section = False #check for uv data in out + specstring_start = 'ABSORPTION SPECTRUM VIA TRANSITION ELECTRIC DIPOLE MOMENTS' #check orca.out from here + specstring_end = 'ABSORPTION SPECTRUM VIA TRANSITION VELOCITY DIPOLE MOMENTS' #stop reading orca.out from here + state_string_start = 'TD-DFT/TDA EXCITED STATES' #check for states from here + state_string_end = 'TD-DFT/TDA-EXCITATION SPECTRA' #stop reading states from here + nto_string_start ='NATURAL TRANSITION ORBITALS' #NTOs start here + found_nto = False #found NTOs in orca.out + #for ORCA 6 + state = 0 #ORCA 6 does not list the state in the table + orca6 = False #for including transitions in case of ORCA 6 on request + + #global lists + statelist = list() #mode + energylist = list() #energy cm-1 + intenslist = list() #fosc + nmlist = list() #wavelength + orblist = list() #list of orbital -> orbital transition + statedict = dict() #dictionary of states with all transitions + selected_statedict = dict() #dictionary of selected states with all transitions and or with those above the threshold + md_table = list() #table for the markdown output + #for ORCA 6 + #in ORCA 6 there is no state given in the list + translist = list() + #for NTO + nto_orblist=list() #list of orbital -> orbital transition for NTOs + nto_statedict=dict() #dictionary of states with all transitions for NTOs + + #check if threshold is between 0 and 100%, reset if not + if threshold: + if threshold > 100 or threshold < 0: + print("Warning! Threshold out of range. Reset to 0.") + threshold=0 + + #open a file + #check existence + try: + with nto_folder.open(filename) as input_file: + for line in input_file: + #start exctract text + if state_string_start in line: + for line in input_file: + #build the state - with several transitions dict: dict[state]=list(orb1 -> orb2, xx%), list(orb3 -> orb4, xx%) + #first the state + if re.search(r"STATE\s{1,}(\d{1,}):",line): + match_state=re.search(r"STATE\s{1,}(\d{1,}):",line) + #transitions here in orblist + elif re.search(r"\d{1,}[a,b]\s{1,}->\s{1,}\d{1,}[a,b]",line): + match_orbs=re.search(r"(\d{1,}[a,b]\s{1,}->\s{1,}\d{1,}[a,b])\s{1,}:\s{1,}(\d{1,}.\d{1,})",line) + orblist.append((match_orbs.group(1).replace(" "," "),match_orbs.group(2))) + #add orblist to statedict and clear orblist for next state + elif re.search(r"^\s*$",line): + if orblist: + statedict[match_state.group(1)] = orblist + orblist=[] + + #exit here + elif nto_string_start in line: + break + elif state_string_end in line: + break + + #same for NTOs + if re.search(r"FOR STATE\s{1,}(\d{1,})",line): + #found NTO in orca.out + found_nto = True + match_state_nto=re.search(r"FOR STATE\s{1,}(\d{1,})",line) + elif re.search(r"\d{1,}[a,b]\s{1,}->\s{1,}\d{1,}[a,b]",line): + match_orbs_nto=re.search(r"(\d{1,}[a,b]\s{1,}->\s{1,}\d{1,}[a,b])\s{1,}: n=\s{1,}(\d{1,}.\d{1,})",line) + nto_orblist.append((match_orbs_nto.group(1).replace(" ","").split("->"),match_orbs_nto.group(2))) + + #add orblist to statedict and clear orblist for next state + elif re.search(r"^\s*$",line): + if nto_orblist: + nto_statedict[match_state_nto.group(1)] = nto_orblist + nto_orblist=[] + + if specstring_start in line: + #found UV data in orca.out + found_uv_section=True + for line in input_file: + #stop exctract text + if specstring_end in line: + break + #only recognize lines that start with number + #split line into 4 lists state, energy, nm, intensities + #line should start with a number + if re.search(r"^\s{1,}\d+\s{1,}\d",line): + statelist.append(int(line.strip().split()[0])) + energylist.append(float(line.strip().split()[1])) + nmlist.append(float(line.strip().split()[2])) + intenslist.append(float(line.strip().split()[3])) + + #file not found -> exit here + except IOError: + print(f"'{filename}'" + " not found") + sys.exit(1) + + #no UV data in orca.out -> exit here + if found_uv_section == False: + print(f"'{specstring_start}'" + " not found in " + f"'{filename}'") + sys.exit(1) + + #no NTO data in orca.out -> exit here + if nto == True and found_nto == False: + print(f"'{nto_string_start}'" + " not found in " + f"'{filename}'") + sys.exit(1) + + #build selected_statedict from statedict with selected states + try: + if states == 'all': + if nto: + selected_statedict = nto_statedict + else: + selected_statedict = statedict + elif re.search(r"\d",states): + matchstateslist=(re.findall(r"\d+",states)) + for elements in matchstateslist: + if nto: + selected_statedict[elements]=nto_statedict[elements] + else: + selected_statedict[elements]=statedict[elements] + except KeyError: + print("Warning! State(s) not present. Exit.") + sys.exit(1) + + #remove transitions below threshold from selected_statedict + for elements in selected_statedict: + transition_list=[] + for v in selected_statedict[elements]: + if float(v[1])*100 >= threshold: + transition_list.append(v) + selected_statedict[elements]=transition_list + + return Dict(selected_statedict) diff --git a/aiidalab_ispg/nto/subworkchains.py b/aiidalab_ispg/nto/subworkchains.py new file mode 100644 index 0000000..020075f --- /dev/null +++ b/aiidalab_ispg/nto/subworkchains.py @@ -0,0 +1,148 @@ +from aiida.engine import WorkChain, calcfunction, ToContext, run_get_node +from aiida.orm import SinglefileData, StructureData, Dict, FolderData, Str, load_code +from aiida.plugins import CalculationFactory +from aiida_shell import launch_shell_job +import io +import os +from cubehandler import Cube + + +OrcaCalculation = CalculationFactory("orca.orca") +# Workchain for a basic ORCA calculation. +class OrcaWorkChain(WorkChain): + @classmethod + def define(cls, spec): + super().define(spec) + #spec.input("geometry", valid_type = SinglefileData, help="Test geometry (.xyz file)") + spec.input("parameters", valid_type = Dict, help = "Dictionary of orca parameters") + spec.output("nto_folder", valid_type=FolderData, help="ORCA output files.") + spec.outline( + cls.submit_orca_calc + ) + + def submit_orca_calc(self): + #Create a builder object for the orca plugin. + builder = OrcaCalculation.get_builder() + #Load orca + builder.code = load_code("orca@localhost") + #Construct a test molecule (acrolein) + structure = StructureData() + structure.append_atom(position=(-0.58780, -0.39670, -0.00030), symbols="C") + structure.append_atom(position=(-1.68290, 0.12550, -0.00000), symbols="O") + structure.append_atom(position=(0.61750, 0.43190, 0.00020), symbols="C") + structure.append_atom(position=(1.82210, -0.14250, -0.00010), symbols="C") + structure.append_atom(position=(-0.50290, -1.47330, 0.00350), symbols="H") + structure.append_atom(position=(0.53260, 1.50860, 0.00090), symbols="H") + structure.append_atom(position=(1.90700, -1.21920, -0.00080), symbols="H") + structure.append_atom(position=(2.71210, 0.46930, 0.00030), symbols="H") + structure.pbc = (False, False, False) + #Pass structure to the builder object + builder.structure = structure + #set parameters + builder.parameters = self.inputs.parameters + + #adding metadata. + builder.metadata.options = { + "additional_retrieve_list": ["*.nto", "aiida.out"], + "resources": {'num_machines': 1, 'num_mpiprocs_per_machine': 1}, + } + #Run ORCA (requires RabbitMQ, not configured by default on the "presto" profile) + #Also I cannot get it to work at all at the moment so using run_get_node instead. + # process = self.submit(builder) + # return ToContext(calc=process) + + #Run without RabbitMQ + results, node = run_get_node(builder) + #Return the output folder. + self.out("nto_folder", results["retrieved"]) + + + +#WorkChain to convert to and compress .cube files. +class NTOProcessingWorkChain(WorkChain): + @classmethod + def define(cls, spec): + super().define(spec) + spec.input("nto_folder", valid_type=FolderData, help="Folder containing the ORCA output from OrcaWorkChain.") + spec.input("s", valid_type=Str, help="Desired excitation.") + spec.input("mo", valid_type=Str, help="Desired orbital number.") + spec.output("compressed_cube", valid_type=SinglefileData, help="Compressed cube file") + spec.outline( + cls.nto_to_cube, + cls.cube_compress + ) + + def nto_to_cube(self): + #load orca_plot + orca_plot = load_code("orca_plot@localhost") + #Define folder with NTOs + folder = self.inputs.nto_folder + #Define electronic transition. + s=(self.inputs.s).value + #Define the specific molecular orbital to plot. + mo=(self.inputs.mo).value + #Create SinglefileData node with orca_plot options (wrapped in a temporary BytesIO file). + plot_options_node = SinglefileData(file=io.BytesIO(("1\n1\n3\n0\n5\n7\n2\n"+mo+"\n10\n11\n").encode("utf-8")), filename="plot_input.txt") + #Define NTO filename. + nto_filename = "aiida.s"+s+".nto" + #Create SinglefileData node with NTO data. + with folder.open(nto_filename, mode="rb") as nto_file: + nto_data_node = SinglefileData(file=nto_file, filename=nto_filename) + + + #Run orca_plot + results, node = launch_shell_job( + "orca_plot", + arguments=["{nto_data}", "-i"], + nodes={"nto_data": nto_data_node, "plot_options": plot_options_node}, + metadata={"options": {"filename_stdin": plot_options_node.filename}}, + outputs=["*.cube"] + ) + #Extract the cube file from the results. + self.ctx.uncompressed_cube = results["aiida_s"+(s)+"_mo"+(mo)+"a_cube"] + + def cube_compress(self): + #Defining the original cube file. + orig_file = self.ctx.uncompressed_cube + + #calcfunction required to create the new cube file "In order to preserve data provenance" apparently. + compressed_node = calc_compression(orig_file) + + + #Output the result + self.out("compressed_cube", compressed_node) + + +@calcfunction +def calc_compression(orig_file): + #Cubehandler requires a local file to read from, so we create a temporary file (bit of a bodge). + temp_in = "temp.cube" + #Opening the original cube file. + with orig_file.open(mode="rb") as orig_handle: + with open(temp_in, "wb") as temp_handle: + temp_handle.write(orig_handle.read()) + + #Reading the original cube data. + orig_cube = Cube.from_file(temp_in) + + #Compress the file + orig_cube.reduce_data_density_slicing(points_per_angstrom=2) + + #Create another temporary file to export the compressed file. + temp_out = "temp2.cube" + orig_cube.write_cube_file(temp_out, low_precision=False) + + #Read the temporary output file back in as a SinglefileData node. + with open(temp_out, "rb") as temp2_handle: + compressed_node = SinglefileData(temp2_handle, filename="compressed.cube") + + #Clean up temp files. + if os.path.exists(temp_in): + os.remove(temp_in) + if os.path.exists(temp_out): + os.remove(temp_out) + return(compressed_node) + + + + \ No newline at end of file diff --git a/aiidalab_ispg/workflows/atmospec.py b/aiidalab_ispg/workflows/atmospec.py index 53ad497..d8def08 100644 --- a/aiidalab_ispg/workflows/atmospec.py +++ b/aiidalab_ispg/workflows/atmospec.py @@ -46,50 +46,53 @@ from aiida.common import CalcInfo, CodeInfo +from ..nto.parsercalcfunction import parse_orca_output -class OrcaPlotCalculation(CalcJob): +from ..nto.subworkchains import NTOProcessingWorkChain + +# class OrcaPlotCalculation(CalcJob): - def _build_process_label(self) -> str: - return "NTO->CUBE workflow" +# def _build_process_label(self) -> str: +# return "NTO->CUBE workflow" - @classmethod - def define(cls, spec): - super().define(spec) +# @classmethod +# def define(cls, spec): +# super().define(spec) - spec.input('code', valid_type=Code) - spec.input('nto_file', valid_type=SinglefileData) - spec.input('plot_input', valid_type=SinglefileData) +# spec.input('code', valid_type=Code) +# spec.input('nto_file', valid_type=SinglefileData) +# spec.input('plot_input', valid_type=SinglefileData) - spec.inputs['metadata']['options']['resources'].default = { - "num_machines": 1, - "num_mpiprocs_per_machine": 1, - } +# spec.inputs['metadata']['options']['resources'].default = { +# "num_machines": 1, +# "num_mpiprocs_per_machine": 1, +# } - spec.inputs['metadata']['options']['withmpi'].default = False +# spec.inputs['metadata']['options']['withmpi'].default = False - spec.output('retrieved') +# spec.output('retrieved') - def prepare_for_submission(self, folder): +# def prepare_for_submission(self, folder): - with self.inputs.nto_file.open(mode='rb') as handle: - folder.create_file_from_filelike(handle, 'input.nto') +# with self.inputs.nto_file.open(mode='rb') as handle: +# folder.create_file_from_filelike(handle, 'input.nto') - with self.inputs.plot_input.open(mode='rb') as handle: - folder.create_file_from_filelike(handle, 'input') +# with self.inputs.plot_input.open(mode='rb') as handle: +# folder.create_file_from_filelike(handle, 'input') - codeinfo = CodeInfo() - codeinfo.code_uuid = self.inputs.code.uuid - codeinfo.cmdline_params = ['input.nto', '-i'] - codeinfo.stdin_name = 'input' +# codeinfo = CodeInfo() +# codeinfo.code_uuid = self.inputs.code.uuid +# codeinfo.cmdline_params = ['input.nto', '-i'] +# codeinfo.stdin_name = 'input' - calcinfo = CalcInfo() - calcinfo.codes_info = [codeinfo] +# calcinfo = CalcInfo() +# calcinfo.codes_info = [codeinfo] - # files to retrieve - calcinfo.retrieve_list = ['*.cube'] +# # files to retrieve +# calcinfo.retrieve_list = ['*.cube'] - return calcinfo +# return calcinfo class OrcaExcitationWorkChain(OrcaBaseWorkChain): @@ -208,7 +211,9 @@ def define(cls, spec): ), cls.excite, cls.inspect_excitation, - cls.nto_to_cube, + # cls.nto_to_cube, + cls.nto_parser, + cls.nto_convert, if_(cls.should_run_wigner)( cls.wigner_sampling, cls.wigner_excite, @@ -249,30 +254,60 @@ def excite(self): calc_exc = self.submit(OrcaExcitationWorkChain, **inputs) calc_exc.label = "franck-condon-excitation" - return ToContext(calc_exc=calc_exc) - def nto_to_cube(self): - - with self.ctx.calc_exc.outputs.retrieved.base.repository.open( - "aiida.s1.nto", "rb" - ) as handler: - nto_file = SinglefileData(handler) - - plot_input = SinglefileData.from_string( - "1\n1\n3\n0\n4\n120\n5\n7\n2\n4\n10\n11" - ) - - inputs = { - "code": self.inputs.plot_code, - "nto_file": nto_file, - "plot_input": plot_input, - } - - calc = self.submit(OrcaPlotCalculation, **inputs) - - return ToContext(calc_cube=calc) - + # def nto_to_cube(self): + + # # with self.ctx.calc_exc.outputs.retrieved.base.repository.open( + # # "aiida.s1.nto", "rb" + # # ) as handler: + # # nto_file = SinglefileData(handler) + + # # plot_input = SinglefileData.from_string( + # # "1\n1\n3\n0\n4\n120\n5\n7\n2\n4\n10\n11" + # # ) + + # # inputs = { + # # "code": self.inputs.plot_code, + # # "nto_file": nto_file, + # # "plot_input": plot_input, + # # } + + # # calc = self.submit(OrcaPlotCalculation, **inputs) + + # # return ToContext(calc_cube=calc) + def nto_parser(self): + self.ctx.relevant_dict = parse_orca_output(self.ctx.calc_exc.outputs.retrieved, "aiida.out", 5.0) + #self.out("transition_info", self.ctx.relevant_dict) + + def nto_convert(self): + builder = NTOProcessingWorkChain.get_builder() + builder.nto_folder = self.ctx.calc_exc.outputs.retrieved + #Returns a folder containing all of the compressed cube files. + cube_folder = FolderData() + #Create a list of tuples containing relevant mo data for each excitation. + relevant_items = list(self.ctx.relevant_dict.items()) + #Iterating through the list. + for excitation in relevant_items: + #Set excitation. + s=excitation[0] + builder.s = s + for electron_hole_pair in excitation[1]: + + for moa in electron_hole_pair[0]: + #Set specific mo. + mo = moa[:-1] + builder.mo = mo + #Run not ideal here but fine for the moment. + results = run(NTOProcessingWorkChain, builder) + for label, value in results.items(): + print(value) + with value.open(mode="rb") as file: + cube_folder.put_object_from_filelike(file, path=("s"+s+"."+mo)) + self.ctx.foldertest = cube_folder + cube_folder.store() + #Output where on the database the compressed files are stored. + self.report(f"Cube folder PK: {cube_folder.pk}") def wigner_sampling(self): self.report(f"Generating {self.inputs.nwigner.value} Wigner geometries") From 358718bee340981457728f37cdaa85655c5e5759 Mon Sep 17 00:00:00 2001 From: Hugh Date: Fri, 24 Apr 2026 18:17:22 +0000 Subject: [PATCH 6/9] The workchain to create and compress cube files is now run through the Aiida daemon. --- aiidalab_ispg/workflows/atmospec.py | 55 ++-- notebooks/atmospec.ipynb | 493 +++++++++++++++++++++++++++- 2 files changed, 516 insertions(+), 32 deletions(-) diff --git a/aiidalab_ispg/workflows/atmospec.py b/aiidalab_ispg/workflows/atmospec.py index d8def08..2f18291 100644 --- a/aiidalab_ispg/workflows/atmospec.py +++ b/aiidalab_ispg/workflows/atmospec.py @@ -211,9 +211,8 @@ def define(cls, spec): ), cls.excite, cls.inspect_excitation, - # cls.nto_to_cube, - cls.nto_parser, - cls.nto_convert, + cls.nto_calc, + cls.nto_collect, if_(cls.should_run_wigner)( cls.wigner_sampling, cls.wigner_excite, @@ -276,35 +275,51 @@ def excite(self): # # calc = self.submit(OrcaPlotCalculation, **inputs) # # return ToContext(calc_cube=calc) - def nto_parser(self): - self.ctx.relevant_dict = parse_orca_output(self.ctx.calc_exc.outputs.retrieved, "aiida.out", 5.0) - #self.out("transition_info", self.ctx.relevant_dict) - - def nto_convert(self): - builder = NTOProcessingWorkChain.get_builder() - builder.nto_folder = self.ctx.calc_exc.outputs.retrieved + def nto_calc(self): + #Check ORCA output for NTOs. + relevant_dict = parse_orca_output(self.ctx.calc_exc.outputs.retrieved, "aiida.out", 5.0) + #This dictionary is also used by the visualiser to create the dropdown menus (not implemented yet). + #self.out("transition_info", relevant_dict) + #Dictionary to store the NTOProcessingWorkChain PKs + nto_processes = {} #Returns a folder containing all of the compressed cube files. cube_folder = FolderData() #Create a list of tuples containing relevant mo data for each excitation. - relevant_items = list(self.ctx.relevant_dict.items()) + relevant_items = list(relevant_dict.items()) #Iterating through the list. for excitation in relevant_items: #Set excitation. s=excitation[0] - builder.s = s for electron_hole_pair in excitation[1]: - for moa in electron_hole_pair[0]: + builder = NTOProcessingWorkChain.get_builder() + builder.nto_folder = self.ctx.calc_exc.outputs.retrieved + builder.s = s #Set specific mo. mo = moa[:-1] builder.mo = mo - #Run not ideal here but fine for the moment. - results = run(NTOProcessingWorkChain, builder) - for label, value in results.items(): - print(value) - with value.open(mode="rb") as file: - cube_folder.put_object_from_filelike(file, path=("s"+s+"."+mo)) - self.ctx.foldertest = cube_folder + #Submit the workchain. + results = self.submit(NTOProcessingWorkChain, builder) + #Add the PK to the dictionary. + nto_processes["s"+s+"_"+mo] = results + #save the dictionary keys for later use. + self.ctx.nto_keys = list(nto_processes.keys()) + #Move to next step when all ntos are processed. + return self.to_context(**nto_processes) + + + + + + def nto_collect(self): + #Create folder to contain cubes + cube_folder = FolderData() + #Iterate through the outputs of the nto processing workchain. + for key in self.ctx.nto_keys: + node = self.ctx.get(key) + if "compressed_cube" in node.outputs: + with node.outputs.compressed_cube.open(mode="rb") as file: + cube_folder.put_object_from_filelike(file, path=(key)) cube_folder.store() #Output where on the database the compressed files are stored. self.report(f"Cube folder PK: {cube_folder.pk}") diff --git a/notebooks/atmospec.ipynb b/notebooks/atmospec.ipynb index 67e2b95..ef6e5b9 100644 --- a/notebooks/atmospec.ipynb +++ b/notebooks/atmospec.ipynb @@ -2,11 +2,44 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "IPython.OutputArea.prototype._should_scroll = function(lines) {\n", + " return false;\n", + "}\n", + "// Trying to fix Mol viewer inside accordion box,\n", + "// padding 15px is the default, reducing it did not help\n", + "var styles = `\n", + " .p-Collapse-contents { \n", + " padding: 15px;\n", + " }\n", + "`\n", + "var styleSheet = document.createElement(\"style\")\n", + "styleSheet.innerText = styles\n", + "\n", + "document.head.appendChild(styleSheet)\n", + "\n", + "document.title = 'AiiDAlab ATMOSPEC app'\n", + "if (document.getElementById('appmode-busy')) {\n", + " window.onbeforeunload = function() {return}\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "%%javascript\n", + "\n", "IPython.OutputArea.prototype._should_scroll = function(lines) {\n", " return false;\n", "}\n", @@ -30,9 +63,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "%%html\n", "\n", @@ -45,9 +96,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "78ced57448754b74ba3a373d5da19b13", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value=\"Loaded AiiDA profile 'default'
Hold on to your hats, ATMOSPEC will be here shortly 🚀\")" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import ipywidgets as ipw\n", "\n", @@ -62,9 +128,295 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " const force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + "const JS_MIME_TYPE = 'application/javascript';\n", + " const HTML_MIME_TYPE = 'text/html';\n", + " const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " const CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " const script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " const cell = handle.cell;\n", + "\n", + " const id = cell.output_area._bokeh_element_id;\n", + " const server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd_clean, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " const id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd_destroy);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " const output_area = handle.output_area;\n", + " const output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " const bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " const script_attrs = bk_div.children[0].attributes;\n", + " for (let i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " const toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " const events = require('base/js/events');\n", + " const OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " const NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " const el = document.getElementById(null);\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error(url) {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (let i = 0; i < css_urls.length; i++) {\n", + " const url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error.bind(null, url);\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " for (let i = 0; i < js_urls.length; i++) {\n", + " const url = js_urls[i];\n", + " const element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error.bind(null, url);\n", + " element.async = false;\n", + " element.src = url;\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\"];\n", + " const css_urls = [];\n", + "\n", + " const inline_js = [ function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + "function(Bokeh) {\n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " if (root.Bokeh !== undefined || force === true) {\n", + " for (let i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + "} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " const cell = $(document.getElementById(null)).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n const NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n const el = document.getElementById(null);\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\"];\n const css_urls = [];\n\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {\n }\n ];\n\n function run_inline_js() {\n if (root.Bokeh !== undefined || force === true) {\n for (let i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n const cell = $(document.getElementById(null)).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Activate Bokeh\n", "\n", @@ -78,9 +430,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + " var style = document.createElement('style');\n", + " style.type = 'text/css';\n", + " style.innerHTML = ``;\n", + " document.head.appendChild(style);\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "88e1481fda7c476485dc13408ae92b96", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import os\n", "from importlib.resources import files\n", @@ -102,9 +484,89 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5d0e95f01cb140cbb70101aeff22c4d5", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='\\n