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* Fix minor issues that I noticed when going through the QE section * Remove the Fermi level align with zero example, which uses bands.show_mpl(), but this doesn't work from the AiiDAlab machines since we don't have X forwarding. * Replace the query demo script by the one from the intro week, which shows off the high-throughput elements more.
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docs/pages/2020_BIGMAP/sections/include/images/demo_query.png
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docs/pages/2020_BIGMAP/sections/include/snippets/demo_query.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,44 +1,94 @@ | ||
| from aiida.orm import Group | ||
| from aiida.plugins import DataFactory, CalculationFactory | ||
| from IPython.display import Image | ||
| from datetime import datetime, timedelta | ||
| import numpy as np | ||
| from matplotlib import gridspec, pyplot as plt | ||
|
|
||
| PwCalculation = CalculationFactory('quantumespresso.pw') | ||
| StructureData = DataFactory('structure') | ||
| KpointsData = DataFactory('array.kpoints') | ||
| Dict = DataFactory('dict') | ||
| UpfData = DataFactory('upf') | ||
|
|
||
| import matplotlib.pyplot as plt | ||
| def plot_results(query_res): | ||
| """ | ||
| :param query_res: The result of an instance of the QueryBuilder | ||
| """ | ||
| smearing_unit_set,magnetization_unit_set,pseudo_family_set = set(), set(), set() | ||
| # Storing results: | ||
| results_dict = {} | ||
| for pseudo_family, formula, smearing, smearing_units, mag, mag_units in query_res: | ||
| if formula not in results_dict: | ||
| results_dict[formula] = {} | ||
| # Storing the results: | ||
| results_dict[formula][pseudo_family] = (smearing, mag) | ||
| # Adding to the unit set: | ||
| smearing_unit_set.add(smearing_units) | ||
| magnetization_unit_set.add(mag_units) | ||
| pseudo_family_set.add(pseudo_family) | ||
|
|
||
| qb = QueryBuilder().append( | ||
| Group, filters={'label': {'like': 'tutorial_%'}}, tag='group', | ||
| project='label' | ||
| ).append( | ||
| PwCalculation, with_group='group', tag='pw' | ||
| ).append( | ||
| StructureData, with_outgoing='pw', | ||
| project='extras.formula' | ||
| ).append( | ||
| Dict, with_incoming='pw', filters={'attributes.absolute_magnetization': {'>': 0.0}}, | ||
| project='attributes.absolute_magnetization' | ||
| ) | ||
| # Sorting by formula: | ||
| sorted_results = sorted(results_dict.items()) | ||
| formula_list = next(zip(*sorted_results)) | ||
| nr_of_results = len(formula_list) | ||
|
|
||
| results_dict = dict() | ||
| formulas = set() | ||
| # Checks that I have not more than 3 pseudo families. | ||
| # If more are needed, define more colors | ||
| #pseudo_list = list(pseudo_family_set) | ||
| if len(pseudo_family_set) > 3: | ||
| raise Exception('I was expecting 3 or less pseudo families') | ||
|
|
||
| for group_label, formula, abs_magnetization in qb.iterall(): | ||
| functional = group_label.split('_')[1].upper() | ||
| results_dict.setdefault(functional, {}) | ||
| results_dict[functional][formula] = abs_magnetization | ||
| formulas.add(formula) | ||
| colors = ['b', 'r', 'g'] | ||
|
|
||
| formulas = list(formulas) | ||
| # Plotting: | ||
| plt.clf() | ||
| fig=plt.figure(figsize=(16, 9), facecolor='w', edgecolor=None) | ||
| gs = gridspec.GridSpec(2,1, hspace=0.01, left=0.1, right=0.94) | ||
|
|
||
| for functional, results in results_dict.items(): | ||
| # Defining barwidth | ||
| barwidth = 1. / (len(pseudo_family_set)+1) | ||
| offset = [-0.5+(0.5+n)*barwidth for n in range(len(pseudo_family_set))] | ||
| # Axing labels with units: | ||
| yaxis = ("Smearing energy [{}]".format(smearing_unit_set.pop()), | ||
| "Total magnetization [{}]".format(magnetization_unit_set.pop())) | ||
| # If more than one unit was specified, I will exit: | ||
| if smearing_unit_set: | ||
| raise ValueError('Found different units for smearing') | ||
| if magnetization_unit_set: | ||
| raise ValueError('Found different units for magnetization') | ||
|
|
||
| abs_magnetizations = [results[formula] for formula in formulas] | ||
| # Making two plots, the top one for the smearing, the bottom one for the magnetization | ||
| for index in range(2): | ||
| ax=fig.add_subplot(gs[index]) | ||
| for i,pseudo_family in enumerate(pseudo_family_set): | ||
| X = np.arange(nr_of_results)+offset[i] | ||
| Y = np.array([thisres[1][pseudo_family][index] for thisres in sorted_results]) | ||
| ax.bar(X, Y, width=0.2, facecolor=colors[i], edgecolor=colors[i], label=pseudo_family) | ||
| ax.set_ylabel(yaxis[index], fontsize=14, labelpad=15*index+5) | ||
| ax.set_xlim(-0.5, nr_of_results-0.5) | ||
| ax.set_xticks(np.arange(nr_of_results)) | ||
| if index == 0: | ||
| plt.setp(ax.get_yticklabels()[0], visible=False) | ||
| ax.xaxis.tick_top() | ||
| ax.legend(loc=3, prop={'size': 18}) | ||
| else: | ||
| plt.setp(ax.get_yticklabels()[-1], visible=False) | ||
| for i in range(0, nr_of_results, 2): | ||
| ax.axvspan(i-0.5, i+0.5, facecolor='y', alpha=0.2) | ||
| ax.set_xticklabels(list(formula_list),rotation=90, size=14, ha='center') | ||
| plt.savefig('demo_query.pdf') | ||
|
|
||
| plt.plot(abs_magnetizations, 's') | ||
| plt.xticks(range(len(formulas)), formulas, rotation=90) | ||
| plt.ylabel('Magnetization [Bohrmag / cell]') | ||
|
|
||
| plt.legend(results_dict.keys()) | ||
| plt.tight_layout() | ||
| plt.savefig('demo_query.pdf') | ||
| qb = QueryBuilder().append( | ||
| Group, filters={'label':{'like':'tutorial_%'}}, project='label', tag='group' | ||
| ).append( | ||
| PwCalculation, tag='calculation', with_group='group' | ||
| ).append( | ||
| StructureData, project=['extras.formula'], tag='structure', with_outgoing='calculation' | ||
| ).append( | ||
| Dict, tag='results', | ||
| project=['attributes.energy_smearing', 'attributes.energy_smearing_units', | ||
| 'attributes.total_magnetization', 'attributes.total_magnetization_units', | ||
| ], with_incoming='calculation' | ||
| ) | ||
|
|
||
| plot_results(qb.all()) |
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