def get_concentration_functions(composition_table_dict):
meta = composition_table_dict["meta"]
composition_table = Table.from_dict(composition_table_dict["data"])
elements = [col for col in composition_table.columns if col not in meta]
x = composition_table["X"].values
y = composition_table["Y"].values
cats = composition_table["X"].unique()
concentration, conc, d, y_c, functions = {}, {}, {}, {}, RecursiveDict()
for el in elements:
concentration[el] = to_numeric(composition_table[el].values) / 100.0
conc[el], d[el], y_c[el] = {}, {}, {}
if meta["X"] == "category":
for i in cats:
k = "{:06.2f}".format(float(i))
y_c[el][k] = to_numeric(y[where(x == i)])
conc[el][k] = to_numeric(concentration[el][where(x == i)])
d[el][k] = interp1d(y_c[el][k], conc[el][k])
functions[el] = lambda a, b, el=el: d[el][a](b)
else:
functions[el] = interp2d(float(x), float(y), concentration[el])
return functions
def get_concentration_functions(composition_table_dict):
meta = composition_table_dict['meta']
composition_table = Table.from_dict(composition_table_dict['data'])
elements = [col for col in composition_table.columns if col not in meta]
x = composition_table["X"].values
y = composition_table["Y"].values
cats = composition_table["X"].unique()
concentration, conc, d, y_c, functions = {}, {}, {}, {}, RecursiveDict()
for el in elements:
concentration[el] = to_numeric(composition_table[el].values)/100.
conc[el], d[el], y_c[el] = {}, {}, {}
if meta['X'] == 'category':
for i in cats:
k = '{:06.2f}'.format(float(i))
y_c[el][k] = to_numeric(y[where(x==i)])
conc[el][k] = to_numeric(concentration[el][where(x==i)])
d[el][k] = interp1d(y_c[el][k], conc[el][k])
functions[el] = lambda a, b, el=el: d[el][a](b)
else:
functions[el] = interp2d(float(x), float(y), concentration[el])
return functions
def iterate(self, nested_dict=None):
"""http://stackoverflow.com/questions/10756427/loop-through-all-nested-dictionary-values"""
from mpcontribs.io.core.components import Table
from pymatgen import Structure
d = self if nested_dict is None else nested_dict
if nested_dict is None:
self.level = 0
for key in list(d.keys()):
value = d[key]
if isinstance(value, _Mapping):
if value.get('@class') == 'Structure':
yield key, Structure.from_dict(value)
continue
yield (self.level, key), None
if value.get('@class') == 'Table':
yield key, Table.from_dict(value)
continue
self.level += 1
for inner_key, inner_value in self.iterate(nested_dict=value):
yield inner_key, inner_value
self.level -= 1
elif isinstance(value, list) and isinstance(value[0], dict):
# index (from archieml parser)
table = ''
for row_dct in value:
table = '\n'.join([table, row_dct['value']])
yield '_'.join([mp_level01_titles[1], key]), table
else:
yield (self.level, key), value
def index(request, cid=None, db_type=None, mdb=None):
try:
response = None
if request.method == 'GET':
axes, dopings = ['<S>', '<σ>', '<S²σ>'], ['n', 'p']
projection = dict(
('content.data.{}'.format(k[1:-1]), 1) for k in axes)
projection.update({'identifier': 1})
docs = mdb.contrib_ad.query_contributions(
{'project': 'carrier_transport'}, projection=projection)
response = {'text': []}
response.update(dict((k, []) for k in axes))
for doc in docs:
d = doc['content']['data']
for doping in dopings:
for idx, k in enumerate(axes):
kk = k[1:-1]
if kk in d and doping in d[kk]:
value = d[kk][doping]['<ε>']
value = float(value.split()[0])
if idx == 2:
value = math.log10(value)
response['text'].append(doc['identifier'])
response[k].append(value)
elif request.method == 'POST':
name = json.loads(request.body)['name']
names = name.split('##')
key, subkey = names[0][1:-1], names[1][0]
table_name = '{}({})'.format(key, subkey)
doc = mdb.contrib_ad.query_contributions(
{'_id': cid},
projection={
'_id': 0,
'content.{}'.format(table_name): 1,
'content.data.{}.{}'.format(key, subkey): 1
})[0]
table = doc['content'].get(table_name)
if table:
table = Table.from_dict(table)
x = [col.split()[0] for col in table.columns[1:]]
y = list(table[table.columns[0]])
z = table[table.columns[1:]].values.tolist()
if not table_name.startswith('S'):
z = [[math.log10(float(c)) for c in r] for r in z]
title = ' '.join([table_name, names[1].split()[-1]])
response = {
'x': x,
'y': y,
'z': z,
'type': 'heatmap',
'colorbar': {
'title': title
}
}
except Exception as ex:
raise ValueError('"REST Error: "{}"'.format(str(ex)))
return {"valid_response": True, 'response': response}
def index(request, cid=None, db_type=None, mdb=None):
try:
response = None
if request.method == 'GET':
axes, dopings = ['<S>', '<σ>', '<S²σ>'], ['n', 'p']
projection = dict(('content.data.{}'.format(k[1:-1]), 1) for k in axes)
projection.update({'identifier': 1})
docs = mdb.contrib_ad.query_contributions(
{'project': 'carrier_transport'}, projection=projection
)
response = {'text': []}
response.update(dict((k, []) for k in axes))
for doc in docs:
d = doc['content']['data']
for doping in dopings:
for idx, k in enumerate(axes):
kk = k[1:-1]
if kk in d and doping in d[kk]:
value = d[kk][doping]['<ε>']
value = float(value.split()[0])
if idx == 2:
value = math.log10(value)
response['text'].append(doc['identifier'])
response[k].append(value)
elif request.method == 'POST':
name = json.loads(request.body)['name']
names = name.split('##')
key, subkey = names[0][1:-1], names[1][0]
table_name = '{}({})'.format(key, subkey)
doc = mdb.contrib_ad.query_contributions(
{'_id': cid}, projection={
'_id': 0, 'content.{}'.format(table_name): 1,
'content.data.{}.{}'.format(key, subkey): 1
}
)[0]
table = doc['content'].get(table_name)
if table:
table = Table.from_dict(table)
x = [col.split()[0] for col in table.columns[1:]]
y = list(table[table.columns[0]])
z = table[table.columns[1:]].values.tolist()
if not table_name.startswith('S'):
z = [[math.log10(float(c)) for c in r] for r in z]
title = ' '.join([table_name, names[1].split()[-1]])
response = {'x': x, 'y': y, 'z': z, 'type': 'heatmap', 'colorbar': {'title': title}}
except Exception as ex:
raise ValueError('"REST Error: "{}"'.format(str(ex)))
return {"valid_response": True, 'response': response}