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import numpy as np
from sympathy.api import node
from sympathy.api.exceptions import SyDataError
from sympathy.api.nodeconfig import Port, Ports, Tag, Tags, adjust
def _get_single_col_editor():
return node.Util.combo_editor('', filter=True, edit=True)
[docs]class IndexTable(node.Node):
name = 'Index table'
description = (
'Uses index-table to perform row indexation from value-table.\n'
'No other datatypes than integer or boolean are allowed in the index '
'column')
author = 'Mathias Broxvall'
version = '0.1'
icon = 'lookup.svg'
nodeid = 'org.sysess.sympathy.data.table.indextable'
tags = Tags(Tag.DataProcessing.TransformStructure)
inputs = Ports([
Port.Table('Value table', name='value'),
Port.Table('Index table', name='index')
])
outputs = Ports([
Port.Table('Result table', name='out')
])
editor = _get_single_col_editor()
parameters = node.parameters()
parameters.set_list(
'index column', label='Select indexing column',
description='Select column used for indexing.',
value=[], editor=editor)
parameters.set_boolean(
'at_one', label='Start at one',
description='Start indexing at one, otherwise at zero',
value=False)
parameters.set_list(
'operation', label='Operation',
list=['Include', 'Exclude'], value=[0],
description='If to include or exclude rows',
editor=node.Util.combo_editor().value())
def update_parameters(self, old_params):
param = 'index column'
if param in old_params:
old_params[param].editor = _get_single_col_editor()
def execute(self, node_context):
index_tbl = node_context.input['index']
value_tbl = node_context.input['value']
out_tbl = node_context.output['out']
at_one = node_context.parameters['at_one'].value
exclude = node_context.parameters['operation'].selected == 'Exclude'
index_col = node_context.parameters['index column'].selected
if index_col:
indices = index_tbl[index_col]
else:
indices = index_tbl[index_tbl.column_names()[0]]
if indices.dtype.kind == 'i':
try:
fail = at_one and np.min(np.ma.compressed(indices)) < 1
except ValueError:
fail = False
if fail:
raise SyDataError('Start at one requires integer column '
'with values >= 1.')
indices = indices - at_one
elif at_one:
raise SyDataError('Invalid datatype {} in index column. '
'Start at one requires integer column.'
.format(indices.dtype))
if indices.dtype.kind not in ['b', 'i']:
raise SyDataError('Invalid datatype {} in index column'
.format(indices.dtype))
for col in value_tbl.cols():
if exclude:
mask = np.ones(col.data.shape[0], dtype=bool)
mask[indices] = False
out_tbl.set_column_from_array(col.name, col.data[mask])
else:
out_tbl.set_column_from_array(col.name, col.data[indices])
def adjust_parameters(self, node_context):
adjust(node_context.parameters['index column'],
node_context.input['index'])
[docs]class CreateIndexTable(node.Node):
"""
Create an index column for table data.
The name of the resulting index column depends on the *name* parameter and
its values are computed depending on the *method* used and the *columns*
selected.
"""
name = 'Create Index Table'
description = 'Create an index column for table data'
icon = 'lookup.svg'
nodeid = 'org.sysess.sympathy.data.table.createindextable'
tags = Tags(Tag.DataProcessing.Index)
inputs = Ports([
Port.Table('Input table', name='input'),
])
outputs = Ports([
Port.Table('Output table', name='output')
])
_enumerate_rows, _enumerate_unique = _options = [
'Enumerate rows', 'Enumerate unique rows']
parameters = node.parameters()
parameters.set_string(
'method', label='Select index creation method',
description='Select method used for index creation.',
value=_enumerate_rows,
editor=node.Editors.combo_editor(options=_options))
parameters.set_list(
'columns', label='Select columns',
description='Select columns used for building the index.',
value=[], editor=node.Editors.multilist_editor(edit=True))
parameters.set_string(
'name', label='Name of index column',
description='Select name for index column.',
value='index')
controllers = node.controller(
when=node.field('method', 'value', value=_enumerate_rows),
action=node.field('columns', 'disabled'))
def execute(self, node_context):
input_ = node_context.input['input']
output = node_context.output['output']
output.source(input_)
method = node_context.parameters['method'].value
name = node_context.parameters['name'].value
method = node_context.parameters['method'].value
if method == self._enumerate_rows:
output[name] = np.arange(input_.number_of_rows())
elif method == self._enumerate_unique:
selected_names = node_context.parameters['columns'].selected_names(
input_.column_names())
unique = {}
indices = []
count = 0
for values in zip(*[input_[col].tolist()
for col in selected_names]):
values = tuple(values)
i = unique.get(values)
if i is not None:
indices.append(i)
else:
unique[values] = count
indices.append(count)
count += 1
output[name] = np.array(indices)
def adjust_parameters(self, node_context):
adjust(node_context.parameters['columns'],
node_context.input['input'])
