Source code for allensdk.api.queries.annotated_section_data_sets_api

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from .rma_api import RmaApi
from ..cache import cacheable


[docs]class AnnotatedSectionDataSetsApi(RmaApi): '''See: `Searching Annotated SectionDataSets <http://help.brain-map.org/display/api/Searching+Annotated+SectionDataSets>`_ ''' def __init__(self, base_uri=None): super(AnnotatedSectionDataSetsApi, self).__init__(base_uri)
[docs] def get_annotated_section_data_sets(self, structures, intensity_values=None, density_values=None, pattern_values=None, age_names=None): '''For a list of target structures, find the SectionDataSet that matches the parameters for intensity_values, density_values, pattern_values, and Age. Parameters ---------- structure_graph_id : dict of integers what to retrieve intensity_values : array of strings, optional 'High','Low', 'Medium' (default) density_values : array of strings, optional 'High', 'Low' pattern_values : array of strings, optional 'Full' age_names : array of strings, options for example 'E11.5', '13.5' Returns ------- data : dict The parsed JSON repsonse message. Notes ----- This method uses the non-RMA Annotated SectionDataSet endpoint. ''' params = ['structures=' + ','.join((str(s) for s in structures))] if intensity_values is not None and len(intensity_values) > 0: params.append('intensity_values=' + ','.join(("'%s'" % (v) for v in intensity_values))) if density_values is not None and len(density_values) > 0: params.append('density_values=' + ','.join(("'%s'" % (v) for v in density_values))) if pattern_values is not None and len(pattern_values) > 0: params.append('pattern_values=' + ','.join(("'%s'" % (v) for v in pattern_values))) if age_names is not None and len(age_names) > 0: params.append('age_names=' + ','.join(("'%s'" % (v) for v in age_names))) url_params = '?' + '&'.join(params) url = ''.join([self.annotated_section_data_sets_endpoint, '.json', url_params]) return self.json_msg_query(url)
@cacheable()
[docs] def get_annotated_section_data_sets_via_rma(self, structures, intensity_values=None, density_values=None, pattern_values=None, age_names=None): '''For a list of target structures, find the SectionDataSet that matches the parameters for intensity_values, density_values, pattern_values, and Age. Parameters ---------- structure_graph_id : dict of integers what to retrieve intensity_values : array of strings, optional intensity values, 'High','Low', 'Medium' (default) density_values : array of strings, optional density values, 'High', 'Low' pattern_values : array of strings, optional pattern values, 'Full' age_names : array of strings, options for example 'E11.5', '13.5' Returns ------- data : dict The parsed JSON response message. Notes ----- This method uses the RMA endpoint to search annotated SectionDataSet data. ''' age_include_strings = ['age'] if age_names is not None and len(age_names) > 0: age_include_strings.append('[name$in') age_include_strings.append( ','.join(("'%s'" % (a) for a in age_names))) age_include_strings.append(']') age_include = ''.join(age_include_strings) criteria_strings = ['manual_annotations'] if intensity_values is not None and len(intensity_values) > 0: criteria_strings.append('[intensity_call$in%s]' % (','.join(("'%s'" % (v) for v in intensity_values)))) if density_values is not None and len(density_values) > 0: criteria_strings.append('[density_call$in%s]' % (','.join(("'%s'" % (v) for v in density_values)))) if pattern_values is not None and len(pattern_values) > 0: criteria_strings.append('[pattern_call$in%s]' % (','.join(("'%s'" % (v) for v in pattern_values)))) criteria_strings.append('(structure[id$in%s])' % (','.join((str(s) for s in structures)))) criteria_clause = ''.join(criteria_strings) include_clause = ''.join(['specimen', '(donor(', age_include, ')),', 'probes(gene),' 'plane_of_section']) order_by_array = ['genes.acronym', 'ages.embryonic+desc', 'ages.days', 'data_sets.id'] data = self.model_query('SectionDataSet', criteria=criteria_clause, include=include_clause, start_row=0, num_rows=50, order=order_by_array) return data
[docs] def get_compound_annotated_section_data_sets(self, queries, fmt='json'): '''Find the SectionDataSet that matches several annotated_section_data_sets queries linked together with a Boolean 'and' or 'or'. Parameters ---------- queries : array of dicts dicts with args like build_query fmt : string, optional 'json' or 'xml' Returns ------- data : dict The parsed JSON repsonse message. ''' url_strings = ['?query='] for query in queries: url_strings.append('[') params = ['structures $in ' + ','.join((str(s) for s in query['structures']))] for key in ['intensity_values', 'density_values', 'pattern_values', 'age_names']: if key in query and len(query[key]) > 0: params.append('%s $in %s' % (key, ','.join(("'%s'" % (v) for v in query['intensity_values'])))) url_strings.append(' : '.join(params)) url_strings.append(']') if 'link' in query and query['link'] == 'or': url_strings.append(' or ') if 'link' in query and query['link'] == 'and': url_strings.append(' and ') url_params = ''.join(url_strings) url = ''.join([self.compound_annotated_section_data_sets_endpoint, '.', fmt, url_params]) return self.json_msg_query(url)