path: root/wqflask/base/data_set.py

# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
#
# This program is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License
# as published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
# See the GNU Affero General Public License for more details.
#
# This program is available from Source Forge: at GeneNetwork Project
# (sourceforge.net/projects/genenetwork/).
#
# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
#
# This module is used by GeneNetwork project (www.genenetwork.org)
from dataclasses import dataclass
from dataclasses import field
from dataclasses import InitVar
from typing import Optional, Dict
from db.call import fetchall, fetchone, fetch1
from utility.logger import getLogger
from utility.tools import USE_GN_SERVER, USE_REDIS, flat_files, flat_file_exists, GN2_BASE_URL
from db.gn_server import menu_main
from pprint import pformat as pf
from utility.db_tools import escape
from utility.db_tools import mescape
from utility.db_tools import create_in_clause
from maintenance import get_group_samplelists
from utility.tools import locate, locate_ignore_error, flat_files
from utility import gen_geno_ob
from utility import chunks
from utility.benchmark import Bench
from utility import webqtlUtil
from db import webqtlDatabaseFunction
from base import species
from base import webqtlConfig
from flask import Flask, g
import os
import math
import string
import collections
import codecs

import json
import requests
import gzip
import pickle as pickle
import itertools

from redis import Redis

r = Redis()

logger = getLogger(__name__)

# Used by create_database to instantiate objects
# Each subclass will add to this
DS_NAME_MAP = {}


def create_dataset(dataset_name, dataset_type=None,
                   get_samplelist=True, group_name=None):
    if dataset_name == "Temp":
        dataset_type = "Temp"

    if not dataset_type:
        dataset_type = Dataset_Getter(dataset_name)

    dataset_ob = DS_NAME_MAP[dataset_type]
    dataset_class = globals()[dataset_ob]
    if dataset_type == "Temp":
        return dataset_class(dataset_name, get_samplelist, group_name)
    else:
        return dataset_class(dataset_name, get_samplelist)


@dataclass
class DatasetType:
    """Create a dictionary of samples where the value is set to Geno,
    Publish or ProbeSet. E.g.

        {'AD-cases-controls-MyersGeno': 'Geno',
         'AD-cases-controls-MyersPublish': 'Publish',
         'AKXDGeno': 'Geno',
         'AXBXAGeno': 'Geno',
         'AXBXAPublish': 'Publish',
         'Aging-Brain-UCIPublish': 'Publish',
         'All Phenotypes': 'Publish',
         'B139_K_1206_M': 'ProbeSet',
         'B139_K_1206_R': 'ProbeSet' ...
        }
        """
    redis_instance: InitVar[Redis]
    datasets: Optional[Dict] = field(init=False, default_factory=dict)
    data: Optional[Dict] = field(init=False)

    def __post_init__(self, redis_instance):
        self.redis_instance = redis_instance
        data = redis_instance.get("dataset_structure")
        if data:
            self.datasets = json.loads(data)
        else:
            # ZS: I don't think this should ever run unless Redis is
            # emptied
            try:
                data = json.loads(requests.get(
                    GN2_BASE_URL + "/api/v_pre1/gen_dropdown",
                    timeout=5).content)
                for _species in data['datasets']:
                    for group in data['datasets'][_species]:
                        for dataset_type in data['datasets'][_species][group]:
                            for dataset in data['datasets'][_species][group][dataset_type]:
                                short_dataset_name = dataset[1]
                                if dataset_type == "Phenotypes":
                                    new_type = "Publish"
                                elif dataset_type == "Genotypes":
                                    new_type = "Geno"
                                else:
                                    new_type = "ProbeSet"
                                self.datasets[short_dataset_name] = new_type
            except Exception:  # Do nothing
                pass

            self.redis_instance.set("dataset_structure",
                                    json.dumps(self.datasets))
        self.data = data

    def set_dataset_key(self, t, name):
        """If name is not in the object's dataset dictionary, set it, and
        update dataset_structure in Redis
        args:
          t: Type of dataset structure which can be: 'mrna_expr', 'pheno',
             'other_pheno', 'geno'
          name: The name of the key to inserted in the datasets dictionary

        """
        sql_query_mapping = {
            'mrna_expr': ("SELECT ProbeSetFreeze.Id FROM "
                          "ProbeSetFreeze WHERE "
                          "ProbeSetFreeze.Name = \"%s\" "),
            'pheno': ("SELECT InfoFiles.GN_AccesionId "
                      "FROM InfoFiles, PublishFreeze, InbredSet "
                      "WHERE InbredSet.Name = '%s' AND "
                      "PublishFreeze.InbredSetId = InbredSet.Id AND "
                      "InfoFiles.InfoPageName = PublishFreeze.Name"),
            'other_pheno': ("SELECT PublishFreeze.Name "
                            "FROM PublishFreeze, InbredSet "
                            "WHERE InbredSet.Name = '%s' AND "
                            "PublishFreeze.InbredSetId = InbredSet.Id"),
            'geno': ("SELECT GenoFreeze.Id FROM GenoFreeze WHERE "
                     "GenoFreeze.Name = \"%s\" ")
        }

        dataset_name_mapping = {
            "mrna_expr": "ProbeSet",
            "pheno": "Publish",
            "other_pheno": "Publish",
            "geno": "Geno",
        }

        group_name = name
        if t in ['pheno', 'other_pheno']:
            group_name = name.replace("Publish", "")

        results = g.db.execute(sql_query_mapping[t] % group_name).fetchone()
        if results:
            self.datasets[name] = dataset_name_mapping[t]
            self.redis_instance.set(
                "dataset_structure", json.dumps(self.datasets))
            return True
        return None

    def __call__(self, name):
        if name not in self.datasets:
            for t in ["mrna_expr", "pheno", "other_pheno", "geno"]:
                # This has side-effects, with the end result being a
                # truth-y value
                if(self.set_dataset_key(t, name)):
                    break
        # Return None if name has not been set
        return self.datasets.get(name, None)


# Do the intensive work at startup one time only
Dataset_Getter = DatasetType(r)


def create_datasets_list():
    if USE_REDIS:
        key = "all_datasets"
        result = r.get(key)

        if result:
            logger.debug("Redis cache hit")
            datasets = pickle.loads(result)

    if result is None:
        datasets = list()
        with Bench("Creating DataSets object"):
            type_dict = {'Publish': 'PublishFreeze',
                         'ProbeSet': 'ProbeSetFreeze',
                         'Geno': 'GenoFreeze'}

            for dataset_type in type_dict:
                query = "SELECT Name FROM {}".format(type_dict[dataset_type])
                for result in fetchall(query):
                    # The query at the beginning of this function isn't
                    # necessary here, but still would rather just reuse
                    # it logger.debug("type: {}\tname:
                    # {}".format(dataset_type, result.Name))
                    dataset = create_dataset(result.Name, dataset_type)
                    datasets.append(dataset)

        if USE_REDIS:
            r.set(key, pickle.dumps(datasets, pickle.HIGHEST_PROTOCOL))
            r.expire(key, 60 * 60)

    return datasets


class Markers:
    """Todo: Build in cacheing so it saves us reading the same file more than once"""

    def __init__(self, name):
        json_data_fh = open(locate(name + ".json", 'genotype/json'))

        markers = []
        with open("%s/%s_snps.txt" % (flat_files('genotype/bimbam'), name), 'r') as bimbam_fh:
            if len(bimbam_fh.readline().split(", ")) > 2:
                delimiter = ", "
            elif len(bimbam_fh.readline().split(",")) > 2:
                delimiter = ","
            elif len(bimbam_fh.readline().split("\t")) > 2:
                delimiter = "\t"
            else:
                delimiter = " "
            for line in bimbam_fh:
                marker = {}
                marker['name'] = line.split(delimiter)[0].rstrip()
                marker['Mb'] = float(line.split(delimiter)[
                                     1].rstrip()) / 1000000
                marker['chr'] = line.split(delimiter)[2].rstrip()
                markers.append(marker)

        for marker in markers:
            if (marker['chr'] != "X") and (marker['chr'] != "Y") and (marker['chr'] != "M"):
                marker['chr'] = int(marker['chr'])
            marker['Mb'] = float(marker['Mb'])

        self.markers = markers

    def add_pvalues(self, p_values):
        logger.debug("length of self.markers:", len(self.markers))
        logger.debug("length of p_values:", len(p_values))

        if isinstance(p_values, list):
            # THIS IS only needed for the case when we are limiting the number of p-values calculated
            # if len(self.markers) > len(p_values):
            #    self.markers = self.markers[:len(p_values)]

            for marker, p_value in zip(self.markers, p_values):
                if not p_value:
                    continue
                marker['p_value'] = float(p_value)
                if math.isnan(marker['p_value']) or marker['p_value'] <= 0:
                    marker['lod_score'] = 0
                    marker['lrs_value'] = 0
                else:
                    marker['lod_score'] = -math.log10(marker['p_value'])
                    # Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values
                    marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61
        elif isinstance(p_values, dict):
            filtered_markers = []
            for marker in self.markers:
                if marker['name'] in p_values:
                    # logger.debug("marker {} IS in p_values".format(i))
                    marker['p_value'] = p_values[marker['name']]
                    if math.isnan(marker['p_value']) or (marker['p_value'] <= 0):
                        marker['lod_score'] = 0
                        marker['lrs_value'] = 0
                    else:
                        marker['lod_score'] = -math.log10(marker['p_value'])
                        # Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values
                        marker['lrs_value'] = - \
                            math.log10(marker['p_value']) * 4.61
                    filtered_markers.append(marker)
            self.markers = filtered_markers


class HumanMarkers(Markers):

    def __init__(self, name, specified_markers=[]):
        marker_data_fh = open(flat_files('mapping') + '/' + name + '.bim')
        self.markers = []
        for line in marker_data_fh:
            splat = line.strip().split()
            # logger.debug("splat:", splat)
            if len(specified_markers) > 0:
                if splat[1] in specified_markers:
                    marker = {}
                    marker['chr'] = int(splat[0])
                    marker['name'] = splat[1]
                    marker['Mb'] = float(splat[3]) / 1000000
                else:
                    continue
            else:
                marker = {}
                marker['chr'] = int(splat[0])
                marker['name'] = splat[1]
                marker['Mb'] = float(splat[3]) / 1000000
            self.markers.append(marker)

    def add_pvalues(self, p_values):
        super(HumanMarkers, self).add_pvalues(p_values)


class DatasetGroup:
    """
    Each group has multiple datasets; each species has multiple groups.

    For example, Mouse has multiple groups (BXD, BXA, etc), and each group
    has multiple datasets associated with it.

    """

    def __init__(self, dataset, name=None):
        """This sets self.group and self.group_id"""
        if name == None:
            self.name, self.id, self.genetic_type = fetchone(
                dataset.query_for_group)
        else:
            self.name, self.id, self.genetic_type = fetchone(
                "SELECT InbredSet.Name, InbredSet.Id, InbredSet.GeneticType FROM InbredSet where Name='%s'" % name)
        if self.name == 'BXD300':
            self.name = "BXD"

        self.f1list = None
        self.parlist = None
        self.get_f1_parent_strains()

        self.mapping_id, self.mapping_names = self.get_mapping_methods()

        self.species = webqtlDatabaseFunction.retrieve_species(self.name)

        self.incparentsf1 = False
        self.allsamples = None
        self._datasets = None
        self.genofile = None

    def get_mapping_methods(self):

        mapping_id = g.db.execute(
            "select MappingMethodId from InbredSet where Name= '%s'" % self.name).fetchone()[0]
        if mapping_id == "1":
            mapping_names = ["GEMMA", "QTLReaper", "R/qtl"]
        elif mapping_id == "2":
            mapping_names = ["GEMMA"]
        elif mapping_id == "3":
            mapping_names = ["R/qtl"]
        elif mapping_id == "4":
            mapping_names = ["GEMMA", "PLINK"]
        else:
            mapping_names = []

        return mapping_id, mapping_names

    def get_markers(self):
        def check_plink_gemma():
            if flat_file_exists("mapping"):
                MAPPING_PATH = flat_files("mapping") + "/"
                if os.path.isfile(MAPPING_PATH + self.name + ".bed"):
                    return True
            return False

        if check_plink_gemma():
            marker_class = HumanMarkers
        else:
            marker_class = Markers

        if self.genofile:
            self.markers = marker_class(self.genofile[:-5])
        else:
            self.markers = marker_class(self.name)

    def get_f1_parent_strains(self):
        try:
            # NL, 07/27/2010. ParInfo has been moved from webqtlForm.py to webqtlUtil.py;
            f1, f12, maternal, paternal = webqtlUtil.ParInfo[self.name]
        except KeyError:
            f1 = f12 = maternal = paternal = None

        if f1 and f12:
            self.f1list = [f1, f12]
        if maternal and paternal:
            self.parlist = [maternal, paternal]

    def get_study_samplelists(self):
        study_sample_file = "%s/study_sample_lists/%s.json" % (webqtlConfig.GENODIR, self.name)
        try:
            f = open(study_sample_file)
        except:
            return None
        study_samples = json.load(f)
        return study_samples

    def get_genofiles(self):
        jsonfile = "%s/%s.json" % (webqtlConfig.GENODIR, self.name)
        try:
            f = open(jsonfile)
        except:
            return None
        jsondata = json.load(f)
        return jsondata['genofile']

    def get_samplelist(self):
        result = None
        key = "samplelist:v3:" + self.name
        if USE_REDIS:
            result = r.get(key)

        if result is not None:
            self.samplelist = json.loads(result)
        else:
            logger.debug("Cache not hit")

            genotype_fn = locate_ignore_error(self.name + ".geno", 'genotype')
            if genotype_fn:
                self.samplelist = get_group_samplelists.get_samplelist(
                    "geno", genotype_fn)
            else:
                self.samplelist = None

            if USE_REDIS:
                r.set(key, json.dumps(self.samplelist))
                r.expire(key, 60 * 5)

    def all_samples_ordered(self):
        result = []
        lists = (self.parlist, self.f1list, self.samplelist)
        [result.extend(l) for l in lists if l]
        return result

    def read_genotype_file(self, use_reaper=False):
        '''Read genotype from .geno file instead of database'''
        # genotype_1 is Dataset Object without parents and f1
        # genotype_2 is Dataset Object with parents and f1 (not for intercross)


        # reaper barfs on unicode filenames, so here we ensure it's a string
        if self.genofile:
            if "RData" in self.genofile:  # ZS: This is a temporary fix; I need to change the way the JSON files that point to multiple genotype files are structured to point to other file types like RData
                full_filename = str(
                    locate(self.genofile.split(".")[0] + ".geno", 'genotype'))
            else:
                full_filename = str(locate(self.genofile, 'genotype'))
        else:
            full_filename = str(locate(self.name + '.geno', 'genotype'))
        genotype_1 = gen_geno_ob.genotype(full_filename)

        if genotype_1.type == "group" and self.parlist:
            genotype_2 = genotype_1.add(
                Mat=self.parlist[0], Pat=self.parlist[1])  # , F1=_f1)
        else:
            genotype_2 = genotype_1

        # determine default genotype object
        if self.incparentsf1 and genotype_1.type != "intercross":
            genotype = genotype_2
        else:
            self.incparentsf1 = 0
            genotype = genotype_1

        self.samplelist = list(genotype.prgy)

        return genotype


def datasets(group_name, this_group=None):
    key = "group_dataset_menu:v2:" + group_name
    dataset_menu = []
    the_results = fetchall('''
         (SELECT '#PublishFreeze',PublishFreeze.FullName,PublishFreeze.Name
          FROM PublishFreeze,InbredSet
          WHERE PublishFreeze.InbredSetId = InbredSet.Id
            and InbredSet.Name = '%s'
          ORDER BY PublishFreeze.Id ASC)
         UNION
         (SELECT '#GenoFreeze',GenoFreeze.FullName,GenoFreeze.Name
          FROM GenoFreeze, InbredSet
          WHERE GenoFreeze.InbredSetId = InbredSet.Id
            and InbredSet.Name = '%s')
         UNION
         (SELECT Tissue.Name, ProbeSetFreeze.FullName,ProbeSetFreeze.Name
          FROM ProbeSetFreeze, ProbeFreeze, InbredSet, Tissue
          WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id
            and ProbeFreeze.TissueId = Tissue.Id
            and ProbeFreeze.InbredSetId = InbredSet.Id
            and InbredSet.Name like %s
          ORDER BY Tissue.Name, ProbeSetFreeze.OrderList DESC)
        ''' % (group_name,
               group_name,
               "'" + group_name + "'"))

    sorted_results = sorted(the_results, key=lambda kv: kv[0])

    # ZS: This is kind of awkward, but need to ensure Phenotypes show up before Genotypes in dropdown
    pheno_inserted = False
    geno_inserted = False
    for dataset_item in sorted_results:
        tissue_name = dataset_item[0]
        dataset = dataset_item[1]
        dataset_short = dataset_item[2]
        if tissue_name in ['#PublishFreeze', '#GenoFreeze']:
            if tissue_name == '#PublishFreeze' and (dataset_short == group_name + 'Publish'):
                dataset_menu.insert(
                    0, dict(tissue=None, datasets=[(dataset, dataset_short)]))
                pheno_inserted = True
            elif pheno_inserted and tissue_name == '#GenoFreeze':
                dataset_menu.insert(
                    1, dict(tissue=None, datasets=[(dataset, dataset_short)]))
                geno_inserted = True
            else:
                dataset_menu.append(
                    dict(tissue=None, datasets=[(dataset, dataset_short)]))
        else:
            tissue_already_exists = False
            for i, tissue_dict in enumerate(dataset_menu):
                if tissue_dict['tissue'] == tissue_name:
                    tissue_already_exists = True
                    break

            if tissue_already_exists:
                dataset_menu[i]['datasets'].append((dataset, dataset_short))
            else:
                dataset_menu.append(dict(tissue=tissue_name,
                                         datasets=[(dataset, dataset_short)]))

    if USE_REDIS:
        r.set(key, pickle.dumps(dataset_menu, pickle.HIGHEST_PROTOCOL))
        r.expire(key, 60 * 5)

    if this_group != None:
        this_group._datasets = dataset_menu
        return this_group._datasets
    else:
        return dataset_menu


class DataSet:
    """
    DataSet class defines a dataset in webqtl, can be either Microarray,
    Published phenotype, genotype, or user input dataset(temp)

    """

    def __init__(self, name, get_samplelist=True, group_name=None):

        assert name, "Need a name"
        self.name = name
        self.id = None
        self.shortname = None
        self.fullname = None
        self.type = None
        self.data_scale = None  # ZS: For example log2
        self.accession_id = None

        self.setup()

        if self.type == "Temp":  # Need to supply group name as input if temp trait
            # sets self.group and self.group_id and gets genotype
            self.group = DatasetGroup(self, name=group_name)
        else:
            self.check_confidentiality()
            self.retrieve_other_names()
            # sets self.group and self.group_id and gets genotype
            self.group = DatasetGroup(self)
            self.accession_id = self.get_accession_id()
        if get_samplelist == True:
            self.group.get_samplelist()
        self.species = species.TheSpecies(self)

    def as_dict(self):
        return {
            'name': self.name,
            'shortname': self.shortname,
            'fullname': self.fullname,
            'type': self.type,
            'data_scale': self.data_scale,
            'group': self.group.name,
            'accession_id': self.accession_id
        }

    def get_accession_id(self):
        if self.type == "Publish":
            results = g.db.execute("""select InfoFiles.GN_AccesionId from InfoFiles, PublishFreeze, InbredSet where
                        InbredSet.Name = %s and
                        PublishFreeze.InbredSetId = InbredSet.Id and
                        InfoFiles.InfoPageName = PublishFreeze.Name and
                        PublishFreeze.public > 0 and
                        PublishFreeze.confidentiality < 1 order by
                        PublishFreeze.CreateTime desc""", (self.group.name)).fetchone()
        elif self.type == "Geno":
            results = g.db.execute("""select InfoFiles.GN_AccesionId from InfoFiles, GenoFreeze, InbredSet where
                        InbredSet.Name = %s and
                        GenoFreeze.InbredSetId = InbredSet.Id and
                        InfoFiles.InfoPageName = GenoFreeze.ShortName and
                        GenoFreeze.public > 0 and
                        GenoFreeze.confidentiality < 1 order by
                        GenoFreeze.CreateTime desc""", (self.group.name)).fetchone()
        else:
            results = None

        if results != None:
            return str(results[0])
        else:
            return "None"

    def retrieve_other_names(self):
        """This method fetches the the dataset names in search_result.

        If the data set name parameter is not found in the 'Name' field of
        the data set table, check if it is actually the FullName or
        ShortName instead.

        This is not meant to retrieve the data set info if no name at
        all is passed.

        """

        try:
            if self.type == "ProbeSet":
                query_args = tuple(escape(x) for x in (
                    self.name,
                    self.name,
                    self.name))

                self.id, self.name, self.fullname, self.shortname, self.data_scale, self.tissue = fetch1("""
    SELECT ProbeSetFreeze.Id, ProbeSetFreeze.Name, ProbeSetFreeze.FullName, ProbeSetFreeze.ShortName, ProbeSetFreeze.DataScale, Tissue.Name
    FROM ProbeSetFreeze, ProbeFreeze, Tissue
    WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id
    AND ProbeFreeze.TissueId = Tissue.Id
    AND (ProbeSetFreeze.Name = '%s' OR ProbeSetFreeze.FullName = '%s' OR ProbeSetFreeze.ShortName = '%s')
                """ % (query_args), "/dataset/" + self.name + ".json",
                    lambda r: (r["id"], r["name"], r["full_name"],
                               r["short_name"], r["data_scale"], r["tissue"])
                )
            else:
                query_args = tuple(escape(x) for x in (
                    (self.type + "Freeze"),
                    self.name,
                    self.name,
                    self.name))

                self.tissue = "N/A"
                self.id, self.name, self.fullname, self.shortname = fetchone("""
                        SELECT Id, Name, FullName, ShortName
                        FROM %s
                        WHERE (Name = '%s' OR FullName = '%s' OR ShortName = '%s')
                    """ % (query_args))

        except TypeError:
            logger.debug(
                "Dataset {} is not yet available in GeneNetwork.".format(self.name))
            pass

    def chunk_dataset(self, dataset, n):

        results = {}

        query = """
                SELECT ProbeSetXRef.DataId,ProbeSet.Name
                FROM ProbeSet, ProbeSetXRef, ProbeSetFreeze
                WHERE ProbeSetFreeze.Name = '{}' AND
                      ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
                      ProbeSetXRef.ProbeSetId = ProbeSet.Id
        """.format(self.name)

        # should cache this

        traits_name_dict = dict(g.db.execute(query).fetchall())

        for i in range(0, len(dataset), n):
            matrix = list(dataset[i:i + n])
            trait_name = traits_name_dict[matrix[0][0]]

            my_values = [value for (trait_name, strain, value) in matrix]
            results[trait_name] = my_values
        return results

    def get_probeset_data(self, sample_list=None, trait_ids=None):

        # improvement of get trait data--->>>
        if sample_list:
            self.samplelist = sample_list

        else:
            self.samplelist = self.group.samplelist

        if self.group.parlist != None and self.group.f1list != None:
            if (self.group.parlist + self.group.f1list) in self.samplelist:
                self.samplelist += self.group.parlist + self.group.f1list

        query = """
            SELECT Strain.Name, Strain.Id FROM Strain, Species
            WHERE Strain.Name IN {}
            and Strain.SpeciesId=Species.Id
            and Species.name = '{}'
            """.format(create_in_clause(self.samplelist), *mescape(self.group.species))
        results = dict(g.db.execute(query).fetchall())
        sample_ids = [results[item] for item in self.samplelist]

        sorted_samplelist = [strain_name for strain_name, strain_id in sorted(
            results.items(), key=lambda item: item[1])]

        query = """SELECT * from ProbeSetData
                where StrainID in {}
                and id in (SELECT ProbeSetXRef.DataId
                FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze)
                WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id
                and ProbeSetFreeze.Name = '{}'
                and ProbeSet.Id = ProbeSetXRef.ProbeSetId)""".format(create_in_clause(sample_ids), self.name)

        query_results = list(g.db.execute(query).fetchall())
        data_results = self.chunk_dataset(query_results, len(sample_ids))
        self.samplelist = sorted_samplelist
        self.trait_data = data_results
        

    def get_trait_data(self, sample_list=None):
        if sample_list:
            self.samplelist = sample_list
        else:
            self.samplelist = self.group.samplelist

        if self.group.parlist != None and self.group.f1list != None:
            if (self.group.parlist + self.group.f1list) in self.samplelist:
                self.samplelist += self.group.parlist + self.group.f1list

        query = """
            SELECT Strain.Name, Strain.Id FROM Strain, Species
            WHERE Strain.Name IN {}
            and Strain.SpeciesId=Species.Id
            and Species.name = '{}'
            """.format(create_in_clause(self.samplelist), *mescape(self.group.species))
        logger.sql(query)
        results = dict(g.db.execute(query).fetchall())
        sample_ids = [results[item] for item in self.samplelist]

        # MySQL limits the number of tables that can be used in a join to 61,
        # so we break the sample ids into smaller chunks
        # Postgres doesn't have that limit, so we can get rid of this after we transition
        chunk_size = 50
        number_chunks = int(math.ceil(len(sample_ids) / chunk_size))
        trait_sample_data = []
        for sample_ids_step in chunks.divide_into_chunks(sample_ids, number_chunks):
            if self.type == "Publish":
                dataset_type = "Phenotype"
            else:
                dataset_type = self.type
            temp = ['T%s.value' % item for item in sample_ids_step]
            if self.type == "Publish":
                query = "SELECT {}XRef.Id,".format(escape(self.type))
            else:
                query = "SELECT {}.Name,".format(escape(dataset_type))
            data_start_pos = 1
            query += ', '.join(temp)
            query += ' FROM ({}, {}XRef, {}Freeze) '.format(*mescape(dataset_type,
                                                                     self.type,
                                                                     self.type))

            for item in sample_ids_step:
                query += """
                        left join {}Data as T{} on T{}.Id = {}XRef.DataId
                        and T{}.StrainId={}\n
                        """.format(*mescape(self.type, item, item, self.type, item, item))

            if self.type == "Publish":
                query += """
                        WHERE {}XRef.InbredSetId = {}Freeze.InbredSetId
                        and {}Freeze.Name = '{}'
                        and {}.Id = {}XRef.{}Id
                        order by {}.Id
                        """.format(*mescape(self.type, self.type, self.type, self.name,
                                            dataset_type, self.type, dataset_type, dataset_type))
            else:
                query += """
                        WHERE {}XRef.{}FreezeId = {}Freeze.Id
                        and {}Freeze.Name = '{}'
                        and {}.Id = {}XRef.{}Id
                        order by {}.Id
                        """.format(*mescape(self.type, self.type, self.type, self.type,
                                            self.name, dataset_type, self.type, self.type, dataset_type))

            results = g.db.execute(query).fetchall()
            trait_sample_data.append(results)

        trait_count = len(trait_sample_data[0])
        self.trait_data = collections.defaultdict(list)

        # put all of the separate data together into a dictionary where the keys are
        # trait names and values are lists of sample values
        for trait_counter in range(trait_count):
            trait_name = trait_sample_data[0][trait_counter][0]
            for chunk_counter in range(int(number_chunks)):
                self.trait_data[trait_name] += (
                    trait_sample_data[chunk_counter][trait_counter][data_start_pos:])


class PhenotypeDataSet(DataSet):
    DS_NAME_MAP['Publish'] = 'PhenotypeDataSet'

    def setup(self):
        # Fields in the database table
        self.search_fields = ['Phenotype.Post_publication_description',
                              'Phenotype.Pre_publication_description',
                              'Phenotype.Pre_publication_abbreviation',
                              'Phenotype.Post_publication_abbreviation',
                              'PublishXRef.mean',
                              'Phenotype.Lab_code',
                              'Publication.PubMed_ID',
                              'Publication.Abstract',
                              'Publication.Title',
                              'Publication.Authors',
                              'PublishXRef.Id']

        # Figure out what display_fields is
        self.display_fields = ['name', 'group_code',
                               'pubmed_id',
                               'pre_publication_description',
                               'post_publication_description',
                               'original_description',
                               'pre_publication_abbreviation',
                               'post_publication_abbreviation',
                               'mean',
                               'lab_code',
                               'submitter', 'owner',
                               'authorized_users',
                               'authors', 'title',
                               'abstract', 'journal',
                               'volume', 'pages',
                               'month', 'year',
                               'sequence', 'units', 'comments']

        # Fields displayed in the search results table header
        self.header_fields = ['Index',
                              'Record',
                              'Description',
                              'Authors',
                              'Year',
                              'Max LRS',
                              'Max LRS Location',
                              'Additive Effect']

        self.type = 'Publish'

        self.query_for_group = '''
                            SELECT
                                    InbredSet.Name, InbredSet.Id, InbredSet.GeneticType
                            FROM
                                    InbredSet, PublishFreeze
                            WHERE
                                    PublishFreeze.InbredSetId = InbredSet.Id AND
                                    PublishFreeze.Name = "%s"
                    ''' % escape(self.name)

    def check_confidentiality(self):
        # (Urgently?) Need to write this
        pass

    def get_trait_info(self, trait_list, species=''):
        for this_trait in trait_list:

            if not this_trait.haveinfo:
                this_trait.retrieve_info(get_qtl_info=True)

            description = this_trait.post_publication_description

            # If the dataset is confidential and the user has access to confidential
            # phenotype traits, then display the pre-publication description instead
            # of the post-publication description
            if this_trait.confidential:
                this_trait.description_display = ""
                continue   # for now, because no authorization features

                if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait(
                        privilege=self.privilege,
                        userName=self.userName,
                        authorized_users=this_trait.authorized_users):

                    description = this_trait.pre_publication_description

            if len(description) > 0:
                this_trait.description_display = description.strip()
            else:
                this_trait.description_display = ""

            if not this_trait.year.isdigit():
                this_trait.pubmed_text = "N/A"
            else:
                this_trait.pubmed_text = this_trait.year

            if this_trait.pubmed_id:
                this_trait.pubmed_link = webqtlConfig.PUBMEDLINK_URL % this_trait.pubmed_id

            # LRS and its location
            this_trait.LRS_score_repr = "N/A"
            this_trait.LRS_location_repr = "N/A"

            if this_trait.lrs:
                query = """
                    select Geno.Chr, Geno.Mb from Geno, Species
                    where Species.Name = '%s' and
                        Geno.Name = '%s' and
                        Geno.SpeciesId = Species.Id
                """ % (species, this_trait.locus)
                logger.sql(query)
                result = g.db.execute(query).fetchone()

                if result:
                    if result[0] and result[1]:
                        LRS_Chr = result[0]
                        LRS_Mb = result[1]

                        this_trait.LRS_score_repr = LRS_score_repr = '%3.1f' % this_trait.lrs
                        this_trait.LRS_location_repr = LRS_location_repr = 'Chr%s: %.6f' % (
                            LRS_Chr, float(LRS_Mb))

    def retrieve_sample_data(self, trait):
        query = """
                    SELECT
                            Strain.Name, PublishData.value, PublishSE.error, NStrain.count, Strain.Name2
                    FROM
                            (PublishData, Strain, PublishXRef, PublishFreeze)
                    left join PublishSE on
                            (PublishSE.DataId = PublishData.Id AND PublishSE.StrainId = PublishData.StrainId)
                    left join NStrain on
                            (NStrain.DataId = PublishData.Id AND
                            NStrain.StrainId = PublishData.StrainId)
                    WHERE
                            PublishXRef.InbredSetId = PublishFreeze.InbredSetId AND
                            PublishData.Id = PublishXRef.DataId AND PublishXRef.Id = %s AND
                            PublishFreeze.Id = %s AND PublishData.StrainId = Strain.Id
                    Order BY
                            Strain.Name
                    """
        logger.sql(query)
        results = g.db.execute(query, (trait, self.id)).fetchall()
        return results


class GenotypeDataSet(DataSet):
    DS_NAME_MAP['Geno'] = 'GenotypeDataSet'

    def setup(self):
        # Fields in the database table
        self.search_fields = ['Name',
                              'Chr']

        # Find out what display_fields is
        self.display_fields = ['name',
                               'chr',
                               'mb',
                               'source2',
                               'sequence']

        # Fields displayed in the search results table header
        self.header_fields = ['Index',
                              'ID',
                              'Location']

        # Todo: Obsolete or rename this field
        self.type = 'Geno'

        self.query_for_group = '''
                SELECT
                        InbredSet.Name, InbredSet.Id, InbredSet.GeneticType
                FROM
                        InbredSet, GenoFreeze
                WHERE
                        GenoFreeze.InbredSetId = InbredSet.Id AND
                        GenoFreeze.Name = "%s"
                ''' % escape(self.name)

    def check_confidentiality(self):
        return geno_mrna_confidentiality(self)

    def get_trait_info(self, trait_list, species=None):
        for this_trait in trait_list:
            if not this_trait.haveinfo:
                this_trait.retrieveInfo()

            if this_trait.chr and this_trait.mb:
                this_trait.location_repr = 'Chr%s: %.6f' % (
                    this_trait.chr, float(this_trait.mb))

    def retrieve_sample_data(self, trait):
        query = """
                    SELECT
                            Strain.Name, GenoData.value, GenoSE.error, "N/A", Strain.Name2
                    FROM
                            (GenoData, GenoFreeze, Strain, Geno, GenoXRef)
                    left join GenoSE on
                            (GenoSE.DataId = GenoData.Id AND GenoSE.StrainId = GenoData.StrainId)
                    WHERE
                            Geno.SpeciesId = %s AND Geno.Name = %s AND GenoXRef.GenoId = Geno.Id AND
                            GenoXRef.GenoFreezeId = GenoFreeze.Id AND
                            GenoFreeze.Name = %s AND
                            GenoXRef.DataId = GenoData.Id AND
                            GenoData.StrainId = Strain.Id
                    Order BY
                            Strain.Name
                    """
        logger.sql(query)
        results = g.db.execute(query,
                               (webqtlDatabaseFunction.retrieve_species_id(self.group.name),
                                trait, self.name)).fetchall()
        return results


class MrnaAssayDataSet(DataSet):
    '''
    An mRNA Assay is a quantitative assessment (assay) associated with an mRNA trait

    This used to be called ProbeSet, but that term only refers specifically to the Affymetrix
    platform and is far too specific.

    '''
    DS_NAME_MAP['ProbeSet'] = 'MrnaAssayDataSet'

    def setup(self):
        # Fields in the database table
        self.search_fields = ['Name',
                              'Description',
                              'Probe_Target_Description',
                              'Symbol',
                              'Alias',
                              'GenbankId',
                              'UniGeneId',
                              'RefSeq_TranscriptId']

        # Find out what display_fields is
        self.display_fields = ['name', 'symbol',
                               'description', 'probe_target_description',
                               'chr', 'mb',
                               'alias', 'geneid',
                               'genbankid', 'unigeneid',
                               'omim', 'refseq_transcriptid',
                               'blatseq', 'targetseq',
                               'chipid', 'comments',
                               'strand_probe', 'strand_gene',
                               'proteinid', 'uniprotid',
                               'probe_set_target_region',
                               'probe_set_specificity',
                               'probe_set_blat_score',
                               'probe_set_blat_mb_start',
                               'probe_set_blat_mb_end',
                               'probe_set_strand',
                               'probe_set_note_by_rw',
                               'flag']

        # Fields displayed in the search results table header
        self.header_fields = ['Index',
                              'Record',
                              'Symbol',
                              'Description',
                              'Location',
                              'Mean',
                              'Max LRS',
                              'Max LRS Location',
                              'Additive Effect']

        # Todo: Obsolete or rename this field
        self.type = 'ProbeSet'

        self.query_for_group = '''
                        SELECT
                                InbredSet.Name, InbredSet.Id, InbredSet.GeneticType
                        FROM
                                InbredSet, ProbeSetFreeze, ProbeFreeze
                        WHERE
                                ProbeFreeze.InbredSetId = InbredSet.Id AND
                                ProbeFreeze.Id = ProbeSetFreeze.ProbeFreezeId AND
                                ProbeSetFreeze.Name = "%s"
                ''' % escape(self.name)

    def check_confidentiality(self):
        return geno_mrna_confidentiality(self)

    def get_trait_info(self, trait_list=None, species=''):

        #  Note: setting trait_list to [] is probably not a great idea.
        if not trait_list:
            trait_list = []

        for this_trait in trait_list:

            if not this_trait.haveinfo:
                this_trait.retrieveInfo(QTL=1)

            if not this_trait.symbol:
                this_trait.symbol = "N/A"

            # XZ, 12/08/2008: description
            # XZ, 06/05/2009: Rob asked to add probe target description
            description_string = str(
                str(this_trait.description).strip(codecs.BOM_UTF8), 'utf-8')
            target_string = str(
                str(this_trait.probe_target_description).strip(codecs.BOM_UTF8), 'utf-8')

            if len(description_string) > 1 and description_string != 'None':
                description_display = description_string
            else:
                description_display = this_trait.symbol

            if (len(description_display) > 1 and description_display != 'N/A'
                    and len(target_string) > 1 and target_string != 'None'):
                description_display = description_display + '; ' + target_string.strip()

            # Save it for the jinja2 template
            this_trait.description_display = description_display

            if this_trait.chr and this_trait.mb:
                this_trait.location_repr = 'Chr%s: %.6f' % (
                    this_trait.chr, float(this_trait.mb))

            # Get mean expression value
            query = (
                """select ProbeSetXRef.mean from ProbeSetXRef, ProbeSet
                where ProbeSetXRef.ProbeSetFreezeId = %s and
                ProbeSet.Id = ProbeSetXRef.ProbeSetId and
                ProbeSet.Name = '%s'
            """ % (escape(str(this_trait.dataset.id)),
                   escape(this_trait.name)))

            logger.sql(query)
            result = g.db.execute(query).fetchone()

            mean = result[0] if result else 0

            if mean:
                this_trait.mean = "%2.3f" % mean

            # LRS and its location
            this_trait.LRS_score_repr = 'N/A'
            this_trait.LRS_location_repr = 'N/A'

            # Max LRS and its Locus location
            if this_trait.lrs and this_trait.locus:
                query = """
                    select Geno.Chr, Geno.Mb from Geno, Species
                    where Species.Name = '{}' and
                        Geno.Name = '{}' and
                        Geno.SpeciesId = Species.Id
                """.format(species, this_trait.locus)
                logger.sql(query)
                result = g.db.execute(query).fetchone()

                if result:
                    lrs_chr, lrs_mb = result
                    this_trait.LRS_score_repr = '%3.1f' % this_trait.lrs
                    this_trait.LRS_location_repr = 'Chr%s: %.6f' % (
                        lrs_chr, float(lrs_mb))

        return trait_list

    def retrieve_sample_data(self, trait):
        query = """
                    SELECT
                            Strain.Name, ProbeSetData.value, ProbeSetSE.error, NStrain.count, Strain.Name2
                    FROM
                            (ProbeSetData, ProbeSetFreeze,
                             Strain, ProbeSet, ProbeSetXRef)
                    left join ProbeSetSE on
                            (ProbeSetSE.DataId = ProbeSetData.Id AND ProbeSetSE.StrainId = ProbeSetData.StrainId)
                    left join NStrain on
                            (NStrain.DataId = ProbeSetData.Id AND
                            NStrain.StrainId = ProbeSetData.StrainId)
                    WHERE
                            ProbeSet.Name = '%s' AND ProbeSetXRef.ProbeSetId = ProbeSet.Id AND
                            ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
                            ProbeSetFreeze.Name = '%s' AND
                            ProbeSetXRef.DataId = ProbeSetData.Id AND
                            ProbeSetData.StrainId = Strain.Id
                    Order BY
                            Strain.Name
                    """ % (escape(trait), escape(self.name))
        logger.sql(query)
        results = g.db.execute(query).fetchall()
        return results

    def retrieve_genes(self, column_name):
        query = """
                    select ProbeSet.Name, ProbeSet.%s
                    from ProbeSet,ProbeSetXRef
                    where ProbeSetXRef.ProbeSetFreezeId = %s and
                    ProbeSetXRef.ProbeSetId=ProbeSet.Id;
                """ % (column_name, escape(str(self.id)))
        logger.sql(query)
        results = g.db.execute(query).fetchall()

        return dict(results)


class TempDataSet(DataSet):
    '''Temporary user-generated data set'''

    DS_NAME_MAP['Temp'] = 'TempDataSet'

    def setup(self):
        self.search_fields = ['name',
                              'description']

        self.display_fields = ['name',
                               'description']

        self.header_fields = ['Name',
                              'Description']

        self.type = 'Temp'

        # Need to double check later how these are used
        self.id = 1
        self.fullname = 'Temporary Storage'
        self.shortname = 'Temp'


def geno_mrna_confidentiality(ob):
    dataset_table = ob.type + "Freeze"

    query = '''SELECT Id, Name, FullName, confidentiality,
                        AuthorisedUsers FROM %s WHERE Name = "%s"''' % (dataset_table, ob.name)
    logger.sql(query)
    result = g.db.execute(query)

    (dataset_id,
     name,
     full_name,
     confidential,
     authorized_users) = result.fetchall()[0]

    if confidential:
        return True
    result = g.db.execute(query)

    (dataset_id,
     name,
     full_name,
     confidential,
     authorized_users) = result.fetchall()[0]

    if confidential:
        return True