path: root/gn3/db/traits.py

"""This class contains functions relating to trait data manipulation"""
import os
from functools import reduce
from typing import Any, Dict, Sequence

from gn3.settings import TMPDIR
from gn3.chancy import random_string
from gn3.function_helpers import compose
from gn3.db.datasets import retrieve_trait_dataset


def export_trait_data(
        trait_data: dict, samplelist: Sequence[str], dtype: str = "val",
        var_exists: bool = False, n_exists: bool = False):
    """
    Export data according to `samplelist`. Mostly used in calculating
    correlations.

    DESCRIPTION:
    Migrated from
    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L166-L211

    PARAMETERS
    trait: (dict)
      The dictionary of key-value pairs representing a trait
    samplelist: (list)
      A list of sample names
    dtype: (str)
      ... verify what this is ...
    var_exists: (bool)
      A flag indicating existence of variance
    n_exists: (bool)
      A flag indicating existence of ndata
    """
    def __export_all_types(tdata, sample):
        sample_data = []
        if tdata[sample]["value"]:
            sample_data.append(tdata[sample]["value"])
            if var_exists:
                if tdata[sample]["variance"]:
                    sample_data.append(tdata[sample]["variance"])
                else:
                    sample_data.append(None)
            if n_exists:
                if tdata[sample]["ndata"]:
                    sample_data.append(tdata[sample]["ndata"])
                else:
                    sample_data.append(None)
        else:
            if var_exists and n_exists:
                sample_data += [None, None, None]
            elif var_exists or n_exists:
                sample_data += [None, None]
            else:
                sample_data.append(None)

        return tuple(sample_data)

    def __exporter(accumulator, sample):
        # pylint: disable=[R0911]
        if sample in trait_data["data"]:
            if dtype == "val":
                return accumulator + (trait_data["data"][sample]["value"], )
            if dtype == "var":
                return accumulator + (trait_data["data"][sample]["variance"], )
            if dtype == "N":
                return accumulator + (trait_data["data"][sample]["ndata"], )
            if dtype == "all":
                return accumulator + __export_all_types(trait_data["data"], sample)
            raise KeyError(f"Type `{dtype}` is incorrect")
        if var_exists and n_exists:
            return accumulator + (None, None, None)
        if var_exists or n_exists:
            return accumulator + (None, None)
        return accumulator + (None,)

    return reduce(__exporter, samplelist, tuple())


def retrieve_publish_trait_info(trait_data_source: Dict[str, Any], conn: Any):
    """Retrieve trait information for type `Publish` traits.

    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L399-L421"""
    keys = (
        "Id", "PubMed_ID", "Pre_publication_description",
        "Post_publication_description", "Original_description",
        "Pre_publication_abbreviation", "Post_publication_abbreviation",
        "Lab_code", "Submitter", "Owner", "Authorized_Users", "Authors",
        "Title", "Abstract", "Journal", "Volume", "Pages", "Month", "Year",
        "Sequence", "Units", "comments")
    columns = (
        "PublishXRef.Id, Publication.PubMed_ID, "
        "Phenotype.Pre_publication_description, "
        "Phenotype.Post_publication_description, "
        "Phenotype.Original_description, "
        "Phenotype.Pre_publication_abbreviation, "
        "Phenotype.Post_publication_abbreviation, "
        "Phenotype.Lab_code, Phenotype.Submitter, Phenotype.Owner, "
        "Phenotype.Authorized_Users, CAST(Publication.Authors AS BINARY), "
        "Publication.Title, Publication.Abstract, Publication.Journal, "
        "Publication.Volume, Publication.Pages, Publication.Month, "
        "Publication.Year, PublishXRef.Sequence, Phenotype.Units, "
        "PublishXRef.comments")
    query = (
        "SELECT "
        f"{columns} "
        "FROM "
        "PublishXRef, Publication, Phenotype "
        "WHERE "
        "PublishXRef.Id = %(trait_name)s AND "
        "Phenotype.Id = PublishXRef.PhenotypeId AND "
        "Publication.Id = PublishXRef.PublicationId AND "
        "PublishXRef.InbredSetId = %(trait_dataset_id)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                k: v for k, v in trait_data_source.items()
                if k in ["trait_name", "trait_dataset_id"]
            })
        return dict(zip([k.lower() for k in keys], cursor.fetchone()))


def set_confidential_field(trait_type, trait_info):
    """Post processing function for 'Publish' trait types.

    It sets the value for the 'confidential' key."""
    if trait_type == "Publish":
        return {
            **trait_info,
            "confidential": 1 if (
                trait_info.get("pre_publication_description", None)
                and not trait_info.get("pubmed_id", None)) else 0}
    return trait_info


def retrieve_probeset_trait_info(trait_data_source: Dict[str, Any], conn: Any):
    """Retrieve trait information for type `ProbeSet` traits.

    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L424-L435"""
    keys = (
        "name", "symbol", "description", "probe_target_description", "chr",
        "mb", "alias", "geneid", "genbankid", "unigeneid", "omim",
        "refseq_transcriptid", "blatseq", "targetseq", "chipid", "comments",
        "strand_probe", "strand_gene", "probe_set_target_region", "proteinid",
        "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")
    columns = (f"ProbeSet.{x}" for x in keys)
    query = (
        f"SELECT {', '.join(columns)} "
        "FROM "
        "ProbeSet, ProbeSetFreeze, ProbeSetXRef "
        "WHERE "
        "ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND "
        "ProbeSetXRef.ProbeSetId = ProbeSet.Id AND "
        "ProbeSetFreeze.Name = %(trait_dataset_name)s AND "
        "ProbeSet.Name = %(trait_name)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                k: v for k, v in trait_data_source.items()
                if k in ["trait_name", "trait_dataset_name"]
            })
        return dict(zip(keys, cursor.fetchone()))


def retrieve_geno_trait_info(trait_data_source: Dict[str, Any], conn: Any):
    """Retrieve trait information for type `Geno` traits.

    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L438-L449"""
    keys = ("name", "chr", "mb", "source2", "sequence")
    columns = ", ".join(f"Geno.{x}" for x in keys)
    query = (
        f"SELECT {columns} "
        "FROM "
        "Geno INNER JOIN GenoXRef ON GenoXRef.GenoId = Geno.Id "
        "INNER JOIN GenoFreeze ON GenoFreeze.Id = GenoXRef.GenoFreezeId "
        "WHERE "
        "GenoFreeze.Name = %(trait_dataset_name)s AND "
        "Geno.Name = %(trait_name)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                k: v for k, v in trait_data_source.items()
                if k in ["trait_name", "trait_dataset_name"]
            })
        return dict(zip(keys, cursor.fetchone()))


def retrieve_temp_trait_info(trait_data_source: Dict[str, Any], conn: Any):
    """Retrieve trait information for type `Temp` traits.

    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L450-452"""
    keys = ("name", "description")
    query = (
        f"SELECT {', '.join(keys)} FROM Temp "
        "WHERE Name = %(trait_name)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                k: v for k, v in trait_data_source.items()
                if k in ["trait_name"]
            })
        return dict(zip(keys, cursor.fetchone()))


def set_haveinfo_field(trait_info):
    """
    Common postprocessing function for all trait types.

    Sets the value for the 'haveinfo' field."""
    return {**trait_info, "haveinfo": 1 if trait_info else 0}


def set_homologene_id_field_probeset(trait_info, conn):
    """
    Postprocessing function for 'ProbeSet' traits.

    Sets the value for the 'homologene' key.
    """
    query = (
        "SELECT HomologeneId FROM Homologene, Species, InbredSet"
        " WHERE Homologene.GeneId = %(geneid)s AND InbredSet.Name = %(group)s"
        " AND InbredSet.SpeciesId = Species.Id AND"
        " Species.TaxonomyId = Homologene.TaxonomyId")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                k: v for k, v in trait_info.items()
                if k in ["geneid", "group"]
            })
        res = cursor.fetchone()
        if res:
            return {**trait_info, "homologeneid": res[0]}
    return {**trait_info, "homologeneid": None}


def set_homologene_id_field(trait_type, trait_info, conn):
    """
    Common postprocessing function for all trait types.

    Sets the value for the 'homologene' key."""
    def set_to_null(ti): return {**ti, "homologeneid": None} # pylint: disable=[C0103, C0321]
    functions_table = {
        "Temp": set_to_null,
        "Geno": set_to_null,
        "Publish": set_to_null,
        "ProbeSet": lambda ti: set_homologene_id_field_probeset(ti, conn)
    }
    return functions_table[trait_type](trait_info)


def load_publish_qtl_info(trait_info, conn):
    """
    Load extra QTL information for `Publish` traits
    """
    query = (
        "SELECT PublishXRef.Locus, PublishXRef.LRS, PublishXRef.additive "
        "FROM PublishXRef, PublishFreeze "
        "WHERE PublishXRef.Id = %(trait_name)s "
        "AND PublishXRef.InbredSetId = PublishFreeze.InbredSetId "
        "AND PublishFreeze.Id = %(dataset_id)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                "trait_name": trait_info["trait_name"],
                "dataset_id": trait_info["db"]["dataset_id"]
            })
        return dict(zip(["locus", "lrs", "additive"], cursor.fetchone()))
    return {"locus": "", "lrs": "", "additive": ""}


def load_probeset_qtl_info(trait_info, conn):
    """
    Load extra QTL information for `ProbeSet` traits
    """
    query = (
        "SELECT ProbeSetXRef.Locus, ProbeSetXRef.LRS, ProbeSetXRef.pValue, "
        "ProbeSetXRef.mean, ProbeSetXRef.additive "
        "FROM ProbeSetXRef, ProbeSet "
        "WHERE ProbeSetXRef.ProbeSetId = ProbeSet.Id "
        " AND ProbeSet.Name = %(trait_name)s "
        "AND ProbeSetXRef.ProbeSetFreezeId = %(dataset_id)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                "trait_name": trait_info["trait_name"],
                "dataset_id": trait_info["db"]["dataset_id"]
            })
        return dict(zip(
            ["locus", "lrs", "pvalue", "mean", "additive"], cursor.fetchone()))
    return {"locus": "", "lrs": "", "pvalue": "", "mean": "", "additive": ""}


def load_qtl_info(qtl, trait_type, trait_info, conn):
    """
    Load extra QTL information for traits

    DESCRIPTION:
    Migrated from
    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L500-L534

    PARAMETERS:
    qtl: boolean
    trait_type: string
      The type of the trait in consideration
    trait_info: map/dictionary
      A dictionary of the trait's key-value pairs
    conn:
      A database connection object
    """
    if not qtl:
        return trait_info
    qtl_info_functions = {
        "Publish": load_publish_qtl_info,
        "ProbeSet": load_probeset_qtl_info
    }
    if trait_info["name"] not in qtl_info_functions:
        return trait_info

    return qtl_info_functions[trait_type](trait_info, conn)


def build_trait_name(trait_fullname):
    """
    Initialises the trait's name, and other values from the search data provided
    """
    def dataset_type(dset_name):
        if dset_name.find('Temp') >= 0:
            return "Temp"
        if dset_name.find('Geno') >= 0:
            return "Geno"
        if dset_name.find('Publish') >= 0:
            return "Publish"
        return "ProbeSet"

    name_parts = trait_fullname.split("::")
    assert len(name_parts) >= 2, f"Name format error: '{trait_fullname}'"
    dataset_name = name_parts[0]
    dataset_type = dataset_type(dataset_name)
    return {
        "db": {
            "dataset_name": dataset_name,
            "dataset_type": dataset_type},
        "trait_fullname": trait_fullname,
        "trait_name": name_parts[1],
        "cellid": name_parts[2] if len(name_parts) == 3 else ""
    }


def retrieve_probeset_sequence(trait, conn):
    """
    Retrieve a 'ProbeSet' trait's sequence information
    """
    query = (
        "SELECT ProbeSet.BlatSeq "
        "FROM ProbeSet, ProbeSetFreeze, ProbeSetXRef "
        "WHERE ProbeSet.Id=ProbeSetXRef.ProbeSetId "
        "AND ProbeSetFreeze.Id = ProbeSetXRef.ProbeSetFreezeId "
        "AND ProbeSet.Name = %(trait_name)s "
        "AND ProbeSetFreeze.Name = %(dataset_name)s")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {
                "trait_name": trait["trait_name"],
                "dataset_name": trait["db"]["dataset_name"]
            })
        seq = cursor.fetchone()
        return {**trait, "sequence": seq[0] if seq else ""}


def retrieve_trait_info(
        threshold: int, trait_full_name: str, conn: Any,
        qtl=None):
    """Retrieves the trait information.

    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L397-L456

    This function, or the dependent functions, might be incomplete as they are
    currently."""
    trait = build_trait_name(trait_full_name)
    trait_dataset_type = trait["db"]["dataset_type"]
    trait_info_function_table = {
        "Publish": retrieve_publish_trait_info,
        "ProbeSet": retrieve_probeset_trait_info,
        "Geno": retrieve_geno_trait_info,
        "Temp": retrieve_temp_trait_info
    }

    common_post_processing_fn = compose(
        lambda ti: load_qtl_info(qtl, trait_dataset_type, ti, conn),
        lambda ti: set_homologene_id_field(trait_dataset_type, ti, conn),
        lambda ti: {"trait_type": trait_dataset_type, **ti},
        lambda ti: {**trait, **ti})

    trait_post_processing_functions_table = {
        "Publish": compose(
            lambda ti: set_confidential_field(trait_dataset_type, ti),
            common_post_processing_fn),
        "ProbeSet": compose(
            lambda ti: retrieve_probeset_sequence(ti, conn),
            common_post_processing_fn),
        "Geno": common_post_processing_fn,
        "Temp": common_post_processing_fn
    }

    retrieve_info = compose(
        set_haveinfo_field, trait_info_function_table[trait_dataset_type])

    trait_dataset = retrieve_trait_dataset(
        trait_dataset_type, trait, threshold, conn)
    trait_info = retrieve_info(
        {
            "trait_name": trait["trait_name"],
            "trait_dataset_id": trait_dataset["dataset_id"],
            "trait_dataset_name": trait_dataset["dataset_name"]
        },
        conn)
    if trait_info["haveinfo"]:
        return {
            **trait_post_processing_functions_table[trait_dataset_type](
                {**trait_info, "group": trait_dataset["group"]}),
            "db": {**trait["db"], **trait_dataset}
        }
    return trait_info


def retrieve_temp_trait_data(trait_info: dict, conn: Any):
    """
    Retrieve trait data for `Temp` traits.
    """
    query = (
        "SELECT "
        "Strain.Name, TempData.value, TempData.SE, TempData.NStrain, "
        "TempData.Id "
        "FROM TempData, Temp, Strain "
        "WHERE TempData.StrainId = Strain.Id "
        "AND TempData.Id = Temp.DataId "
        "AND Temp.name = %(trait_name)s "
        "ORDER BY Strain.Name")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {"trait_name": trait_info["trait_name"]})
        return [dict(zip(
            ["sample_name", "value", "se_error", "nstrain", "id"],
            row))
                for row in cursor.fetchall()]
    return []


def retrieve_species_id(group, conn: Any):
    """
    Retrieve a species id given the Group value
    """
    with conn.cursor as cursor:
        cursor.execute(
            "SELECT SpeciesId from InbredSet WHERE Name = %(group)s",
            {"group": group})
        return cursor.fetchone()[0]
    return None


def retrieve_geno_trait_data(trait_info: Dict, conn: Any):
    """
    Retrieve trait data for `Geno` traits.
    """
    query = (
        "SELECT Strain.Name, GenoData.value, GenoSE.error, GenoData.Id "
        "FROM (GenoData, GenoFreeze, Strain, Geno, GenoXRef) "
        "LEFT JOIN GenoSE ON "
        "(GenoSE.DataId = GenoData.Id AND GenoSE.StrainId = GenoData.StrainId) "
        "WHERE Geno.SpeciesId = %(species_id)s "
        "AND Geno.Name = %(trait_name)s AND GenoXRef.GenoId = Geno.Id "
        "AND GenoXRef.GenoFreezeId = GenoFreeze.Id "
        "AND GenoFreeze.Name = %(dataset_name)s "
        "AND GenoXRef.DataId = GenoData.Id "
        "AND GenoData.StrainId = Strain.Id "
        "ORDER BY Strain.Name")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {"trait_name": trait_info["trait_name"],
             "dataset_name": trait_info["db"]["dataset_name"],
             "species_id": retrieve_species_id(
                 trait_info["db"]["group"], conn)})
        return [
            dict(zip(
                ["sample_name", "value", "se_error", "id"],
                row))
            for row in cursor.fetchall()]
    return []


def retrieve_publish_trait_data(trait_info: Dict, conn: Any):
    """
    Retrieve trait data for `Publish` traits.
    """
    query = (
        "SELECT "
        "Strain.Name, PublishData.value, PublishSE.error, NStrain.count, "
        "PublishData.Id "
        "FROM (PublishData, Strain, PublishXRef) "
        "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 PublishData.Id = PublishXRef.DataId "
        "AND PublishXRef.Id = %(trait_name)s "
        "AND PublishXRef.InbredSetId = %(dataset_id)s "
        "AND PublishData.StrainId = Strain.Id "
        "ORDER BY Strain.Name")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {"trait_name": trait_info["trait_name"],
             "dataset_id": trait_info["db"]["dataset_id"]})
        return [
            dict(zip(
                ["sample_name", "value", "se_error", "nstrain", "id"], row))
            for row in cursor.fetchall()]
    return []


def retrieve_cellid_trait_data(trait_info: Dict, conn: Any):
    """
    Retrieve trait data for `Probe Data` types.
    """
    query = (
        "SELECT "
        "Strain.Name, ProbeData.value, ProbeSE.error, ProbeData.Id "
        "FROM (ProbeData, ProbeFreeze, ProbeSetFreeze, ProbeXRef, Strain,"
        " Probe, ProbeSet) "
        "LEFT JOIN ProbeSE ON "
        "(ProbeSE.DataId = ProbeData.Id "
        " AND ProbeSE.StrainId = ProbeData.StrainId) "
        "WHERE Probe.Name = %(cellid)s "
        "AND ProbeSet.Name = %(trait_name)s "
        "AND Probe.ProbeSetId = ProbeSet.Id "
        "AND ProbeXRef.ProbeId = Probe.Id "
        "AND ProbeXRef.ProbeFreezeId = ProbeFreeze.Id "
        "AND ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id "
        "AND ProbeSetFreeze.Name = %(dataset_name)s "
        "AND ProbeXRef.DataId = ProbeData.Id "
        "AND ProbeData.StrainId = Strain.Id "
        "ORDER BY Strain.Name")
    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {"cellid": trait_info["cellid"],
             "trait_name": trait_info["trait_name"],
             "dataset_id": trait_info["db"]["dataset_id"]})
        return [
            dict(zip(
                ["sample_name", "value", "se_error", "id"], row))
            for row in cursor.fetchall()]
    return []


def retrieve_probeset_trait_data(trait_info: Dict, conn: Any):
    """
    Retrieve trait data for `ProbeSet` traits.
    """
    query = (
        "SELECT Strain.Name, ProbeSetData.value, ProbeSetSE.error, "
        "ProbeSetData.Id "
        "FROM (ProbeSetData, ProbeSetFreeze, Strain, ProbeSet, ProbeSetXRef) "
        "LEFT JOIN ProbeSetSE ON "
        "(ProbeSetSE.DataId = ProbeSetData.Id "
        "AND ProbeSetSE.StrainId = ProbeSetData.StrainId) "
        "WHERE ProbeSet.Name = %(trait_name)s "
        "AND ProbeSetXRef.ProbeSetId = ProbeSet.Id "
        "AND ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
        "AND ProbeSetFreeze.Name = %(dataset_name)s "
        "AND ProbeSetXRef.DataId = ProbeSetData.Id "
        "AND ProbeSetData.StrainId = Strain.Id "
        "ORDER BY Strain.Name")

    with conn.cursor() as cursor:
        cursor.execute(
            query,
            {"trait_name": trait_info["trait_name"],
             "dataset_name": trait_info["db"]["dataset_name"]})
        return [
            dict(zip(
                ["sample_name", "value", "se_error", "id"], row))
            for row in cursor.fetchall()]
    return []


def with_samplelist_data_setup(samplelist: Sequence[str]):
    """
    Build function that computes the trait data from provided list of samples.

    PARAMETERS
    samplelist: (list)
      A list of sample names

    RETURNS:
      Returns a function that given some data from the database, computes the
      sample's value, variance and ndata values, only if the sample is present
      in the provided `samplelist` variable.
    """
    def setup_fn(tdata):
        if tdata["sample_name"] in samplelist:
            val = tdata["value"]
            if val is not None:
                return {
                    "sample_name": tdata["sample_name"],
                    "value": val,
                    "variance": tdata["se_error"],
                    "ndata": tdata.get("nstrain", None)
                }
        return None
    return setup_fn


def without_samplelist_data_setup():
    """
    Build function that computes the trait data.

    RETURNS:
      Returns a function that given some data from the database, computes the
      sample's value, variance and ndata values.
    """
    def setup_fn(tdata):
        val = tdata["value"]
        if val is not None:
            return {
                "sample_name": tdata["sample_name"],
                "value": val,
                "variance": tdata["se_error"],
                "ndata": tdata.get("nstrain", None)
            }
        return None
    return setup_fn


def retrieve_trait_data(trait: dict, conn: Any, samplelist: Sequence[str] = tuple()):
    """
    Retrieve trait data

    DESCRIPTION
    Retrieve trait data as is done in
    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L258-L386
    """
    # I do not like this section, but it retains the flow in the old codebase
    if trait["db"]["dataset_type"] == "Temp":
        results = retrieve_temp_trait_data(trait, conn)
    elif trait["db"]["dataset_type"] == "Publish":
        results = retrieve_publish_trait_data(trait, conn)
    elif trait["cellid"]:
        results = retrieve_cellid_trait_data(trait, conn)
    elif trait["db"]["dataset_type"] == "ProbeSet":
        results = retrieve_probeset_trait_data(trait, conn)
    else:
        results = retrieve_geno_trait_data(trait, conn)

    if results:
        # do something with mysqlid
        mysqlid = results[0]["id"]
        if samplelist:
            data = [
                item for item in
                map(with_samplelist_data_setup(samplelist), results)
                if item is not None]
        else:
            data = [
                item for item in
                map(without_samplelist_data_setup(), results)
                if item is not None]

        return {
            "mysqlid": mysqlid,
            "data": dict(map(
                lambda x: (
                    x["sample_name"],
                    {k: v for k, v in x.items() if x != "sample_name"}),
                data))}
    return {}


def generate_traits_filename(base_path: str = TMPDIR):
    """Generate a unique filename for use with generated traits files."""
    return (
        f"{os.path.abspath(base_path)}/traits_test_file_{random_string(10)}.txt")


def export_informative(trait_data: dict, inc_var: bool = False) -> tuple:
    """
    Export informative strain

    This is a migration of the `exportInformative` function in
    web/webqtl/base/webqtlTrait.py module in GeneNetwork1.

    There is a chance that the original implementation has a bug, especially
    dealing with the `inc_var` value. It the `inc_var` value is meant to control
    the inclusion of the `variance` value, then the current implementation, and
    that one in GN1 have a bug.
    """
    def __exporter__(acc, data_item):
        if not inc_var or data_item["variance"] is not None:
            return (
                acc[0] + (data_item["sample_name"],),
                acc[1] + (data_item["value"],),
                acc[2] + (data_item["variance"],))
        return acc
    return reduce(
        __exporter__,
        filter(lambda td: td["value"] is not None,
               trait_data["data"].values()),
        (tuple(), tuple(), tuple()))