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def depth_september_average_ground_temperature(self, value=None):
"""Corresponds to IDD Field
`depth_september_average_ground_temperature`
Args:
value (float): value for IDD Field `depth_september_average_ground_temperature`
Unit: C
if `value` is None... |
def depth_october_average_ground_temperature(self, value=None):
"""Corresponds to IDD Field `depth_october_average_ground_temperature`
Args:
value (float): value for IDD Field `depth_october_average_ground_temperature`
Unit: C
if `value` is None it will not b... |
def depth_november_average_ground_temperature(self, value=None):
"""Corresponds to IDD Field `depth_november_average_ground_temperature`
Args:
value (float): value for IDD Field `depth_november_average_ground_temperature`
Unit: C
if `value` is None it will no... |
def depth_december_average_ground_temperature(self, value=None):
"""Corresponds to IDD Field `depth_december_average_ground_temperature`
Args:
value (float): value for IDD Field `depth_december_average_ground_temperature`
Unit: C
if `value` is None it will no... |
def export(self, top=True):
"""Exports object to its string representation.
Args:
top (bool): if True appends `internal_name` before values.
All non list objects should be exported with value top=True,
all list objects, that are embedded in as fields inlist ... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
count = int(vals[i])
i += 1
for _ in range(count):
obj = GroundTemperature()
obj.read(vals[i:i + obj.field_count])
... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
if len(vals[i]) == 0:
self.holiday_name = None
else:
self.holiday_name = vals[i]
i += 1
if len(vals[i]) == 0:
... |
def holiday_name(self, value=None):
"""Corresponds to IDD Field `holiday_name`
Args:
value (str): value for IDD Field `holiday_name`
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
Raises:
... |
def holiday_day(self, value=None):
"""Corresponds to IDD Field `holiday_day`
Args:
value (str): value for IDD Field `holiday_day`
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
Raises:
... |
def export(self, top=True):
"""Exports object to its string representation.
Args:
top (bool): if True appends `internal_name` before values.
All non list objects should be exported with value top=True,
all list objects, that are embedded in as fields inlist ... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
if len(vals[i]) == 0:
self.leapyear_observed = None
else:
self.leapyear_observed = vals[i]
i += 1
if len(vals[i]) =... |
def leapyear_observed(self, value=None):
"""Corresponds to IDD Field `leapyear_observed` Yes if Leap Year will
be observed for this file No if Leap Year days (29 Feb) should be
ignored in this file.
Args:
value (str): value for IDD Field `leapyear_observed`
A... |
def daylight_saving_start_day(self, value=None):
"""Corresponds to IDD Field `daylight_saving_start_day`
Args:
value (str): value for IDD Field `daylight_saving_start_day`
if `value` is None it will not be checked against the
specification and is assumed to b... |
def daylight_saving_end_day(self, value=None):
"""Corresponds to IDD Field `daylight_saving_end_day`
Args:
value (str): value for IDD Field `daylight_saving_end_day`
if `value` is None it will not be checked against the
specification and is assumed to be a mi... |
def export(self, top=True):
"""Exports object to its string representation.
Args:
top (bool): if True appends `internal_name` before values.
All non list objects should be exported with value top=True,
all list objects, that are embedded in as fields inlist ... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
if len(vals[i]) == 0:
self.comments_1 = None
else:
self.comments_1 = vals[i]
i += 1 |
def comments_1(self, value=None):
"""Corresponds to IDD Field `comments_1`
Args:
value (str): value for IDD Field `comments_1`
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
Raises:
... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
if len(vals[i]) == 0:
self.comments_2 = None
else:
self.comments_2 = vals[i]
i += 1 |
def comments_2(self, value=None):
"""Corresponds to IDD Field `comments_2`
Args:
value (str): value for IDD Field `comments_2`
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
Raises:
... |
def export(self, top=True):
"""Exports object to its string representation.
Args:
top (bool): if True appends `internal_name` before values.
All non list objects should be exported with value top=True,
all list objects, that are embedded in as fields inlist ... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
if len(vals[i]) == 0:
self.number_of_records_per_hour = None
else:
self.number_of_records_per_hour = vals[i]
i += 1
... |
def number_of_records_per_hour(self, value=None):
"""Corresponds to IDD Field `number_of_records_per_hour`
Args:
value (int): value for IDD Field `number_of_records_per_hour`
if `value` is None it will not be checked against the
specification and is assumed t... |
def data_period_name_or_description(self, value=None):
"""Corresponds to IDD Field `data_period_name_or_description`
Args:
value (str): value for IDD Field `data_period_name_or_description`
if `value` is None it will not be checked against the
specification a... |
def data_period_start_day_of_week(self, value=None):
"""Corresponds to IDD Field `data_period_start_day_of_week`
Args:
value (str): value for IDD Field `data_period_start_day_of_week`
Accepted values are:
- Sunday
- Monday
... |
def data_period_start_day(self, value=None):
"""Corresponds to IDD Field `data_period_start_day`
Args:
value (str): value for IDD Field `data_period_start_day`
if `value` is None it will not be checked against the
specification and is assumed to be a missing ... |
def data_period_end_day(self, value=None):
"""Corresponds to IDD Field `data_period_end_day`
Args:
value (str): value for IDD Field `data_period_end_day`
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
... |
def export(self, top=True):
"""Exports object to its string representation.
Args:
top (bool): if True appends `internal_name` before values.
All non list objects should be exported with value top=True,
all list objects, that are embedded in as fields inlist ... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
count = int(vals[i])
i += 1
for _ in range(count):
obj = DataPeriod()
obj.read(vals[i:i + obj.field_count])
sel... |
def read(self, vals):
"""Read values.
Args:
vals (list): list of strings representing values
"""
i = 0
if len(vals[i]) == 0:
self.year = None
else:
self.year = vals[i]
i += 1
if len(vals[i]) == 0:
self.mont... |
def year(self, value=None):
"""Corresponds to IDD Field `year`
Args:
value (int): value for IDD Field `year`
if `value` is None it will not be checked against the
specification and is assumed to be a missing value
Raises:
ValueError: if `... |
def month(self, value=None):
"""Corresponds to IDD Field `month`
Args:
value (int): value for IDD Field `month`
value >= 1
value <= 12
if `value` is None it will not be checked against the
specification and is assumed to be a m... |
def day(self, value=None):
"""Corresponds to IDD Field `day`
Args:
value (int): value for IDD Field `day`
value >= 1
value <= 31
if `value` is None it will not be checked against the
specification and is assumed to be a missing... |
def hour(self, value=None):
"""Corresponds to IDD Field `hour`
Args:
value (int): value for IDD Field `hour`
value >= 1
value <= 24
if `value` is None it will not be checked against the
specification and is assumed to be a miss... |
def minute(self, value=None):
"""Corresponds to IDD Field `minute`
Args:
value (int): value for IDD Field `minute`
value >= 0
value <= 60
if `value` is None it will not be checked against the
specification and is assumed to be ... |
def data_source_and_uncertainty_flags(self, value=None):
"""Corresponds to IDD Field `data_source_and_uncertainty_flags` Initial
day of weather file is checked by EnergyPlus for validity (as shown
below) Each field is checked for "missing" as shown below. Reasonable
values, calculated va... |
def dry_bulb_temperature(self, value=99.9):
"""Corresponds to IDD Field `dry_bulb_temperature`
Args:
value (float): value for IDD Field `dry_bulb_temperature`
Unit: C
value > -70.0
value < 70.0
Missing value: 99.9
... |
def dew_point_temperature(self, value=99.9):
"""Corresponds to IDD Field `dew_point_temperature`
Args:
value (float): value for IDD Field `dew_point_temperature`
Unit: C
value > -70.0
value < 70.0
Missing value: 99.9
... |
def relative_humidity(self, value=999):
"""Corresponds to IDD Field `relative_humidity`
Args:
value (int): value for IDD Field `relative_humidity`
value >= 0
value <= 110
Missing value: 999
if `value` is None it will not be che... |
def atmospheric_station_pressure(self, value=999999):
"""Corresponds to IDD Field `atmospheric_station_pressure`
Args:
value (int): value for IDD Field `atmospheric_station_pressure`
Unit: Pa
value > 31000
value < 120000
Missin... |
def extraterrestrial_horizontal_radiation(self, value=9999.0):
"""Corresponds to IDD Field `extraterrestrial_horizontal_radiation`
Args:
value (float): value for IDD Field `extraterrestrial_horizontal_radiation`
Unit: Wh/m2
value >= 0.0
Missin... |
def extraterrestrial_direct_normal_radiation(self, value=9999.0):
"""Corresponds to IDD Field `extraterrestrial_direct_normal_radiation`
Args:
value (float): value for IDD Field `extraterrestrial_direct_normal_radiation`
Unit: Wh/m2
value >= 0.0
... |
def horizontal_infrared_radiation_intensity(self, value=9999.0):
"""Corresponds to IDD Field `horizontal_infrared_radiation_intensity`
Args:
value (float): value for IDD Field `horizontal_infrared_radiation_intensity`
Unit: Wh/m2
value >= 0.0
... |
def global_horizontal_radiation(self, value=9999.0):
"""Corresponds to IDD Field `global_horizontal_radiation`
Args:
value (float): value for IDD Field `global_horizontal_radiation`
Unit: Wh/m2
value >= 0.0
Missing value: 9999.0
... |
def direct_normal_radiation(self, value=9999.0):
"""Corresponds to IDD Field `direct_normal_radiation`
Args:
value (float): value for IDD Field `direct_normal_radiation`
Unit: Wh/m2
value >= 0.0
Missing value: 9999.0
if `value`... |
def diffuse_horizontal_radiation(self, value=9999.0):
"""Corresponds to IDD Field `diffuse_horizontal_radiation`
Args:
value (float): value for IDD Field `diffuse_horizontal_radiation`
Unit: Wh/m2
value >= 0.0
Missing value: 9999.0
... |
def global_horizontal_illuminance(self, value=999999.0):
""" Corresponds to IDD Field `global_horizontal_illuminance`
will be missing if >= 999900
Args:
value (float): value for IDD Field `global_horizontal_illuminance`
Unit: lux
value >= 0.0
... |
def direct_normal_illuminance(self, value=999999.0):
""" Corresponds to IDD Field `direct_normal_illuminance`
will be missing if >= 999900
Args:
value (float): value for IDD Field `direct_normal_illuminance`
Unit: lux
value >= 0.0
Mis... |
def diffuse_horizontal_illuminance(self, value=999999.0):
""" Corresponds to IDD Field `diffuse_horizontal_illuminance`
will be missing if >= 999900
Args:
value (float): value for IDD Field `diffuse_horizontal_illuminance`
Unit: lux
value >= 0.0
... |
def zenith_luminance(self, value=9999.0):
""" Corresponds to IDD Field `zenith_luminance`
will be missing if >= 9999
Args:
value (float): value for IDD Field `zenith_luminance`
Unit: Cd/m2
value >= 0.0
Missing value: 9999.0
... |
def wind_direction(self, value=999.0):
"""Corresponds to IDD Field `wind_direction`
Args:
value (float): value for IDD Field `wind_direction`
Unit: degrees
value >= 0.0
value <= 360.0
Missing value: 999.0
if `va... |
def wind_speed(self, value=999.0):
"""Corresponds to IDD Field `wind_speed`
Args:
value (float): value for IDD Field `wind_speed`
Unit: m/s
value >= 0.0
value <= 40.0
Missing value: 999.0
if `value` is None it w... |
def total_sky_cover(self, value=99.0):
"""Corresponds to IDD Field `total_sky_cover` This is the value for
total sky cover (tenths of coverage). (i.e. 1 is 1/10 covered. 10 is
total coverage). (Amount of sky dome in tenths covered by clouds or
obscuring phenomena at the hour indicated a... |
def opaque_sky_cover(self, value=99.0):
"""Corresponds to IDD Field `opaque_sky_cover` This is the value for
opaque sky cover (tenths of coverage). (i.e. 1 is 1/10 covered. 10 is
total coverage). (Amount of sky dome in tenths covered by clouds or
obscuring phenomena that prevent observ... |
def visibility(self, value=9999.0):
"""Corresponds to IDD Field `visibility` This is the value for
visibility in km. (Horizontal visibility at the time indicated.)
Args:
value (float): value for IDD Field `visibility`
Unit: km
Missing value: 9999.0
... |
def ceiling_height(self, value=99999.0):
"""Corresponds to IDD Field `ceiling_height` This is the value for
ceiling height in m. (77777 is unlimited ceiling height. 88888 is
cirroform ceiling.) It is not currently used in EnergyPlus
calculations.
Args:
value (float):... |
def present_weather_observation(self, value=None):
"""Corresponds to IDD Field `present_weather_observation` If the value
of the field is 0, then the observed weather codes are taken from the
following field. If the value of the field is 9, then "missing" weather
is assumed. Since the pr... |
def present_weather_codes(self, value=None):
"""Corresponds to IDD Field `present_weather_codes`
Args:
value (int): value for IDD Field `present_weather_codes`
if `value` is None it will not be checked against the
specification and is assumed to be a missing ... |
def precipitable_water(self, value=999.0):
"""Corresponds to IDD Field `precipitable_water`
Args:
value (float): value for IDD Field `precipitable_water`
Unit: mm
Missing value: 999.0
if `value` is None it will not be checked against the
... |
def aerosol_optical_depth(self, value=0.999):
"""Corresponds to IDD Field `aerosol_optical_depth`
Args:
value (float): value for IDD Field `aerosol_optical_depth`
Unit: thousandths
Missing value: 0.999
if `value` is None it will not be checked... |
def snow_depth(self, value=999.0):
"""Corresponds to IDD Field `snow_depth`
Args:
value (float): value for IDD Field `snow_depth`
Unit: cm
Missing value: 999.0
if `value` is None it will not be checked against the
specification... |
def days_since_last_snowfall(self, value=99):
"""Corresponds to IDD Field `days_since_last_snowfall`
Args:
value (int): value for IDD Field `days_since_last_snowfall`
Missing value: 99
if `value` is None it will not be checked against the
spec... |
def albedo(self, value=999.0):
"""Corresponds to IDD Field `albedo`
Args:
value (float): value for IDD Field `albedo`
Missing value: 999.0
if `value` is None it will not be checked against the
specification and is assumed to be a missing value... |
def liquid_precipitation_depth(self, value=999.0):
"""Corresponds to IDD Field `liquid_precipitation_depth`
Args:
value (float): value for IDD Field `liquid_precipitation_depth`
Unit: mm
Missing value: 999.0
if `value` is None it will not be c... |
def liquid_precipitation_quantity(self, value=99.0):
"""Corresponds to IDD Field `liquid_precipitation_quantity`
Args:
value (float): value for IDD Field `liquid_precipitation_quantity`
Unit: hr
Missing value: 99.0
if `value` is None it will n... |
def export(self, top=True):
"""Exports object to its string representation.
Args:
top (bool): if True appends `internal_name` before values.
All non list objects should be exported with value top=True,
all list objects, that are embedded in as fields inlist ... |
def add_weatherdata(self, data):
"""Appends weather data.
Args:
data (WeatherData): weather data object
"""
if not isinstance(data, WeatherData):
raise ValueError('Weather data need to be of type WeatherData')
self._data["WEATHER DATA"].append(data) |
def save(self, path, check=True):
"""Save WeatherData in EPW format to path.
Args:
path (str): path where EPW file should be saved
"""
with open(path, 'w') as f:
if check:
if ("LOCATION" not in self._data or
self._data["LO... |
def _create_datadict(cls, internal_name):
"""Creates an object depending on `internal_name`
Args:
internal_name (str): IDD name
Raises:
ValueError: if `internal_name` cannot be matched to a data dictionary object
"""
if internal_name == "LOCATION":
... |
def read(self, path):
"""Read EPW weather data from path.
Args:
path (str): path to read weather data from
"""
with open(path, "r") as f:
for line in f:
line = line.strip()
match_obj_name = re.search(r"^([A-Z][A-Z/ \d]+),", line)
... |
def display_url(target):
"""Displaying URL in an IPython notebook to allow the user to click and check on information. With thanks to Fernando Perez for putting together the implementation!
:param target: the url to display.
:type target: string."""
prefix = u"http://" if not target.startswith("http") ... |
def iframe_url(target, width=500, height=400, scrolling=True, border=0, frameborder=0):
"""Produce an iframe for displaying an item in HTML window.
:param target: the target url.
:type target: string
:param width: the width of the iframe (default 500).
:type width: int
:param height: the height ... |
def display_iframe_url(target, **kwargs):
"""Display the contents of a URL in an IPython notebook.
:param target: the target url.
:type target: string
.. seealso:: `iframe_url()` for additional arguments."""
txt = iframe_url(target, **kwargs)
display(HTML(txt)) |
def display_google_book(id, page=None, width=700, height=500, **kwargs):
"""Display an embedded version of a Google book.
:param id: the id of the google book to display.
:type id: string
:param page: the start page for the book.
:type id: string or int."""
if isinstance(page, int):
url ... |
def code_toggle(start_show=False, message=None):
"""Toggling on and off code in a notebook.
:param start_show: Whether to display the code or not on first load (default is False).
:type start_show: bool
:param message: the message used to toggle display of the code.
:type message: string
The t... |
def display_prediction(basis, num_basis=4, wlim=(-1.,1.), fig=None, ax=None, xlim=None, ylim=None, num_points=1000, offset=0.0, **kwargs):
"""Interactive widget for displaying a prediction function based on summing separate basis functions.
:param basis: a function handle that calls the basis functions.
:ty... |
def display_plots(filebase, directory=None, width=700, height=500, **kwargs):
"""Display a series of plots controlled by sliders. The function relies on Python string format functionality to index through a series of plots."""
def show_figure(filebase, directory, **kwargs):
"""Helper function to load in... |
def answer(part, module='mlai2014.json'):
"""Returns the answers to the lab classes."""
marks = json.load(open(os.path.join(data_directory, module), 'rb'))
return marks['Lab ' + str(part+1)] |
def latex(self):
"""Gives a latex representation of the assessment."""
output = self.latex_preamble
output += self._repr_latex_()
output += self.latex_post
return output |
def html(self):
"""Gives an html representation of the assessment."""
output = self.html_preamble
output += self._repr_html_()
output += self.html_post
return output |
def marksheet(self):
"""Returns an pandas empty dataframe object containing rows and columns for marking. This can then be passed to a google doc that is distributed to markers for editing with the mark for each section."""
columns=['Number', 'Question', 'Correct (a fraction)', 'Max Mark', 'Comments']
... |
def total_marks(self):
"""Compute the total mark for the assessment."""
total = 0
for answer in self.answers:
for number, part in enumerate(answer):
if number>0:
if part[2]>0:
total+=part[2]
return total |
def download(name, course, github='SheffieldML/notebook/master/lab_classes/'):
"""Download a lab class from the relevant course
:param course: the course short name to download the class from.
:type course: string
:param reference: reference to the course for downloading the class.
:type reference: ... |
def read(self, vals):
""" Read values
Args:
vals (list): list of strings representing values
"""
i = 0
{%- for field in fields %}
{%- if field.is_list %}
count = int(vals[i])
i += 1
for _ in range(count):
obj = {{field.... |
def permute(num):
"Permutation for randomizing data order."
if permute_data:
return np.random.permutation(num)
else:
logging.warning("Warning not permuting data")
return np.arange(num) |
def discrete(cats, name='discrete'):
"""Return a class category that shows the encoding"""
import json
ks = list(cats)
for key in ks:
if isinstance(key, bytes):
cats[key.decode('utf-8')] = cats.pop(key)
return 'discrete(' + json.dumps([cats, name]) + ')' |
def prompt_stdin(prompt):
"""Ask user for agreeing to data set licenses."""
# raw_input returns the empty string for "enter"
yes = set(['yes', 'y'])
no = set(['no','n'])
try:
print(prompt)
if sys.version_info>=(3,0):
choice = input().lower()
else:
cho... |
def clear_cache(dataset_name=None):
"""Remove a data set from the cache"""
dr = data_resources[dataset_name]
if 'dirs' in dr:
for dirs, files in zip(dr['dirs'], dr['files']):
for dir, file in zip(dirs, files):
path = os.path.join(data_path, dataset_name, dir, file)
... |
def data_available(dataset_name=None):
"""Check if the data set is available on the local machine already."""
dr = data_resources[dataset_name]
if 'dirs' in dr:
for dirs, files in zip(dr['dirs'], dr['files']):
for dir, file in zip(dirs, files):
if not os.path.exists(os.pa... |
def download_data(dataset_name=None, prompt=prompt_stdin):
"""Check with the user that the are happy with terms and conditions for the data set, then download it."""
dr = data_resources[dataset_name]
if not authorize_download(dataset_name, prompt=prompt):
raise Exception("Permission to down... |
def df2arff(df, dataset_name, pods_data):
"""Write an arff file from a data set loaded in from pods"""
def java_simple_date(date_format):
date_format = date_format.replace('%Y', 'yyyy').replace('%m', 'MM').replace('%d', 'dd').replace('%H', 'HH')
return date_format.replace('%h', 'hh').replace('%M... |
def to_arff(dataset, **kwargs):
"""Take a pods data set and write it as an ARFF file"""
pods_data = dataset(**kwargs)
vals = list(kwargs.values())
for i, v in enumerate(vals):
if isinstance(v, list):
vals[i] = '|'.join(v)
else:
vals[i] = str(v)
args = '_'.join... |
def epomeo_gpx(data_set='epomeo_gpx', sample_every=4):
"""Data set of three GPS traces of the same movement on Mt Epomeo in Ischia. Requires gpxpy to run."""
import gpxpy
import gpxpy.gpx
if not data_available(data_set):
download_data(data_set)
files = ['endomondo_1', 'endomondo_2', 'garmin_... |
def pmlr(volumes='all', data_set='pmlr'):
"""Abstracts from the Proceedings of Machine Learning Research"""
if not data_available(data_set):
download_data(data_set)
proceedings_file = open(os.path.join(data_path, data_set, 'proceedings.yaml'), 'r')
import yaml
proceedings = yaml.loa... |
def football_data(season='1617', data_set='football_data'):
"""Football data from English games since 1993. This downloads data from football-data.co.uk for the given season. """
league_dict = {'E0':0, 'E1':1, 'E2': 2, 'E3': 3, 'EC':4}
def league2num(string):
if isinstance(string, bytes):
... |
def lee_yeast_ChIP(data_set='lee_yeast_ChIP'):
"""Yeast ChIP data from Lee et al."""
if not data_available(data_set):
download_data(data_set)
from pandas import read_csv
dir_path = os.path.join(data_path, data_set)
filename = os.path.join(dir_path, 'binding_by_gene.tsv')
S = read_csv(fil... |
def google_trends(query_terms=['big data', 'machine learning', 'data science'], data_set='google_trends', refresh_data=False):
"""
Data downloaded from Google trends for given query terms. Warning,
if you use this function multiple times in a row you get blocked
due to terms of service violations.
... |
def osu_run1(data_set='osu_run1', sample_every=4):
"""Ohio State University's Run1 motion capture data set."""
path = os.path.join(data_path, data_set)
if not data_available(data_set):
import zipfile
download_data(data_set)
zip = zipfile.ZipFile(os.path.join(data_path, data_set, 'run... |
def toy_linear_1d_classification(seed=default_seed):
"""Simple classification data in one dimension for illustrating models."""
def sample_class(f):
p = 1. / (1. + np.exp(-f))
c = np.random.binomial(1, p)
c = np.where(c, 1, -1)
return c
np.random.seed(seed=seed)
x1 = np.... |
def airline_delay(data_set='airline_delay', num_train=700000, num_test=100000, seed=default_seed):
"""Airline delay data used in Gaussian Processes for Big Data by Hensman, Fusi and Lawrence"""
if not data_available(data_set):
download_data(data_set)
dir_path = os.path.join(data_path, data_set)
... |
def olympic_sprints(data_set='rogers_girolami_data'):
"""All olympics sprint winning times for multiple output prediction."""
X = np.zeros((0, 2))
Y = np.zeros((0, 1))
cats = {}
for i, dataset in enumerate([olympic_100m_men,
olympic_100m_women,
... |
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