def call_tsne(self, other_args: List[str]):
"""Process tsne command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="tsne",
description=
"""Get similar companies to compare with using sklearn TSNE.""",
)
parser.add_argument(
"-l",
"--learnrate",
default=200,
dest="lr",
type=check_non_negative,
help="TSNE Learning rate. Typical values are between 50 and 200",
)
parser.add_argument("-p",
"--no_plot",
action="store_true",
default=False,
dest="no_plot")
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
self.similar = yahoo_finance_model.get_sp500_comps_tsne(
self.ticker, lr=ns_parser.lr, no_plot=ns_parser.no_plot)
print(f"[ML] Similar Companies: {', '.join(self.similar)}", "\n")
except Exception as e:
print(e, "\n")
def call_tsne(self, other_args: List[str]):
"""Process tsne command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="tsne",
description=
"""Get similar companies to compare with using sklearn TSNE.""",
)
parser.add_argument(
"-r",
"--learnrate",
default=200,
dest="lr",
type=check_non_negative,
help="TSNE Learning rate. Typical values are between 50 and 200",
)
parser.add_argument(
"-l",
"--limit",
default=10,
dest="limit",
type=check_positive,
help=
"Limit of stocks to retrieve. The subsample will occur randomly.",
)
parser.add_argument("-p",
"--no_plot",
action="store_true",
default=False,
dest="no_plot")
if other_args and "-" not in other_args[0][0]:
other_args.insert(0, "-l")
ns_parser = parse_known_args_and_warn(parser, other_args)
if ns_parser:
if self.ticker:
self.similar = yahoo_finance_model.get_sp500_comps_tsne(
self.ticker,
lr=ns_parser.lr,
no_plot=ns_parser.no_plot,
num_tickers=ns_parser.limit,
)
self.similar = [self.ticker] + self.similar
console.print(
f"[ML] Similar Companies: {', '.join(self.similar)}", "\n")
else:
console.print(
"You need to 'set' a ticker to get similar companies from first!"
)
def test_get_sp500_comps_tsne(mocker, recorder):
# FORCE SINGLE THREADING
yf_download = yahoo_finance_model.yf.download
def mock_yf_download(*args, **kwargs):
kwargs["threads"] = False
return yf_download(*args, **kwargs)
mocker.patch("yfinance.download", side_effect=mock_yf_download)
mocker.patch(
"gamestonk_terminal.stocks.comparison_analysis.yahoo_finance_model.normalize",
side_effect=lambda x: x,
)
mocker.patch("matplotlib.pyplot.show")
mocker.patch(
"sklearn.manifold.TSNE.fit_transform",
side_effect=lambda x: np.full((len(x), 2), 1),
)
result_df = yahoo_finance_model.get_sp500_comps_tsne(
ticker="TOT.TO",
)
recorder.capture(result_df)