def check_csv(csvpath, split=None):
try:
period = int(csvpath.split(".")[-2])
except ValueError:
period = None
_, data, _ = read_csv(csvpath, split=split)
seasons, trend = fit_seasons(data)
assert seasons is None or len(seasons) == period, \
"expected period {}, got {}".format(
period, len(seasons) if seasons else None)
def check_csv(csvpath, split=None):
try:
period = int(csvpath.split(".")[-2])
except ValueError:
period = None
_, data, _ = read_csv(csvpath, split=split)
seasons, trend = fit_seasons(data)
assert seasons is None or len(seasons) == period, \
"expected period {}, got {}".format(
period, len(seasons) if seasons else None)
def main():
import os.path
from optparse import OptionParser
from textwrap import dedent
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
from seasonal.application import read_csv
parser = OptionParser(
usage="usage: %prog [options] csv-files...",
description="Holt-Winters demo using the seasonal package"
)
parser.add_option("--column", default=-1,
help="csv column to use (name or 0-based index, default rightmost)")
parser.add_option("--split", type="float", default=None,
help=("split data at the split*100% or int(split) " +
"point for initialization"))
parser.add_option("--demo", action="store_true",
help="demonstrate with some air passenger data")
(options, args) = parser.parse_args()
if options.demo:
args = [os.path.join(os.path.dirname(seasonal.__file__),
"data/airPassengers.csv")]
if options.split is None:
options.split = 0.20
if not args:
parser.print_help()
exit(-1)
if not plt:
stderr.write(
"Error: matplotlib must be installed\n")
exit(-1)
for csvpath in args:
_, data, column = read_csv(csvpath, column=options.column)
fcast, smoothed = hw(data, options.split)
plt.figure()
plt.title("Holt Winters demonstration")
plt.plot(data, label=column)
plt.plot(fcast, label="forecast")
plt.plot(smoothed, label="smoothed")
leg = plt.legend(loc='upper left')
leg.get_frame().set_alpha(0.5)
plt.show()
def main():
import os.path
from optparse import OptionParser
from textwrap import dedent
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
from seasonal.application import read_csv
parser = OptionParser(
usage="usage: %prog [options] csv-files...",
description="Holt-Winters demo using the seasonal package")
parser.add_option(
"--column",
default=-1,
help="csv column to use (name or 0-based index, default rightmost)")
parser.add_option("--split",
type="float",
default=None,
help=("split data at the split*100% or int(split) " +
"point for initialization"))
parser.add_option("--params",
help=("comma-separated list of alpha, beta, gamma. " +
"default is to estimate these from ALL the data"))
parser.add_option("--demo",
action="store_true",
help="demonstrate with some air passenger data")
(options, args) = parser.parse_args()
if options.demo:
args = [
os.path.join(os.path.dirname(seasonal.__file__),
"data/airPassengers.csv")
]
if options.split is None:
options.split = 0.20
if not args:
parser.print_help()
exit(-1)
if not plt:
stderr.write("Error: matplotlib must be installed\n")
exit(-1)
if options.params is not None:
try:
params = [float(p) for p in options.params.split(',')]
options.params = HWParams(*params)
except Exception:
stderr.write("\nError: --params wants alpha,beta,gamma\n")
parser.print_help()
exit(-1)
for csvpath in args:
index, data, column = read_csv(csvpath, column=options.column)
fcast, smoothed = hw(data, options.split, params=options.params)
plt.figure(1)
plt.subplot(211)
plt.title("Holt Winters for " + os.path.basename(csvpath))
plt.plot(index, data, label=column)
plt.plot(index, fcast, label="forecast")
plt.plot(index, smoothed, label="smoothed")
leg = plt.legend(loc='upper left')
leg.get_frame().set_alpha(0.5)
plt.subplot(212)
plt.title("Forecast Error")
plt.plot(index, fcast - data)
plt.show()
