def main():
util.redirect_iostream()
parser = ArgumentParser(description=native_str("导表工具"))
parser.add_argument("config_file", help=native_str("配置文件路径"))
parser.add_argument("--gen-header",
action="store_true",
help=native_str("根据转换器信息生成Excel表头"))
parser.add_argument("--gen-code",
action="store_true",
help=native_str("生成代码文件"))
parser.add_argument("--export", action="store_true", help=native_str("导表"))
parser.add_argument("--fast-mode",
action="store_true",
help=native_str("快速导表。Excel没有改动就不进行导表。"))
#parser.add_argument("--encode-log", action="store_true", help=native_str("log编码转换"))
parser.add_argument("--force-run",
action="store_true",
help=native_str("出错后仍然继续下去"))
option = parser.parse_args()
#parser.print_help()
try:
load_configure(option.config_file)
except:
traceback.print_exc()
print "Error: Failed to load configure file", option.config_file
return
xlsconfig.FAST_MODE = option.fast_mode
xlsconfig.FORCE_RUN = option.force_run
if not install_package.check_plugin(("openpyxl", )):
return
for generator in xlsconfig.DATA_WRITERS:
util.safe_makedirs(generator["file_path"], not xlsconfig.FAST_MODE)
for generator in xlsconfig.CODE_GENERATORS:
util.safe_makedirs(generator["file_path"], not xlsconfig.FAST_MODE)
if option.gen_header:
import generate_header
generate_header.generate_header()
if option.export or option.gen_code:
export_excel()
if option.gen_code:
import generate_code
generate_code.generate_code()
print "=== 完毕 ===\n"
return
def main():
util.redirect_iostream()
parser = ArgumentParser(description=native_str("导表工具"))
parser.add_argument("config_file", help=native_str("配置文件路径"))
parser.add_argument("--gen-header", action="store_true", help=native_str("根据转换器信息生成Excel表头"))
parser.add_argument("--gen-code", action="store_true", help=native_str("生成代码文件"))
parser.add_argument("--export", action="store_true", help=native_str("导表"))
parser.add_argument("--fast-mode", action="store_true", help=native_str("快速导表。Excel没有改动就不进行导表。"))
parser.add_argument("--force-run", action="store_true", help=native_str("出错后仍然继续下去"))
parser.add_argument("-input", help=native_str("Excel的输入路径"))
parser.add_argument("-output", help=native_str("输出路径"))
parser.add_argument("-temp", help=native_str("临时目录"))
option = parser.parse_args()
#parser.print_help()
try:
load_configure(option.config_file, option)
except:
traceback.print_exc()
print "Error: Failed to load configure file", option.config_file
return
xlsconfig.FAST_MODE = option.fast_mode
xlsconfig.FORCE_RUN = option.force_run
if not install_package.check_plugin(("openpyxl", )):
return
if option.gen_header:
import generate_header
generate_header.generate_header()
if option.export or option.gen_code:
export_excel()
if option.gen_code:
import generate_code
generate_code.generate_code()
print "=== 完毕 ===\n"
return
We\'re going to find the best parameters for your model. This might take some minutes.
Now it's a good time to grab some coffee.
''')
p, d, q, P, D, Q, s = grid_search_arima(train_set, exog_train, range(p+2), range(q+2), range(P+2), range(Q+2), d=d, D=D, s=s)
# Forecasting data
st.markdown('# Out-of-sample Forecast')
# Creating final model
with st.spinner('Training model with entire dataset. Please wait.'):
final_model = train_ts_model(transformation_function(ts), p, d, q, P, D, Q, s, exog_variables=exog_variables, quiet=True)
st.success('Done!')
if type(exog_variables) == type(pd.DataFrame()):
st.write('You are using exogenous variables. We can\'t forecast the future since we don\'t have the exogenous variables for future periods. Adapt the code below to use them.' )
else:
if transformation_function == np.log1p:
forecasts = np.expm1(final_model.forecast(periods_to_forecast))
confidence_interval = np.expm1(final_model.get_forecast(periods_to_forecast).conf_int())
else:
forecasts = final_model.forecast(periods_to_forecast)
confidence_interval = final_model.get_forecast(periods_to_forecast).conf_int()
confidence_interval.columns = ['ci_lower', 'ci_upper']
plot_forecasts(forecasts, confidence_interval, data_frequency)
st.write('# Here\'s your code')
st.markdown(generate_code(filename, ds_column, y, test_stationarity_code, test_set_size,
seasonality, p, d, q, P, D, Q, s, exog_variables_names, transformation_function,
periods_to_forecast, data_frequency))