Python union_dicts Examples

Example #1

class ARResultsWrapper(wrap.ResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(tsbase.TimeSeriesResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(tsbase.TimeSeriesResultsWrapper._wrap_methods,
                                     _methods)

Example #2

class RecursiveLSResultsWrapper(MLEResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(MLEResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(MLEResultsWrapper._wrap_methods,
                                     _methods)

Example #3

File: model.py Project: zabop/statsmodels

class ARIMAResultsWrapper(sarimax.SARIMAXResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(sarimax.SARIMAXResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(
        sarimax.SARIMAXResultsWrapper._wrap_methods, _methods)

Example #4

File: tsa_model.py Project: xiaoxiawu/statsmodels

class TimeSeriesResultsWrapper(wrap.ResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(base.LikelihoodResultsWrapper._wrap_attrs,
                                    _attrs)
    _methods = {'predict' : 'dates'}
    _wrap_methods = wrap.union_dicts(base.LikelihoodResultsWrapper._wrap_methods,
                                     _methods)

Example #5

File: exponential_smoothing.py Project: timgates42/statsmodels

class ExponentialSmoothingResultsWrapper(MLEResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(MLEResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(MLEResultsWrapper._wrap_methods,
                                     _methods)

Example #6

class VARMAXResultsWrapper(MLEResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(MLEResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(MLEResultsWrapper._wrap_methods,
                                     _methods)

Example #7

class MLEResultsWrapper(mlemodel.MLEResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(mlemodel.MLEResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(mlemodel.MLEResultsWrapper._wrap_methods,
                                     _methods)

Example #8

File: DynamicRegression.py Project: AliHeggie/DynamicRegression

class DynamicRegressionResultsWrapper(MLEResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(MLEResultsWrapper._wrap_attrs,
                                   _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(MLEResultsWrapper._wrap_methods,
                                     _methods)

Example #9

File: structural.py Project: knut0815/dismalpy

class UnobservedComponentsResultsWrapper(
        mlemodel.MLEResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(
        mlemodel.MLEResultsWrapper._wrap_attrs, _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(
        mlemodel.MLEResultsWrapper._wrap_methods, _methods)

Example #10

class HoltWintersResultsWrapper(ResultsWrapper):
    _attrs = {'fittedvalues': 'rows',
              'level': 'rows',
              'resid': 'rows',
              'season': 'rows',
              'slope': 'rows'}
    _wrap_attrs = union_dicts(ResultsWrapper._wrap_attrs, _attrs)
    _methods = {'predict': 'dates',
                'forecast': 'dates'}
    _wrap_methods = union_dicts(ResultsWrapper._wrap_methods, _methods)

Example #11

File: var_model.py Project: yarikoptic/pystatsmodels

class VARResultsWrapper(wrap.ResultsWrapper):
    _attrs = {'bse' : 'columns_eq', 'cov_params' : 'cov',
              'params' : 'columns_eq', 'pvalues' : 'columns_eq',
              'tvalues' : 'columns_eq', 'sigma_u' : 'cov_eq',
              'sigma_u_mle' : 'cov_eq',
              'stderr' : 'columns_eq'}
    _wrap_attrs = wrap.union_dicts(tsbase.TimeSeriesResultsWrapper._wrap_attrs,
                                    _attrs)
    _methods = {}
    _wrap_methods = wrap.union_dicts(tsbase.TimeSeriesResultsWrapper._wrap_methods,
                                     _methods)
    _wrap_methods.pop('cov_params') # not yet a method in VARResults

Example #12

File: results.py Project: zabop/statsmodels

class HoltWintersResultsWrapper(ResultsWrapper):
    _attrs = {
        "fittedvalues": "rows",
        "level": "rows",
        "resid": "rows",
        "season": "rows",
        "trend": "rows",
        "slope": "rows",
    }
    _wrap_attrs = union_dicts(ResultsWrapper._wrap_attrs, _attrs)
    _methods = {"predict": "dates", "forecast": "dates"}
    _wrap_methods = union_dicts(ResultsWrapper._wrap_methods, _methods)

Example #13

class MLEResultsWrapper(wrap.ResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(tsbase.TimeSeriesResultsWrapper._wrap_attrs,
                                   _attrs)
    # TODO right now, predict with full_results=True can return something other
    # than a time series, so the `attach_dates` call will fail if we have
    # 'predict': 'dates' here. In the future, remove `full_results` and replace
    # it with new methods, e.g. get_prediction, get_forecast, and likely will
    # want those to be a subclass of FilterResults with e.g. confidence
    # intervals calculated and dates attached.
    # Also, need to modify `attach_dates` to account for DataFrames.
    _methods = {'predict': None}
    _wrap_methods = wrap.union_dicts(
        tsbase.TimeSeriesResultsWrapper._wrap_methods, _methods)

Example #14

File: generalized_linear_model.py Project: saurabh14m/statsmodels

class GLMResultsWrapper(lm.RegressionResultsWrapper):
    _attrs = {
        'resid_anscombe' : 'rows',
        'resid_deviance' : 'rows',
        'resid_pearson' : 'rows',
        'resid_response' : 'rows',
        'resid_working' : 'rows'
    }
    _wrap_attrs = wrap.union_dicts(lm.RegressionResultsWrapper._wrap_attrs,
                                   _attrs)

Example #15

class NewsResultsWrapper(wrap.ResultsWrapper):
    _attrs = {}
    _wrap_attrs = wrap.union_dicts(_attrs)

    _methods = {}
    _wrap_methods = wrap.union_dicts(_methods)