Python SimpleTable.extend_right方法代码示例

# 需要导入模块: from statsmodels.iolib.table import SimpleTable [as 别名]
# 或者: from statsmodels.iolib.table.SimpleTable import extend_right [as 别名]
    def test_simple_table_2(self):
        #  Test SimpleTable.extend_right()
        desired = '''
=============================================================
           header s1 header d1            header s2 header d2
-------------------------------------------------------------
stub R1 C1  10.30312  10.73999 stub R1 C2  50.95038  50.65765
stub R2 C1  90.30312  90.73999 stub R2 C2  40.95038  40.65765
-------------------------------------------------------------
'''
        data1 = [[10.30312, 10.73999], [90.30312, 90.73999]]
        data2 = [[50.95038, 50.65765], [40.95038, 40.65765]]
        stubs1 = ['stub R1 C1', 'stub R2 C1']
        stubs2 = ['stub R1 C2', 'stub R2 C2']
        header1 = ['header s1', 'header d1']
        header2 = ['header s2', 'header d2']
        actual1 = SimpleTable(data1, header1, stubs1, txt_fmt=default_txt_fmt)
        actual2 = SimpleTable(data2, header2, stubs2, txt_fmt=default_txt_fmt)
        actual1.extend_right(actual2)
        actual = '\n%s\n' % actual1.as_text()
        assert_equal(desired, str(actual))

# 需要导入模块: from statsmodels.iolib.table import SimpleTable [as 别名]
# 或者: from statsmodels.iolib.table.SimpleTable import extend_right [as 别名]

#.........这里部分代码省略.........
          ('Model:', lambda: [results.model.__class__.__name__]),
          #('Model type:', lambda: [results.model.__class__.__name__]),
          ('Date:', lambda: [date]),
          ('Time:', lambda: time_of_day),
          ('Number of Obs:', lambda: [results.nobs]),
          #('No. of Observations:', lambda: ["%#6d" % results.nobs]),
          ('No. Observations:', lambda: ["%#6d" % results.nobs]),
          #('Df model:', lambda: [results.df_model]),
          ('Df Model:', lambda: ["%#6d" % results.df_model]),
          #TODO: check when we have non-integer df
          ('Df Residuals:', lambda: ["%#6d" % results.df_resid]),
          #('Df resid:', lambda: [results.df_resid]),
          #('df resid:', lambda: [results.df_resid]), #check capitalization
          ('Log-Likelihood:', lambda: ["%#8.5g" % results.llf]) #doesn't exist for RLM - exception
          #('Method:', lambda: [???]), #no default for this
          ])

    if title is None:
        title = results.model.__class__.__name__ + 'Regression Results'

    if gen_left is None:
        #default: General part of the summary table, Applicable to all? models
        gen_left = [('Dep. Variable:', None),
                    ('Model type:', None),
                    ('Date:', None),
                    ('No. Observations:', None)
                    ('Df model:', None),
                    ('Df resid:', None)]

        try:
            llf = results.llf
            gen_left.append(('Log-Likelihood', None))
        except: #AttributeError, NotImplementedError
            pass

        gen_right = []


    gen_title = title
    gen_header = None

    #needed_values = [k for k,v in gleft + gright if v is None] #not used anymore
    #replace missing (None) values with default values
    gen_left_ = []
    for item, value in gen_left:
        if value is None:
            value = default_items[item]()  #let KeyErrors raise exception
        gen_left_.append((item, value))
    gen_left = gen_left_

    if gen_right:
        gen_right_ = []
        for item, value in gen_right:
            if value is None:
                value = default_items[item]()  #let KeyErrors raise exception
            gen_right_.append((item, value))
        gen_right = gen_right_

    #check
    missing_values = [k for k,v in gen_left + gen_right if v is None]
    assert missing_values == [], missing_values

    #pad both tables to equal number of rows
    if gen_right:
        if len(gen_right) < len(gen_left):
            #fill up with blank lines to same length
            gen_right += [(' ', ' ')] * (len(gen_left) - len(gen_right))
        elif len(gen_right) > len(gen_left):
            #fill up with blank lines to same length, just to keep it symmetric
            gen_left += [(' ', ' ')] * (len(gen_right) - len(gen_left))

        #padding in SimpleTable doesn't work like I want
        #force extra spacing and exact string length in right table
        gen_right = [('%-21s' % ('  '+k), v) for k,v in gen_right]
        gen_stubs_right, gen_data_right = zip_longest(*gen_right) #transpose row col
        gen_table_right = SimpleTable(gen_data_right,
                                      gen_header,
                                      gen_stubs_right,
                                      title = gen_title,
                                      txt_fmt = fmt_2cols #gen_fmt
                                      )
    else:
        gen_table_right = []  #because .extend_right seems works with []


    #moved below so that we can pad if needed to match length of gen_right
    #transpose rows and columns, `unzip`
    gen_stubs_left, gen_data_left = zip_longest(*gen_left) #transpose row col

    gen_table_left = SimpleTable(gen_data_left,
                                 gen_header,
                                 gen_stubs_left,
                                 title = gen_title,
                                 txt_fmt = fmt_2cols
                                 )

    gen_table_left.extend_right(gen_table_right)
    general_table = gen_table_left

    return general_table #, gen_table_left, gen_table_right

# 需要导入模块: from statsmodels.iolib.table import SimpleTable [as 别名]
# 或者: from statsmodels.iolib.table.SimpleTable import extend_right [as 别名]

#.........这里部分代码省略.........
##    gen_stubs_left = ('Model type:',
##                      'Date:',
##                      'Dependent Variable:',
##                      'df model'
##                  )
##    gen_data_left = [[modeltype],
##                     [date],
##                     yname, #What happens with multiple names?
##                     [df_model]
##                     ]
    gen_table_left = SimpleTable(gen_data_left,
                                 gen_header,
                                 gen_stubs_left,
                                 title = gen_title,
                                 txt_fmt = gen_fmt
                                 )

    gen_stubs_right = ('Method:',
                      'Time:',
                      'Number of Obs:',
                      'df resid'
                      )
    gen_data_right = ([modeltype], #was dist family need to look at more
                      time_of_day,
                      [nobs],
                      [df_resid]
                      )
    gen_table_right = SimpleTable(gen_data_right,
                                 gen_header,
                                 gen_stubs_right,
                                 title = gen_title,
                                 txt_fmt = gen_fmt
                                 )
    gen_table_left.extend_right(gen_table_right)
    general_table = gen_table_left

    #Parameters part of the summary table
    #------------------------------------
    #Note: this is not necessary since we standardized names, only t versus normal
    tstats = {'OLS' : self.t(),
            'GLS' : self.t(),
            'GLSAR' : self.t(),
            'WLS' : self.t(),
            'RLM' : self.t(),
            'GLM' : self.t()
            }
    prob_stats = {'OLS' : self.pvalues,
                 'GLS' : self.pvalues,
                 'GLSAR' : self.pvalues,
                 'WLS' : self.pvalues,
                 'RLM' : self.pvalues,
                 'GLM' : self.pvalues
                }
    #Dictionary to store the header names for the parameter part of the
    #summary table. look up by modeltype
    alp = str((1-alpha)*100)+'%'
    param_header = {
         'OLS'   : ['coef', 'std err', 't', 'P>|t|', alp + ' Conf. Interval'],
         'GLS'   : ['coef', 'std err', 't', 'P>|t|', alp + ' Conf. Interval'],
         'GLSAR' : ['coef', 'std err', 't', 'P>|t|', alp + ' Conf. Interval'],
         'WLS'   : ['coef', 'std err', 't', 'P>|t|', alp + ' Conf. Interval'],
         'GLM'   : ['coef', 'std err', 't', 'P>|t|', alp + ' Conf. Interval'], #glm uses t-distribution
         'RLM'   : ['coef', 'std err', 'z', 'P>|z|', alp + ' Conf. Interval']  #checke z
                   }
    params_stubs = xname
    params = self.params

# 需要导入模块: from statsmodels.iolib.table import SimpleTable [as 别名]
# 或者: from statsmodels.iolib.table.SimpleTable import extend_right [as 别名]
    def summary(self):
        """
        Constructs a summary of the results from a fit model.

        Returns
        -------
        summary : Summary instance
            Object that contains tables and facilitated export to text, html or
            latex
        """
        # Summary layout
        # 1. Overall information
        # 2. Mean parameters
        # 3. Volatility parameters
        # 4. Distribution parameters
        # 5. Notes

        model = self.model
        model_name = model.name + ' - ' + model.volatility.name

        # Summary Header
        top_left = [('Dep. Variable:', self._dep_name),
                    ('Mean Model:', model.name),
                    ('Vol Model:', model.volatility.name),
                    ('Distribution:', model.distribution.name),
                    ('Method:', 'User-specified Parameters'),
                    ('', ''),
                    ('Date:', self._datetime.strftime('%a, %b %d %Y')),
                    ('Time:', self._datetime.strftime('%H:%M:%S'))]

        top_right = [('R-squared:', '--'),
                     ('Adj. R-squared:', '--'),
                     ('Log-Likelihood:', '%#10.6g' % self.loglikelihood),
                     ('AIC:', '%#10.6g' % self.aic),
                     ('BIC:', '%#10.6g' % self.bic),
                     ('No. Observations:', self._nobs),
                     ('', ''),
                     ('', ''),]

        title = model_name + ' Model Results'
        stubs = []
        vals = []
        for stub, val in top_left:
            stubs.append(stub)
            vals.append([val])
        table = SimpleTable(vals, txt_fmt=fmt_2cols, title=title, stubs=stubs)

        # create summary table instance
        smry = Summary()
        # Top Table
        # Parameter table
        fmt = fmt_2cols
        fmt['data_fmts'][1] = '%18s'

        top_right = [('%-21s' % ('  ' + k), v) for k, v in top_right]
        stubs = []
        vals = []
        for stub, val in top_right:
            stubs.append(stub)
            vals.append([val])
        table.extend_right(SimpleTable(vals, stubs=stubs))
        smry.tables.append(table)

        stubs = self._names
        header = ['coef']
        vals = (self.params,)
        formats = [(10, 4)]
        pos = 0
        param_table_data = []
        for _ in range(len(vals[0])):
            row = []
            for i, val in enumerate(vals):
                if isinstance(val[pos], np.float64):
                    converted = format_float_fixed(val[pos], *formats[i])
                else:
                    converted = val[pos]
                row.append(converted)
            pos += 1
            param_table_data.append(row)

        mc = self.model.num_params
        vc = self.model.volatility.num_params
        dc = self.model.distribution.num_params
        counts = (mc, vc, dc)
        titles = ('Mean Model', 'Volatility Model', 'Distribution')
        total = 0
        for title, count in zip(titles, counts):
            if count == 0:
                continue

            table_data = param_table_data[total:total + count]
            table_stubs = stubs[total:total + count]
            total += count
            table = SimpleTable(table_data,
                                stubs=table_stubs,
                                txt_fmt=fmt_params,
                                headers=header, title=title)
            smry.tables.append(table)

        extra_text = ('Results generated with user-specified parameters.',
#.........这里部分代码省略.........

# 需要导入模块: from statsmodels.iolib.table import SimpleTable [as 别名]
# 或者: from statsmodels.iolib.table.SimpleTable import extend_right [as 别名]
    def summary(self):
        """
        Constructs a summary of the results from a fit model.

        Returns
        -------
        summary : Summary instance
            Object that contains tables and facilitated export to text, html or
            latex
        """
        # Summary layout
        # 1. Overall information
        # 2. Mean parameters
        # 3. Volatility parameters
        # 4. Distribution parameters
        # 5. Notes

        model = self.model
        model_name = model.name + " - " + model.volatility.name

        # Summary Header
        top_left = [
            ("Dep. Variable:", self._dep_name),
            ("Mean Model:", model.name),
            ("Vol Model:", model.volatility.name),
            ("Distribution:", model.distribution.name),
            ("Method:", "User-specified Parameters"),
            ("", ""),
            ("Date:", self._datetime.strftime("%a, %b %d %Y")),
            ("Time:", self._datetime.strftime("%H:%M:%S")),
        ]

        top_right = [
            ("R-squared:", "--"),
            ("Adj. R-squared:", "--"),
            ("Log-Likelihood:", "%#10.6g" % self.loglikelihood),
            ("AIC:", "%#10.6g" % self.aic),
            ("BIC:", "%#10.6g" % self.bic),
            ("No. Observations:", self._nobs),
            ("", ""),
            ("", ""),
        ]

        title = model_name + " Model Results"
        stubs = []
        vals = []
        for stub, val in top_left:
            stubs.append(stub)
            vals.append([val])
        table = SimpleTable(vals, txt_fmt=fmt_2cols, title=title, stubs=stubs)

        # create summary table instance
        smry = Summary()
        # Top Table
        # Parameter table
        fmt = fmt_2cols
        fmt["data_fmts"][1] = "%18s"

        top_right = [("%-21s" % ("  " + k), v) for k, v in top_right]
        stubs = []
        vals = []
        for stub, val in top_right:
            stubs.append(stub)
            vals.append([val])
        table.extend_right(SimpleTable(vals, stubs=stubs))
        smry.tables.append(table)

        stubs = self._names
        header = ["coef"]
        vals = (self.params,)
        formats = [(10, 4)]
        pos = 0
        param_table_data = []
        for _ in range(len(vals[0])):
            row = []
            for i, val in enumerate(vals):
                if isinstance(val[pos], np.float64):
                    converted = format_float_fixed(val[pos], *formats[i])
                else:
                    converted = val[pos]
                row.append(converted)
            pos += 1
            param_table_data.append(row)

        mc = self.model.num_params
        vc = self.model.volatility.num_params
        dc = self.model.distribution.num_params
        counts = (mc, vc, dc)
        titles = ("Mean Model", "Volatility Model", "Distribution")
        total = 0
        for title, count in zip(titles, counts):
            if count == 0:
                continue

            table_data = param_table_data[total : total + count]
            table_stubs = stubs[total : total + count]
            total += count
            table = SimpleTable(table_data, stubs=table_stubs, txt_fmt=fmt_params, headers=header, title=title)
            smry.tables.append(table)

#.........这里部分代码省略.........