Python robjects.IntVector方法代码示例

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def _convert_vector(obj):
    if isinstance(obj, robj.IntVector):
        return _convert_int_vector(obj)
    elif isinstance(obj, robj.StrVector):
        return _convert_str_vector(obj)
    # Check if the vector has extra information attached to it that can be used
    # as an index
    try:
        attributes = set(r['attributes'](obj).names)
    except AttributeError:
        return list(obj)
    if 'names' in attributes:
        return pd.Series(list(obj), index=r['names'](obj)) 
    elif 'tsp' in attributes:
        return pd.Series(list(obj), index=r['time'](obj)) 
    elif 'labels' in attributes:
        return pd.Series(list(obj), index=r['labels'](obj))
    if _rclass(obj) == 'dist':
        # For 'eurodist'. WARNING: This results in a DataFrame, not a Series or list.
        matrix = r['as.matrix'](obj)
        return convert_robj(matrix)
    else:
        return list(obj) 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def plot_module_eigengene(self, module):
        '''
        barchart illustrating module eigengene
        '''
        eigengene = self.eigengenes.get_module_eigengene(module)

        params = {}
        params['height'] = base().as_numeric(eigengene)

        limit = max(abs(base().max(eigengene)[0]), abs(base().min(eigengene)[0]))
        ylim = [-1 * limit, limit]
        params['ylim'] = ro.IntVector(ylim)

        colors = ["red" if e[0] > 0 else "blue" for e in eigengene]
        params['col'] = ro.StrVector(colors)

        params['border'] = ro.NA_Logical
        params['las'] = 2
        params['names.arg'] = ro.StrVector(self.eigengenes.samples())
        params['cex.names'] = 0.6
        params['main'] = "Eigengene: " + module
        manager = RManager(eigengene, params)
        manager.barchart() 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def plot_eigengene_network(self):
        '''
        wrapper for plotEigengeneNetworks function
        plots an eigengene network
        '''
        params = {}
        params['multiME'] = base().as_data_frame(self.transpose_data())
        params['setLabels'] = ''
        params['marDendro'] = ro.IntVector([0, 4, 1, 2])
        params['marHeatmap'] = ro.IntVector([3, 4, 1, 2])
        params['cex.lab'] = 0.8
        params['xLabelsAngle'] = 90
        params['colorLabels'] = False
        params['signed'] = True

        wgcna().plotEigengeneNetworks(**params) 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def set_sample_size(self, sampsize):
        # sampsize[0] *= self.other_sample_rate
        if self.is_onco_pred and self.is_tsg_pred:
            sampsize[1] *= self.driver_sample_rate
            sampsize[2] *= self.driver_sample_rate
            tmp_total_driver = sampsize[1] + sampsize[2]
        else:
            sampsize[1] *= self.driver_sample_rate
            tmp_total_driver = sampsize[1]
        sampsize[0] = int(self.other_sample_ratio * tmp_total_driver)
        self.sample_size = ro.IntVector(sampsize) 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def r_bats(self, y, components):
        components = components.copy()
        if 'seasonal_periods' in components:
            components['seasonal_periods'] = ro.IntVector(components['seasonal_periods'])
        importr('forecast')
        r_bats_func = ro.r['bats']
        r_forecast = ro.r['forecast']
        r_y = ro.FloatVector(list(y))
        r_model = r_bats_func(r_y, **components)
        summary = r_forecast(r_model)
        # predictions = np.array(summary.rx('fitted')).flatten()
        return summary, r_model 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def r_tbats(self, y, components):
        components = components.copy()
        if 'seasonal_periods' in components:
            components['seasonal_periods'] = ro.IntVector(components['seasonal_periods'])
        importr('forecast')
        r_bats_func = ro.r['tbats']
        r_forecast = ro.r['forecast']
        r_y = ro.FloatVector(list(y))
        r_model = r_bats_func(r_y, **components)
        summary = r_forecast(r_model)
        # predictions = np.array(summary.rx('fitted')).flatten()
        return summary, r_model 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_init_from_OrdDict():
    od = rlc.OrdDict(c=(('a', robjects.IntVector((1,2))),
                        ('b', robjects.StrVector(('c', 'd')))
                        ))
    dataf = robjects.DataFrame(od)
    assert dataf.rx2('a')[0] == 1 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_init_from_dict():
    od = {'a': robjects.IntVector((1,2)),
          'b': robjects.StrVector(('c', 'd'))}
    dataf = robjects.DataFrame(od)
    assert dataf.rx2('a')[0] == 1 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_init_stringsasfactors():
    od = {'a': robjects.IntVector((1,2)),
          'b': robjects.StrVector(('c', 'd'))}
    dataf = robjects.DataFrame(od, stringsasfactor=True)
    assert isinstance(dataf.rx2('b'), robjects.FactorVector)
    dataf = robjects.DataFrame(od, stringsasfactor=False)
    assert isinstance(dataf.rx2('b'), robjects.StrVector) 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_to_csvfile():
    fh = tempfile.NamedTemporaryFile(mode = "w", delete = False)
    fh.close()
    d = {'letter': robjects.StrVector('abc'),
         'value' : robjects.IntVector((1, 2, 3))}
    dataf = robjects.DataFrame(d)
    dataf.to_csvfile(fh.name)
    dataf = robjects.DataFrame.from_csvfile(fh.name)
    assert dataf.nrow == 3
    assert dataf.ncol == 2 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def tests_package_from_env(self):
        env = robjects.Environment()
        env['a'] = robjects.StrVector('abcd')
        env['b'] = robjects.IntVector((1,2,3))
        env['c'] = robjects.r(''' function(x) x^2''')
        pck = robjects.packages.Package(env, "dummy_package")
        assert isinstance(pck.a, robjects.Vector)
        assert isinstance(pck.b, robjects.Vector)
        assert isinstance(pck.c, robjects.Function) 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_new_with_dot_conflict(self):
        env = robjects.Environment()
        env['a.a_a'] = robjects.StrVector('abcd')
        env['a_a.a'] = robjects.IntVector((1,2,3))
        env['c'] = robjects.r(''' function(x) x^2''')
        with pytest.raises(packages.LibraryError):
            robjects.packages.Package(env, "dummy_package") 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_call_with_sexp():
    ri_f = rinterface.baseenv.find('sum')
    ro_f = Function(ri_f)

    ro_v = robjects.IntVector(array.array('i', [1,2,3]))

    s = ro_f(ro_v)
    assert s[0] == 6 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_call():
    ri_f = rinterface.baseenv.find('sum')
    ro_f = robjects.Function(ri_f)

    ro_v = robjects.IntVector(array.array('i', [1,2,3]))

    s = ro_f(ro_v)
    assert s[0] == 6 

# 需要导入模块: from rpy2 import robjects [as 别名]
# 或者: from rpy2.robjects import IntVector [as 别名]
def test_init():
    identical = ri.baseenv["identical"]
    py_a = array.array('i', [1,2,3])
    ro_v = robjects.IntVector(py_a)
    assert ro_v.typeof == ri.RTYPES.INTSXP

    ri_v = ri.IntSexpVector(py_a)
    ro_v = robjects.IntVector(ri_v)

    assert identical(ro_v, ri_v)[0]

    del(ri_v)
    assert ro_v.typeof == ri.RTYPES.INTSXP