body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1 value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
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5b7f7184e9336f8a205a2c50946d636c6af362f40f4aa16644d3b562e9b1234e | @cy_log
def set_node_combo_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Set opacity for node fill, border and label all together.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_combo_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_combo_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_combo_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_BORDER_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
_update_visual_property('NODE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
_update_visual_property('NODE_BORDER_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
res = _update_visual_property('NODE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
return res | Set opacity for node fill, border and label all together.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_combo_opacity_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_node_combo_opacity_mapping('Degree', table_column_values=['1', '2'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_combo_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_combo_opacity_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_combo_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Set opacity for node fill, border and label all together.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_combo_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_combo_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_combo_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_BORDER_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
_update_visual_property('NODE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
_update_visual_property('NODE_BORDER_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
res = _update_visual_property('NODE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
return res | @cy_log
def set_node_combo_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Set opacity for node fill, border and label all together.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_combo_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_combo_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_combo_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_BORDER_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
_update_visual_property('NODE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
_update_visual_property('NODE_BORDER_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
res = _update_visual_property('NODE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)
return res<|docstring|>Set opacity for node fill, border and label all together.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_combo_opacity_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_node_combo_opacity_mapping('Degree', table_column_values=['1', '2'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_combo_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
''<|endoftext|> |
90c1b88a83b07fc6fd5287ea733d830fd4c75ed50eda4c54686465a7aa386558 | @cy_log
def set_node_fill_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Set opacity for node fill only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_fill_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_fill_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_fill_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Set opacity for node fill only.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_fill_opacity_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_node_fill_opacity_mapping('Degree', table_column_values=['1', '2'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_fill_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_fill_opacity_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_fill_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Set opacity for node fill only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_fill_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_fill_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_fill_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_node_fill_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Set opacity for node fill only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_fill_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_fill_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_fill_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Set opacity for node fill only.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_fill_opacity_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_node_fill_opacity_mapping('Degree', table_column_values=['1', '2'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_fill_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
''<|endoftext|> |
4c92cdd2b83fd7b417308387a45a2dedd923eb773d94ae468d7ee78e20482c0f | @cy_log
def set_node_font_face_mapping(table_column, table_column_values=None, fonts=None, mapping_type='d', default_font=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets font face for node labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_font_face_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], fonts=[\'Arial,plain,12\', \'Arial Bold,bold,12\'], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_face_mapping(\'PassthruCol\', mapping_type=\'p\', default_font=\'Arial,plain,12\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_font is not None):
style_defaults.set_node_font_face_default(default_font, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_FONT_FACE', table_column, table_column_values=table_column_values, range_map=fonts, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, supported_mappings=['d', 'p']) | Sets font face for node labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_font_face_mapping('Degree', table_column_values=['1', '2'], fonts=['Arial,plain,12', 'Arial Bold,bold,12'], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_font_face_mapping('PassthruCol', mapping_type='p', default_font='Arial,plain,12', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_font_face_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_font_face_mapping(table_column, table_column_values=None, fonts=None, mapping_type='d', default_font=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets font face for node labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_font_face_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], fonts=[\'Arial,plain,12\', \'Arial Bold,bold,12\'], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_face_mapping(\'PassthruCol\', mapping_type=\'p\', default_font=\'Arial,plain,12\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_font is not None):
style_defaults.set_node_font_face_default(default_font, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_FONT_FACE', table_column, table_column_values=table_column_values, range_map=fonts, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, supported_mappings=['d', 'p']) | @cy_log
def set_node_font_face_mapping(table_column, table_column_values=None, fonts=None, mapping_type='d', default_font=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets font face for node labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_font_face_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], fonts=[\'Arial,plain,12\', \'Arial Bold,bold,12\'], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_face_mapping(\'PassthruCol\', mapping_type=\'p\', default_font=\'Arial,plain,12\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_font is not None):
style_defaults.set_node_font_face_default(default_font, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_FONT_FACE', table_column, table_column_values=table_column_values, range_map=fonts, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, supported_mappings=['d', 'p'])<|docstring|>Sets font face for node labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_font_face_mapping('Degree', table_column_values=['1', '2'], fonts=['Arial,plain,12', 'Arial Bold,bold,12'], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_font_face_mapping('PassthruCol', mapping_type='p', default_font='Arial,plain,12', style_name='galFiltered Style')
''<|endoftext|> |
4dbc94df5f928676e3e57ae59e2d8b47e3c9a32c1063e52a4aa7619e8e441e8b | def set_node_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to sizes to set the node size.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of size values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_font_size_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[20, 80], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_size_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[40, 90], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=20, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_node_font_size_default(default_size, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_FONT_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Map table column values to sizes to set the node size.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
sizes (list): List of size values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_size (int): Size value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid size
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_font_size_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[20, 80], style_name='galFiltered Style')
''
>>> set_node_font_size_mapping('Degree', table_column_values=['1', '2'], sizes=[40, 90], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_font_size_mapping('PassthruCol', mapping_type='p', default_size=20, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_font_size_mapping | tyasird/py4cytoscape | 0 | python | def set_node_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to sizes to set the node size.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of size values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_font_size_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[20, 80], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_size_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[40, 90], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=20, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_node_font_size_default(default_size, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_FONT_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | def set_node_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to sizes to set the node size.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of size values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_font_size_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[20, 80], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_size_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[40, 90], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_font_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=20, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_node_font_size_default(default_size, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_FONT_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to sizes to set the node size.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
sizes (list): List of size values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_size (int): Size value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid size
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_font_size_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[20, 80], style_name='galFiltered Style')
''
>>> set_node_font_size_mapping('Degree', table_column_values=['1', '2'], sizes=[40, 90], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_font_size_mapping('PassthruCol', mapping_type='p', default_size=20, style_name='galFiltered Style')
''<|endoftext|> |
7e94dd954921dbf856a43074d42db76eb03d5e8210dd2c0b073a2d4e122ff0a0 | @cy_log
def set_node_height_mapping(table_column, table_column_values=None, heights=None, mapping_type='c', default_height=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to the node heights.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n heights (list): List of height values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_height (int): Height value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid height\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_height_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_height_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[140, 190], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_height_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=120, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('height', heights)
if (default_height is not None):
style_defaults.set_node_height_default(default_height, style_name=style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(False, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_HEIGHT', table_column, table_column_values=table_column_values, range_map=heights, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Map table column values to the node heights.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
heights (list): List of height values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_height (int): Height value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid height
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_height_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name='galFiltered Style')
''
>>> set_node_height_mapping('Degree', table_column_values=['1', '2'], sizes=[140, 190], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_height_mapping('PassthruCol', mapping_type='p', default_size=120, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_height_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_height_mapping(table_column, table_column_values=None, heights=None, mapping_type='c', default_height=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to the node heights.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n heights (list): List of height values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_height (int): Height value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid height\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_height_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_height_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[140, 190], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_height_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=120, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('height', heights)
if (default_height is not None):
style_defaults.set_node_height_default(default_height, style_name=style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(False, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_HEIGHT', table_column, table_column_values=table_column_values, range_map=heights, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_node_height_mapping(table_column, table_column_values=None, heights=None, mapping_type='c', default_height=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to the node heights.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n heights (list): List of height values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_height (int): Height value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid height\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_height_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_height_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[140, 190], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_height_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=120, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('height', heights)
if (default_height is not None):
style_defaults.set_node_height_default(default_height, style_name=style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(False, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_HEIGHT', table_column, table_column_values=table_column_values, range_map=heights, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to the node heights.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
heights (list): List of height values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_height (int): Height value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid height
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_height_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name='galFiltered Style')
''
>>> set_node_height_mapping('Degree', table_column_values=['1', '2'], sizes=[140, 190], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_height_mapping('PassthruCol', mapping_type='p', default_size=120, style_name='galFiltered Style')
''<|endoftext|> |
53e2482f5ad7f365855a5efda78522e20387548fad5f75df7fde2dc0695a9f17 | @cy_log
def set_node_label_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as node labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str or None: \'\' if successful or None if error\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_mapping(\'name\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_mapping(\'name\')\n \'\'\n '
if (not table_column_exists(table_column, 'node', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('NODE_LABEL', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res | Pass the values from a table column to display as node labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str or None: '' if successful or None if error
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_label_mapping('name', style_name='galFiltered Style')
''
>>> set_node_label_mapping('name')
'' | py4cytoscape/style_mappings.py | set_node_label_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_label_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as node labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str or None: \'\' if successful or None if error\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_mapping(\'name\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_mapping(\'name\')\n \'\'\n '
if (not table_column_exists(table_column, 'node', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('NODE_LABEL', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res | @cy_log
def set_node_label_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as node labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str or None: \'\' if successful or None if error\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_mapping(\'name\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_mapping(\'name\')\n \'\'\n '
if (not table_column_exists(table_column, 'node', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('NODE_LABEL', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res<|docstring|>Pass the values from a table column to display as node labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str or None: '' if successful or None if error
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_label_mapping('name', style_name='galFiltered Style')
''
>>> set_node_label_mapping('name')
''<|endoftext|> |
7f01a19a3acbe777033e67d052fbcaefc9f880d6480aa4c421cd509f36d46797 | @cy_log
def set_node_label_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the node border color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_color_mapping(\'AverageShortestPathLength\', [1.0, 16.36], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_color_mapping(\'Degree\', [\'1\', \'2\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_node_label_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_COLOR', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Map table column values to colors to set the node border color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_label_color_mapping('AverageShortestPathLength', [1.0, 16.36], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_node_label_color_mapping('Degree', ['1', '2'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_node_label_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_label_color_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_label_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the node border color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_color_mapping(\'AverageShortestPathLength\', [1.0, 16.36], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_color_mapping(\'Degree\', [\'1\', \'2\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_node_label_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_COLOR', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_node_label_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the node border color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_color_mapping(\'AverageShortestPathLength\', [1.0, 16.36], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_color_mapping(\'Degree\', [\'1\', \'2\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_node_label_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_COLOR', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to colors to set the node border color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_label_color_mapping('AverageShortestPathLength', [1.0, 16.36], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_node_label_color_mapping('Degree', ['1', '2'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_node_label_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
''<|endoftext|> |
b75a282d03229a3603220939c5b1c96875ab531e28ed748be265874077e64610 | @cy_log
def set_node_label_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets opacity for node label only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Sets opacity for node label only.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_label_opacity_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_node_label_opacity_mapping('Degree', table_column_values=['1', '2'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_label_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_label_opacity_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_label_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets opacity for node label only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_node_label_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets opacity for node label only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_label_opacity_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_opacity_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_label_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'NODE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Sets opacity for node label only.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_label_opacity_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_node_label_opacity_mapping('Degree', table_column_values=['1', '2'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_label_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
''<|endoftext|> |
cfa73c81e5f74cfc3e9e692d06fe22d06f3fa75115d6df7a80a8b5399e1ab861 | @cy_log
def set_node_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the node shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_node_shapes()``\n default_shape (str): Shape to set as default. See ``get_node_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_shape_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], shapes=[\'TRIANGLE\', \'OCTAGON\'], default_shape=\'ELLIPSE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_node_shape_default(default_shape, style_name, base_url=base_url)
return _update_visual_property('NODE_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, supported_mappings=['d']) | Map table column values to shapes to set the node shape.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of shapes to map to ``table_column_values``. See ``get_node_shapes()``
default_shape (str): Shape to set as default. See ``get_node_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_shape_mapping('Degree', table_column_values=['1', '2'], shapes=['TRIANGLE', 'OCTAGON'], default_shape='ELLIPSE', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_shape_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the node shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_node_shapes()``\n default_shape (str): Shape to set as default. See ``get_node_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_shape_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], shapes=[\'TRIANGLE\', \'OCTAGON\'], default_shape=\'ELLIPSE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_node_shape_default(default_shape, style_name, base_url=base_url)
return _update_visual_property('NODE_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, supported_mappings=['d']) | @cy_log
def set_node_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the node shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_node_shapes()``\n default_shape (str): Shape to set as default. See ``get_node_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_shape_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], shapes=[\'TRIANGLE\', \'OCTAGON\'], default_shape=\'ELLIPSE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_node_shape_default(default_shape, style_name, base_url=base_url)
return _update_visual_property('NODE_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, supported_mappings=['d'])<|docstring|>Map table column values to shapes to set the node shape.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of shapes to map to ``table_column_values``. See ``get_node_shapes()``
default_shape (str): Shape to set as default. See ``get_node_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_shape_mapping('Degree', table_column_values=['1', '2'], shapes=['TRIANGLE', 'OCTAGON'], default_shape='ELLIPSE', style_name='galFiltered Style')
''<|endoftext|> |
3291075bb76c33c17881511e707c3eeb9aebf7e25b829a40ddc612f1ecbfa868 | @cy_log
def set_node_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to node sizes.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of sizes of nodes\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_size_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[60, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_size_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[60, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=40, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_node_size_default(default_size, style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(True, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Map table column values to node sizes.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
sizes (list): List of sizes of nodes
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_size (int): Size value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid size
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_size_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[60, 100], style_name='galFiltered Style')
''
>>> set_node_size_mapping('Degree', table_column_values=['1', '2'], sizes=[60, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_size_mapping('PassthruCol', mapping_type='p', default_opacity=40, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_size_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to node sizes.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of sizes of nodes\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_size_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[60, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_size_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[60, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=40, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_node_size_default(default_size, style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(True, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_node_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to node sizes.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of sizes of nodes\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_size_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[60, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_size_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[60, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=40, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_node_size_default(default_size, style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(True, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to node sizes.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
sizes (list): List of sizes of nodes
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_size (int): Size value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid size
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_size_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[60, 100], style_name='galFiltered Style')
''
>>> set_node_size_mapping('Degree', table_column_values=['1', '2'], sizes=[60, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_size_mapping('PassthruCol', mapping_type='p', default_opacity=40, style_name='galFiltered Style')
''<|endoftext|> |
2cf6c681f9ced4c128651ea8c68327b9c0141d44b555d0a588aabf7e7d9fb39b | @cy_log
def set_node_tooltip_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as node tooltips.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_tooltip_mapping(\'PassthruCol\', style_name=\'galFiltered Style\')\n \'\'\n '
if (not table_column_exists(table_column, 'node', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('NODE_TOOLTIP', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res | Pass the values from a table column to display as node tooltips.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_tooltip_mapping('PassthruCol', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_tooltip_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_tooltip_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as node tooltips.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_tooltip_mapping(\'PassthruCol\', style_name=\'galFiltered Style\')\n \'\'\n '
if (not table_column_exists(table_column, 'node', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('NODE_TOOLTIP', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res | @cy_log
def set_node_tooltip_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as node tooltips.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_tooltip_mapping(\'PassthruCol\', style_name=\'galFiltered Style\')\n \'\'\n '
if (not table_column_exists(table_column, 'node', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('NODE_TOOLTIP', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res<|docstring|>Pass the values from a table column to display as node tooltips.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_tooltip_mapping('PassthruCol', style_name='galFiltered Style')
''<|endoftext|> |
ab04ce3a996fb0b184e4df20f4b44b9b79f496e38cfe0e4bd5c7e8561ce35bdc | @cy_log
def set_node_width_mapping(table_column, table_column_values=None, widths=None, mapping_type='c', default_width=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to the node widths.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n widths (list): List of widths values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_width (int): Width value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid width\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_width_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_width_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[140, 190], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_width_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=120, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('width', widths)
if (default_width is not None):
style_defaults.set_node_width_default(default_width, style_name=style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(False, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_WIDTH', table_column, table_column_values=table_column_values, range_map=widths, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | Map table column values to the node widths.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
widths (list): List of widths values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_width (int): Width value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid width
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_width_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name='galFiltered Style')
''
>>> set_node_width_mapping('Degree', table_column_values=['1', '2'], sizes=[140, 190], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_width_mapping('PassthruCol', mapping_type='p', default_size=120, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_node_width_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_node_width_mapping(table_column, table_column_values=None, widths=None, mapping_type='c', default_width=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to the node widths.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n widths (list): List of widths values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_width (int): Width value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid width\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_width_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_width_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[140, 190], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_width_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=120, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('width', widths)
if (default_width is not None):
style_defaults.set_node_width_default(default_width, style_name=style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(False, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_WIDTH', table_column, table_column_values=table_column_values, range_map=widths, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_node_width_mapping(table_column, table_column_values=None, widths=None, mapping_type='c', default_width=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to the node widths.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n widths (list): List of widths values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_width (int): Width value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid width\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_node_width_mapping(\'AverageShortestPathLength\', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_width_mapping(\'Degree\', table_column_values=[\'1\', \'2\'], sizes=[140, 190], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_node_width_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=120, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('width', widths)
if (default_width is not None):
style_defaults.set_node_width_default(default_width, style_name=style_name, base_url=base_url)
style_dependencies.lock_node_dimensions(False, style_name=style_name, base_url=base_url)
return _update_visual_property('NODE_WIDTH', table_column, table_column_values=table_column_values, range_map=widths, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to the node widths.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
widths (list): List of widths values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_width (int): Width value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid width
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_node_width_mapping('AverageShortestPathLength', table_column_values=[1.0, 16.36], sizes=[120, 180], style_name='galFiltered Style')
''
>>> set_node_width_mapping('Degree', table_column_values=['1', '2'], sizes=[140, 190], mapping_type='d', style_name='galFiltered Style')
''
>>> set_node_width_mapping('PassthruCol', mapping_type='p', default_size=120, style_name='galFiltered Style')
''<|endoftext|> |
092b90ccc51713b06acf8f6fd3040b8b70adeb1b46709164f797b3afb671941b | @cy_log
def set_edge_font_face_mapping(table_column, table_column_values=None, fonts=None, mapping_type='d', default_font=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets font face for edge labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_font_face_mapping(\'interaction\', table_column_values=[\'pp\', \'pd\'], fonts=[\'Arial,plain,12\', \'Arial Bold,bold,12\'], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_face_mapping(\'PassthruCol\', mapping_type=\'p\', default_font=\'Arial,plain,12\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_font is not None):
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_LABEL_FONT_FACE', 'value': default_font}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_FONT_FACE', table_column, table_column_values=table_column_values, range_map=fonts, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, supported_mappings=['d', 'p'], table='edge') | Sets font face for edge labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_font_face_mapping('interaction', table_column_values=['pp', 'pd'], fonts=['Arial,plain,12', 'Arial Bold,bold,12'], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_font_face_mapping('PassthruCol', mapping_type='p', default_font='Arial,plain,12', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_font_face_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_font_face_mapping(table_column, table_column_values=None, fonts=None, mapping_type='d', default_font=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets font face for edge labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_font_face_mapping(\'interaction\', table_column_values=[\'pp\', \'pd\'], fonts=[\'Arial,plain,12\', \'Arial Bold,bold,12\'], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_face_mapping(\'PassthruCol\', mapping_type=\'p\', default_font=\'Arial,plain,12\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_font is not None):
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_LABEL_FONT_FACE', 'value': default_font}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_FONT_FACE', table_column, table_column_values=table_column_values, range_map=fonts, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, supported_mappings=['d', 'p'], table='edge') | @cy_log
def set_edge_font_face_mapping(table_column, table_column_values=None, fonts=None, mapping_type='d', default_font=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets font face for edge labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_font_face_mapping(\'interaction\', table_column_values=[\'pp\', \'pd\'], fonts=[\'Arial,plain,12\', \'Arial Bold,bold,12\'], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_face_mapping(\'PassthruCol\', mapping_type=\'p\', default_font=\'Arial,plain,12\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_font is not None):
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_LABEL_FONT_FACE', 'value': default_font}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_FONT_FACE', table_column, table_column_values=table_column_values, range_map=fonts, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, supported_mappings=['d', 'p'], table='edge')<|docstring|>Sets font face for edge labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
fonts (list): List of string specifications of font face, style and size, e.g., ["SansSerif,plain,12", "Dialog,plain,10"]
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_font (str): String specification of font face, style and size, e.g., "SansSerif,plain,12" or "Dialog,plain,10"
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_font_face_mapping('interaction', table_column_values=['pp', 'pd'], fonts=['Arial,plain,12', 'Arial Bold,bold,12'], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_font_face_mapping('PassthruCol', mapping_type='p', default_font='Arial,plain,12', style_name='galFiltered Style')
''<|endoftext|> |
b9ba788e1f3272cef08342ea5d37ad06f451ec76e02c58eccb8d05436ceccb5f | @cy_log
def set_edge_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to sizes to set the edge size.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of size values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_font_size_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], sizes=[20, 80], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_size_mapping(\'interaction\', table_column_values=[\'pp\', \'pd\'], sizes=[40, 90], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=20, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_edge_font_size_default(default_size, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_FONT_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to sizes to set the edge size.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
sizes (list): List of size values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_size (int): Size value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid size
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_font_size_mapping('EdgeBetweenness', table_column_values=[2.0, 20000.0], sizes=[20, 80], style_name='galFiltered Style')
''
>>> set_edge_font_size_mapping('interaction', table_column_values=['pp', 'pd'], sizes=[40, 90], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_font_size_mapping('PassthruCol', mapping_type='p', default_size=20, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_font_size_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to sizes to set the edge size.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of size values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_font_size_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], sizes=[20, 80], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_size_mapping(\'interaction\', table_column_values=[\'pp\', \'pd\'], sizes=[40, 90], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=20, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_edge_font_size_default(default_size, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_FONT_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to sizes to set the edge size.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n sizes (list): List of size values to map to ``table_column_values``\n mapping_type (str): discrete or passthrough (d,p); default is discrete\n default_size (int): Size value to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid size\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_font_size_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], sizes=[20, 80], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_size_mapping(\'interaction\', table_column_values=[\'pp\', \'pd\'], sizes=[40, 90], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_font_size_mapping(\'PassthruCol\', mapping_type=\'p\', default_size=20, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('size', sizes)
if (default_size is not None):
style_defaults.set_edge_font_size_default(default_size, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_FONT_SIZE', table_column, table_column_values=table_column_values, range_map=sizes, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to sizes to set the edge size.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
sizes (list): List of size values to map to ``table_column_values``
mapping_type (str): discrete or passthrough (d,p); default is discrete
default_size (int): Size value to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid size
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_font_size_mapping('EdgeBetweenness', table_column_values=[2.0, 20000.0], sizes=[20, 80], style_name='galFiltered Style')
''
>>> set_edge_font_size_mapping('interaction', table_column_values=['pp', 'pd'], sizes=[40, 90], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_font_size_mapping('PassthruCol', mapping_type='p', default_size=20, style_name='galFiltered Style')
''<|endoftext|> |
5930a234e55cf500305555b826167bb07484e29ccc2a873445956685461fb656 | @cy_log
def set_edge_label_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as edge labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_mapping(\'name\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_mapping(\'name\')\n \'\'\n '
if (not table_column_exists(table_column, 'edge', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('EDGE_LABEL', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res | Pass the values from a table column to display as edge labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_label_mapping('name', style_name='galFiltered Style')
''
>>> set_edge_label_mapping('name')
'' | py4cytoscape/style_mappings.py | set_edge_label_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_label_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as edge labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_mapping(\'name\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_mapping(\'name\')\n \'\'\n '
if (not table_column_exists(table_column, 'edge', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('EDGE_LABEL', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res | @cy_log
def set_edge_label_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as edge labels.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_mapping(\'name\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_mapping(\'name\')\n \'\'\n '
if (not table_column_exists(table_column, 'edge', network=network, base_url=base_url)):
raise CyError(f'Table column "{table_column}" does not exist')
mvp = map_visual_property('EDGE_LABEL', table_column, 'p', network=network, base_url=base_url)
res = update_style_mapping(style_name, mvp, base_url=base_url)
return res<|docstring|>Pass the values from a table column to display as edge labels.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_label_mapping('name', style_name='galFiltered Style')
''
>>> set_edge_label_mapping('name')
''<|endoftext|> |
649f0bc879389d09216343132712d302d22aa0982cb00e4b57e7a427cc310c6c | @cy_log
def set_edge_label_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the edge border color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuou\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_color_mapping(\'interaction\', [\'pp\', \'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_label_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_COLOR', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to colors to set the edge border color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuou
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_label_color_mapping('EdgeBetweenness', [2.0, 20000.0], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_edge_label_color_mapping('interaction', ['pp', 'pd'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_edge_label_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_label_color_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_label_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the edge border color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuou\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_color_mapping(\'interaction\', [\'pp\', \'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_label_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_COLOR', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_label_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the edge border color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuou\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_color_mapping(\'interaction\', [\'pp\', \'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_label_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_COLOR', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to colors to set the edge border color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuou
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_label_color_mapping('EdgeBetweenness', [2.0, 20000.0], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_edge_label_color_mapping('interaction', ['pp', 'pd'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_edge_label_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
''<|endoftext|> |
d88a345da2b565babf21ecce2c7980f6fae2f731b5c244fc96a6b10d81830d60 | @cy_log
def set_edge_label_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets opacity for edge label only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_opacity_mapping(\'EdgeBetweenness\', [2.0, 20000.0], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_opacity_mapping(\'interaction\', [\'pp\', \'pd\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Sets opacity for edge label only.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_label_opacity_mapping('EdgeBetweenness', [2.0, 20000.0], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_edge_label_opacity_mapping('interaction', ['pp', 'pd'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_label_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_label_opacity_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_label_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets opacity for edge label only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_opacity_mapping(\'EdgeBetweenness\', [2.0, 20000.0], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_opacity_mapping(\'interaction\', [\'pp\', \'pd\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_label_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Sets opacity for edge label only.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_label_opacity_mapping(\'EdgeBetweenness\', [2.0, 20000.0], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_opacity_mapping(\'interaction\', [\'pp\', \'pd\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_label_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_LABEL_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LABEL_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Sets opacity for edge label only.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_label_opacity_mapping('EdgeBetweenness', [2.0, 20000.0], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_edge_label_opacity_mapping('interaction', ['pp', 'pd'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_label_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
''<|endoftext|> |
60f0ad0ee10c7a5f657138eceae562cef5d1ed6155105ab8ee6b0c1db0b45d1b | @cy_log
def set_edge_line_style_mapping(table_column, table_column_values=None, line_styles=None, default_line_style='SOLID', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to styles to set the edge style.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n line_styles (list): List of styles to map to ``table_column_values``. See ``get_line_styles()``\n default_line_style (str): Style to set as default. See ``get_line_styles()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_line_style_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'ZIGZAG\', \'SINEWAVE\'], default_shape=\'EQUAL_DASH\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_line_style is not None):
style_defaults.set_edge_line_style_default(default_line_style, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LINE_TYPE', table_column, table_column_values=table_column_values, range_map=line_styles, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to styles to set the edge style.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
line_styles (list): List of styles to map to ``table_column_values``. See ``get_line_styles()``
default_line_style (str): Style to set as default. See ``get_line_styles()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_line_style_mapping('interaction', table_column_values=['pp','pd'], shapes=['ZIGZAG', 'SINEWAVE'], default_shape='EQUAL_DASH', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_line_style_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_line_style_mapping(table_column, table_column_values=None, line_styles=None, default_line_style='SOLID', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to styles to set the edge style.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n line_styles (list): List of styles to map to ``table_column_values``. See ``get_line_styles()``\n default_line_style (str): Style to set as default. See ``get_line_styles()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_line_style_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'ZIGZAG\', \'SINEWAVE\'], default_shape=\'EQUAL_DASH\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_line_style is not None):
style_defaults.set_edge_line_style_default(default_line_style, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LINE_TYPE', table_column, table_column_values=table_column_values, range_map=line_styles, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_line_style_mapping(table_column, table_column_values=None, line_styles=None, default_line_style='SOLID', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to styles to set the edge style.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n line_styles (list): List of styles to map to ``table_column_values``. See ``get_line_styles()``\n default_line_style (str): Style to set as default. See ``get_line_styles()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_line_style_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'ZIGZAG\', \'SINEWAVE\'], default_shape=\'EQUAL_DASH\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_line_style is not None):
style_defaults.set_edge_line_style_default(default_line_style, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_LINE_TYPE', table_column, table_column_values=table_column_values, range_map=line_styles, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to styles to set the edge style.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
line_styles (list): List of styles to map to ``table_column_values``. See ``get_line_styles()``
default_line_style (str): Style to set as default. See ``get_line_styles()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_line_style_mapping('interaction', table_column_values=['pp','pd'], shapes=['ZIGZAG', 'SINEWAVE'], default_shape='EQUAL_DASH', style_name='galFiltered Style')
''<|endoftext|> |
c456b97f0a933ca90278070b9f92c6ba38c34544bd08d9209a54dee9db4deb33 | @cy_log
def set_edge_line_width_mapping(table_column, table_column_values=None, widths=None, mapping_type='c', default_width=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to widths to set the node border width.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n widths (list): List of width values to map to ``table_column_values``\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_width (int): Width value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid width\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_line_width_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], widths=[5, 10], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_line_width_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], widths=[5, 10], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_line_width_mapping(\'PassthruCol\', mapping_type=\'p\', default_width=3, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('width', widths)
if (default_width is not None):
style_defaults.set_edge_line_width_default(default_width, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_WIDTH', table_column, table_column_values=table_column_values, range_map=widths, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to widths to set the node border width.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
widths (list): List of width values to map to ``table_column_values``
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_width (int): Width value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid width
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_line_width_mapping('EdgeBetweenness', table_column_values=[2.0, 20000.0], widths=[5, 10], style_name='galFiltered Style')
''
>>> set_edge_line_width_mapping('interaction', table_column_values=['pp','pd'], widths=[5, 10], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_line_width_mapping('PassthruCol', mapping_type='p', default_width=3, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_line_width_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_line_width_mapping(table_column, table_column_values=None, widths=None, mapping_type='c', default_width=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to widths to set the node border width.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n widths (list): List of width values to map to ``table_column_values``\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_width (int): Width value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid width\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_line_width_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], widths=[5, 10], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_line_width_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], widths=[5, 10], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_line_width_mapping(\'PassthruCol\', mapping_type=\'p\', default_width=3, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('width', widths)
if (default_width is not None):
style_defaults.set_edge_line_width_default(default_width, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_WIDTH', table_column, table_column_values=table_column_values, range_map=widths, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_line_width_mapping(table_column, table_column_values=None, widths=None, mapping_type='c', default_width=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to widths to set the node border width.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n widths (list): List of width values to map to ``table_column_values``\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_width (int): Width value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid width\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_line_width_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], widths=[5, 10], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_line_width_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], widths=[5, 10], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_line_width_mapping(\'PassthruCol\', mapping_type=\'p\', default_width=3, style_name=\'galFiltered Style\')\n \'\'\n '
verify_dimensions('width', widths)
if (default_width is not None):
style_defaults.set_edge_line_width_default(default_width, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_WIDTH', table_column, table_column_values=table_column_values, range_map=widths, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to widths to set the node border width.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
widths (list): List of width values to map to ``table_column_values``
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_width (int): Width value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid width
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_line_width_mapping('EdgeBetweenness', table_column_values=[2.0, 20000.0], widths=[5, 10], style_name='galFiltered Style')
''
>>> set_edge_line_width_mapping('interaction', table_column_values=['pp','pd'], widths=[5, 10], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_line_width_mapping('PassthruCol', mapping_type='p', default_width=3, style_name='galFiltered Style')
''<|endoftext|> |
d86113e02f251f103251e7dc6580b22a1ba65277289566b0e0ad0f15ed121664 | @cy_log
def set_edge_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to opacities to set the edge opacity.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_opacity_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_opacity_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to opacities to set the edge opacity.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_opacity_mapping('EdgeBetweenness', table_column_values=[2.0, 20000.0], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_edge_opacity_mapping('interaction', table_column_values=['pp','pd'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_opacity_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to opacities to set the edge opacity.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_opacity_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_opacity_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_opacity_mapping(table_column, table_column_values=None, opacities=None, mapping_type='c', default_opacity=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to opacities to set the edge opacity.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n opacities (list): int values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous\n default_opacity (int): Opacity value to set as default for all unmapped values\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type, or if invalid opacity\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_opacity_mapping(\'EdgeBetweenness\', table_column_values=[2.0, 20000.0], opacities=[50, 100], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_opacity_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], opacities=[50, 100], mapping_type=\'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_opacity_mapping(\'PassthruCol\', mapping_type=\'p\', default_opacity=225, style_name=\'galFiltered Style\')\n \'\'\n '
verify_opacities(opacities)
if (default_opacity is not None):
verify_opacities(default_opacity)
style_defaults.set_visual_property_default({'visualProperty': 'EDGE_TRANSPARENCY', 'value': str(default_opacity)}, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_TRANSPARENCY', table_column, table_column_values=table_column_values, range_map=opacities, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to opacities to set the edge opacity.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
opacities (list): int values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuous
default_opacity (int): Opacity value to set as default for all unmapped values
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type, or if invalid opacity
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_opacity_mapping('EdgeBetweenness', table_column_values=[2.0, 20000.0], opacities=[50, 100], style_name='galFiltered Style')
''
>>> set_edge_opacity_mapping('interaction', table_column_values=['pp','pd'], opacities=[50, 100], mapping_type='d', style_name='galFiltered Style')
''
>>> set_edge_opacity_mapping('PassthruCol', mapping_type='p', default_opacity=225, style_name='galFiltered Style')
''<|endoftext|> |
71539eef2b885b048763e8c58fa49ce2910e0a86340ad0b82e5420a3f8c1c6f5 | @cy_log
def set_edge_target_arrow_maping(table_column, table_column_values=None, shapes=None, default_shape='ARROW', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the target arrow shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Style to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_target_arrow_maping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'CIRCLE\', \'ARROW\'], default_shape=\'NONE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_edge_target_arrow_shape_default(default_shape, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_TARGET_ARROW_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['d']) | Map table column values to shapes to set the target arrow shape.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Style to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_target_arrow_maping('interaction', table_column_values=['pp','pd'], shapes=['CIRCLE', 'ARROW'], default_shape='NONE', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_target_arrow_maping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_target_arrow_maping(table_column, table_column_values=None, shapes=None, default_shape='ARROW', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the target arrow shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Style to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_target_arrow_maping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'CIRCLE\', \'ARROW\'], default_shape=\'NONE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_edge_target_arrow_shape_default(default_shape, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_TARGET_ARROW_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['d']) | @cy_log
def set_edge_target_arrow_maping(table_column, table_column_values=None, shapes=None, default_shape='ARROW', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the target arrow shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Style to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_target_arrow_maping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'CIRCLE\', \'ARROW\'], default_shape=\'NONE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_edge_target_arrow_shape_default(default_shape, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_TARGET_ARROW_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['d'])<|docstring|>Map table column values to shapes to set the target arrow shape.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Style to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_target_arrow_maping('interaction', table_column_values=['pp','pd'], shapes=['CIRCLE', 'ARROW'], default_shape='NONE', style_name='galFiltered Style')
''<|endoftext|> |
e0678145879f28c2bd70c6528168d694d252f813b6536bd70e0bf328c44c06ea | @cy_log
def set_edge_source_arrow_mapping(table_column, table_column_values=None, shapes=None, default_shape='ARROW', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the source arrow shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Style to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'CIRCLE\', \'ARROW\'], default_shape=\'NONE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_edge_source_arrow_shape_default(default_shape, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_SOURCE_ARROW_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['d']) | Map table column values to shapes to set the source arrow shape.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Style to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_mapping('interaction', table_column_values=['pp','pd'], shapes=['CIRCLE', 'ARROW'], default_shape='NONE', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_source_arrow_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_source_arrow_mapping(table_column, table_column_values=None, shapes=None, default_shape='ARROW', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the source arrow shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Style to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'CIRCLE\', \'ARROW\'], default_shape=\'NONE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_edge_source_arrow_shape_default(default_shape, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_SOURCE_ARROW_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['d']) | @cy_log
def set_edge_source_arrow_mapping(table_column, table_column_values=None, shapes=None, default_shape='ARROW', style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to shapes to set the source arrow shape.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Style to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'CIRCLE\', \'ARROW\'], default_shape=\'NONE\', style_name=\'galFiltered Style\')\n \'\'\n '
if (default_shape is not None):
style_defaults.set_edge_source_arrow_shape_default(default_shape, style_name=style_name, base_url=base_url)
return _update_visual_property('EDGE_SOURCE_ARROW_SHAPE', table_column, table_column_values=table_column_values, range_map=shapes, mapping_type='d', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['d'])<|docstring|>Map table column values to shapes to set the source arrow shape.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Style to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_mapping('interaction', table_column_values=['pp','pd'], shapes=['CIRCLE', 'ARROW'], default_shape='NONE', style_name='galFiltered Style')
''<|endoftext|> |
507d85f75c86c6b55a87841ce34a46a27b90bfdf5a9083ff6ba605e497b86e73 | @cy_log
def set_edge_target_arrow_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the target arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_target_arrow_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_target_arrow_color_mapping(\'interaction\', [\'pp\',\'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_target_arrow_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_target_arrow_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_TARGET_ARROW_UNSELECTED_PAINT', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to colors to set the target arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_target_arrow_color_mapping('EdgeBetweenness', [2.0, 20000.0], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_edge_target_arrow_color_mapping('interaction', ['pp','pd'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_edge_target_arrow_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_target_arrow_color_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_target_arrow_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the target arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_target_arrow_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_target_arrow_color_mapping(\'interaction\', [\'pp\',\'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_target_arrow_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_target_arrow_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_TARGET_ARROW_UNSELECTED_PAINT', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_target_arrow_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the target arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_target_arrow_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_target_arrow_color_mapping(\'interaction\', [\'pp\',\'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_target_arrow_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_target_arrow_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_TARGET_ARROW_UNSELECTED_PAINT', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to colors to set the target arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_target_arrow_color_mapping('EdgeBetweenness', [2.0, 20000.0], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_edge_target_arrow_color_mapping('interaction', ['pp','pd'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_edge_target_arrow_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
''<|endoftext|> |
5e04207635c0c94e7145a3e6b62fa9f83358205ac352a2a955e15ae7efdf4d4d | @cy_log
def set_edge_source_arrow_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the source arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_source_arrow_color_mapping(\'interaction\', [\'pp\',\'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_source_arrow_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_source_arrow_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_SOURCE_ARROW_UNSELECTED_PAINT', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | Map table column values to colors to set the source arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_color_mapping('EdgeBetweenness', [2.0, 20000.0], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_edge_source_arrow_color_mapping('interaction', ['pp','pd'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_edge_source_arrow_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_source_arrow_color_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_source_arrow_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the source arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_source_arrow_color_mapping(\'interaction\', [\'pp\',\'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_source_arrow_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_source_arrow_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_SOURCE_ARROW_UNSELECTED_PAINT', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge') | @cy_log
def set_edge_source_arrow_color_mapping(table_column, table_column_values=None, colors=None, mapping_type='c', default_color=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the source arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n colors (list): values between 0 and 255; 0 is invisible\n mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue\n default_color (str): Hex color to set as default\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if invalid color, table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_color_mapping(\'EdgeBetweenness\', [2.0, 20000.0], [\'#FBE723\', \'#440256\'], style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_source_arrow_color_mapping(\'interaction\', [\'pp\',\'pd\'], [\'#FFFF00\', \'#00FF00\'], \'d\', style_name=\'galFiltered Style\')\n \'\'\n >>> set_edge_source_arrow_color_mapping(\'ColorCol\', mapping_type=\'p\', default_color=\'#654321\', style_name=\'galFiltered Style\')\n \'\'\n '
verify_hex_colors(colors)
if (default_color is not None):
style_defaults.set_edge_source_arrow_color_default(default_color, style_name, base_url=base_url)
return _update_visual_property('EDGE_SOURCE_ARROW_UNSELECTED_PAINT', table_column, table_column_values=table_column_values, range_map=colors, mapping_type=mapping_type, style_name=style_name, network=network, base_url=base_url, table='edge')<|docstring|>Map table column values to colors to set the source arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
colors (list): values between 0 and 255; 0 is invisible
mapping_type (str): continuous, discrete or passthrough (c,d,p); default is continuoue
default_color (str): Hex color to set as default
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if invalid color, table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_color_mapping('EdgeBetweenness', [2.0, 20000.0], ['#FBE723', '#440256'], style_name='galFiltered Style')
''
>>> set_edge_source_arrow_color_mapping('interaction', ['pp','pd'], ['#FFFF00', '#00FF00'], 'd', style_name='galFiltered Style')
''
>>> set_edge_source_arrow_color_mapping('ColorCol', mapping_type='p', default_color='#654321', style_name='galFiltered Style')
''<|endoftext|> |
e767f5f698262770d2c1bb1677d6cb82b69f3bff98d8be51e31d22cb74473df0 | @cy_log
def set_edge_target_arrow_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the target arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Shape to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_target_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'DIAMOND\', \'CIRCLE\'], style_name=\'galFiltered Style\')\n \'\'\n\n Note:\n This is the same function as ``set_edge_target_arrow_mapping()``\n\n See also:\n :meth:`set_edge_target_arrow_mapping`\n '
return set_edge_target_arrow_maping(table_column, table_column_values=table_column_values, shapes=shapes, default_shape=default_shape, style_name=style_name, network=network, base_url=base_url) | Map table column values to colors to set the target arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Shape to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_target_mapping('interaction', table_column_values=['pp','pd'], shapes=['DIAMOND', 'CIRCLE'], style_name='galFiltered Style')
''
Note:
This is the same function as ``set_edge_target_arrow_mapping()``
See also:
:meth:`set_edge_target_arrow_mapping` | py4cytoscape/style_mappings.py | set_edge_target_arrow_shape_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_target_arrow_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the target arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Shape to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_target_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'DIAMOND\', \'CIRCLE\'], style_name=\'galFiltered Style\')\n \'\'\n\n Note:\n This is the same function as ``set_edge_target_arrow_mapping()``\n\n See also:\n :meth:`set_edge_target_arrow_mapping`\n '
return set_edge_target_arrow_maping(table_column, table_column_values=table_column_values, shapes=shapes, default_shape=default_shape, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_edge_target_arrow_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the target arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Shape to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_target_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'DIAMOND\', \'CIRCLE\'], style_name=\'galFiltered Style\')\n \'\'\n\n Note:\n This is the same function as ``set_edge_target_arrow_mapping()``\n\n See also:\n :meth:`set_edge_target_arrow_mapping`\n '
return set_edge_target_arrow_maping(table_column, table_column_values=table_column_values, shapes=shapes, default_shape=default_shape, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to colors to set the target arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Shape to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_target_mapping('interaction', table_column_values=['pp','pd'], shapes=['DIAMOND', 'CIRCLE'], style_name='galFiltered Style')
''
Note:
This is the same function as ``set_edge_target_arrow_mapping()``
See also:
:meth:`set_edge_target_arrow_mapping`<|endoftext|> |
3380184c4a9d72ed85d2d7cbf6c019711f4a513060cef04fadb4f5161cc4a2e8 | @cy_log
def set_edge_source_arrow_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the source arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Shape to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_shape_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'DIAMOND\', \'CIRCLE\'], style_name=\'galFiltered Style\')\n \'\'\n\n Note:\n This is the same function as ``set_edge_source_arrow_mapping()``\n\n See also:\n :meth:`set_edge_source_arrow_mapping`\n '
return set_edge_source_arrow_mapping(table_column, table_column_values=table_column_values, shapes=shapes, default_shape=default_shape, style_name=style_name, network=network, base_url=base_url) | Map table column values to colors to set the source arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Shape to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_shape_mapping('interaction', table_column_values=['pp','pd'], shapes=['DIAMOND', 'CIRCLE'], style_name='galFiltered Style')
''
Note:
This is the same function as ``set_edge_source_arrow_mapping()``
See also:
:meth:`set_edge_source_arrow_mapping` | py4cytoscape/style_mappings.py | set_edge_source_arrow_shape_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_source_arrow_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the source arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Shape to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_shape_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'DIAMOND\', \'CIRCLE\'], style_name=\'galFiltered Style\')\n \'\'\n\n Note:\n This is the same function as ``set_edge_source_arrow_mapping()``\n\n See also:\n :meth:`set_edge_source_arrow_mapping`\n '
return set_edge_source_arrow_mapping(table_column, table_column_values=table_column_values, shapes=shapes, default_shape=default_shape, style_name=style_name, network=network, base_url=base_url) | @cy_log
def set_edge_source_arrow_shape_mapping(table_column, table_column_values=None, shapes=None, default_shape=None, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Map table column values to colors to set the source arrow color.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n table_column_values (list): List of values from Cytoscape table to be used in mapping\n shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``\n default_shape (str): Shape to set as default. See ``get_arrow_shapes()``\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_source_arrow_shape_mapping(\'interaction\', table_column_values=[\'pp\',\'pd\'], shapes=[\'DIAMOND\', \'CIRCLE\'], style_name=\'galFiltered Style\')\n \'\'\n\n Note:\n This is the same function as ``set_edge_source_arrow_mapping()``\n\n See also:\n :meth:`set_edge_source_arrow_mapping`\n '
return set_edge_source_arrow_mapping(table_column, table_column_values=table_column_values, shapes=shapes, default_shape=default_shape, style_name=style_name, network=network, base_url=base_url)<|docstring|>Map table column values to colors to set the source arrow color.
Args:
table_column (str): Name of Cytoscape table column to map values from
table_column_values (list): List of values from Cytoscape table to be used in mapping
shapes (list): List of arrow shapes to map to ``table_column_values``. See ``get_arrow_shapes()``
default_shape (str): Shape to set as default. See ``get_arrow_shapes()``
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_source_arrow_shape_mapping('interaction', table_column_values=['pp','pd'], shapes=['DIAMOND', 'CIRCLE'], style_name='galFiltered Style')
''
Note:
This is the same function as ``set_edge_source_arrow_mapping()``
See also:
:meth:`set_edge_source_arrow_mapping`<|endoftext|> |
d52a6c9935ae4534e0a97a14b59fb29c14505b5034eabcca47cfac4af34a685e | @cy_log
def set_edge_tooltip_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as edge tooltips.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_tooltip_mapping(\'PassthruCol\', style_name=\'galFiltered Style\')\n \'\'\n '
return _update_visual_property('EDGE_TOOLTIP', table_column, mapping_type='p', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['p']) | Pass the values from a table column to display as edge tooltips.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_tooltip_mapping('PassthruCol', style_name='galFiltered Style')
'' | py4cytoscape/style_mappings.py | set_edge_tooltip_mapping | tyasird/py4cytoscape | 0 | python | @cy_log
def set_edge_tooltip_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as edge tooltips.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_tooltip_mapping(\'PassthruCol\', style_name=\'galFiltered Style\')\n \'\'\n '
return _update_visual_property('EDGE_TOOLTIP', table_column, mapping_type='p', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['p']) | @cy_log
def set_edge_tooltip_mapping(table_column, style_name='default', network=None, base_url=DEFAULT_BASE_URL):
'Pass the values from a table column to display as edge tooltips.\n\n Args:\n table_column (str): Name of Cytoscape table column to map values from\n style_name (str): name for style\n network (SUID or str or None): Name or SUID of a network or view. Default is the\n "current" network active in Cytoscape.\n base_url (str): Ignore unless you need to specify a custom domain,\n port or version to connect to the CyREST API. Default is http://localhost:1234\n and the latest version of the CyREST API supported by this version of py4cytoscape.\n\n Returns:\n str: \'\'\n\n Raises:\n CyError: if table column doesn\'t exist, table column values doesn\'t match values list, or invalid style name, network or mapping type\n requests.exceptions.RequestException: if can\'t connect to Cytoscape or Cytoscape returns an error\n\n Examples:\n >>> set_edge_tooltip_mapping(\'PassthruCol\', style_name=\'galFiltered Style\')\n \'\'\n '
return _update_visual_property('EDGE_TOOLTIP', table_column, mapping_type='p', style_name=style_name, network=network, base_url=base_url, table='edge', supported_mappings=['p'])<|docstring|>Pass the values from a table column to display as edge tooltips.
Args:
table_column (str): Name of Cytoscape table column to map values from
style_name (str): name for style
network (SUID or str or None): Name or SUID of a network or view. Default is the
"current" network active in Cytoscape.
base_url (str): Ignore unless you need to specify a custom domain,
port or version to connect to the CyREST API. Default is http://localhost:1234
and the latest version of the CyREST API supported by this version of py4cytoscape.
Returns:
str: ''
Raises:
CyError: if table column doesn't exist, table column values doesn't match values list, or invalid style name, network or mapping type
requests.exceptions.RequestException: if can't connect to Cytoscape or Cytoscape returns an error
Examples:
>>> set_edge_tooltip_mapping('PassthruCol', style_name='galFiltered Style')
''<|endoftext|> |
739202b14432e0031a2727f5458adf8e4aeb1d25f147917aef282465dbd2d1c5 | @property
def active_tuning_curve_render_configs(self):
'The active_tuning_curve_render_configs property.'
return self.active_neuron_render_configs | The active_tuning_curve_render_configs property. | src/pyphoplacecellanalysis/PhoPositionalData/plotting/mixins/placefield_plotting_mixins.py | active_tuning_curve_render_configs | CommanderPho/pyPhoPlaceCellAnalysis | 0 | python | @property
def active_tuning_curve_render_configs(self):
return self.active_neuron_render_configs | @property
def active_tuning_curve_render_configs(self):
return self.active_neuron_render_configs<|docstring|>The active_tuning_curve_render_configs property.<|endoftext|> |
466ace5c181c36f102c986c226db8476d6c7e1311d4c754763a9ba8bab580eb7 | def update_active_placefields(self, placefield_indicies):
' \n Usage: \n included_cell_ids = [48, 61]\n included_cell_INDEXES = [ipcDataExplorer.get_neuron_id_and_idx(cell_id=an_included_cell_ID)[0] for an_included_cell_ID in included_cell_ids] # get the indexes from the cellIDs\n ipcDataExplorer.update_active_placefields(included_cell_INDEXES) # actives only the placefields that have aclu values (cell ids) in the included_cell_ids array.\n '
self._hide_all_tuning_curves()
for a_pf_idx in placefield_indicies:
self._show_tuning_curve(a_pf_idx) | Usage:
included_cell_ids = [48, 61]
included_cell_INDEXES = [ipcDataExplorer.get_neuron_id_and_idx(cell_id=an_included_cell_ID)[0] for an_included_cell_ID in included_cell_ids] # get the indexes from the cellIDs
ipcDataExplorer.update_active_placefields(included_cell_INDEXES) # actives only the placefields that have aclu values (cell ids) in the included_cell_ids array. | src/pyphoplacecellanalysis/PhoPositionalData/plotting/mixins/placefield_plotting_mixins.py | update_active_placefields | CommanderPho/pyPhoPlaceCellAnalysis | 0 | python | def update_active_placefields(self, placefield_indicies):
' \n Usage: \n included_cell_ids = [48, 61]\n included_cell_INDEXES = [ipcDataExplorer.get_neuron_id_and_idx(cell_id=an_included_cell_ID)[0] for an_included_cell_ID in included_cell_ids] # get the indexes from the cellIDs\n ipcDataExplorer.update_active_placefields(included_cell_INDEXES) # actives only the placefields that have aclu values (cell ids) in the included_cell_ids array.\n '
self._hide_all_tuning_curves()
for a_pf_idx in placefield_indicies:
self._show_tuning_curve(a_pf_idx) | def update_active_placefields(self, placefield_indicies):
' \n Usage: \n included_cell_ids = [48, 61]\n included_cell_INDEXES = [ipcDataExplorer.get_neuron_id_and_idx(cell_id=an_included_cell_ID)[0] for an_included_cell_ID in included_cell_ids] # get the indexes from the cellIDs\n ipcDataExplorer.update_active_placefields(included_cell_INDEXES) # actives only the placefields that have aclu values (cell ids) in the included_cell_ids array.\n '
self._hide_all_tuning_curves()
for a_pf_idx in placefield_indicies:
self._show_tuning_curve(a_pf_idx)<|docstring|>Usage:
included_cell_ids = [48, 61]
included_cell_INDEXES = [ipcDataExplorer.get_neuron_id_and_idx(cell_id=an_included_cell_ID)[0] for an_included_cell_ID in included_cell_ids] # get the indexes from the cellIDs
ipcDataExplorer.update_active_placefields(included_cell_INDEXES) # actives only the placefields that have aclu values (cell ids) in the included_cell_ids array.<|endoftext|> |
4ba13228f20c4e1ce7b022ff5c34621b3861541e99a29d21b12ddc78252b04ee | def update_tuning_curve_configs(self):
" update the configs from the actual actors' state "
for (i, aTuningCurveActor) in enumerate(self.tuning_curve_plot_actors):
self.active_tuning_curve_render_configs[i].isVisible = bool(aTuningCurveActor.GetVisibility()) | update the configs from the actual actors' state | src/pyphoplacecellanalysis/PhoPositionalData/plotting/mixins/placefield_plotting_mixins.py | update_tuning_curve_configs | CommanderPho/pyPhoPlaceCellAnalysis | 0 | python | def update_tuning_curve_configs(self):
" "
for (i, aTuningCurveActor) in enumerate(self.tuning_curve_plot_actors):
self.active_tuning_curve_render_configs[i].isVisible = bool(aTuningCurveActor.GetVisibility()) | def update_tuning_curve_configs(self):
" "
for (i, aTuningCurveActor) in enumerate(self.tuning_curve_plot_actors):
self.active_tuning_curve_render_configs[i].isVisible = bool(aTuningCurveActor.GetVisibility())<|docstring|>update the configs from the actual actors' state<|endoftext|> |
d13efa8fc755a5c4ec94a7bc1ca9784f9822ddb488dd3f0c47d004b407e3263b | def apply_tuning_curve_configs(self):
' update the actual actors from the configs '
for (i, aTuningCurveActor) in enumerate(self.tuning_curve_plot_actors):
aTuningCurveActor.SetVisibility(int(self.active_tuning_curve_render_configs[i].isVisible)) | update the actual actors from the configs | src/pyphoplacecellanalysis/PhoPositionalData/plotting/mixins/placefield_plotting_mixins.py | apply_tuning_curve_configs | CommanderPho/pyPhoPlaceCellAnalysis | 0 | python | def apply_tuning_curve_configs(self):
' '
for (i, aTuningCurveActor) in enumerate(self.tuning_curve_plot_actors):
aTuningCurveActor.SetVisibility(int(self.active_tuning_curve_render_configs[i].isVisible)) | def apply_tuning_curve_configs(self):
' '
for (i, aTuningCurveActor) in enumerate(self.tuning_curve_plot_actors):
aTuningCurveActor.SetVisibility(int(self.active_tuning_curve_render_configs[i].isVisible))<|docstring|>update the actual actors from the configs<|endoftext|> |
ea9ed46c04763ccc0aa020c747104646e449f43dc44a32177b428a63426ef88e | def comp_npv(self):
'\n lasketaan montako timestep:iä max_age:n jälkeen henkilö on vanhuuseläkkeellä \n hyvin yksinkertainen toteutus\n '
npv = np.zeros(self.n_groups)
for g in range(self.n_groups):
cpsum = 1
for x in np.arange(100, self.max_age, (- self.timestep)):
intx = int(np.floor(x))
m = self.mort_intensity[(intx, g)]
cpsum = ((m * 1) + ((1 - m) * (1 + (self.gamma * cpsum))))
npv[g] = cpsum
return npv | lasketaan montako timestep:iä max_age:n jälkeen henkilö on vanhuuseläkkeellä
hyvin yksinkertainen toteutus | gym_unemployment/envs/test_environment.py | comp_npv | ajtanskanen/econogym | 1 | python | def comp_npv(self):
'\n lasketaan montako timestep:iä max_age:n jälkeen henkilö on vanhuuseläkkeellä \n hyvin yksinkertainen toteutus\n '
npv = np.zeros(self.n_groups)
for g in range(self.n_groups):
cpsum = 1
for x in np.arange(100, self.max_age, (- self.timestep)):
intx = int(np.floor(x))
m = self.mort_intensity[(intx, g)]
cpsum = ((m * 1) + ((1 - m) * (1 + (self.gamma * cpsum))))
npv[g] = cpsum
return npv | def comp_npv(self):
'\n lasketaan montako timestep:iä max_age:n jälkeen henkilö on vanhuuseläkkeellä \n hyvin yksinkertainen toteutus\n '
npv = np.zeros(self.n_groups)
for g in range(self.n_groups):
cpsum = 1
for x in np.arange(100, self.max_age, (- self.timestep)):
intx = int(np.floor(x))
m = self.mort_intensity[(intx, g)]
cpsum = ((m * 1) + ((1 - m) * (1 + (self.gamma * cpsum))))
npv[g] = cpsum
return npv<|docstring|>lasketaan montako timestep:iä max_age:n jälkeen henkilö on vanhuuseläkkeellä
hyvin yksinkertainen toteutus<|endoftext|> |
acd36f9ae41dcc588e4cdc6297563ae8acffd103487bd1188aef2ef3fbe2cef6 | def comp_benefits(self, wage, old_wage, pension, employment_status, time_in_state, ika=25, irtisanottu=0, tyossaoloehto=0, tyohistoria=0):
'\n Kutsuu fin_benefits-modulia, jonka avulla lasketaan etuudet ja huomioidaan verotus\n Laske etuuksien arvo, kun \n wage on palkka\n old_wage on vanha palkka\n pension on eläkkeen määrä\n employment_status on töissä olo (0)/työttömyys (1)/eläkkeellä olo (2)\n prev_empl on työttömyyden kesto (0/1/2)\n ika on henkilön ikä\n '
p = {}
p['perustulo'] = self.perustulo
p['opiskelija'] = self.perustulo
p['toimeentulotuki_vahennys'] = 0
p['ika'] = ika
p['lapsia'] = 0
p['paivahoidossa'] = 0
p['aikuisia'] = 1
p['veromalli'] = 0
p['kuntaryhma'] = 3
p['lapsia_kotihoidontuella'] = 0
p['alle3v'] = 0
p['tyottomyyden_kesto'] = 1
p['puolison_tyottomyyden_kesto'] = 10
p['isyysvapaalla'] = 0
p['aitiysvapaalla'] = 0
p['kotihoidontuella'] = 0
p['alle_kouluikaisia'] = 0
p['tyoelake'] = 0
p['elakkeella'] = 0
if (employment_status == 1):
p['tyoton'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = (wage / 12)
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 0):
if (ika <= 65):
p['tyoton'] = 1
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['tyottomyyden_kesto'] = ((12 * 21.5) * time_in_state)
if ((((tyohistoria >= self.tyohistoria_vaatimus) and (p['tyottomyyden_kesto'] <= self.ansiopvraha_kesto400)) or (p['tyottomyyden_kesto'] <= self.ansiopvraha_kesto300)) and (tyossaoloehto >= self.toe_vaatimus) and ((irtisanottu > 0) or (time_in_state >= self.karenssi_kesto))):
p['saa_ansiopaivarahaa'] = 1
else:
p['saa_ansiopaivarahaa'] = 0
else:
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 3):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
elif (employment_status == 4):
if (ika <= 65):
p['tyoton'] = 1
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
if ((tyossaoloehto > self.toe_vaatimus) and ((irtisanottu > 0) or (time_in_state >= self.karenssi_kesto))):
p['saa_ansiopaivarahaa'] = 1
else:
p['saa_ansiopaivarahaa'] = 0
else:
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 5):
p['aitiysvapaalla'] = 1
p['tyoton'] = 0
p['aitiysvapaa_kesto'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 1
elif (employment_status == 6):
p['isyysvapaalla'] = 1
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 1
elif (employment_status == 7):
p['kotihoidontuella'] = 1
p['lapsia'] = 1
p['tyoton'] = 0
p['alle3v'] = 1
p['kotihoidontuki_kesto'] = time_in_state
p['lapsia_kotihoidontuella'] = p['lapsia']
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 2):
if (ika > self.min_retirementage):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
else:
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 0
p['tyoelake'] = 0
elif (employment_status == 8):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
elif (employment_status == 9):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
elif (employment_status == 10):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
elif (employment_status == 11):
p['tyoton'] = 0
p['toimeentulotuki_vahennys'] = 1
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
elif (employment_status == 12):
p['tyoton'] = 0
p['opiskelija'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
else:
print('Unknown employment_status ', employment_status)
p['asumismenot_toimeentulo'] = 500
p['asumismenot_asumistuki'] = 500
p['ansiopvrahan_suojaosa'] = 1
p['ansiopvraha_lapsikorotus'] = 1
p['puolison_tulot'] = 0
p['puoliso_tyoton'] = 0
p['puoliso_vakiintunutpalkka'] = 0
p['puoliso_saa_ansiopaivarahaa'] = 0
p['puolison_tulot'] = 0
(netto, benefitq) = self.ben.laske_tulot(p)
netto = max(0, (netto - p['asumismenot_asumistuki']))
netto = (netto * 12)
return netto | Kutsuu fin_benefits-modulia, jonka avulla lasketaan etuudet ja huomioidaan verotus
Laske etuuksien arvo, kun
wage on palkka
old_wage on vanha palkka
pension on eläkkeen määrä
employment_status on töissä olo (0)/työttömyys (1)/eläkkeellä olo (2)
prev_empl on työttömyyden kesto (0/1/2)
ika on henkilön ikä | gym_unemployment/envs/test_environment.py | comp_benefits | ajtanskanen/econogym | 1 | python | def comp_benefits(self, wage, old_wage, pension, employment_status, time_in_state, ika=25, irtisanottu=0, tyossaoloehto=0, tyohistoria=0):
'\n Kutsuu fin_benefits-modulia, jonka avulla lasketaan etuudet ja huomioidaan verotus\n Laske etuuksien arvo, kun \n wage on palkka\n old_wage on vanha palkka\n pension on eläkkeen määrä\n employment_status on töissä olo (0)/työttömyys (1)/eläkkeellä olo (2)\n prev_empl on työttömyyden kesto (0/1/2)\n ika on henkilön ikä\n '
p = {}
p['perustulo'] = self.perustulo
p['opiskelija'] = self.perustulo
p['toimeentulotuki_vahennys'] = 0
p['ika'] = ika
p['lapsia'] = 0
p['paivahoidossa'] = 0
p['aikuisia'] = 1
p['veromalli'] = 0
p['kuntaryhma'] = 3
p['lapsia_kotihoidontuella'] = 0
p['alle3v'] = 0
p['tyottomyyden_kesto'] = 1
p['puolison_tyottomyyden_kesto'] = 10
p['isyysvapaalla'] = 0
p['aitiysvapaalla'] = 0
p['kotihoidontuella'] = 0
p['alle_kouluikaisia'] = 0
p['tyoelake'] = 0
p['elakkeella'] = 0
if (employment_status == 1):
p['tyoton'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = (wage / 12)
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 0):
if (ika <= 65):
p['tyoton'] = 1
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['tyottomyyden_kesto'] = ((12 * 21.5) * time_in_state)
if ((((tyohistoria >= self.tyohistoria_vaatimus) and (p['tyottomyyden_kesto'] <= self.ansiopvraha_kesto400)) or (p['tyottomyyden_kesto'] <= self.ansiopvraha_kesto300)) and (tyossaoloehto >= self.toe_vaatimus) and ((irtisanottu > 0) or (time_in_state >= self.karenssi_kesto))):
p['saa_ansiopaivarahaa'] = 1
else:
p['saa_ansiopaivarahaa'] = 0
else:
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 3):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
elif (employment_status == 4):
if (ika <= 65):
p['tyoton'] = 1
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
if ((tyossaoloehto > self.toe_vaatimus) and ((irtisanottu > 0) or (time_in_state >= self.karenssi_kesto))):
p['saa_ansiopaivarahaa'] = 1
else:
p['saa_ansiopaivarahaa'] = 0
else:
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 5):
p['aitiysvapaalla'] = 1
p['tyoton'] = 0
p['aitiysvapaa_kesto'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 1
elif (employment_status == 6):
p['isyysvapaalla'] = 1
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 1
elif (employment_status == 7):
p['kotihoidontuella'] = 1
p['lapsia'] = 1
p['tyoton'] = 0
p['alle3v'] = 1
p['kotihoidontuki_kesto'] = time_in_state
p['lapsia_kotihoidontuella'] = p['lapsia']
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 2):
if (ika > self.min_retirementage):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
else:
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 0
p['tyoelake'] = 0
elif (employment_status == 8):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
elif (employment_status == 9):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
elif (employment_status == 10):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
elif (employment_status == 11):
p['tyoton'] = 0
p['toimeentulotuki_vahennys'] = 1
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
elif (employment_status == 12):
p['tyoton'] = 0
p['opiskelija'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
else:
print('Unknown employment_status ', employment_status)
p['asumismenot_toimeentulo'] = 500
p['asumismenot_asumistuki'] = 500
p['ansiopvrahan_suojaosa'] = 1
p['ansiopvraha_lapsikorotus'] = 1
p['puolison_tulot'] = 0
p['puoliso_tyoton'] = 0
p['puoliso_vakiintunutpalkka'] = 0
p['puoliso_saa_ansiopaivarahaa'] = 0
p['puolison_tulot'] = 0
(netto, benefitq) = self.ben.laske_tulot(p)
netto = max(0, (netto - p['asumismenot_asumistuki']))
netto = (netto * 12)
return netto | def comp_benefits(self, wage, old_wage, pension, employment_status, time_in_state, ika=25, irtisanottu=0, tyossaoloehto=0, tyohistoria=0):
'\n Kutsuu fin_benefits-modulia, jonka avulla lasketaan etuudet ja huomioidaan verotus\n Laske etuuksien arvo, kun \n wage on palkka\n old_wage on vanha palkka\n pension on eläkkeen määrä\n employment_status on töissä olo (0)/työttömyys (1)/eläkkeellä olo (2)\n prev_empl on työttömyyden kesto (0/1/2)\n ika on henkilön ikä\n '
p = {}
p['perustulo'] = self.perustulo
p['opiskelija'] = self.perustulo
p['toimeentulotuki_vahennys'] = 0
p['ika'] = ika
p['lapsia'] = 0
p['paivahoidossa'] = 0
p['aikuisia'] = 1
p['veromalli'] = 0
p['kuntaryhma'] = 3
p['lapsia_kotihoidontuella'] = 0
p['alle3v'] = 0
p['tyottomyyden_kesto'] = 1
p['puolison_tyottomyyden_kesto'] = 10
p['isyysvapaalla'] = 0
p['aitiysvapaalla'] = 0
p['kotihoidontuella'] = 0
p['alle_kouluikaisia'] = 0
p['tyoelake'] = 0
p['elakkeella'] = 0
if (employment_status == 1):
p['tyoton'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = (wage / 12)
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 0):
if (ika <= 65):
p['tyoton'] = 1
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['tyottomyyden_kesto'] = ((12 * 21.5) * time_in_state)
if ((((tyohistoria >= self.tyohistoria_vaatimus) and (p['tyottomyyden_kesto'] <= self.ansiopvraha_kesto400)) or (p['tyottomyyden_kesto'] <= self.ansiopvraha_kesto300)) and (tyossaoloehto >= self.toe_vaatimus) and ((irtisanottu > 0) or (time_in_state >= self.karenssi_kesto))):
p['saa_ansiopaivarahaa'] = 1
else:
p['saa_ansiopaivarahaa'] = 0
else:
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 3):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
elif (employment_status == 4):
if (ika <= 65):
p['tyoton'] = 1
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
if ((tyossaoloehto > self.toe_vaatimus) and ((irtisanottu > 0) or (time_in_state >= self.karenssi_kesto))):
p['saa_ansiopaivarahaa'] = 1
else:
p['saa_ansiopaivarahaa'] = 0
else:
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 5):
p['aitiysvapaalla'] = 1
p['tyoton'] = 0
p['aitiysvapaa_kesto'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 1
elif (employment_status == 6):
p['isyysvapaalla'] = 1
p['tyoton'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 1
elif (employment_status == 7):
p['kotihoidontuella'] = 1
p['lapsia'] = 1
p['tyoton'] = 0
p['alle3v'] = 1
p['kotihoidontuki_kesto'] = time_in_state
p['lapsia_kotihoidontuella'] = p['lapsia']
p['t'] = 0
p['vakiintunutpalkka'] = (old_wage / 12)
p['saa_ansiopaivarahaa'] = 0
elif (employment_status == 2):
if (ika > self.min_retirementage):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
else:
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 0
p['tyoelake'] = 0
elif (employment_status == 8):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
elif (employment_status == 9):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
p['elakkeella'] = 1
p['tyoelake'] = (pension / 12)
elif (employment_status == 10):
p['tyoton'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = (wage / 12)
p['vakiintunutpalkka'] = 0
elif (employment_status == 11):
p['tyoton'] = 0
p['toimeentulotuki_vahennys'] = 1
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
elif (employment_status == 12):
p['tyoton'] = 0
p['opiskelija'] = 0
p['saa_ansiopaivarahaa'] = 0
p['t'] = 0
p['vakiintunutpalkka'] = 0
else:
print('Unknown employment_status ', employment_status)
p['asumismenot_toimeentulo'] = 500
p['asumismenot_asumistuki'] = 500
p['ansiopvrahan_suojaosa'] = 1
p['ansiopvraha_lapsikorotus'] = 1
p['puolison_tulot'] = 0
p['puoliso_tyoton'] = 0
p['puoliso_vakiintunutpalkka'] = 0
p['puoliso_saa_ansiopaivarahaa'] = 0
p['puolison_tulot'] = 0
(netto, benefitq) = self.ben.laske_tulot(p)
netto = max(0, (netto - p['asumismenot_asumistuki']))
netto = (netto * 12)
return netto<|docstring|>Kutsuu fin_benefits-modulia, jonka avulla lasketaan etuudet ja huomioidaan verotus
Laske etuuksien arvo, kun
wage on palkka
old_wage on vanha palkka
pension on eläkkeen määrä
employment_status on töissä olo (0)/työttömyys (1)/eläkkeellä olo (2)
prev_empl on työttömyyden kesto (0/1/2)
ika on henkilön ikä<|endoftext|> |
1c1370478a61962645145f95611f8334689e65d4b952f2b601cbc3b1a9847b7a | def seed(self, seed=None):
'\n Open AI interfacen mukainen seed-funktio, joka alustaa satunnaisluvut\n '
(self.np_random, seed) = seeding.np_random(seed)
return [seed] | Open AI interfacen mukainen seed-funktio, joka alustaa satunnaisluvut | gym_unemployment/envs/test_environment.py | seed | ajtanskanen/econogym | 1 | python | def seed(self, seed=None):
'\n \n '
(self.np_random, seed) = seeding.np_random(seed)
return [seed] | def seed(self, seed=None):
'\n \n '
(self.np_random, seed) = seeding.np_random(seed)
return [seed]<|docstring|>Open AI interfacen mukainen seed-funktio, joka alustaa satunnaisluvut<|endoftext|> |
8b45a7a0930fc6c22ee9940375a09eb653df4152d5e5bc82e00c13029afd84e7 | def env_seed(self, seed=None):
'\n Alustetaan numpy.random enviä varten\n '
np.random.seed(seed) | Alustetaan numpy.random enviä varten | gym_unemployment/envs/test_environment.py | env_seed | ajtanskanen/econogym | 1 | python | def env_seed(self, seed=None):
'\n \n '
np.random.seed(seed) | def env_seed(self, seed=None):
'\n \n '
np.random.seed(seed)<|docstring|>Alustetaan numpy.random enviä varten<|endoftext|> |
27820b62068a65aa4616da90303a99de40e59bc2525e0b915d9b05afec319eec | def get_wage(self, age, time_in_state):
'\n palkka age-ikäiselle time_in_state-vähennyksellä työllistymispalkkaan\n '
if ((age <= self.max_age) and (age >= (self.min_age - 1))):
return (self.salary[int(np.floor(age))] * (1 - (min(time_in_state, 5) * self.salary_const)))
else:
return 0 | palkka age-ikäiselle time_in_state-vähennyksellä työllistymispalkkaan | gym_unemployment/envs/test_environment.py | get_wage | ajtanskanen/econogym | 1 | python | def get_wage(self, age, time_in_state):
'\n \n '
if ((age <= self.max_age) and (age >= (self.min_age - 1))):
return (self.salary[int(np.floor(age))] * (1 - (min(time_in_state, 5) * self.salary_const)))
else:
return 0 | def get_wage(self, age, time_in_state):
'\n \n '
if ((age <= self.max_age) and (age >= (self.min_age - 1))):
return (self.salary[int(np.floor(age))] * (1 - (min(time_in_state, 5) * self.salary_const)))
else:
return 0<|docstring|>palkka age-ikäiselle time_in_state-vähennyksellä työllistymispalkkaan<|endoftext|> |
3341bbc156fce86fbe8e4a03f9fc864b34c6cbcb827432d7ff0e2f929113aa13 | def get_mort_rate(self, debug=False):
'\n Kuolleisuus-intensiteetit eri ryhmille\n '
mort = np.zeros((101, self.n_groups))
if debug:
dfactor = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
else:
dfactor = np.array([1.5, 1.0, 0.5, 1.2, 1.0, 0.8])
mort[(:, 1)] = (np.array([2.12, 0.32, 0.17, 0.07, 0.07, 0.1, 0.0, 0.09, 0.03, 0.13, 0.03, 0.07, 0.1, 0.1, 0.1, 0.23, 0.5, 0.52, 0.42, 0.87, 0.79, 0.66, 0.71, 0.69, 0.98, 0.8, 0.77, 1.07, 0.97, 0.76, 0.83, 1.03, 0.98, 1.2, 1.03, 0.76, 1.22, 1.29, 1.1, 1.26, 1.37, 1.43, 1.71, 2.32, 2.22, 1.89, 2.05, 2.15, 2.71, 2.96, 3.52, 3.54, 4.3, 4.34, 5.09, 4.75, 6.17, 5.88, 6.67, 8.0, 9.2, 10.52, 10.3, 12.26, 12.74, 13.22, 15.03, 17.24, 18.14, 17.78, 20.35, 25.57, 23.53, 26.5, 28.57, 31.87, 34.65, 40.88, 42.43, 52.28, 59.26, 62.92, 68.86, 72.7, 94.04, 99.88, 113.11, 128.52, 147.96, 161.89, 175.99, 199.39, 212.52, 248.32, 260.47, 284.01, 319.98, 349.28, 301.37, 370.17, 370.17]) / 1000.0)
mort[(:, 0)] = (dfactor[0] * mort[(:, 1)])
mort[(:, 2)] = (dfactor[2] * mort[(:, 1)])
mort[(:, 4)] = (np.array([1.89, 0.3, 0.11, 0.03, 0.14, 0.03, 0.16, 0.07, 0.13, 0.03, 0.0, 0.07, 0.07, 0.07, 0.18, 0.14, 0.07, 0.31, 0.31, 0.3, 0.33, 0.26, 0.18, 0.33, 0.56, 0.17, 0.32, 0.29, 0.35, 0.24, 0.55, 0.35, 0.23, 0.39, 0.48, 0.38, 0.35, 0.8, 0.42, 0.65, 0.5, 0.68, 0.8, 1.12, 0.99, 0.88, 1.13, 1.01, 1.07, 1.68, 1.79, 2.16, 1.87, 2.32, 2.67, 2.69, 2.88, 2.86, 3.73, 4.19, 3.66, 4.97, 5.2, 5.52, 6.05, 7.17, 7.48, 7.32, 8.88, 10.33, 10.72, 12.77, 12.13, 13.3, 16.18, 18.3, 17.5, 24.63, 26.53, 29.88, 32.65, 38.88, 46.95, 51.3, 60.0, 64.73, 79.35, 90.94, 105.11, 118.46, 141.44, 155.07, 163.11, 198.45, 207.92, 237.21, 254.75, 311.31, 299.59, 356.64, 356.64]) / 1000.0)
mort[(:, 3)] = (dfactor[3] * mort[(:, 4)])
mort[(:, 5)] = (dfactor[5] * mort[(:, 4)])
return mort | Kuolleisuus-intensiteetit eri ryhmille | gym_unemployment/envs/test_environment.py | get_mort_rate | ajtanskanen/econogym | 1 | python | def get_mort_rate(self, debug=False):
'\n \n '
mort = np.zeros((101, self.n_groups))
if debug:
dfactor = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
else:
dfactor = np.array([1.5, 1.0, 0.5, 1.2, 1.0, 0.8])
mort[(:, 1)] = (np.array([2.12, 0.32, 0.17, 0.07, 0.07, 0.1, 0.0, 0.09, 0.03, 0.13, 0.03, 0.07, 0.1, 0.1, 0.1, 0.23, 0.5, 0.52, 0.42, 0.87, 0.79, 0.66, 0.71, 0.69, 0.98, 0.8, 0.77, 1.07, 0.97, 0.76, 0.83, 1.03, 0.98, 1.2, 1.03, 0.76, 1.22, 1.29, 1.1, 1.26, 1.37, 1.43, 1.71, 2.32, 2.22, 1.89, 2.05, 2.15, 2.71, 2.96, 3.52, 3.54, 4.3, 4.34, 5.09, 4.75, 6.17, 5.88, 6.67, 8.0, 9.2, 10.52, 10.3, 12.26, 12.74, 13.22, 15.03, 17.24, 18.14, 17.78, 20.35, 25.57, 23.53, 26.5, 28.57, 31.87, 34.65, 40.88, 42.43, 52.28, 59.26, 62.92, 68.86, 72.7, 94.04, 99.88, 113.11, 128.52, 147.96, 161.89, 175.99, 199.39, 212.52, 248.32, 260.47, 284.01, 319.98, 349.28, 301.37, 370.17, 370.17]) / 1000.0)
mort[(:, 0)] = (dfactor[0] * mort[(:, 1)])
mort[(:, 2)] = (dfactor[2] * mort[(:, 1)])
mort[(:, 4)] = (np.array([1.89, 0.3, 0.11, 0.03, 0.14, 0.03, 0.16, 0.07, 0.13, 0.03, 0.0, 0.07, 0.07, 0.07, 0.18, 0.14, 0.07, 0.31, 0.31, 0.3, 0.33, 0.26, 0.18, 0.33, 0.56, 0.17, 0.32, 0.29, 0.35, 0.24, 0.55, 0.35, 0.23, 0.39, 0.48, 0.38, 0.35, 0.8, 0.42, 0.65, 0.5, 0.68, 0.8, 1.12, 0.99, 0.88, 1.13, 1.01, 1.07, 1.68, 1.79, 2.16, 1.87, 2.32, 2.67, 2.69, 2.88, 2.86, 3.73, 4.19, 3.66, 4.97, 5.2, 5.52, 6.05, 7.17, 7.48, 7.32, 8.88, 10.33, 10.72, 12.77, 12.13, 13.3, 16.18, 18.3, 17.5, 24.63, 26.53, 29.88, 32.65, 38.88, 46.95, 51.3, 60.0, 64.73, 79.35, 90.94, 105.11, 118.46, 141.44, 155.07, 163.11, 198.45, 207.92, 237.21, 254.75, 311.31, 299.59, 356.64, 356.64]) / 1000.0)
mort[(:, 3)] = (dfactor[3] * mort[(:, 4)])
mort[(:, 5)] = (dfactor[5] * mort[(:, 4)])
return mort | def get_mort_rate(self, debug=False):
'\n \n '
mort = np.zeros((101, self.n_groups))
if debug:
dfactor = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
else:
dfactor = np.array([1.5, 1.0, 0.5, 1.2, 1.0, 0.8])
mort[(:, 1)] = (np.array([2.12, 0.32, 0.17, 0.07, 0.07, 0.1, 0.0, 0.09, 0.03, 0.13, 0.03, 0.07, 0.1, 0.1, 0.1, 0.23, 0.5, 0.52, 0.42, 0.87, 0.79, 0.66, 0.71, 0.69, 0.98, 0.8, 0.77, 1.07, 0.97, 0.76, 0.83, 1.03, 0.98, 1.2, 1.03, 0.76, 1.22, 1.29, 1.1, 1.26, 1.37, 1.43, 1.71, 2.32, 2.22, 1.89, 2.05, 2.15, 2.71, 2.96, 3.52, 3.54, 4.3, 4.34, 5.09, 4.75, 6.17, 5.88, 6.67, 8.0, 9.2, 10.52, 10.3, 12.26, 12.74, 13.22, 15.03, 17.24, 18.14, 17.78, 20.35, 25.57, 23.53, 26.5, 28.57, 31.87, 34.65, 40.88, 42.43, 52.28, 59.26, 62.92, 68.86, 72.7, 94.04, 99.88, 113.11, 128.52, 147.96, 161.89, 175.99, 199.39, 212.52, 248.32, 260.47, 284.01, 319.98, 349.28, 301.37, 370.17, 370.17]) / 1000.0)
mort[(:, 0)] = (dfactor[0] * mort[(:, 1)])
mort[(:, 2)] = (dfactor[2] * mort[(:, 1)])
mort[(:, 4)] = (np.array([1.89, 0.3, 0.11, 0.03, 0.14, 0.03, 0.16, 0.07, 0.13, 0.03, 0.0, 0.07, 0.07, 0.07, 0.18, 0.14, 0.07, 0.31, 0.31, 0.3, 0.33, 0.26, 0.18, 0.33, 0.56, 0.17, 0.32, 0.29, 0.35, 0.24, 0.55, 0.35, 0.23, 0.39, 0.48, 0.38, 0.35, 0.8, 0.42, 0.65, 0.5, 0.68, 0.8, 1.12, 0.99, 0.88, 1.13, 1.01, 1.07, 1.68, 1.79, 2.16, 1.87, 2.32, 2.67, 2.69, 2.88, 2.86, 3.73, 4.19, 3.66, 4.97, 5.2, 5.52, 6.05, 7.17, 7.48, 7.32, 8.88, 10.33, 10.72, 12.77, 12.13, 13.3, 16.18, 18.3, 17.5, 24.63, 26.53, 29.88, 32.65, 38.88, 46.95, 51.3, 60.0, 64.73, 79.35, 90.94, 105.11, 118.46, 141.44, 155.07, 163.11, 198.45, 207.92, 237.21, 254.75, 311.31, 299.59, 356.64, 356.64]) / 1000.0)
mort[(:, 3)] = (dfactor[3] * mort[(:, 4)])
mort[(:, 5)] = (dfactor[5] * mort[(:, 4)])
return mort<|docstring|>Kuolleisuus-intensiteetit eri ryhmille<|endoftext|> |
f6592c7aa6ff823e9a65488f50d64b929904cf35413b64ba7263f5bb2684f613 | def get_disability_rate(self, debug=False):
'\n Työkyvyttömyys-alkavuudet eri ryhmille\n '
disab = np.zeros((69, self.n_groups))
if debug:
dfactor = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
else:
dfactor = np.array([1.5, 1.0, 0.5, 1.2, 1.0, 0.8])
for g in range(self.n_groups):
factor = dfactor[g]
disab[(20, g)] = (1.99 * factor)
disab[(21, g)] = (1.99 * factor)
disab[(22, g)] = (1.99 * factor)
disab[(23, g)] = (1.99 * factor)
disab[(24, g)] = (1.99 * factor)
disab[(25, g)] = (1.99 * factor)
disab[(26, g)] = (1.84 * factor)
disab[(27, g)] = (2.45 * factor)
disab[(28, g)] = (1.95 * factor)
disab[(29, g)] = (2.06 * factor)
disab[(30, g)] = (1.74 * factor)
disab[(31, g)] = (2.2 * factor)
disab[(32, g)] = (2.37 * factor)
disab[(33, g)] = (2.35 * factor)
disab[(34, g)] = (2.52 * factor)
disab[(35, g)] = (2.33 * factor)
disab[(36, g)] = (2.83 * factor)
disab[(37, g)] = (2.5 * factor)
disab[(38, g)] = (2.77 * factor)
disab[(39, g)] = (2.91 * factor)
disab[(40, g)] = (3.47 * factor)
disab[(41, g)] = (3.17 * factor)
disab[(42, g)] = (3.16 * factor)
disab[(43, g)] = (3.48 * factor)
disab[(44, g)] = (4.21 * factor)
disab[(45, g)] = (4.16 * factor)
disab[(46, g)] = (4.13 * factor)
disab[(47, g)] = (4.43 * factor)
disab[(48, g)] = (5.08 * factor)
disab[(49, g)] = (5.7 * factor)
disab[(50, g)] = (5.89 * factor)
disab[(51, g)] = (6.76 * factor)
disab[(52, g)] = (7.43 * factor)
disab[(53, g)] = (8.43 * factor)
disab[(54, g)] = (8.79 * factor)
disab[(55, g)] = (10.4 * factor)
disab[(56, g)] = (12.41 * factor)
disab[(57, g)] = (14.54 * factor)
disab[(58, g)] = (17.12 * factor)
disab[(59, g)] = (21.69 * factor)
disab[(60, g)] = (28.88 * factor)
disab[(61, g)] = (30.86 * factor)
disab[(62, g)] = (24.45 * factor)
disab[(63, g)] = (24.45 * factor)
disab[(64, g)] = (24.45 * factor)
disab[(65, g)] = (24.45 * factor)
disab = (disab / 1000)
return disab | Työkyvyttömyys-alkavuudet eri ryhmille | gym_unemployment/envs/test_environment.py | get_disability_rate | ajtanskanen/econogym | 1 | python | def get_disability_rate(self, debug=False):
'\n \n '
disab = np.zeros((69, self.n_groups))
if debug:
dfactor = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
else:
dfactor = np.array([1.5, 1.0, 0.5, 1.2, 1.0, 0.8])
for g in range(self.n_groups):
factor = dfactor[g]
disab[(20, g)] = (1.99 * factor)
disab[(21, g)] = (1.99 * factor)
disab[(22, g)] = (1.99 * factor)
disab[(23, g)] = (1.99 * factor)
disab[(24, g)] = (1.99 * factor)
disab[(25, g)] = (1.99 * factor)
disab[(26, g)] = (1.84 * factor)
disab[(27, g)] = (2.45 * factor)
disab[(28, g)] = (1.95 * factor)
disab[(29, g)] = (2.06 * factor)
disab[(30, g)] = (1.74 * factor)
disab[(31, g)] = (2.2 * factor)
disab[(32, g)] = (2.37 * factor)
disab[(33, g)] = (2.35 * factor)
disab[(34, g)] = (2.52 * factor)
disab[(35, g)] = (2.33 * factor)
disab[(36, g)] = (2.83 * factor)
disab[(37, g)] = (2.5 * factor)
disab[(38, g)] = (2.77 * factor)
disab[(39, g)] = (2.91 * factor)
disab[(40, g)] = (3.47 * factor)
disab[(41, g)] = (3.17 * factor)
disab[(42, g)] = (3.16 * factor)
disab[(43, g)] = (3.48 * factor)
disab[(44, g)] = (4.21 * factor)
disab[(45, g)] = (4.16 * factor)
disab[(46, g)] = (4.13 * factor)
disab[(47, g)] = (4.43 * factor)
disab[(48, g)] = (5.08 * factor)
disab[(49, g)] = (5.7 * factor)
disab[(50, g)] = (5.89 * factor)
disab[(51, g)] = (6.76 * factor)
disab[(52, g)] = (7.43 * factor)
disab[(53, g)] = (8.43 * factor)
disab[(54, g)] = (8.79 * factor)
disab[(55, g)] = (10.4 * factor)
disab[(56, g)] = (12.41 * factor)
disab[(57, g)] = (14.54 * factor)
disab[(58, g)] = (17.12 * factor)
disab[(59, g)] = (21.69 * factor)
disab[(60, g)] = (28.88 * factor)
disab[(61, g)] = (30.86 * factor)
disab[(62, g)] = (24.45 * factor)
disab[(63, g)] = (24.45 * factor)
disab[(64, g)] = (24.45 * factor)
disab[(65, g)] = (24.45 * factor)
disab = (disab / 1000)
return disab | def get_disability_rate(self, debug=False):
'\n \n '
disab = np.zeros((69, self.n_groups))
if debug:
dfactor = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
else:
dfactor = np.array([1.5, 1.0, 0.5, 1.2, 1.0, 0.8])
for g in range(self.n_groups):
factor = dfactor[g]
disab[(20, g)] = (1.99 * factor)
disab[(21, g)] = (1.99 * factor)
disab[(22, g)] = (1.99 * factor)
disab[(23, g)] = (1.99 * factor)
disab[(24, g)] = (1.99 * factor)
disab[(25, g)] = (1.99 * factor)
disab[(26, g)] = (1.84 * factor)
disab[(27, g)] = (2.45 * factor)
disab[(28, g)] = (1.95 * factor)
disab[(29, g)] = (2.06 * factor)
disab[(30, g)] = (1.74 * factor)
disab[(31, g)] = (2.2 * factor)
disab[(32, g)] = (2.37 * factor)
disab[(33, g)] = (2.35 * factor)
disab[(34, g)] = (2.52 * factor)
disab[(35, g)] = (2.33 * factor)
disab[(36, g)] = (2.83 * factor)
disab[(37, g)] = (2.5 * factor)
disab[(38, g)] = (2.77 * factor)
disab[(39, g)] = (2.91 * factor)
disab[(40, g)] = (3.47 * factor)
disab[(41, g)] = (3.17 * factor)
disab[(42, g)] = (3.16 * factor)
disab[(43, g)] = (3.48 * factor)
disab[(44, g)] = (4.21 * factor)
disab[(45, g)] = (4.16 * factor)
disab[(46, g)] = (4.13 * factor)
disab[(47, g)] = (4.43 * factor)
disab[(48, g)] = (5.08 * factor)
disab[(49, g)] = (5.7 * factor)
disab[(50, g)] = (5.89 * factor)
disab[(51, g)] = (6.76 * factor)
disab[(52, g)] = (7.43 * factor)
disab[(53, g)] = (8.43 * factor)
disab[(54, g)] = (8.79 * factor)
disab[(55, g)] = (10.4 * factor)
disab[(56, g)] = (12.41 * factor)
disab[(57, g)] = (14.54 * factor)
disab[(58, g)] = (17.12 * factor)
disab[(59, g)] = (21.69 * factor)
disab[(60, g)] = (28.88 * factor)
disab[(61, g)] = (30.86 * factor)
disab[(62, g)] = (24.45 * factor)
disab[(63, g)] = (24.45 * factor)
disab[(64, g)] = (24.45 * factor)
disab[(65, g)] = (24.45 * factor)
disab = (disab / 1000)
return disab<|docstring|>Työkyvyttömyys-alkavuudet eri ryhmille<|endoftext|> |
69198e3af94fd608572f81cf7dcec3ad2a77400c950714a418395021c2c889ac | def scale_pension(self, pension, age):
'\n Elinaikakertoimen ja lykkäyskorotuksen huomiointi\n '
return (((self.elinaikakerroin * pension) * self.elakeindeksi) * (1 + (0.048 * (age - self.min_retirementage)))) | Elinaikakertoimen ja lykkäyskorotuksen huomiointi | gym_unemployment/envs/test_environment.py | scale_pension | ajtanskanen/econogym | 1 | python | def scale_pension(self, pension, age):
'\n \n '
return (((self.elinaikakerroin * pension) * self.elakeindeksi) * (1 + (0.048 * (age - self.min_retirementage)))) | def scale_pension(self, pension, age):
'\n \n '
return (((self.elinaikakerroin * pension) * self.elakeindeksi) * (1 + (0.048 * (age - self.min_retirementage))))<|docstring|>Elinaikakertoimen ja lykkäyskorotuksen huomiointi<|endoftext|> |
807a3417f3eb3cbea852fafc05648423c945ac1208b13ce25dee0f36f398c4dd | def move_to_parttime(self, pension, old_wage, age, toe, tyoura, time_in_state):
'\n Siirtymä osa-aikaiseen työskentelyyn\n '
employment_status = 10
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
parttimewage = (0.5 * wage)
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
time_in_state = 0
old_wage = 0
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
netto = self.comp_benefits(parttimewage, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto, toe, tyoura) | Siirtymä osa-aikaiseen työskentelyyn | gym_unemployment/envs/test_environment.py | move_to_parttime | ajtanskanen/econogym | 1 | python | def move_to_parttime(self, pension, old_wage, age, toe, tyoura, time_in_state):
'\n \n '
employment_status = 10
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
parttimewage = (0.5 * wage)
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
time_in_state = 0
old_wage = 0
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
netto = self.comp_benefits(parttimewage, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto, toe, tyoura) | def move_to_parttime(self, pension, old_wage, age, toe, tyoura, time_in_state):
'\n \n '
employment_status = 10
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
parttimewage = (0.5 * wage)
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
time_in_state = 0
old_wage = 0
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
netto = self.comp_benefits(parttimewage, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto, toe, tyoura)<|docstring|>Siirtymä osa-aikaiseen työskentelyyn<|endoftext|> |
60972b1330eeaef36aeaa93cec98e6708aad280a984bc2b36460668404893c87 | def move_to_work(self, pension, old_wage, age, time_in_state, toe, tyoura):
'\n Siirtymä täysiaikaiseen työskentelyyn\n '
employment_status = 1
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state = 0
old_wage = 0
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto, toe, tyoura) | Siirtymä täysiaikaiseen työskentelyyn | gym_unemployment/envs/test_environment.py | move_to_work | ajtanskanen/econogym | 1 | python | def move_to_work(self, pension, old_wage, age, time_in_state, toe, tyoura):
'\n \n '
employment_status = 1
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state = 0
old_wage = 0
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto, toe, tyoura) | def move_to_work(self, pension, old_wage, age, time_in_state, toe, tyoura):
'\n \n '
employment_status = 1
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state = 0
old_wage = 0
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto, toe, tyoura)<|docstring|>Siirtymä täysiaikaiseen työskentelyyn<|endoftext|> |
3cd109bdd82ff3bfae2ce77f84ab13530df35e6d2a5eef9638682e3e66eb8b9b | def move_to_retwork(self, pension, old_wage, age, time_in_state, paid_pension):
'\n Siirtymä vanhuuseläkkeellä työskentelyyn\n '
employment_status = 8
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state += self.timestep
paid_pension = (paid_pension * self.elakeindeksi)
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, 0, paid_pension, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto) | Siirtymä vanhuuseläkkeellä työskentelyyn | gym_unemployment/envs/test_environment.py | move_to_retwork | ajtanskanen/econogym | 1 | python | def move_to_retwork(self, pension, old_wage, age, time_in_state, paid_pension):
'\n \n '
employment_status = 8
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state += self.timestep
paid_pension = (paid_pension * self.elakeindeksi)
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, 0, paid_pension, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto) | def move_to_retwork(self, pension, old_wage, age, time_in_state, paid_pension):
'\n \n '
employment_status = 8
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state += self.timestep
paid_pension = (paid_pension * self.elakeindeksi)
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, 0, paid_pension, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto)<|docstring|>Siirtymä vanhuuseläkkeellä työskentelyyn<|endoftext|> |
f8e39dee520f3b369428e375787c571cf28ea7f85899d699c66d0eae7a6f62ee | def move_to_retpartwork(self, pension, old_wage, age, time_in_state, paid_pension):
'\n Siirtymä osa-aikaiseen vanhuuseläkkeellä työskentelyyn\n '
employment_status = 9
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state += self.timestep
paid_pension = (paid_pension * self.elakeindeksi)
pension = ((pension * self.palkkakerroin) + ((self.acc * wage) * 0.5))
netto = self.comp_benefits((wage * 0.5), 0, paid_pension, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto) | Siirtymä osa-aikaiseen vanhuuseläkkeellä työskentelyyn | gym_unemployment/envs/test_environment.py | move_to_retpartwork | ajtanskanen/econogym | 1 | python | def move_to_retpartwork(self, pension, old_wage, age, time_in_state, paid_pension):
'\n \n '
employment_status = 9
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state += self.timestep
paid_pension = (paid_pension * self.elakeindeksi)
pension = ((pension * self.palkkakerroin) + ((self.acc * wage) * 0.5))
netto = self.comp_benefits((wage * 0.5), 0, paid_pension, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto) | def move_to_retpartwork(self, pension, old_wage, age, time_in_state, paid_pension):
'\n \n '
employment_status = 9
intage = int(np.floor(age))
wage = self.get_wage(intage, time_in_state)
time_in_state += self.timestep
paid_pension = (paid_pension * self.elakeindeksi)
pension = ((pension * self.palkkakerroin) + ((self.acc * wage) * 0.5))
netto = self.comp_benefits((wage * 0.5), 0, paid_pension, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto)<|docstring|>Siirtymä osa-aikaiseen vanhuuseläkkeellä työskentelyyn<|endoftext|> |
d504608859afe9b9287411e7aa82b5d232bdda35af222c94cc309f70ddb92df1 | def move_to_retirement(self, pension, old_wage, age, paid_pension, employment_status, all_acc=True):
'\n Siirtymä vanhuuseläkkeelle\n '
if (age > self.min_retirementage):
if all_acc:
if (employment_status in set([2, 8, 9])):
paid_pension = (pension + paid_pension)
elif (employment_status == 3):
employment_status = 3
else:
paid_pension = self.scale_pension(pension, age)
paid_pension += self.ben.laske_kansanelake(age, paid_pension, 1)
pension = 0
time_in_state = 0
employment_status = 2
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
else:
time_in_state = 0
employment_status = 2
wage = old_wage
netto = self.comp_benefits(0, 0, 0, employment_status, 0, age)
return (employment_status, paid_pension, pension, wage, time_in_state, netto) | Siirtymä vanhuuseläkkeelle | gym_unemployment/envs/test_environment.py | move_to_retirement | ajtanskanen/econogym | 1 | python | def move_to_retirement(self, pension, old_wage, age, paid_pension, employment_status, all_acc=True):
'\n \n '
if (age > self.min_retirementage):
if all_acc:
if (employment_status in set([2, 8, 9])):
paid_pension = (pension + paid_pension)
elif (employment_status == 3):
employment_status = 3
else:
paid_pension = self.scale_pension(pension, age)
paid_pension += self.ben.laske_kansanelake(age, paid_pension, 1)
pension = 0
time_in_state = 0
employment_status = 2
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
else:
time_in_state = 0
employment_status = 2
wage = old_wage
netto = self.comp_benefits(0, 0, 0, employment_status, 0, age)
return (employment_status, paid_pension, pension, wage, time_in_state, netto) | def move_to_retirement(self, pension, old_wage, age, paid_pension, employment_status, all_acc=True):
'\n \n '
if (age > self.min_retirementage):
if all_acc:
if (employment_status in set([2, 8, 9])):
paid_pension = (pension + paid_pension)
elif (employment_status == 3):
employment_status = 3
else:
paid_pension = self.scale_pension(pension, age)
paid_pension += self.ben.laske_kansanelake(age, paid_pension, 1)
pension = 0
time_in_state = 0
employment_status = 2
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
else:
time_in_state = 0
employment_status = 2
wage = old_wage
netto = self.comp_benefits(0, 0, 0, employment_status, 0, age)
return (employment_status, paid_pension, pension, wage, time_in_state, netto)<|docstring|>Siirtymä vanhuuseläkkeelle<|endoftext|> |
3a090c691fbccc77ec06f6bb6ea41728dc25b5a07f28379953980bdc89c21cda | def move_to_unemp(self, pension, old_wage, age, toe, irtisanottu):
'\n Siirtymä työttömyysturvalle\n '
if ((age >= self.min_tyottputki_ika) and self.include_putki):
employment_status = 4
else:
employment_status = 0
time_in_state = 0
intage = int(np.floor(age))
wage = self.get_wage(intage, 0)
if (age <= 65):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, irtisanottu=irtisanottu)
return (employment_status, pension, wage, time_in_state, netto, toe) | Siirtymä työttömyysturvalle | gym_unemployment/envs/test_environment.py | move_to_unemp | ajtanskanen/econogym | 1 | python | def move_to_unemp(self, pension, old_wage, age, toe, irtisanottu):
'\n \n '
if ((age >= self.min_tyottputki_ika) and self.include_putki):
employment_status = 4
else:
employment_status = 0
time_in_state = 0
intage = int(np.floor(age))
wage = self.get_wage(intage, 0)
if (age <= 65):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, irtisanottu=irtisanottu)
return (employment_status, pension, wage, time_in_state, netto, toe) | def move_to_unemp(self, pension, old_wage, age, toe, irtisanottu):
'\n \n '
if ((age >= self.min_tyottputki_ika) and self.include_putki):
employment_status = 4
else:
employment_status = 0
time_in_state = 0
intage = int(np.floor(age))
wage = self.get_wage(intage, 0)
if (age <= 65):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, irtisanottu=irtisanottu)
return (employment_status, pension, wage, time_in_state, netto, toe)<|docstring|>Siirtymä työttömyysturvalle<|endoftext|> |
9ad5fbdd72925a0f2987165e92521d014736713b1ec0cfd70a50e7a8acb41fa3 | def move_to_outsider(self, pension, old_wage, age, toe, irtisanottu):
'\n Siirtymä työvoiman ulkopuolelle, ei käytössä\n '
employment_status = 11
time_in_state = 0
intage = int(np.floor(age))
old_wage = self.get_wage((intage - 1), 0)
toe = max(0, (toe - self.timestep))
wage = old_wage
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, irtisanottu=0)
paid_pension = 0
return (employment_status, paid_pension, pension, wage, time_in_state, toe, netto) | Siirtymä työvoiman ulkopuolelle, ei käytössä | gym_unemployment/envs/test_environment.py | move_to_outsider | ajtanskanen/econogym | 1 | python | def move_to_outsider(self, pension, old_wage, age, toe, irtisanottu):
'\n \n '
employment_status = 11
time_in_state = 0
intage = int(np.floor(age))
old_wage = self.get_wage((intage - 1), 0)
toe = max(0, (toe - self.timestep))
wage = old_wage
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, irtisanottu=0)
paid_pension = 0
return (employment_status, paid_pension, pension, wage, time_in_state, toe, netto) | def move_to_outsider(self, pension, old_wage, age, toe, irtisanottu):
'\n \n '
employment_status = 11
time_in_state = 0
intage = int(np.floor(age))
old_wage = self.get_wage((intage - 1), 0)
toe = max(0, (toe - self.timestep))
wage = old_wage
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, irtisanottu=0)
paid_pension = 0
return (employment_status, paid_pension, pension, wage, time_in_state, toe, netto)<|docstring|>Siirtymä työvoiman ulkopuolelle, ei käytössä<|endoftext|> |
73d5104ddf4a79dbf17bf7a609ba1af17a77b2ebf5861fb261034aa2f4fb19f0 | def move_to_disab(self, pension, old_wage, age):
'\n Siirtymä työkyvyttömyyseläkkeelle\n '
employment_status = 3
paid_pension = (((self.elinaikakerroin * pension) * self.elakeindeksi) + ((self.acc * old_wage) * max(0, (self.min_retirementage - age))))
paid_pension = self.ben.laske_kokonaiselake(65, paid_pension)
pension = 0
time_in_state = 0
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
return (employment_status, pension, paid_pension, wage, time_in_state, netto) | Siirtymä työkyvyttömyyseläkkeelle | gym_unemployment/envs/test_environment.py | move_to_disab | ajtanskanen/econogym | 1 | python | def move_to_disab(self, pension, old_wage, age):
'\n \n '
employment_status = 3
paid_pension = (((self.elinaikakerroin * pension) * self.elakeindeksi) + ((self.acc * old_wage) * max(0, (self.min_retirementage - age))))
paid_pension = self.ben.laske_kokonaiselake(65, paid_pension)
pension = 0
time_in_state = 0
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
return (employment_status, pension, paid_pension, wage, time_in_state, netto) | def move_to_disab(self, pension, old_wage, age):
'\n \n '
employment_status = 3
paid_pension = (((self.elinaikakerroin * pension) * self.elakeindeksi) + ((self.acc * old_wage) * max(0, (self.min_retirementage - age))))
paid_pension = self.ben.laske_kokonaiselake(65, paid_pension)
pension = 0
time_in_state = 0
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
return (employment_status, pension, paid_pension, wage, time_in_state, netto)<|docstring|>Siirtymä työkyvyttömyyseläkkeelle<|endoftext|> |
e5195240402a8bb82852170f44ea71529430e7c1f34b94e56a88feb93803908f | def move_to_deceiced(self, pension, old_wage, age):
'\n Siirtymä tilaan kuollut\n '
employment_status = 13
wage = old_wage
pension = pension
netto = 0
time_in_state = 0
return (employment_status, pension, wage, time_in_state, netto) | Siirtymä tilaan kuollut | gym_unemployment/envs/test_environment.py | move_to_deceiced | ajtanskanen/econogym | 1 | python | def move_to_deceiced(self, pension, old_wage, age):
'\n \n '
employment_status = 13
wage = old_wage
pension = pension
netto = 0
time_in_state = 0
return (employment_status, pension, wage, time_in_state, netto) | def move_to_deceiced(self, pension, old_wage, age):
'\n \n '
employment_status = 13
wage = old_wage
pension = pension
netto = 0
time_in_state = 0
return (employment_status, pension, wage, time_in_state, netto)<|docstring|>Siirtymä tilaan kuollut<|endoftext|> |
ff0fb1be4d8461e06fb309df32d0d45dc75a12d0a715c54a65255fd707d268e9 | def move_to_kht(self, pension, old_wage, age):
'\n Siirtymä kotihoidontuelle\n '
employment_status = 7
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_kht))
time_in_state = 0
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto) | Siirtymä kotihoidontuelle | gym_unemployment/envs/test_environment.py | move_to_kht | ajtanskanen/econogym | 1 | python | def move_to_kht(self, pension, old_wage, age):
'\n \n '
employment_status = 7
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_kht))
time_in_state = 0
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto) | def move_to_kht(self, pension, old_wage, age):
'\n \n '
employment_status = 7
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_kht))
time_in_state = 0
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age)
return (employment_status, pension, wage, time_in_state, netto)<|docstring|>Siirtymä kotihoidontuelle<|endoftext|> |
b4c8754cd3effe0abf354028e0b3b5768e61ad37efcb4f7d3db71a7da9c26605 | def move_to_fatherleave(self, pension, old_wage, age):
'\n Siirtymä isyysvapaalle\n '
employment_status = 6
time_in_state = 0
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc_family * wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
return (employment_status, pension, wage, time_in_state, netto) | Siirtymä isyysvapaalle | gym_unemployment/envs/test_environment.py | move_to_fatherleave | ajtanskanen/econogym | 1 | python | def move_to_fatherleave(self, pension, old_wage, age):
'\n \n '
employment_status = 6
time_in_state = 0
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc_family * wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
return (employment_status, pension, wage, time_in_state, netto) | def move_to_fatherleave(self, pension, old_wage, age):
'\n \n '
employment_status = 6
time_in_state = 0
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc_family * wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
return (employment_status, pension, wage, time_in_state, netto)<|docstring|>Siirtymä isyysvapaalle<|endoftext|> |
93258aa5454b22730fa395f5c66fab1e05952c5fbaa5104148d9ab8702c779b6 | def move_to_motherleave(self, pension, old_wage, age):
'\n Siirtymä äitiysvapaalle\n '
employment_status = 5
time_in_state = 0
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc_family * wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
return (employment_status, pension, wage, time_in_state, netto) | Siirtymä äitiysvapaalle | gym_unemployment/envs/test_environment.py | move_to_motherleave | ajtanskanen/econogym | 1 | python | def move_to_motherleave(self, pension, old_wage, age):
'\n \n '
employment_status = 5
time_in_state = 0
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc_family * wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
return (employment_status, pension, wage, time_in_state, netto) | def move_to_motherleave(self, pension, old_wage, age):
'\n \n '
employment_status = 5
time_in_state = 0
wage = old_wage
pension = ((pension * self.palkkakerroin) + (self.acc_family * wage))
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
return (employment_status, pension, wage, time_in_state, netto)<|docstring|>Siirtymä äitiysvapaalle<|endoftext|> |
71aa2dbb79dba407b7f880d9ddae71c495b6f1c30fcf79e2acb23a18d326e41d | def step(self, action, dynprog=False, debug=False):
'\n Open AI interfacen mukainen step-funktio, joka tekee askeleen eteenpäin\n toiminnon action mukaan \n \n Keskeinen funktio simuloinnissa\n '
assert self.action_space.contains(action), ('%r (%s) invalid' % (action, type(action)))
(employment_status, g, pension, old_wage, age, time_in_state, paid_pension, pinkslip, toe, tyoura) = self.state_decode(self.state)
intage = int(np.floor(age))
if self.randomness:
sattuma = np.random.uniform(size=4)
if ((age <= self.min_retirementage) and (sattuma[0] < self.disability_intensity[(intage, g)])):
action = 11
if ((age <= 50) and (sattuma[2] < self.birth_intensity[(intage, g)])):
sattuma2 = np.random.uniform(size=2)
if (g > 2):
action = 5
elif (sattuma2[1] < 0.5):
action = 6
if ((sattuma[3] < self.mort_intensity[(intage, g)]) and self.include_mort):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_deceiced(pension, old_wage, age)
else:
sattuma = np.ones(4)
if (employment_status == 13):
if (not self.include_mort):
print('emp state 13')
wage = old_wage
nextwage = wage
toe = 0
if self.mortstop:
done = True
else:
done = (age >= self.max_age)
done = bool(done)
self.state = self.state_encode(employment_status, g, pension, wage, (age + self.timestep), time_in_state, paid_pension, pinkslip, toe, tyoura, nextwage)
reward = 0
return (np.array(self.state), reward, done, {})
elif (age > self.max_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, 0, age, paid_pension, employment_status, all_acc=True)
elif (employment_status == 0):
if (action == 0):
employment_status = 0
wage = old_wage
time_in_state += self.timestep
toe = max(0.0, (toe - self.timestep))
if (age <= 65):
if (time_in_state <= self.ansiopvraha_kesto400):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
else:
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_tmtuki))
else:
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, 0)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
else:
print('error 17')
elif (employment_status == 4):
if (action == 0):
employment_status = 4
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
if (age <= 65):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
else:
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, 0)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 1: ', action)
elif (employment_status == 1):
if (sattuma[1] < self.pinkslip_intensity):
if (age <= self.min_retirementage):
pinkslip = 1
action = 1
else:
pinkslip = 0
action = 2
else:
pinkslip = 0
if (action == 0):
employment_status = 1
wage = self.get_wage(intage, 0)
time_in_state += self.timestep
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, 0, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, 0)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 3):
if (age > self.min_retirementage):
employment_status = 3
else:
employment_status = 3
time_in_state += self.timestep
toe = max(0, (toe - self.timestep))
paid_pension = (paid_pension * self.elakeindeksi)
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
elif (employment_status == 2):
if (age > self.min_retirementage):
if ((action == 0) or (action == 3) or (((action == 1) or (action == 2)) and (age > self.max_retirementage))):
employment_status = 2
old_wage = 0
time_in_state += self.timestep
if (age >= self.max_retirementage):
paid_pension += pension
pension = 0
else:
pension = (pension * self.palkkakerroin)
paid_pension = (paid_pension * self.elakeindeksi)
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
elif ((action == 1) and (age <= self.max_retirementage)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif ((action == 2) and (age <= self.max_retirementage)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retpartwork(pension, old_wage, age, time_in_state, paid_pension)
else:
print('error 221, action {} age {}'.format(action, age))
elif (action == 0):
employment_status = 2
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = 1
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 5):
time_in_state += self.timestep
if (time_in_state > self.aitiysvapaa_kesto):
pinkslip = 0
if (action == 0):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_kht(pension, old_wage, age)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 21')
else:
pension = ((pension * self.palkkakerroin) + (self.acc_family * old_wage))
wage = old_wage
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
elif (employment_status == 6):
time_in_state += self.timestep
if (time_in_state > self.isyysvapaa_kesto):
pinkslip = 0
if ((action == 0) or (action == 2)):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, 0, toe, tyoura)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_kht(pension, old_wage, age)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, 0)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 23')
else:
pension = ((pension * self.palkkakerroin) + (self.acc_family * old_wage))
wage = old_wage
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
elif (employment_status == 7):
time_in_state += self.timestep
if (action == 0):
if (time_in_state <= self.kht_kesto):
employment_status = 7
else:
employment_status = 0
wage = old_wage
time_in_state += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_kht))
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 2):
pinkslip = 0
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 25')
elif (employment_status == 8):
if (sattuma[1] < self.pinkslip_intensity):
action = 2
if ((action == 0) or (action == 3)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retpartwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 2):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status, all_acc=False)
else:
print('error 14, action {} age {}'.format(action, age))
elif (employment_status == 9):
if (sattuma[1] < self.pinkslip_intensity):
action = 2
if ((action == 0) or (action == 3)):
employment_status = 9
wage = self.get_wage(intage, 0)
parttimewage = (0.5 * wage)
time_in_state += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
paid_pension = (paid_pension * self.elakeindeksi)
netto = self.comp_benefits(parttimewage, 0, paid_pension, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 2):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status, all_acc=False)
else:
print('error 14, action {} age {}'.format(action, age))
elif (employment_status == 10):
if (sattuma[1] < self.pinkslip_intensity):
if (age <= self.min_retirementage):
action = 1
pinkslip = 1
else:
action = 2
pinkslip = 0
else:
pinkslip = 0
if (action == 0):
employment_status = 10
wage = self.get_wage(intage, 0)
parttimewage = (0.5 * wage)
time_in_state += self.timestep
toe = min((28 / 12), (toe + self.timestep))
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
netto = self.comp_benefits(parttimewage, 0, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, 0, toe, tyoura)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 11):
if (action == 0):
employment_status = 11
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 19: ', action)
elif (employment_status == 12):
if (action == 0):
employment_status = 12
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 19: ', action)
else:
print('Unknown employment_status {s} of type {t}'.format(s=employment_status, t=type(employment_status)))
done = (age >= self.max_age)
done = bool(done)
if self.plotdebug:
self.render()
if (not done):
reward = self.log_utility(netto, int(employment_status), age)
elif (self.steps_beyond_done is None):
self.steps_beyond_done = 0
netto = self.comp_benefits(0, old_wage, paid_pension, employment_status, time_in_state, age)
if (employment_status in set([2, 8, 9])):
reward = (self.npv[g] * self.log_utility(netto, employment_status, age))
else:
reward = 0
pinkslip = 0
time_in_state += self.timestep
elif (not dynprog):
if (self.steps_beyond_done == 0):
logger.warn("You are calling 'step()' even though this environment has already returned done = True. You should always call 'reset()' once you receive 'done = True' -- any further steps are undefined behavior.")
self.steps_beyond_done += 1
reward = 0.0
next_wage = self.get_wage(int(np.floor((age + self.timestep))), 0)
self.state = self.state_encode(employment_status, g, pension, wage, (age + self.timestep), time_in_state, paid_pension, pinkslip, toe, tyoura, next_wage)
return (np.array(self.state), reward, done, {}) | Open AI interfacen mukainen step-funktio, joka tekee askeleen eteenpäin
toiminnon action mukaan
Keskeinen funktio simuloinnissa | gym_unemployment/envs/test_environment.py | step | ajtanskanen/econogym | 1 | python | def step(self, action, dynprog=False, debug=False):
'\n Open AI interfacen mukainen step-funktio, joka tekee askeleen eteenpäin\n toiminnon action mukaan \n \n Keskeinen funktio simuloinnissa\n '
assert self.action_space.contains(action), ('%r (%s) invalid' % (action, type(action)))
(employment_status, g, pension, old_wage, age, time_in_state, paid_pension, pinkslip, toe, tyoura) = self.state_decode(self.state)
intage = int(np.floor(age))
if self.randomness:
sattuma = np.random.uniform(size=4)
if ((age <= self.min_retirementage) and (sattuma[0] < self.disability_intensity[(intage, g)])):
action = 11
if ((age <= 50) and (sattuma[2] < self.birth_intensity[(intage, g)])):
sattuma2 = np.random.uniform(size=2)
if (g > 2):
action = 5
elif (sattuma2[1] < 0.5):
action = 6
if ((sattuma[3] < self.mort_intensity[(intage, g)]) and self.include_mort):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_deceiced(pension, old_wage, age)
else:
sattuma = np.ones(4)
if (employment_status == 13):
if (not self.include_mort):
print('emp state 13')
wage = old_wage
nextwage = wage
toe = 0
if self.mortstop:
done = True
else:
done = (age >= self.max_age)
done = bool(done)
self.state = self.state_encode(employment_status, g, pension, wage, (age + self.timestep), time_in_state, paid_pension, pinkslip, toe, tyoura, nextwage)
reward = 0
return (np.array(self.state), reward, done, {})
elif (age > self.max_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, 0, age, paid_pension, employment_status, all_acc=True)
elif (employment_status == 0):
if (action == 0):
employment_status = 0
wage = old_wage
time_in_state += self.timestep
toe = max(0.0, (toe - self.timestep))
if (age <= 65):
if (time_in_state <= self.ansiopvraha_kesto400):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
else:
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_tmtuki))
else:
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, 0)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
else:
print('error 17')
elif (employment_status == 4):
if (action == 0):
employment_status = 4
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
if (age <= 65):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
else:
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, 0)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 1: ', action)
elif (employment_status == 1):
if (sattuma[1] < self.pinkslip_intensity):
if (age <= self.min_retirementage):
pinkslip = 1
action = 1
else:
pinkslip = 0
action = 2
else:
pinkslip = 0
if (action == 0):
employment_status = 1
wage = self.get_wage(intage, 0)
time_in_state += self.timestep
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, 0, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, 0)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 3):
if (age > self.min_retirementage):
employment_status = 3
else:
employment_status = 3
time_in_state += self.timestep
toe = max(0, (toe - self.timestep))
paid_pension = (paid_pension * self.elakeindeksi)
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
elif (employment_status == 2):
if (age > self.min_retirementage):
if ((action == 0) or (action == 3) or (((action == 1) or (action == 2)) and (age > self.max_retirementage))):
employment_status = 2
old_wage = 0
time_in_state += self.timestep
if (age >= self.max_retirementage):
paid_pension += pension
pension = 0
else:
pension = (pension * self.palkkakerroin)
paid_pension = (paid_pension * self.elakeindeksi)
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
elif ((action == 1) and (age <= self.max_retirementage)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif ((action == 2) and (age <= self.max_retirementage)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retpartwork(pension, old_wage, age, time_in_state, paid_pension)
else:
print('error 221, action {} age {}'.format(action, age))
elif (action == 0):
employment_status = 2
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = 1
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 5):
time_in_state += self.timestep
if (time_in_state > self.aitiysvapaa_kesto):
pinkslip = 0
if (action == 0):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_kht(pension, old_wage, age)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 21')
else:
pension = ((pension * self.palkkakerroin) + (self.acc_family * old_wage))
wage = old_wage
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
elif (employment_status == 6):
time_in_state += self.timestep
if (time_in_state > self.isyysvapaa_kesto):
pinkslip = 0
if ((action == 0) or (action == 2)):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, 0, toe, tyoura)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_kht(pension, old_wage, age)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, 0)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 23')
else:
pension = ((pension * self.palkkakerroin) + (self.acc_family * old_wage))
wage = old_wage
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
elif (employment_status == 7):
time_in_state += self.timestep
if (action == 0):
if (time_in_state <= self.kht_kesto):
employment_status = 7
else:
employment_status = 0
wage = old_wage
time_in_state += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_kht))
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 2):
pinkslip = 0
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 25')
elif (employment_status == 8):
if (sattuma[1] < self.pinkslip_intensity):
action = 2
if ((action == 0) or (action == 3)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retpartwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 2):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status, all_acc=False)
else:
print('error 14, action {} age {}'.format(action, age))
elif (employment_status == 9):
if (sattuma[1] < self.pinkslip_intensity):
action = 2
if ((action == 0) or (action == 3)):
employment_status = 9
wage = self.get_wage(intage, 0)
parttimewage = (0.5 * wage)
time_in_state += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
paid_pension = (paid_pension * self.elakeindeksi)
netto = self.comp_benefits(parttimewage, 0, paid_pension, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 2):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status, all_acc=False)
else:
print('error 14, action {} age {}'.format(action, age))
elif (employment_status == 10):
if (sattuma[1] < self.pinkslip_intensity):
if (age <= self.min_retirementage):
action = 1
pinkslip = 1
else:
action = 2
pinkslip = 0
else:
pinkslip = 0
if (action == 0):
employment_status = 10
wage = self.get_wage(intage, 0)
parttimewage = (0.5 * wage)
time_in_state += self.timestep
toe = min((28 / 12), (toe + self.timestep))
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
netto = self.comp_benefits(parttimewage, 0, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, 0, toe, tyoura)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 11):
if (action == 0):
employment_status = 11
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 19: ', action)
elif (employment_status == 12):
if (action == 0):
employment_status = 12
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 19: ', action)
else:
print('Unknown employment_status {s} of type {t}'.format(s=employment_status, t=type(employment_status)))
done = (age >= self.max_age)
done = bool(done)
if self.plotdebug:
self.render()
if (not done):
reward = self.log_utility(netto, int(employment_status), age)
elif (self.steps_beyond_done is None):
self.steps_beyond_done = 0
netto = self.comp_benefits(0, old_wage, paid_pension, employment_status, time_in_state, age)
if (employment_status in set([2, 8, 9])):
reward = (self.npv[g] * self.log_utility(netto, employment_status, age))
else:
reward = 0
pinkslip = 0
time_in_state += self.timestep
elif (not dynprog):
if (self.steps_beyond_done == 0):
logger.warn("You are calling 'step()' even though this environment has already returned done = True. You should always call 'reset()' once you receive 'done = True' -- any further steps are undefined behavior.")
self.steps_beyond_done += 1
reward = 0.0
next_wage = self.get_wage(int(np.floor((age + self.timestep))), 0)
self.state = self.state_encode(employment_status, g, pension, wage, (age + self.timestep), time_in_state, paid_pension, pinkslip, toe, tyoura, next_wage)
return (np.array(self.state), reward, done, {}) | def step(self, action, dynprog=False, debug=False):
'\n Open AI interfacen mukainen step-funktio, joka tekee askeleen eteenpäin\n toiminnon action mukaan \n \n Keskeinen funktio simuloinnissa\n '
assert self.action_space.contains(action), ('%r (%s) invalid' % (action, type(action)))
(employment_status, g, pension, old_wage, age, time_in_state, paid_pension, pinkslip, toe, tyoura) = self.state_decode(self.state)
intage = int(np.floor(age))
if self.randomness:
sattuma = np.random.uniform(size=4)
if ((age <= self.min_retirementage) and (sattuma[0] < self.disability_intensity[(intage, g)])):
action = 11
if ((age <= 50) and (sattuma[2] < self.birth_intensity[(intage, g)])):
sattuma2 = np.random.uniform(size=2)
if (g > 2):
action = 5
elif (sattuma2[1] < 0.5):
action = 6
if ((sattuma[3] < self.mort_intensity[(intage, g)]) and self.include_mort):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_deceiced(pension, old_wage, age)
else:
sattuma = np.ones(4)
if (employment_status == 13):
if (not self.include_mort):
print('emp state 13')
wage = old_wage
nextwage = wage
toe = 0
if self.mortstop:
done = True
else:
done = (age >= self.max_age)
done = bool(done)
self.state = self.state_encode(employment_status, g, pension, wage, (age + self.timestep), time_in_state, paid_pension, pinkslip, toe, tyoura, nextwage)
reward = 0
return (np.array(self.state), reward, done, {})
elif (age > self.max_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, 0, age, paid_pension, employment_status, all_acc=True)
elif (employment_status == 0):
if (action == 0):
employment_status = 0
wage = old_wage
time_in_state += self.timestep
toe = max(0.0, (toe - self.timestep))
if (age <= 65):
if (time_in_state <= self.ansiopvraha_kesto400):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
else:
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_tmtuki))
else:
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, 0)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
else:
print('error 17')
elif (employment_status == 4):
if (action == 0):
employment_status = 4
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
if (age <= 65):
pension = ((pension * self.palkkakerroin) + (self.acc_unemp * old_wage))
else:
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, 0)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 1: ', action)
elif (employment_status == 1):
if (sattuma[1] < self.pinkslip_intensity):
if (age <= self.min_retirementage):
pinkslip = 1
action = 1
else:
pinkslip = 0
action = 2
else:
pinkslip = 0
if (action == 0):
employment_status = 1
wage = self.get_wage(intage, 0)
time_in_state += self.timestep
toe = min(self.max_toe, (toe + self.timestep))
tyoura += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * wage))
netto = self.comp_benefits(wage, 0, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, 0)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 3):
if (age > self.min_retirementage):
employment_status = 3
else:
employment_status = 3
time_in_state += self.timestep
toe = max(0, (toe - self.timestep))
paid_pension = (paid_pension * self.elakeindeksi)
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
elif (employment_status == 2):
if (age > self.min_retirementage):
if ((action == 0) or (action == 3) or (((action == 1) or (action == 2)) and (age > self.max_retirementage))):
employment_status = 2
old_wage = 0
time_in_state += self.timestep
if (age >= self.max_retirementage):
paid_pension += pension
pension = 0
else:
pension = (pension * self.palkkakerroin)
paid_pension = (paid_pension * self.elakeindeksi)
wage = old_wage
netto = self.comp_benefits(0, 0, paid_pension, employment_status, 0, age)
elif ((action == 1) and (age <= self.max_retirementage)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif ((action == 2) and (age <= self.max_retirementage)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retpartwork(pension, old_wage, age, time_in_state, paid_pension)
else:
print('error 221, action {} age {}'.format(action, age))
elif (action == 0):
employment_status = 2
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = 1
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 5):
time_in_state += self.timestep
if (time_in_state > self.aitiysvapaa_kesto):
pinkslip = 0
if (action == 0):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_kht(pension, old_wage, age)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 21')
else:
pension = ((pension * self.palkkakerroin) + (self.acc_family * old_wage))
wage = old_wage
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
elif (employment_status == 6):
time_in_state += self.timestep
if (time_in_state > self.isyysvapaa_kesto):
pinkslip = 0
if ((action == 0) or (action == 2)):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, 0, toe, tyoura)
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_kht(pension, old_wage, age)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, 0)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 23')
else:
pension = ((pension * self.palkkakerroin) + (self.acc_family * old_wage))
wage = old_wage
netto = self.comp_benefits(0, old_wage, 0, employment_status, 0, age)
elif (employment_status == 7):
time_in_state += self.timestep
if (action == 0):
if (time_in_state <= self.kht_kesto):
employment_status = 7
else:
employment_status = 0
wage = old_wage
time_in_state += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * self.accbasis_kht))
netto = self.comp_benefits(0, old_wage, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
elif (action == 2):
pinkslip = 0
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('Error 25')
elif (employment_status == 8):
if (sattuma[1] < self.pinkslip_intensity):
action = 2
if ((action == 0) or (action == 3)):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retpartwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 2):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status, all_acc=False)
else:
print('error 14, action {} age {}'.format(action, age))
elif (employment_status == 9):
if (sattuma[1] < self.pinkslip_intensity):
action = 2
if ((action == 0) or (action == 3)):
employment_status = 9
wage = self.get_wage(intage, 0)
parttimewage = (0.5 * wage)
time_in_state += self.timestep
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
paid_pension = (paid_pension * self.elakeindeksi)
netto = self.comp_benefits(parttimewage, 0, paid_pension, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_retwork(pension, old_wage, age, time_in_state, paid_pension)
elif (action == 2):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status, all_acc=False)
else:
print('error 14, action {} age {}'.format(action, age))
elif (employment_status == 10):
if (sattuma[1] < self.pinkslip_intensity):
if (age <= self.min_retirementage):
action = 1
pinkslip = 1
else:
action = 2
pinkslip = 0
else:
pinkslip = 0
if (action == 0):
employment_status = 10
wage = self.get_wage(intage, 0)
parttimewage = (0.5 * wage)
time_in_state += self.timestep
toe = min((28 / 12), (toe + self.timestep))
pension = ((pension * self.palkkakerroin) + (self.acc * parttimewage))
netto = self.comp_benefits(parttimewage, 0, 0, employment_status, time_in_state, age)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
elif (action == 2):
if (age > self.min_retirementage):
(employment_status, paid_pension, pension, wage, time_in_state, netto) = self.move_to_retirement(pension, old_wage, age, paid_pension, employment_status)
else:
(employment_status, paid_pension, pension, wage, time_in_state, toe, netto) = self.move_to_outsider(pension, old_wage, age, toe, pinkslip)
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, 0, toe, tyoura)
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
else:
print('error 12')
elif (employment_status == 11):
if (action == 0):
employment_status = 11
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 19: ', action)
elif (employment_status == 12):
if (action == 0):
employment_status = 12
time_in_state += self.timestep
wage = old_wage
toe = max(0, (toe - self.timestep))
pension = (pension * self.palkkakerroin)
netto = self.comp_benefits(0, 0, 0, employment_status, time_in_state, age, tyossaoloehto=toe, tyohistoria=tyoura)
elif (action == 1):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_work(pension, old_wage, age, time_in_state, toe, tyoura)
pinkslip = 0
elif (action == 2):
(employment_status, pension, wage, time_in_state, netto, toe) = self.move_to_unemp(pension, old_wage, age, toe, pinkslip)
pinkslip = 0
elif (action == 3):
(employment_status, pension, wage, time_in_state, netto, toe, tyoura) = self.move_to_parttime(pension, old_wage, age, toe, tyoura, time_in_state)
pinkslip = 0
elif (action == 5):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_motherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 6):
(employment_status, pension, wage, time_in_state, netto) = self.move_to_fatherleave(pension, old_wage, age)
pinkslip = 0
elif (action == 11):
(employment_status, pension, paid_pension, wage, time_in_state, netto) = self.move_to_disab(pension, old_wage, age)
pinkslip = 0
else:
print('error 19: ', action)
else:
print('Unknown employment_status {s} of type {t}'.format(s=employment_status, t=type(employment_status)))
done = (age >= self.max_age)
done = bool(done)
if self.plotdebug:
self.render()
if (not done):
reward = self.log_utility(netto, int(employment_status), age)
elif (self.steps_beyond_done is None):
self.steps_beyond_done = 0
netto = self.comp_benefits(0, old_wage, paid_pension, employment_status, time_in_state, age)
if (employment_status in set([2, 8, 9])):
reward = (self.npv[g] * self.log_utility(netto, employment_status, age))
else:
reward = 0
pinkslip = 0
time_in_state += self.timestep
elif (not dynprog):
if (self.steps_beyond_done == 0):
logger.warn("You are calling 'step()' even though this environment has already returned done = True. You should always call 'reset()' once you receive 'done = True' -- any further steps are undefined behavior.")
self.steps_beyond_done += 1
reward = 0.0
next_wage = self.get_wage(int(np.floor((age + self.timestep))), 0)
self.state = self.state_encode(employment_status, g, pension, wage, (age + self.timestep), time_in_state, paid_pension, pinkslip, toe, tyoura, next_wage)
return (np.array(self.state), reward, done, {})<|docstring|>Open AI interfacen mukainen step-funktio, joka tekee askeleen eteenpäin
toiminnon action mukaan
Keskeinen funktio simuloinnissa<|endoftext|> |
5f60ce74f020aec740f2c290a46f67571c8da7102857b6f53bf2a4d2c2191dc0 | def log_utility_norandomness(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos laskelmissa ei satunnaisuutta\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.15
else:
kappa_kokoaika = 0.6
kappa_osaaika = 0.4
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.15
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif ((employment_state == 2) and (age > self.min_retirementage)):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif ((employment_state == 12) and (age < 25)):
if (age < 25):
kappa = max(0, (((25 - age) / 5) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10) | Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005
Käytetään, jos laskelmissa ei satunnaisuutta | gym_unemployment/envs/test_environment.py | log_utility_norandomness | ajtanskanen/econogym | 1 | python | def log_utility_norandomness(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos laskelmissa ei satunnaisuutta\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.15
else:
kappa_kokoaika = 0.6
kappa_osaaika = 0.4
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.15
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif ((employment_state == 2) and (age > self.min_retirementage)):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif ((employment_state == 12) and (age < 25)):
if (age < 25):
kappa = max(0, (((25 - age) / 5) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10) | def log_utility_norandomness(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos laskelmissa ei satunnaisuutta\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.15
else:
kappa_kokoaika = 0.6
kappa_osaaika = 0.4
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.15
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif ((employment_state == 2) and (age > self.min_retirementage)):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif ((employment_state == 12) and (age < 25)):
if (age < 25):
kappa = max(0, (((25 - age) / 5) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10)<|docstring|>Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005
Käytetään, jos laskelmissa ei satunnaisuutta<|endoftext|> |
1fb0f42288337271770ca6a961385ae68520db454031ec80689c8bd22e1b19b1 | def log_utility_randomness(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos laskelmissa on mukana satunnaisuutta\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 0.8
mu = 0.17
else:
kappa_kokoaika = 0.7
kappa_osaaika = 0.45
kappa_ve = 0.0
kappa_opiskelija = 1.2
mu = 0.2
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif (employment_state == 2):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif ((employment_state == 12) and (age < 25)):
if (age < 25):
kappa = max(0, (((27 - age) / (27 - 20)) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10) | Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005
Käytetään, jos laskelmissa on mukana satunnaisuutta | gym_unemployment/envs/test_environment.py | log_utility_randomness | ajtanskanen/econogym | 1 | python | def log_utility_randomness(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos laskelmissa on mukana satunnaisuutta\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 0.8
mu = 0.17
else:
kappa_kokoaika = 0.7
kappa_osaaika = 0.45
kappa_ve = 0.0
kappa_opiskelija = 1.2
mu = 0.2
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif (employment_state == 2):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif ((employment_state == 12) and (age < 25)):
if (age < 25):
kappa = max(0, (((27 - age) / (27 - 20)) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10) | def log_utility_randomness(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos laskelmissa on mukana satunnaisuutta\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 0.8
mu = 0.17
else:
kappa_kokoaika = 0.7
kappa_osaaika = 0.45
kappa_ve = 0.0
kappa_opiskelija = 1.2
mu = 0.2
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif (employment_state == 2):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif ((employment_state == 12) and (age < 25)):
if (age < 25):
kappa = max(0, (((27 - age) / (27 - 20)) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10)<|docstring|>Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005
Käytetään, jos laskelmissa on mukana satunnaisuutta<|endoftext|> |
1a7bfd20d0026f56a22cdd4f2c2d544ab251f62b95b7207ebc2591f709ee4b24 | def log_utility_perustulo(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos perustulolaskelmissa\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.2
else:
kappa_kokoaika = 0.6
kappa_osaaika = 0.4
kappa_ve = 0.18
kappa_opiskelija = 1.0
mu = 0.2
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif (employment_state == 2):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif (employment_state == 12):
if (age < 25):
kappa = max(0, (((25 - age) / 5) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10) | Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005
Käytetään, jos perustulolaskelmissa | gym_unemployment/envs/test_environment.py | log_utility_perustulo | ajtanskanen/econogym | 1 | python | def log_utility_perustulo(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos perustulolaskelmissa\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.2
else:
kappa_kokoaika = 0.6
kappa_osaaika = 0.4
kappa_ve = 0.18
kappa_opiskelija = 1.0
mu = 0.2
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif (employment_state == 2):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif (employment_state == 12):
if (age < 25):
kappa = max(0, (((25 - age) / 5) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10) | def log_utility_perustulo(self, income, employment_state, age):
'\n Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005\n \n Käytetään, jos perustulolaskelmissa\n '
if self.deterministic:
kappa_kokoaika = 0.3
kappa_osaaika = 0.2
kappa_ve = 0.1
kappa_opiskelija = 1.0
mu = 0.2
else:
kappa_kokoaika = 0.6
kappa_osaaika = 0.4
kappa_ve = 0.18
kappa_opiskelija = 1.0
mu = 0.2
if (age > 58):
kappa_kokoaika *= (1 + (mu * max(0, (age - 58))))
kappa_osaaika *= (1 + (mu * max(0, (age - 58))))
if ((employment_state == 1) or (employment_state == 8)):
u = (np.log(income) - kappa_kokoaika)
elif ((employment_state == 10) or (employment_state == 9)):
u = (np.log(income) - kappa_osaaika)
elif (employment_state == 2):
u = (np.log(income) + kappa_ve)
elif (employment_state == 11):
u = (np.log(income) + kappa_ve)
elif (employment_state == 12):
if (age < 25):
kappa = max(0, (((25 - age) / 5) * kappa_opiskelija))
u = (np.log(income) + kappa)
else:
u = (np.log(income) + kappa_ve)
else:
u = np.log(income)
if (u is np.inf):
print('inf: state ', employment_state)
if (income < 1):
print('inf: state ', employment_state)
return (u / 10)<|docstring|>Log-utiliteettifunktio hieman muokattuna lähteestä Määttänen, 2013 & Hakola & Määttänen, 2005
Käytetään, jos perustulolaskelmissa<|endoftext|> |
4f4ec1d35b499164f9d46f62e10b983cf40ee8cc0ca9b98b3110c269318e00f3 | def wage_process(self, w, age, ave=(3300 * 12)):
'\n Palkkaprosessi lähteestä Määttänen, 2013 \n '
eps = np.random.normal(loc=0, scale=0.02, size=1)[0]
a0 = ave
a1 = 0.89
if (w > 0):
wt = (a0 * np.exp(((a1 * np.log((w / a0))) + eps)))
else:
wt = (a0 * np.exp(eps))
return wt | Palkkaprosessi lähteestä Määttänen, 2013 | gym_unemployment/envs/test_environment.py | wage_process | ajtanskanen/econogym | 1 | python | def wage_process(self, w, age, ave=(3300 * 12)):
'\n \n '
eps = np.random.normal(loc=0, scale=0.02, size=1)[0]
a0 = ave
a1 = 0.89
if (w > 0):
wt = (a0 * np.exp(((a1 * np.log((w / a0))) + eps)))
else:
wt = (a0 * np.exp(eps))
return wt | def wage_process(self, w, age, ave=(3300 * 12)):
'\n \n '
eps = np.random.normal(loc=0, scale=0.02, size=1)[0]
a0 = ave
a1 = 0.89
if (w > 0):
wt = (a0 * np.exp(((a1 * np.log((w / a0))) + eps)))
else:
wt = (a0 * np.exp(eps))
return wt<|docstring|>Palkkaprosessi lähteestä Määttänen, 2013<|endoftext|> |
45428602dbf3828c627e40ff83f03d49a89b38e2899092a75b43ee19dc26dcd0 | def wage_process_simple(self, w, age, ave=(3300 * 12)):
'\n debug-versio palkkaprosessista\n '
return w | debug-versio palkkaprosessista | gym_unemployment/envs/test_environment.py | wage_process_simple | ajtanskanen/econogym | 1 | python | def wage_process_simple(self, w, age, ave=(3300 * 12)):
'\n \n '
return w | def wage_process_simple(self, w, age, ave=(3300 * 12)):
'\n \n '
return w<|docstring|>debug-versio palkkaprosessista<|endoftext|> |
1a8d64c6c094f47c52457d973994dffffd9242c2d999042e56f60cea4e969881 | def compute_salary(self, group=1, debug=True):
'\n Alussa ajettava funktio, joka tekee palkat yhtä episodia varten\n '
group_ave = (np.array([2000, 3300, 5000, (0.85 * 2000), (0.85 * 3300), (0.85 * 5000)]) * 12)
a0 = group_ave[group]
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(12 * 1000), size=1)[0])
if debug:
self.salary[(self.min_age + 1):(self.max_age + 1)] = self.salary[self.min_age]
else:
for age in range((self.min_age + 1), (self.max_age + 1)):
self.salary[age] = self.wage_process(self.salary[(age - 1)], age, ave=a0) | Alussa ajettava funktio, joka tekee palkat yhtä episodia varten | gym_unemployment/envs/test_environment.py | compute_salary | ajtanskanen/econogym | 1 | python | def compute_salary(self, group=1, debug=True):
'\n \n '
group_ave = (np.array([2000, 3300, 5000, (0.85 * 2000), (0.85 * 3300), (0.85 * 5000)]) * 12)
a0 = group_ave[group]
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(12 * 1000), size=1)[0])
if debug:
self.salary[(self.min_age + 1):(self.max_age + 1)] = self.salary[self.min_age]
else:
for age in range((self.min_age + 1), (self.max_age + 1)):
self.salary[age] = self.wage_process(self.salary[(age - 1)], age, ave=a0) | def compute_salary(self, group=1, debug=True):
'\n \n '
group_ave = (np.array([2000, 3300, 5000, (0.85 * 2000), (0.85 * 3300), (0.85 * 5000)]) * 12)
a0 = group_ave[group]
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(12 * 1000), size=1)[0])
if debug:
self.salary[(self.min_age + 1):(self.max_age + 1)] = self.salary[self.min_age]
else:
for age in range((self.min_age + 1), (self.max_age + 1)):
self.salary[age] = self.wage_process(self.salary[(age - 1)], age, ave=a0)<|docstring|>Alussa ajettava funktio, joka tekee palkat yhtä episodia varten<|endoftext|> |
4dff405728cf79d0830ceff66c0c016ecc1bb7e40ce7f70a8660d6f02dd5e799 | def wage_process_TK(self, w, age, a0=(3300 * 12), a1=(3300 * 12), g=1):
'\n Palkkaprosessi lähteestä Määttänen, 2013 \n '
group_sigmas = [0.08, 0.1, 0.15]
sigma = group_sigmas[g]
eps = np.random.normal(loc=0, scale=sigma, size=1)[0]
c1 = 0.89
if (w > 0):
wt = (a1 * np.exp((((c1 * np.log((w / a0))) + eps) - ((0.5 * sigma) * sigma))))
else:
wt = (a1 * np.exp(eps))
wt = np.maximum(8000, wt)
return wt | Palkkaprosessi lähteestä Määttänen, 2013 | gym_unemployment/envs/test_environment.py | wage_process_TK | ajtanskanen/econogym | 1 | python | def wage_process_TK(self, w, age, a0=(3300 * 12), a1=(3300 * 12), g=1):
'\n \n '
group_sigmas = [0.08, 0.1, 0.15]
sigma = group_sigmas[g]
eps = np.random.normal(loc=0, scale=sigma, size=1)[0]
c1 = 0.89
if (w > 0):
wt = (a1 * np.exp((((c1 * np.log((w / a0))) + eps) - ((0.5 * sigma) * sigma))))
else:
wt = (a1 * np.exp(eps))
wt = np.maximum(8000, wt)
return wt | def wage_process_TK(self, w, age, a0=(3300 * 12), a1=(3300 * 12), g=1):
'\n \n '
group_sigmas = [0.08, 0.1, 0.15]
sigma = group_sigmas[g]
eps = np.random.normal(loc=0, scale=sigma, size=1)[0]
c1 = 0.89
if (w > 0):
wt = (a1 * np.exp((((c1 * np.log((w / a0))) + eps) - ((0.5 * sigma) * sigma))))
else:
wt = (a1 * np.exp(eps))
wt = np.maximum(8000, wt)
return wt<|docstring|>Palkkaprosessi lähteestä Määttänen, 2013<|endoftext|> |
d9b0b9ac59fc68301c4e32d333cf56e8f8c4ad221c619f8cfae9cf7b5be32b02 | def compute_salary_TK(self, group=1, debug=False):
'\n Alussa ajettava funktio, joka tekee palkat yhtä episodia varten\n '
palkat_ika_miehet = (12.5 * np.array([2339.01, 2489.09, 2571.4, 2632.58, 2718.03, 2774.21, 2884.89, 2987.55, 3072.4, 3198.48, 3283.81, 3336.51, 3437.3, 3483.45, 3576.67, 3623.0, 3731.27, 3809.58, 3853.66, 3995.9, 4006.16, 4028.6, 4104.72, 4181.51, 4134.13, 4157.54, 4217.15, 4165.21, 4141.23, 4172.14, 4121.26, 4127.43, 4134.0, 4093.1, 4065.53, 4063.17, 4085.31, 4071.25, 4026.5, 4031.17, 4047.32, 4026.96, 4028.39, 4163.14, 4266.42, 4488.4, 4201.4, 4252.15, 4443.96, 3316.92, 3536.03, 3536.03]))
palkat_ika_naiset = (12.5 * np.array([2223.96, 2257.1, 2284.57, 2365.57, 2443.64, 2548.35, 2648.06, 2712.89, 2768.83, 2831.99, 2896.76, 2946.37, 2963.84, 2993.79, 3040.83, 3090.43, 3142.91, 3159.91, 3226.95, 3272.29, 3270.97, 3297.32, 3333.42, 3362.99, 3381.84, 3342.78, 3345.25, 3360.21, 3324.67, 3322.28, 3326.72, 3326.06, 3314.82, 3303.73, 3302.65, 3246.03, 3244.65, 3248.04, 3223.94, 3211.96, 3167.0, 3156.29, 3175.23, 3228.67, 3388.39, 3457.17, 3400.23, 3293.52, 2967.68, 2702.05, 2528.84, 2528.84]))
g_r = [0.75, 1.0, 1.3]
if debug:
a0 = (3465.0 * 12.5)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(12 * 1000), size=1)[0])
self.salary[(self.min_age + 1):(self.max_age + 1)] = self.salary[self.min_age]
elif (group > 2):
r = g_r[(group - 3)]
a0 = (palkat_ika_naiset[0] * r)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(a0 / 10), size=1)[0])
for age in range((self.min_age + 1), (self.max_age + 1)):
a0 = (palkat_ika_miehet[(age - self.min_age)] * r)
a1 = (palkat_ika_miehet[(age - self.min_age)] * r)
self.salary[age] = self.wage_process_TK(self.salary[(age - 1)], age, a0, a1)
else:
r = g_r[group]
a0 = (palkat_ika_miehet[0] * r)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(a0 / 10), size=1)[0])
for age in range((self.min_age + 1), (self.max_age + 1)):
a0 = (palkat_ika_miehet[(age - self.min_age)] * r)
a1 = (palkat_ika_miehet[(age - self.min_age)] * r)
self.salary[age] = self.wage_process_TK(self.salary[(age - 1)], age, a0, a1) | Alussa ajettava funktio, joka tekee palkat yhtä episodia varten | gym_unemployment/envs/test_environment.py | compute_salary_TK | ajtanskanen/econogym | 1 | python | def compute_salary_TK(self, group=1, debug=False):
'\n \n '
palkat_ika_miehet = (12.5 * np.array([2339.01, 2489.09, 2571.4, 2632.58, 2718.03, 2774.21, 2884.89, 2987.55, 3072.4, 3198.48, 3283.81, 3336.51, 3437.3, 3483.45, 3576.67, 3623.0, 3731.27, 3809.58, 3853.66, 3995.9, 4006.16, 4028.6, 4104.72, 4181.51, 4134.13, 4157.54, 4217.15, 4165.21, 4141.23, 4172.14, 4121.26, 4127.43, 4134.0, 4093.1, 4065.53, 4063.17, 4085.31, 4071.25, 4026.5, 4031.17, 4047.32, 4026.96, 4028.39, 4163.14, 4266.42, 4488.4, 4201.4, 4252.15, 4443.96, 3316.92, 3536.03, 3536.03]))
palkat_ika_naiset = (12.5 * np.array([2223.96, 2257.1, 2284.57, 2365.57, 2443.64, 2548.35, 2648.06, 2712.89, 2768.83, 2831.99, 2896.76, 2946.37, 2963.84, 2993.79, 3040.83, 3090.43, 3142.91, 3159.91, 3226.95, 3272.29, 3270.97, 3297.32, 3333.42, 3362.99, 3381.84, 3342.78, 3345.25, 3360.21, 3324.67, 3322.28, 3326.72, 3326.06, 3314.82, 3303.73, 3302.65, 3246.03, 3244.65, 3248.04, 3223.94, 3211.96, 3167.0, 3156.29, 3175.23, 3228.67, 3388.39, 3457.17, 3400.23, 3293.52, 2967.68, 2702.05, 2528.84, 2528.84]))
g_r = [0.75, 1.0, 1.3]
if debug:
a0 = (3465.0 * 12.5)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(12 * 1000), size=1)[0])
self.salary[(self.min_age + 1):(self.max_age + 1)] = self.salary[self.min_age]
elif (group > 2):
r = g_r[(group - 3)]
a0 = (palkat_ika_naiset[0] * r)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(a0 / 10), size=1)[0])
for age in range((self.min_age + 1), (self.max_age + 1)):
a0 = (palkat_ika_miehet[(age - self.min_age)] * r)
a1 = (palkat_ika_miehet[(age - self.min_age)] * r)
self.salary[age] = self.wage_process_TK(self.salary[(age - 1)], age, a0, a1)
else:
r = g_r[group]
a0 = (palkat_ika_miehet[0] * r)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(a0 / 10), size=1)[0])
for age in range((self.min_age + 1), (self.max_age + 1)):
a0 = (palkat_ika_miehet[(age - self.min_age)] * r)
a1 = (palkat_ika_miehet[(age - self.min_age)] * r)
self.salary[age] = self.wage_process_TK(self.salary[(age - 1)], age, a0, a1) | def compute_salary_TK(self, group=1, debug=False):
'\n \n '
palkat_ika_miehet = (12.5 * np.array([2339.01, 2489.09, 2571.4, 2632.58, 2718.03, 2774.21, 2884.89, 2987.55, 3072.4, 3198.48, 3283.81, 3336.51, 3437.3, 3483.45, 3576.67, 3623.0, 3731.27, 3809.58, 3853.66, 3995.9, 4006.16, 4028.6, 4104.72, 4181.51, 4134.13, 4157.54, 4217.15, 4165.21, 4141.23, 4172.14, 4121.26, 4127.43, 4134.0, 4093.1, 4065.53, 4063.17, 4085.31, 4071.25, 4026.5, 4031.17, 4047.32, 4026.96, 4028.39, 4163.14, 4266.42, 4488.4, 4201.4, 4252.15, 4443.96, 3316.92, 3536.03, 3536.03]))
palkat_ika_naiset = (12.5 * np.array([2223.96, 2257.1, 2284.57, 2365.57, 2443.64, 2548.35, 2648.06, 2712.89, 2768.83, 2831.99, 2896.76, 2946.37, 2963.84, 2993.79, 3040.83, 3090.43, 3142.91, 3159.91, 3226.95, 3272.29, 3270.97, 3297.32, 3333.42, 3362.99, 3381.84, 3342.78, 3345.25, 3360.21, 3324.67, 3322.28, 3326.72, 3326.06, 3314.82, 3303.73, 3302.65, 3246.03, 3244.65, 3248.04, 3223.94, 3211.96, 3167.0, 3156.29, 3175.23, 3228.67, 3388.39, 3457.17, 3400.23, 3293.52, 2967.68, 2702.05, 2528.84, 2528.84]))
g_r = [0.75, 1.0, 1.3]
if debug:
a0 = (3465.0 * 12.5)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(12 * 1000), size=1)[0])
self.salary[(self.min_age + 1):(self.max_age + 1)] = self.salary[self.min_age]
elif (group > 2):
r = g_r[(group - 3)]
a0 = (palkat_ika_naiset[0] * r)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(a0 / 10), size=1)[0])
for age in range((self.min_age + 1), (self.max_age + 1)):
a0 = (palkat_ika_miehet[(age - self.min_age)] * r)
a1 = (palkat_ika_miehet[(age - self.min_age)] * r)
self.salary[age] = self.wage_process_TK(self.salary[(age - 1)], age, a0, a1)
else:
r = g_r[group]
a0 = (palkat_ika_miehet[0] * r)
self.salary[self.min_age] = np.maximum(8000, np.random.normal(loc=a0, scale=(a0 / 10), size=1)[0])
for age in range((self.min_age + 1), (self.max_age + 1)):
a0 = (palkat_ika_miehet[(age - self.min_age)] * r)
a1 = (palkat_ika_miehet[(age - self.min_age)] * r)
self.salary[age] = self.wage_process_TK(self.salary[(age - 1)], age, a0, a1)<|docstring|>Alussa ajettava funktio, joka tekee palkat yhtä episodia varten<|endoftext|> |
49e3baea1d0ea4277ed8eee5f0e3bb365f7a2093b50b085a5cb63bd9405dbb4b | def state_encode_mort(self, emp, g, pension, old_wage, age, time_in_state, paid_pension, pink, toe, tyohist, next_wage):
'\n Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan\n \n Käytetään, jos kuolleisuus mukana\n '
d = np.zeros(((self.n_empl + self.n_groups) + 11))
states = self.n_empl
if (emp == 1):
d[0:states] = np.array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 0):
d[0:states] = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 2):
d[0:states] = np.array([0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 3):
d[0:states] = np.array([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 4):
d[0:states] = np.array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 5):
d[0:states] = np.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 6):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 7):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])
elif (emp == 8):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0])
elif (emp == 9):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0])
elif (emp == 10):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])
elif (emp == 11):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
elif (emp == 12):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
elif (emp == 13):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
else:
print(('state_encode error ' + str(emp)))
states2 = (states + self.n_groups)
if (g == 1):
d[states:states2] = np.array([0, 1, 0, 0, 0, 0])
elif (g == 0):
d[states:states2] = np.array([1, 0, 0, 0, 0, 0])
elif (g == 2):
d[states:states2] = np.array([0, 0, 1, 0, 0, 0])
elif (g == 3):
d[states:states2] = np.array([0, 0, 0, 1, 0, 0])
elif (g == 4):
d[states:states2] = np.array([0, 0, 0, 0, 1, 0])
elif (g == 5):
d[states:states2] = np.array([0, 0, 0, 0, 0, 1])
else:
print(('state_encode g-error ' + str(g)))
if self.log_transform:
d[states2] = np.log(((pension / 20000) + self.eps))
d[(states2 + 1)] = np.log(((old_wage / 40000) + self.eps))
d[(states2 + 4)] = np.log(((paid_pension / 20000) + self.eps))
else:
d[states2] = ((pension - 20000) / 10000)
d[(states2 + 1)] = ((old_wage - 40000) / 15000)
d[(states2 + 4)] = ((paid_pension - 20000) / 10000)
if (tyohist > self.tyohistoria_vaatimus):
hist400 = 1
else:
hist400 = 0
d[(states2 + 2)] = ((age - ((self.max_age + self.min_age) / 2)) / 20)
d[(states2 + 3)] = ((time_in_state - 3) / 10)
d[(states2 + 5)] = pink
d[(states2 + 6)] = (toe - (14 / 12))
d[(states2 + 7)] = ((tyohist - 3) / 10)
d[(states2 + 8)] = hist400
if (age > self.min_retirementage):
retaged = 1
else:
retaged = 0
d[(states2 + 9)] = retaged
d[(states2 + 10)] = ((next_wage - 40000) / 15000)
return d | Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan
Käytetään, jos kuolleisuus mukana | gym_unemployment/envs/test_environment.py | state_encode_mort | ajtanskanen/econogym | 1 | python | def state_encode_mort(self, emp, g, pension, old_wage, age, time_in_state, paid_pension, pink, toe, tyohist, next_wage):
'\n Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan\n \n Käytetään, jos kuolleisuus mukana\n '
d = np.zeros(((self.n_empl + self.n_groups) + 11))
states = self.n_empl
if (emp == 1):
d[0:states] = np.array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 0):
d[0:states] = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 2):
d[0:states] = np.array([0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 3):
d[0:states] = np.array([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 4):
d[0:states] = np.array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 5):
d[0:states] = np.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 6):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 7):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])
elif (emp == 8):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0])
elif (emp == 9):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0])
elif (emp == 10):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])
elif (emp == 11):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
elif (emp == 12):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
elif (emp == 13):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
else:
print(('state_encode error ' + str(emp)))
states2 = (states + self.n_groups)
if (g == 1):
d[states:states2] = np.array([0, 1, 0, 0, 0, 0])
elif (g == 0):
d[states:states2] = np.array([1, 0, 0, 0, 0, 0])
elif (g == 2):
d[states:states2] = np.array([0, 0, 1, 0, 0, 0])
elif (g == 3):
d[states:states2] = np.array([0, 0, 0, 1, 0, 0])
elif (g == 4):
d[states:states2] = np.array([0, 0, 0, 0, 1, 0])
elif (g == 5):
d[states:states2] = np.array([0, 0, 0, 0, 0, 1])
else:
print(('state_encode g-error ' + str(g)))
if self.log_transform:
d[states2] = np.log(((pension / 20000) + self.eps))
d[(states2 + 1)] = np.log(((old_wage / 40000) + self.eps))
d[(states2 + 4)] = np.log(((paid_pension / 20000) + self.eps))
else:
d[states2] = ((pension - 20000) / 10000)
d[(states2 + 1)] = ((old_wage - 40000) / 15000)
d[(states2 + 4)] = ((paid_pension - 20000) / 10000)
if (tyohist > self.tyohistoria_vaatimus):
hist400 = 1
else:
hist400 = 0
d[(states2 + 2)] = ((age - ((self.max_age + self.min_age) / 2)) / 20)
d[(states2 + 3)] = ((time_in_state - 3) / 10)
d[(states2 + 5)] = pink
d[(states2 + 6)] = (toe - (14 / 12))
d[(states2 + 7)] = ((tyohist - 3) / 10)
d[(states2 + 8)] = hist400
if (age > self.min_retirementage):
retaged = 1
else:
retaged = 0
d[(states2 + 9)] = retaged
d[(states2 + 10)] = ((next_wage - 40000) / 15000)
return d | def state_encode_mort(self, emp, g, pension, old_wage, age, time_in_state, paid_pension, pink, toe, tyohist, next_wage):
'\n Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan\n \n Käytetään, jos kuolleisuus mukana\n '
d = np.zeros(((self.n_empl + self.n_groups) + 11))
states = self.n_empl
if (emp == 1):
d[0:states] = np.array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 0):
d[0:states] = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 2):
d[0:states] = np.array([0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 3):
d[0:states] = np.array([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 4):
d[0:states] = np.array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 5):
d[0:states] = np.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 6):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 7):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])
elif (emp == 8):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0])
elif (emp == 9):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0])
elif (emp == 10):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])
elif (emp == 11):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
elif (emp == 12):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
elif (emp == 13):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
else:
print(('state_encode error ' + str(emp)))
states2 = (states + self.n_groups)
if (g == 1):
d[states:states2] = np.array([0, 1, 0, 0, 0, 0])
elif (g == 0):
d[states:states2] = np.array([1, 0, 0, 0, 0, 0])
elif (g == 2):
d[states:states2] = np.array([0, 0, 1, 0, 0, 0])
elif (g == 3):
d[states:states2] = np.array([0, 0, 0, 1, 0, 0])
elif (g == 4):
d[states:states2] = np.array([0, 0, 0, 0, 1, 0])
elif (g == 5):
d[states:states2] = np.array([0, 0, 0, 0, 0, 1])
else:
print(('state_encode g-error ' + str(g)))
if self.log_transform:
d[states2] = np.log(((pension / 20000) + self.eps))
d[(states2 + 1)] = np.log(((old_wage / 40000) + self.eps))
d[(states2 + 4)] = np.log(((paid_pension / 20000) + self.eps))
else:
d[states2] = ((pension - 20000) / 10000)
d[(states2 + 1)] = ((old_wage - 40000) / 15000)
d[(states2 + 4)] = ((paid_pension - 20000) / 10000)
if (tyohist > self.tyohistoria_vaatimus):
hist400 = 1
else:
hist400 = 0
d[(states2 + 2)] = ((age - ((self.max_age + self.min_age) / 2)) / 20)
d[(states2 + 3)] = ((time_in_state - 3) / 10)
d[(states2 + 5)] = pink
d[(states2 + 6)] = (toe - (14 / 12))
d[(states2 + 7)] = ((tyohist - 3) / 10)
d[(states2 + 8)] = hist400
if (age > self.min_retirementage):
retaged = 1
else:
retaged = 0
d[(states2 + 9)] = retaged
d[(states2 + 10)] = ((next_wage - 40000) / 15000)
return d<|docstring|>Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan
Käytetään, jos kuolleisuus mukana<|endoftext|> |
c46f0383e49f6495a469316ce7c63113d95ad3d85dffb32088ff4b0b9a3044af | def state_encode_nomort(self, emp, g, pension, old_wage, age, time_in_state, paid_pension, pink, toe, tyohist, next_wage):
'\n Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan\n \n Käytetään, jos kuolleisuus ei mukana\n '
d = np.zeros(((self.n_empl + self.n_groups) + 11))
states = self.n_empl
if (emp == 1):
d[0:states] = np.array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 0):
d[0:states] = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 2):
d[0:states] = np.array([0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 3):
d[0:states] = np.array([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 4):
d[0:states] = np.array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 5):
d[0:states] = np.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 6):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])
elif (emp == 7):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0])
elif (emp == 8):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0])
elif (emp == 9):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])
elif (emp == 10):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
elif (emp == 11):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
elif (emp == 12):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
elif (emp == 13):
print('state 13 in state_encode_nomort!')
else:
print(('state_encode error ' + str(emp)))
states2 = (states + self.n_groups)
if (g == 1):
d[states:states2] = np.array([0, 1, 0, 0, 0, 0])
elif (g == 0):
d[states:states2] = np.array([1, 0, 0, 0, 0, 0])
elif (g == 2):
d[states:states2] = np.array([0, 0, 1, 0, 0, 0])
elif (g == 3):
d[states:states2] = np.array([0, 0, 0, 1, 0, 0])
elif (g == 4):
d[states:states2] = np.array([0, 0, 0, 0, 1, 0])
elif (g == 5):
d[states:states2] = np.array([0, 0, 0, 0, 0, 1])
else:
print(('state_encode g-error ' + str(g)))
if self.log_transform:
d[states2] = np.log(((pension / 20000) + self.eps))
d[(states2 + 1)] = np.log(((old_wage / 40000) + self.eps))
d[(states2 + 4)] = np.log(((paid_pension / 20000) + self.eps))
else:
d[states2] = ((pension - 20000) / 10000)
d[(states2 + 1)] = ((old_wage - 40000) / 15000)
d[(states2 + 4)] = ((paid_pension - 20000) / 10000)
d[(states2 + 2)] = ((age - ((self.max_age + self.min_age) / 2)) / 20)
d[(states2 + 3)] = ((time_in_state - 3) / 10)
if (age > self.min_retirementage):
retaged = 1
else:
retaged = 0
d[(states2 + 5)] = pink
d[(states2 + 6)] = (toe - (14 / 12))
d[(states2 + 7)] = ((tyohist - 3) / 10)
if (tyohist > self.tyohistoria_vaatimus):
hist400 = 1
else:
hist400 = 0
d[(states2 + 8)] = hist400
d[(states2 + 9)] = retaged
d[(states2 + 10)] = ((next_wage - 40000) / 15000)
return d | Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan
Käytetään, jos kuolleisuus ei mukana | gym_unemployment/envs/test_environment.py | state_encode_nomort | ajtanskanen/econogym | 1 | python | def state_encode_nomort(self, emp, g, pension, old_wage, age, time_in_state, paid_pension, pink, toe, tyohist, next_wage):
'\n Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan\n \n Käytetään, jos kuolleisuus ei mukana\n '
d = np.zeros(((self.n_empl + self.n_groups) + 11))
states = self.n_empl
if (emp == 1):
d[0:states] = np.array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 0):
d[0:states] = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 2):
d[0:states] = np.array([0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 3):
d[0:states] = np.array([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 4):
d[0:states] = np.array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 5):
d[0:states] = np.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 6):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])
elif (emp == 7):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0])
elif (emp == 8):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0])
elif (emp == 9):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])
elif (emp == 10):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
elif (emp == 11):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
elif (emp == 12):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
elif (emp == 13):
print('state 13 in state_encode_nomort!')
else:
print(('state_encode error ' + str(emp)))
states2 = (states + self.n_groups)
if (g == 1):
d[states:states2] = np.array([0, 1, 0, 0, 0, 0])
elif (g == 0):
d[states:states2] = np.array([1, 0, 0, 0, 0, 0])
elif (g == 2):
d[states:states2] = np.array([0, 0, 1, 0, 0, 0])
elif (g == 3):
d[states:states2] = np.array([0, 0, 0, 1, 0, 0])
elif (g == 4):
d[states:states2] = np.array([0, 0, 0, 0, 1, 0])
elif (g == 5):
d[states:states2] = np.array([0, 0, 0, 0, 0, 1])
else:
print(('state_encode g-error ' + str(g)))
if self.log_transform:
d[states2] = np.log(((pension / 20000) + self.eps))
d[(states2 + 1)] = np.log(((old_wage / 40000) + self.eps))
d[(states2 + 4)] = np.log(((paid_pension / 20000) + self.eps))
else:
d[states2] = ((pension - 20000) / 10000)
d[(states2 + 1)] = ((old_wage - 40000) / 15000)
d[(states2 + 4)] = ((paid_pension - 20000) / 10000)
d[(states2 + 2)] = ((age - ((self.max_age + self.min_age) / 2)) / 20)
d[(states2 + 3)] = ((time_in_state - 3) / 10)
if (age > self.min_retirementage):
retaged = 1
else:
retaged = 0
d[(states2 + 5)] = pink
d[(states2 + 6)] = (toe - (14 / 12))
d[(states2 + 7)] = ((tyohist - 3) / 10)
if (tyohist > self.tyohistoria_vaatimus):
hist400 = 1
else:
hist400 = 0
d[(states2 + 8)] = hist400
d[(states2 + 9)] = retaged
d[(states2 + 10)] = ((next_wage - 40000) / 15000)
return d | def state_encode_nomort(self, emp, g, pension, old_wage, age, time_in_state, paid_pension, pink, toe, tyohist, next_wage):
'\n Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan\n \n Käytetään, jos kuolleisuus ei mukana\n '
d = np.zeros(((self.n_empl + self.n_groups) + 11))
states = self.n_empl
if (emp == 1):
d[0:states] = np.array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 0):
d[0:states] = np.array([1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 2):
d[0:states] = np.array([0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 3):
d[0:states] = np.array([0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 4):
d[0:states] = np.array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 5):
d[0:states] = np.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0])
elif (emp == 6):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])
elif (emp == 7):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0])
elif (emp == 8):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0])
elif (emp == 9):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0])
elif (emp == 10):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
elif (emp == 11):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
elif (emp == 12):
d[0:states] = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1])
elif (emp == 13):
print('state 13 in state_encode_nomort!')
else:
print(('state_encode error ' + str(emp)))
states2 = (states + self.n_groups)
if (g == 1):
d[states:states2] = np.array([0, 1, 0, 0, 0, 0])
elif (g == 0):
d[states:states2] = np.array([1, 0, 0, 0, 0, 0])
elif (g == 2):
d[states:states2] = np.array([0, 0, 1, 0, 0, 0])
elif (g == 3):
d[states:states2] = np.array([0, 0, 0, 1, 0, 0])
elif (g == 4):
d[states:states2] = np.array([0, 0, 0, 0, 1, 0])
elif (g == 5):
d[states:states2] = np.array([0, 0, 0, 0, 0, 1])
else:
print(('state_encode g-error ' + str(g)))
if self.log_transform:
d[states2] = np.log(((pension / 20000) + self.eps))
d[(states2 + 1)] = np.log(((old_wage / 40000) + self.eps))
d[(states2 + 4)] = np.log(((paid_pension / 20000) + self.eps))
else:
d[states2] = ((pension - 20000) / 10000)
d[(states2 + 1)] = ((old_wage - 40000) / 15000)
d[(states2 + 4)] = ((paid_pension - 20000) / 10000)
d[(states2 + 2)] = ((age - ((self.max_age + self.min_age) / 2)) / 20)
d[(states2 + 3)] = ((time_in_state - 3) / 10)
if (age > self.min_retirementage):
retaged = 1
else:
retaged = 0
d[(states2 + 5)] = pink
d[(states2 + 6)] = (toe - (14 / 12))
d[(states2 + 7)] = ((tyohist - 3) / 10)
if (tyohist > self.tyohistoria_vaatimus):
hist400 = 1
else:
hist400 = 0
d[(states2 + 8)] = hist400
d[(states2 + 9)] = retaged
d[(states2 + 10)] = ((next_wage - 40000) / 15000)
return d<|docstring|>Tilan koodaus neuroverkkoa varten. Arvot skaalataan ja tilat one-hot-enkoodataan
Käytetään, jos kuolleisuus ei mukana<|endoftext|> |
58d445ac8f9e78b29edaa515c3938907ae29c1a4a8e7e33d2961302674f8c5ee | def state_decode(self, vec):
'\n Tilan dekoodaus laskentaa varten\n \n Käytetään, jos aina\n '
emp = (- 1)
for k in range(self.n_empl):
if (vec[k] > 0):
emp = k
break
if (emp < 0):
print(('state error ' + str(vec)))
g = (- 1)
pos = (self.n_empl + self.n_groups)
for k in range(self.n_empl, pos):
if (vec[k] > 0):
g = (k - self.n_empl)
break
if (g < 0):
print(('state error ' + str(vec)))
if self.log_transform:
pension = ((np.exp(vec[pos]) - self.eps) * 20000)
wage = ((np.exp(vec[(pos + 1)]) - self.eps) * 40000)
paid_pension = ((np.exp(vec[(pos + 4)]) - self.eps) * 20000)
else:
pension = ((vec[pos] * 10000) + 20000)
wage = ((vec[(pos + 1)] * 15000) + 40000)
paid_pension = ((vec[(pos + 4)] * 10000) + 20000)
age = ((vec[(pos + 2)] * 20) + ((self.max_age + self.min_age) / 2))
time_in_state = ((vec[(pos + 3)] * 10) + 3)
pink = vec[(pos + 5)]
toe = (vec[(pos + 6)] + (14 / 12))
tyohist = ((vec[(pos + 7)] * 10) + 3)
return (int(emp), int(g), pension, wage, age, time_in_state, paid_pension, int(pink), toe, tyohist) | Tilan dekoodaus laskentaa varten
Käytetään, jos aina | gym_unemployment/envs/test_environment.py | state_decode | ajtanskanen/econogym | 1 | python | def state_decode(self, vec):
'\n Tilan dekoodaus laskentaa varten\n \n Käytetään, jos aina\n '
emp = (- 1)
for k in range(self.n_empl):
if (vec[k] > 0):
emp = k
break
if (emp < 0):
print(('state error ' + str(vec)))
g = (- 1)
pos = (self.n_empl + self.n_groups)
for k in range(self.n_empl, pos):
if (vec[k] > 0):
g = (k - self.n_empl)
break
if (g < 0):
print(('state error ' + str(vec)))
if self.log_transform:
pension = ((np.exp(vec[pos]) - self.eps) * 20000)
wage = ((np.exp(vec[(pos + 1)]) - self.eps) * 40000)
paid_pension = ((np.exp(vec[(pos + 4)]) - self.eps) * 20000)
else:
pension = ((vec[pos] * 10000) + 20000)
wage = ((vec[(pos + 1)] * 15000) + 40000)
paid_pension = ((vec[(pos + 4)] * 10000) + 20000)
age = ((vec[(pos + 2)] * 20) + ((self.max_age + self.min_age) / 2))
time_in_state = ((vec[(pos + 3)] * 10) + 3)
pink = vec[(pos + 5)]
toe = (vec[(pos + 6)] + (14 / 12))
tyohist = ((vec[(pos + 7)] * 10) + 3)
return (int(emp), int(g), pension, wage, age, time_in_state, paid_pension, int(pink), toe, tyohist) | def state_decode(self, vec):
'\n Tilan dekoodaus laskentaa varten\n \n Käytetään, jos aina\n '
emp = (- 1)
for k in range(self.n_empl):
if (vec[k] > 0):
emp = k
break
if (emp < 0):
print(('state error ' + str(vec)))
g = (- 1)
pos = (self.n_empl + self.n_groups)
for k in range(self.n_empl, pos):
if (vec[k] > 0):
g = (k - self.n_empl)
break
if (g < 0):
print(('state error ' + str(vec)))
if self.log_transform:
pension = ((np.exp(vec[pos]) - self.eps) * 20000)
wage = ((np.exp(vec[(pos + 1)]) - self.eps) * 40000)
paid_pension = ((np.exp(vec[(pos + 4)]) - self.eps) * 20000)
else:
pension = ((vec[pos] * 10000) + 20000)
wage = ((vec[(pos + 1)] * 15000) + 40000)
paid_pension = ((vec[(pos + 4)] * 10000) + 20000)
age = ((vec[(pos + 2)] * 20) + ((self.max_age + self.min_age) / 2))
time_in_state = ((vec[(pos + 3)] * 10) + 3)
pink = vec[(pos + 5)]
toe = (vec[(pos + 6)] + (14 / 12))
tyohist = ((vec[(pos + 7)] * 10) + 3)
return (int(emp), int(g), pension, wage, age, time_in_state, paid_pension, int(pink), toe, tyohist)<|docstring|>Tilan dekoodaus laskentaa varten
Käytetään, jos aina<|endoftext|> |
d4f8bf7c7c814895517483ccc8ed9990291a67d412fc71f80ef1f9196d1cf8a0 | def reset(self, init=None):
'\n Open AI-interfacen mukainen reset-funktio, joka nollaa laskennan alkutilaan\n '
employment_status = 12
age = int(self.min_age)
pension = 0
time_in_state = 0
pink = 0
toe = 0
tyohist = 0
g = random.choices(np.array([0, 1, 2], dtype=int), weights=[0.3, 0.5, 0.2])[0]
gender = random.choices(np.array([0, 1], dtype=int), weights=[0.5, 0.5])[0]
group = int((g + (gender * 3)))
self.compute_salary_TK(group=group)
old_wage = self.salary[self.min_age]
next_wage = old_wage
self.state = self.state_encode(employment_status, group, pension, old_wage, self.min_age, time_in_state, 0, pink, toe, tyohist, next_wage)
self.steps_beyond_done = None
return np.array(self.state) | Open AI-interfacen mukainen reset-funktio, joka nollaa laskennan alkutilaan | gym_unemployment/envs/test_environment.py | reset | ajtanskanen/econogym | 1 | python | def reset(self, init=None):
'\n \n '
employment_status = 12
age = int(self.min_age)
pension = 0
time_in_state = 0
pink = 0
toe = 0
tyohist = 0
g = random.choices(np.array([0, 1, 2], dtype=int), weights=[0.3, 0.5, 0.2])[0]
gender = random.choices(np.array([0, 1], dtype=int), weights=[0.5, 0.5])[0]
group = int((g + (gender * 3)))
self.compute_salary_TK(group=group)
old_wage = self.salary[self.min_age]
next_wage = old_wage
self.state = self.state_encode(employment_status, group, pension, old_wage, self.min_age, time_in_state, 0, pink, toe, tyohist, next_wage)
self.steps_beyond_done = None
return np.array(self.state) | def reset(self, init=None):
'\n \n '
employment_status = 12
age = int(self.min_age)
pension = 0
time_in_state = 0
pink = 0
toe = 0
tyohist = 0
g = random.choices(np.array([0, 1, 2], dtype=int), weights=[0.3, 0.5, 0.2])[0]
gender = random.choices(np.array([0, 1], dtype=int), weights=[0.5, 0.5])[0]
group = int((g + (gender * 3)))
self.compute_salary_TK(group=group)
old_wage = self.salary[self.min_age]
next_wage = old_wage
self.state = self.state_encode(employment_status, group, pension, old_wage, self.min_age, time_in_state, 0, pink, toe, tyohist, next_wage)
self.steps_beyond_done = None
return np.array(self.state)<|docstring|>Open AI-interfacen mukainen reset-funktio, joka nollaa laskennan alkutilaan<|endoftext|> |
fb5fc864f8f887c4b1de5dcf1d437df20d09e642a49866b3773f9bd8d4250ea1 | def render(self, mode='human', close=False):
'\n Tulostus-rutiini\n '
(emp, g, pension, wage, age, time_in_state, paid_pension, pink, toe, tyohist) = self.state_decode(self.state)
print('Tila {} ryhmä {} palkka {} ikä {} t-i-s {} tul.eläke {} alk.eläke {} irtisanottu {} toe {} työhist {}'.format(emp, g, wage, age, time_in_state, pension, paid_pension, pink, toe, tyohist)) | Tulostus-rutiini | gym_unemployment/envs/test_environment.py | render | ajtanskanen/econogym | 1 | python | def render(self, mode='human', close=False):
'\n \n '
(emp, g, pension, wage, age, time_in_state, paid_pension, pink, toe, tyohist) = self.state_decode(self.state)
print('Tila {} ryhmä {} palkka {} ikä {} t-i-s {} tul.eläke {} alk.eläke {} irtisanottu {} toe {} työhist {}'.format(emp, g, wage, age, time_in_state, pension, paid_pension, pink, toe, tyohist)) | def render(self, mode='human', close=False):
'\n \n '
(emp, g, pension, wage, age, time_in_state, paid_pension, pink, toe, tyohist) = self.state_decode(self.state)
print('Tila {} ryhmä {} palkka {} ikä {} t-i-s {} tul.eläke {} alk.eläke {} irtisanottu {} toe {} työhist {}'.format(emp, g, wage, age, time_in_state, pension, paid_pension, pink, toe, tyohist))<|docstring|>Tulostus-rutiini<|endoftext|> |
4d47340fd3dbcf37e6b0fdd2acbb71a2d213510e766aa4933411ec25bf6b9449 | def close(self):
'\n Ei käytössä\n '
if self.viewer:
self.viewer.close()
self.viewer = None | Ei käytössä | gym_unemployment/envs/test_environment.py | close | ajtanskanen/econogym | 1 | python | def close(self):
'\n \n '
if self.viewer:
self.viewer.close()
self.viewer = None | def close(self):
'\n \n '
if self.viewer:
self.viewer.close()
self.viewer = None<|docstring|>Ei käytössä<|endoftext|> |
f22af48471c46d5975e7eb1172ade6bc432b437c756a4c3165423a701cb9fc98 | def set_state_limits(self, debug=False):
'\n Rajat tiloille\n '
if self.log_transform:
pension_min = np.log(((0 / 20000) + self.eps))
pension_max = np.log(((200000 / 20000) + self.eps))
wage_max = np.log(((500000 / 40000) + self.eps))
wage_min = np.log(((0 / 40000) + self.eps))
paid_pension_max = np.log(((20000 / 20000) + self.eps))
paid_pension_min = np.log(((0 / 20000) + self.eps))
else:
pension_max = ((200000 - 20000) / 10000)
pension_min = ((0 - 20000) / 10000)
wage_max = ((500000 - 40000) / 15000)
wage_min = ((0 - 40000) / 15000)
paid_pension_min = ((0 - 20000) / 10000)
paid_pension_max = ((200000 - 20000) / 10000)
age_max = ((self.max_age - ((self.max_age + self.min_age) / 2)) / 20)
age_min = ((self.min_age - ((self.max_age + self.min_age) / 2)) / 20)
tis_max = (((self.max_age - self.min_age) - 3) / 10)
tis_min = ((- 3) / 10)
pink_min = 0
pink_max = 1
toe_min = (0 - (14 / 12))
toe_max = ((28 / 12) - (14 / 12))
thist_min = ((- 3) / 10)
thist_max = (((self.max_age - self.min_age) - 3) / 10)
group_min = 0
group_max = 1
state_min = 0
state_max = 1
if self.include_mort:
self.low = np.array([state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, group_min, group_min, group_min, group_min, group_min, group_min, pension_min, wage_min, age_min, tis_min, paid_pension_min, pink_min, toe_min, thist_min, state_min, state_min, wage_max])
self.high = np.array([state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, group_max, group_max, group_max, group_max, group_max, group_max, pension_max, wage_max, age_max, tis_max, paid_pension_max, pink_max, toe_max, thist_max, state_max, state_max, wage_max])
else:
self.low = np.array([state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, group_min, group_min, group_min, group_min, group_min, group_min, pension_min, wage_min, age_min, tis_min, paid_pension_min, pink_min, toe_min, thist_min, state_min, state_min, wage_max])
self.high = np.array([state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, group_max, group_max, group_max, group_max, group_max, group_max, pension_max, wage_max, age_max, tis_max, paid_pension_max, pink_max, toe_max, thist_max, state_max, state_max, wage_max])
if debug:
print(self.low.shape, self.high.shape) | Rajat tiloille | gym_unemployment/envs/test_environment.py | set_state_limits | ajtanskanen/econogym | 1 | python | def set_state_limits(self, debug=False):
'\n \n '
if self.log_transform:
pension_min = np.log(((0 / 20000) + self.eps))
pension_max = np.log(((200000 / 20000) + self.eps))
wage_max = np.log(((500000 / 40000) + self.eps))
wage_min = np.log(((0 / 40000) + self.eps))
paid_pension_max = np.log(((20000 / 20000) + self.eps))
paid_pension_min = np.log(((0 / 20000) + self.eps))
else:
pension_max = ((200000 - 20000) / 10000)
pension_min = ((0 - 20000) / 10000)
wage_max = ((500000 - 40000) / 15000)
wage_min = ((0 - 40000) / 15000)
paid_pension_min = ((0 - 20000) / 10000)
paid_pension_max = ((200000 - 20000) / 10000)
age_max = ((self.max_age - ((self.max_age + self.min_age) / 2)) / 20)
age_min = ((self.min_age - ((self.max_age + self.min_age) / 2)) / 20)
tis_max = (((self.max_age - self.min_age) - 3) / 10)
tis_min = ((- 3) / 10)
pink_min = 0
pink_max = 1
toe_min = (0 - (14 / 12))
toe_max = ((28 / 12) - (14 / 12))
thist_min = ((- 3) / 10)
thist_max = (((self.max_age - self.min_age) - 3) / 10)
group_min = 0
group_max = 1
state_min = 0
state_max = 1
if self.include_mort:
self.low = np.array([state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, group_min, group_min, group_min, group_min, group_min, group_min, pension_min, wage_min, age_min, tis_min, paid_pension_min, pink_min, toe_min, thist_min, state_min, state_min, wage_max])
self.high = np.array([state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, group_max, group_max, group_max, group_max, group_max, group_max, pension_max, wage_max, age_max, tis_max, paid_pension_max, pink_max, toe_max, thist_max, state_max, state_max, wage_max])
else:
self.low = np.array([state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, group_min, group_min, group_min, group_min, group_min, group_min, pension_min, wage_min, age_min, tis_min, paid_pension_min, pink_min, toe_min, thist_min, state_min, state_min, wage_max])
self.high = np.array([state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, group_max, group_max, group_max, group_max, group_max, group_max, pension_max, wage_max, age_max, tis_max, paid_pension_max, pink_max, toe_max, thist_max, state_max, state_max, wage_max])
if debug:
print(self.low.shape, self.high.shape) | def set_state_limits(self, debug=False):
'\n \n '
if self.log_transform:
pension_min = np.log(((0 / 20000) + self.eps))
pension_max = np.log(((200000 / 20000) + self.eps))
wage_max = np.log(((500000 / 40000) + self.eps))
wage_min = np.log(((0 / 40000) + self.eps))
paid_pension_max = np.log(((20000 / 20000) + self.eps))
paid_pension_min = np.log(((0 / 20000) + self.eps))
else:
pension_max = ((200000 - 20000) / 10000)
pension_min = ((0 - 20000) / 10000)
wage_max = ((500000 - 40000) / 15000)
wage_min = ((0 - 40000) / 15000)
paid_pension_min = ((0 - 20000) / 10000)
paid_pension_max = ((200000 - 20000) / 10000)
age_max = ((self.max_age - ((self.max_age + self.min_age) / 2)) / 20)
age_min = ((self.min_age - ((self.max_age + self.min_age) / 2)) / 20)
tis_max = (((self.max_age - self.min_age) - 3) / 10)
tis_min = ((- 3) / 10)
pink_min = 0
pink_max = 1
toe_min = (0 - (14 / 12))
toe_max = ((28 / 12) - (14 / 12))
thist_min = ((- 3) / 10)
thist_max = (((self.max_age - self.min_age) - 3) / 10)
group_min = 0
group_max = 1
state_min = 0
state_max = 1
if self.include_mort:
self.low = np.array([state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, group_min, group_min, group_min, group_min, group_min, group_min, pension_min, wage_min, age_min, tis_min, paid_pension_min, pink_min, toe_min, thist_min, state_min, state_min, wage_max])
self.high = np.array([state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, group_max, group_max, group_max, group_max, group_max, group_max, pension_max, wage_max, age_max, tis_max, paid_pension_max, pink_max, toe_max, thist_max, state_max, state_max, wage_max])
else:
self.low = np.array([state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, state_min, group_min, group_min, group_min, group_min, group_min, group_min, pension_min, wage_min, age_min, tis_min, paid_pension_min, pink_min, toe_min, thist_min, state_min, state_min, wage_max])
self.high = np.array([state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, state_max, group_max, group_max, group_max, group_max, group_max, group_max, pension_max, wage_max, age_max, tis_max, paid_pension_max, pink_max, toe_max, thist_max, state_max, state_max, wage_max])
if debug:
print(self.low.shape, self.high.shape)<|docstring|>Rajat tiloille<|endoftext|> |
b4bf8036927cd74cecf8c01809e23ee1c5de2e8760deb69da8e032578a2629fc | def test_hashtags_search(self):
'\n\t\tMake sure we can simply use the search.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
self.assertEqual(response.status_code, 200) | Make sure we can simply use the search. | hashtagsv2/hashtags/tests.py | test_hashtags_search | 3to1null/hashtags | 0 | python | def test_hashtags_search(self):
'\n\t\t\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
self.assertEqual(response.status_code, 200) | def test_hashtags_search(self):
'\n\t\t\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
self.assertEqual(response.status_code, 200)<|docstring|>Make sure we can simply use the search.<|endoftext|> |
9c7fd4a7fca193c2698fbc5546c8066e08d50df94302966ca002de0489b4b8af | def test_hashtags_results(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with only a hashtag.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 5) | Test that we receive the correct object list when
searching with only a hashtag. | hashtagsv2/hashtags/tests.py | test_hashtags_results | 3to1null/hashtags | 0 | python | def test_hashtags_results(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with only a hashtag.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 5) | def test_hashtags_results(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with only a hashtag.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 5)<|docstring|>Test that we receive the correct object list when
searching with only a hashtag.<|endoftext|> |
4ad1221cc43b61c544ebd0a5203ed85beb8166bcf8dede977ae8fe72c93d12cc | def test_hashtags_results_2(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a hashtag and a project.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag3', 'project': 'fr.wikipedia.org'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.project_hashtag.get_values_list()) | Test that we receive the correct object list when
searching with a hashtag and a project. | hashtagsv2/hashtags/tests.py | test_hashtags_results_2 | 3to1null/hashtags | 0 | python | def test_hashtags_results_2(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a hashtag and a project.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag3', 'project': 'fr.wikipedia.org'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.project_hashtag.get_values_list()) | def test_hashtags_results_2(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a hashtag and a project.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag3', 'project': 'fr.wikipedia.org'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.project_hashtag.get_values_list())<|docstring|>Test that we receive the correct object list when
searching with a hashtag and a project.<|endoftext|> |
9146245ba916400b46e1d64f4b2fcfca90c999b02ba536120ef408ea39e7a2cf | def test_hashtags_results_3(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a hashtag, a project, and a date range.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag4', 'project': 'ja.wikipedia.org', 'startdate': '2017-01-01', 'enddate': '2018-01-01'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.date_hashtag.get_values_list()) | Test that we receive the correct object list when
searching with a hashtag, a project, and a date range. | hashtagsv2/hashtags/tests.py | test_hashtags_results_3 | 3to1null/hashtags | 0 | python | def test_hashtags_results_3(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a hashtag, a project, and a date range.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag4', 'project': 'ja.wikipedia.org', 'startdate': '2017-01-01', 'enddate': '2018-01-01'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.date_hashtag.get_values_list()) | def test_hashtags_results_3(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a hashtag, a project, and a date range.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag4', 'project': 'ja.wikipedia.org', 'startdate': '2017-01-01', 'enddate': '2018-01-01'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.date_hashtag.get_values_list())<|docstring|>Test that we receive the correct object list when
searching with a hashtag, a project, and a date range.<|endoftext|> |
bd75b6e9ab16df000bff1b92712e9fac6a542a3ad0a871e6dab3d3dedf122348 | def test_hashtags_results_4(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a query that contains an octothorpe\n\t\t'
factory = RequestFactory()
data = {'query': '#hashtag4'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.date_hashtag.get_values_list()) | Test that we receive the correct object list when
searching with a query that contains an octothorpe | hashtagsv2/hashtags/tests.py | test_hashtags_results_4 | 3to1null/hashtags | 0 | python | def test_hashtags_results_4(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a query that contains an octothorpe\n\t\t'
factory = RequestFactory()
data = {'query': '#hashtag4'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.date_hashtag.get_values_list()) | def test_hashtags_results_4(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching with a query that contains an octothorpe\n\t\t'
factory = RequestFactory()
data = {'query': '#hashtag4'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 1)
self.assertEqual(object_list[0], self.date_hashtag.get_values_list())<|docstring|>Test that we receive the correct object list when
searching with a query that contains an octothorpe<|endoftext|> |
2db4c636e7c3aaa76ccd5dc2d416a6a07886dbc0011552217ae1b6b29fafc8c6 | def test_hashtags_results_5(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching for multiple hashtags\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag4, hashtag3'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 2)
self.assertIn(self.date_hashtag.get_values_list(), object_list)
self.assertIn(self.project_hashtag.get_values_list(), object_list) | Test that we receive the correct object list when
searching for multiple hashtags | hashtagsv2/hashtags/tests.py | test_hashtags_results_5 | 3to1null/hashtags | 0 | python | def test_hashtags_results_5(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching for multiple hashtags\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag4, hashtag3'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 2)
self.assertIn(self.date_hashtag.get_values_list(), object_list)
self.assertIn(self.project_hashtag.get_values_list(), object_list) | def test_hashtags_results_5(self):
'\n\t\tTest that we receive the correct object list when\n\t\tsearching for multiple hashtags\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag4, hashtag3'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
object_list = response.context_data['object_list']
self.assertEqual(object_list.count(), 2)
self.assertIn(self.date_hashtag.get_values_list(), object_list)
self.assertIn(self.project_hashtag.get_values_list(), object_list)<|docstring|>Test that we receive the correct object list when
searching for multiple hashtags<|endoftext|> |
06150b181ec851728a17cde8450909fe2a72b1149e0858fd61e473829116f0ae | def test_hashtags_results_template(self):
'\n\t\tTest that only the hashtags we expect are listed in the\n\t\tresults table.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
page_content = response.render().content
self.assertEqual(page_content.decode().count('<tr>'), 10) | Test that only the hashtags we expect are listed in the
results table. | hashtagsv2/hashtags/tests.py | test_hashtags_results_template | 3to1null/hashtags | 0 | python | def test_hashtags_results_template(self):
'\n\t\tTest that only the hashtags we expect are listed in the\n\t\tresults table.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
page_content = response.render().content
self.assertEqual(page_content.decode().count('<tr>'), 10) | def test_hashtags_results_template(self):
'\n\t\tTest that only the hashtags we expect are listed in the\n\t\tresults table.\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.url, data)
response = views.Index.as_view()(request)
page_content = response.render().content
self.assertEqual(page_content.decode().count('<tr>'), 10)<|docstring|>Test that only the hashtags we expect are listed in the
results table.<|endoftext|> |
37c4f155680358f14f37ff393e805eaa9ec8e7c4bda0950a6df28254dadc5461 | def test_hashtags_download_csv(self):
'\n\t\tMake sure the CSV download works with just a hashtag\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.download_url, data)
response = views.csv_download(request)
page_content = response.content
self.assertEqual(len(page_content.splitlines()), 6) | Make sure the CSV download works with just a hashtag | hashtagsv2/hashtags/tests.py | test_hashtags_download_csv | 3to1null/hashtags | 0 | python | def test_hashtags_download_csv(self):
'\n\t\t\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.download_url, data)
response = views.csv_download(request)
page_content = response.content
self.assertEqual(len(page_content.splitlines()), 6) | def test_hashtags_download_csv(self):
'\n\t\t\n\t\t'
factory = RequestFactory()
data = {'query': 'hashtag1'}
request = factory.get(self.download_url, data)
response = views.csv_download(request)
page_content = response.content
self.assertEqual(len(page_content.splitlines()), 6)<|docstring|>Make sure the CSV download works with just a hashtag<|endoftext|> |
2ba275dea12573b8478f4bdab4537e1c2f5fcc5b250fb87a8e8725d4a9e6bbdb | def put(handler, parameters, url_parameters, ids_parameters):
'PUT method'
[tournament_id] = ids_parameters
if (not parameters):
handler.logger.debug('Ignoring')
handler.send_json('{}')
return
result = handler.session.query(Tournament).where((Tournament.id == int(tournament_id))).first()
if (not result):
handler.logger.debug((('The tournament ' + tournament_id) + ' does not exists'))
handler.send_error(404, 'This tournament does not exist')
return
handler.session.update_columns(Tournament, int(tournament_id), parameters)
handler.logger.debug('Updated succesfully')
handler.send_json('{}') | PUT method | server/routes/api/v1/tosurnament/tournaments/single.py | put | SpartanPlume/TosurnamentWeb | 1 | python | def put(handler, parameters, url_parameters, ids_parameters):
[tournament_id] = ids_parameters
if (not parameters):
handler.logger.debug('Ignoring')
handler.send_json('{}')
return
result = handler.session.query(Tournament).where((Tournament.id == int(tournament_id))).first()
if (not result):
handler.logger.debug((('The tournament ' + tournament_id) + ' does not exists'))
handler.send_error(404, 'This tournament does not exist')
return
handler.session.update_columns(Tournament, int(tournament_id), parameters)
handler.logger.debug('Updated succesfully')
handler.send_json('{}') | def put(handler, parameters, url_parameters, ids_parameters):
[tournament_id] = ids_parameters
if (not parameters):
handler.logger.debug('Ignoring')
handler.send_json('{}')
return
result = handler.session.query(Tournament).where((Tournament.id == int(tournament_id))).first()
if (not result):
handler.logger.debug((('The tournament ' + tournament_id) + ' does not exists'))
handler.send_error(404, 'This tournament does not exist')
return
handler.session.update_columns(Tournament, int(tournament_id), parameters)
handler.logger.debug('Updated succesfully')
handler.send_json('{}')<|docstring|>PUT method<|endoftext|> |
1dd2ddbed70ebdaf1b16d037a2dbfbb593c44ca68dbcd62889de6cc7e1f901a7 | def delete(handler, parameters, url_parameters, ids_parameters):
'DELETE method'
[tournament_id] = ids_parameters
result = handler.session.query(Tournament).where((Tournament.id == int(tournament_id))).first()
if (not result):
handler.logger.debug((('The tournament ' + tournament_id) + ' does not exists'))
handler.send_error(404, 'This tournament does not exist')
return
handler.session.delete(result)
handler.logger.debug('Deleted succesfully')
handler.send_json('{}') | DELETE method | server/routes/api/v1/tosurnament/tournaments/single.py | delete | SpartanPlume/TosurnamentWeb | 1 | python | def delete(handler, parameters, url_parameters, ids_parameters):
[tournament_id] = ids_parameters
result = handler.session.query(Tournament).where((Tournament.id == int(tournament_id))).first()
if (not result):
handler.logger.debug((('The tournament ' + tournament_id) + ' does not exists'))
handler.send_error(404, 'This tournament does not exist')
return
handler.session.delete(result)
handler.logger.debug('Deleted succesfully')
handler.send_json('{}') | def delete(handler, parameters, url_parameters, ids_parameters):
[tournament_id] = ids_parameters
result = handler.session.query(Tournament).where((Tournament.id == int(tournament_id))).first()
if (not result):
handler.logger.debug((('The tournament ' + tournament_id) + ' does not exists'))
handler.send_error(404, 'This tournament does not exist')
return
handler.session.delete(result)
handler.logger.debug('Deleted succesfully')
handler.send_json('{}')<|docstring|>DELETE method<|endoftext|> |
74e2048ff47cc58901723d8749909498ac7b7a60938a297e9afcb082690d99d0 | def weight_variable(shape):
'Create a weight variable with appropriate initialization.'
initial = tf.random.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial) | Create a weight variable with appropriate initialization. | tensorflow/lite/micro/examples/micro_mnist/model/layers.py | weight_variable | PeteBlackerThe3rd/tensorflow | 0 | python | def weight_variable(shape):
initial = tf.random.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial) | def weight_variable(shape):
initial = tf.random.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial)<|docstring|>Create a weight variable with appropriate initialization.<|endoftext|> |
994e3864c57e24bbc9c8d510b79f94699db61e5c7de5b2118db895a65f5675bd | def bias_variable(shape):
'Create a bias variable with appropriate initialization.'
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial) | Create a bias variable with appropriate initialization. | tensorflow/lite/micro/examples/micro_mnist/model/layers.py | bias_variable | PeteBlackerThe3rd/tensorflow | 0 | python | def bias_variable(shape):
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial) | def bias_variable(shape):
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial)<|docstring|>Create a bias variable with appropriate initialization.<|endoftext|> |
3deca6834372d5d057bfbfad5eb66068a3989adccbb1024dcda66d79b694e631 | def variable_summaries(var):
'Attach a lot of summaries to a Tensor (for TensorBoard visualization).'
with tf.name_scope('summaries'):
mean = tf.reduce_mean(var)
tf.compat.v1.summary.scalar('mean', mean)
with tf.name_scope('stddev'):
stddev = tf.sqrt(tf.reduce_mean(tf.square((var - mean))))
tf.compat.v1.summary.scalar('stddev', stddev)
tf.compat.v1.summary.scalar('max', tf.reduce_max(var))
tf.compat.v1.summary.scalar('min', tf.reduce_min(var))
tf.compat.v1.summary.histogram('histogram', var) | Attach a lot of summaries to a Tensor (for TensorBoard visualization). | tensorflow/lite/micro/examples/micro_mnist/model/layers.py | variable_summaries | PeteBlackerThe3rd/tensorflow | 0 | python | def variable_summaries(var):
with tf.name_scope('summaries'):
mean = tf.reduce_mean(var)
tf.compat.v1.summary.scalar('mean', mean)
with tf.name_scope('stddev'):
stddev = tf.sqrt(tf.reduce_mean(tf.square((var - mean))))
tf.compat.v1.summary.scalar('stddev', stddev)
tf.compat.v1.summary.scalar('max', tf.reduce_max(var))
tf.compat.v1.summary.scalar('min', tf.reduce_min(var))
tf.compat.v1.summary.histogram('histogram', var) | def variable_summaries(var):
with tf.name_scope('summaries'):
mean = tf.reduce_mean(var)
tf.compat.v1.summary.scalar('mean', mean)
with tf.name_scope('stddev'):
stddev = tf.sqrt(tf.reduce_mean(tf.square((var - mean))))
tf.compat.v1.summary.scalar('stddev', stddev)
tf.compat.v1.summary.scalar('max', tf.reduce_max(var))
tf.compat.v1.summary.scalar('min', tf.reduce_min(var))
tf.compat.v1.summary.histogram('histogram', var)<|docstring|>Attach a lot of summaries to a Tensor (for TensorBoard visualization).<|endoftext|> |
938d8207dcb41cc0896dc829304f7198034ab283b7e85e33b5d4b6501dd63ed9 | def nn_layer(input_tensor, input_dim, output_dim, layer_name, act=tf.nn.relu):
'Reusable code for making a simple neural net layer.\n It does a matrix multiply, bias add, and then uses an activation function\n (ReLu defauly) to nonlinearize. It also sets up name scoping so that the\n resultant graph is easy to read, and adds a number of summary ops.\n '
with tf.name_scope(layer_name):
with tf.name_scope('weights'):
weights = weight_variable([input_dim, output_dim])
variable_summaries(weights)
with tf.name_scope('biases'):
biases = bias_variable([output_dim])
variable_summaries(biases)
with tf.name_scope('Wx_plus_b'):
preactivate = (tf.matmul(input_tensor, weights) + biases)
tf.compat.v1.summary.histogram('pre_activations', preactivate)
activations = act(preactivate, name='activation')
tf.compat.v1.summary.histogram('activations', activations)
return activations | Reusable code for making a simple neural net layer.
It does a matrix multiply, bias add, and then uses an activation function
(ReLu defauly) to nonlinearize. It also sets up name scoping so that the
resultant graph is easy to read, and adds a number of summary ops. | tensorflow/lite/micro/examples/micro_mnist/model/layers.py | nn_layer | PeteBlackerThe3rd/tensorflow | 0 | python | def nn_layer(input_tensor, input_dim, output_dim, layer_name, act=tf.nn.relu):
'Reusable code for making a simple neural net layer.\n It does a matrix multiply, bias add, and then uses an activation function\n (ReLu defauly) to nonlinearize. It also sets up name scoping so that the\n resultant graph is easy to read, and adds a number of summary ops.\n '
with tf.name_scope(layer_name):
with tf.name_scope('weights'):
weights = weight_variable([input_dim, output_dim])
variable_summaries(weights)
with tf.name_scope('biases'):
biases = bias_variable([output_dim])
variable_summaries(biases)
with tf.name_scope('Wx_plus_b'):
preactivate = (tf.matmul(input_tensor, weights) + biases)
tf.compat.v1.summary.histogram('pre_activations', preactivate)
activations = act(preactivate, name='activation')
tf.compat.v1.summary.histogram('activations', activations)
return activations | def nn_layer(input_tensor, input_dim, output_dim, layer_name, act=tf.nn.relu):
'Reusable code for making a simple neural net layer.\n It does a matrix multiply, bias add, and then uses an activation function\n (ReLu defauly) to nonlinearize. It also sets up name scoping so that the\n resultant graph is easy to read, and adds a number of summary ops.\n '
with tf.name_scope(layer_name):
with tf.name_scope('weights'):
weights = weight_variable([input_dim, output_dim])
variable_summaries(weights)
with tf.name_scope('biases'):
biases = bias_variable([output_dim])
variable_summaries(biases)
with tf.name_scope('Wx_plus_b'):
preactivate = (tf.matmul(input_tensor, weights) + biases)
tf.compat.v1.summary.histogram('pre_activations', preactivate)
activations = act(preactivate, name='activation')
tf.compat.v1.summary.histogram('activations', activations)
return activations<|docstring|>Reusable code for making a simple neural net layer.
It does a matrix multiply, bias add, and then uses an activation function
(ReLu defauly) to nonlinearize. It also sets up name scoping so that the
resultant graph is easy to read, and adds a number of summary ops.<|endoftext|> |
586403098e6a3fb1c3d14699d9d1fea7169c948d1077a9a0a29c490c4928aa4a | def cross_entropy_training(y, y_, learning_rate=0.001):
'Reusable code to add a cross entropy loss function and\n optimser to a model'
with tf.name_scope('cross_entropy'):
with tf.name_scope('total'):
cross_entropy = tf.compat.v1.losses.sparse_softmax_cross_entropy(labels=y_, logits=y)
tf.compat.v1.summary.scalar('cross_entropy', cross_entropy)
with tf.name_scope('train'):
train_step = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(cross_entropy)
with tf.name_scope('accuracy'):
with tf.name_scope('correct_prediction'):
correct_prediction = tf.equal(tf.argmax(y, 1), y_)
with tf.name_scope('accuracy'):
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
tf.compat.v1.summary.scalar('accuracy', accuracy)
return [train_step, accuracy] | Reusable code to add a cross entropy loss function and
optimser to a model | tensorflow/lite/micro/examples/micro_mnist/model/layers.py | cross_entropy_training | PeteBlackerThe3rd/tensorflow | 0 | python | def cross_entropy_training(y, y_, learning_rate=0.001):
'Reusable code to add a cross entropy loss function and\n optimser to a model'
with tf.name_scope('cross_entropy'):
with tf.name_scope('total'):
cross_entropy = tf.compat.v1.losses.sparse_softmax_cross_entropy(labels=y_, logits=y)
tf.compat.v1.summary.scalar('cross_entropy', cross_entropy)
with tf.name_scope('train'):
train_step = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(cross_entropy)
with tf.name_scope('accuracy'):
with tf.name_scope('correct_prediction'):
correct_prediction = tf.equal(tf.argmax(y, 1), y_)
with tf.name_scope('accuracy'):
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
tf.compat.v1.summary.scalar('accuracy', accuracy)
return [train_step, accuracy] | def cross_entropy_training(y, y_, learning_rate=0.001):
'Reusable code to add a cross entropy loss function and\n optimser to a model'
with tf.name_scope('cross_entropy'):
with tf.name_scope('total'):
cross_entropy = tf.compat.v1.losses.sparse_softmax_cross_entropy(labels=y_, logits=y)
tf.compat.v1.summary.scalar('cross_entropy', cross_entropy)
with tf.name_scope('train'):
train_step = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(cross_entropy)
with tf.name_scope('accuracy'):
with tf.name_scope('correct_prediction'):
correct_prediction = tf.equal(tf.argmax(y, 1), y_)
with tf.name_scope('accuracy'):
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
tf.compat.v1.summary.scalar('accuracy', accuracy)
return [train_step, accuracy]<|docstring|>Reusable code to add a cross entropy loss function and
optimser to a model<|endoftext|> |
7328b8e0885887402d93e17fd1889def9097ebd5b042122941e3e6cc0c3e6263 | @property
def correction_mode(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CorrectionMode() As long\n | \n | Returns or sets the correction mode (threshold, point, tangency or\n | curvature) applied to the smoothed curve.\n | Legal values:\n | \n | 0\n | CATGSMCSCorrectionMode_Threshold. no continuity \n | 1\n | CATGSMCSCorrectionMode_Point. continuity in point\n | (C0).\n | 2\n | CATGSMCSCorrectionMode_Tangency. continuity in tangency\n | (C1).\n | 3\n | CATGSMCSCorrectionMode_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oMode the correction mode for the\n | hybShpCurveSmooth hybrid shape feature.\n | \n | oMode = hybShpCurveSmooth.CorrectionMode\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.CorrectionMode | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CorrectionMode() As long
|
| Returns or sets the correction mode (threshold, point, tangency or
| curvature) applied to the smoothed curve.
| Legal values:
|
| 0
| CATGSMCSCorrectionMode_Threshold. no continuity
| 1
| CATGSMCSCorrectionMode_Point. continuity in point
| (C0).
| 2
| CATGSMCSCorrectionMode_Tangency. continuity in tangency
| (C1).
| 3
| CATGSMCSCorrectionMode_Curvature. continuity in curvature
| (C2).
|
| Example:
| This example retrieves in oMode the correction mode for the
| hybShpCurveSmooth hybrid shape feature.
|
| oMode = hybShpCurveSmooth.CorrectionMode
:return: int
:rtype: int | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | correction_mode | Luanee/pycatia | 1 | python | @property
def correction_mode(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CorrectionMode() As long\n | \n | Returns or sets the correction mode (threshold, point, tangency or\n | curvature) applied to the smoothed curve.\n | Legal values:\n | \n | 0\n | CATGSMCSCorrectionMode_Threshold. no continuity \n | 1\n | CATGSMCSCorrectionMode_Point. continuity in point\n | (C0).\n | 2\n | CATGSMCSCorrectionMode_Tangency. continuity in tangency\n | (C1).\n | 3\n | CATGSMCSCorrectionMode_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oMode the correction mode for the\n | hybShpCurveSmooth hybrid shape feature.\n | \n | oMode = hybShpCurveSmooth.CorrectionMode\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.CorrectionMode | @property
def correction_mode(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CorrectionMode() As long\n | \n | Returns or sets the correction mode (threshold, point, tangency or\n | curvature) applied to the smoothed curve.\n | Legal values:\n | \n | 0\n | CATGSMCSCorrectionMode_Threshold. no continuity \n | 1\n | CATGSMCSCorrectionMode_Point. continuity in point\n | (C0).\n | 2\n | CATGSMCSCorrectionMode_Tangency. continuity in tangency\n | (C1).\n | 3\n | CATGSMCSCorrectionMode_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oMode the correction mode for the\n | hybShpCurveSmooth hybrid shape feature.\n | \n | oMode = hybShpCurveSmooth.CorrectionMode\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.CorrectionMode<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CorrectionMode() As long
|
| Returns or sets the correction mode (threshold, point, tangency or
| curvature) applied to the smoothed curve.
| Legal values:
|
| 0
| CATGSMCSCorrectionMode_Threshold. no continuity
| 1
| CATGSMCSCorrectionMode_Point. continuity in point
| (C0).
| 2
| CATGSMCSCorrectionMode_Tangency. continuity in tangency
| (C1).
| 3
| CATGSMCSCorrectionMode_Curvature. continuity in curvature
| (C2).
|
| Example:
| This example retrieves in oMode the correction mode for the
| hybShpCurveSmooth hybrid shape feature.
|
| oMode = hybShpCurveSmooth.CorrectionMode
:return: int
:rtype: int<|endoftext|> |
aa66ee566e8f3757288f0442470497f06214fc131d8ff532a1a32059c1d20e16 | @correction_mode.setter
def correction_mode(self, value: int):
'\n :param int value:\n '
self.hybrid_shape_curve_smooth.CorrectionMode = value | :param int value: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | correction_mode | Luanee/pycatia | 1 | python | @correction_mode.setter
def correction_mode(self, value: int):
'\n \n '
self.hybrid_shape_curve_smooth.CorrectionMode = value | @correction_mode.setter
def correction_mode(self, value: int):
'\n \n '
self.hybrid_shape_curve_smooth.CorrectionMode = value<|docstring|>:param int value:<|endoftext|> |
f80298388ca5e7ffd19ff616c3f2f8198fc8677de540b2c2bfb46ec159efb397 | @property
def curvature_threshold(self) -> float:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurvatureThreshold() As double\n | \n | Returns or sets the CurvatureThreshold.\n | \n | Example: This example retrieves the CurvatureThreshold of the\n | hybShpCurveSmooth in CurvatureThH.\n | \n | Dim CurvatureThH as double\n | CurvatureThH = hybShpCurvePar.CurvatureThreshold\n\n :return: float\n :rtype: float\n '
return self.hybrid_shape_curve_smooth.CurvatureThreshold | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CurvatureThreshold() As double
|
| Returns or sets the CurvatureThreshold.
|
| Example: This example retrieves the CurvatureThreshold of the
| hybShpCurveSmooth in CurvatureThH.
|
| Dim CurvatureThH as double
| CurvatureThH = hybShpCurvePar.CurvatureThreshold
:return: float
:rtype: float | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | curvature_threshold | Luanee/pycatia | 1 | python | @property
def curvature_threshold(self) -> float:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurvatureThreshold() As double\n | \n | Returns or sets the CurvatureThreshold.\n | \n | Example: This example retrieves the CurvatureThreshold of the\n | hybShpCurveSmooth in CurvatureThH.\n | \n | Dim CurvatureThH as double\n | CurvatureThH = hybShpCurvePar.CurvatureThreshold\n\n :return: float\n :rtype: float\n '
return self.hybrid_shape_curve_smooth.CurvatureThreshold | @property
def curvature_threshold(self) -> float:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurvatureThreshold() As double\n | \n | Returns or sets the CurvatureThreshold.\n | \n | Example: This example retrieves the CurvatureThreshold of the\n | hybShpCurveSmooth in CurvatureThH.\n | \n | Dim CurvatureThH as double\n | CurvatureThH = hybShpCurvePar.CurvatureThreshold\n\n :return: float\n :rtype: float\n '
return self.hybrid_shape_curve_smooth.CurvatureThreshold<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CurvatureThreshold() As double
|
| Returns or sets the CurvatureThreshold.
|
| Example: This example retrieves the CurvatureThreshold of the
| hybShpCurveSmooth in CurvatureThH.
|
| Dim CurvatureThH as double
| CurvatureThH = hybShpCurvePar.CurvatureThreshold
:return: float
:rtype: float<|endoftext|> |
961d074cff2653ab8750124a73ae54bfb98e1c9a2fbab38e4e4cbce4f3a9205b | @curvature_threshold.setter
def curvature_threshold(self, value: float):
'\n :param float value:\n '
self.hybrid_shape_curve_smooth.CurvatureThreshold = value | :param float value: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | curvature_threshold | Luanee/pycatia | 1 | python | @curvature_threshold.setter
def curvature_threshold(self, value: float):
'\n \n '
self.hybrid_shape_curve_smooth.CurvatureThreshold = value | @curvature_threshold.setter
def curvature_threshold(self, value: float):
'\n \n '
self.hybrid_shape_curve_smooth.CurvatureThreshold = value<|docstring|>:param float value:<|endoftext|> |
b404785a71b667b5eaccbb9d92187302db9672b46bb62103a698bb2b0ca04935 | @property
def curvature_threshold_activity(self) -> bool:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurvatureThresholdActivity() As boolean\n | \n | Returns or sets the CurvatureThresholdActivity.\n | \n | Example: This example retrieves the CurvatureThresholdActivity of the\n | hybShpCurveSmooth in CurvatureActivity .\n | \n | Dim CurvatureActivity as boolean \n | CurvatureActivity = hybShpCurvePar.CurvatureThresholdActivity\n\n :return: bool\n :rtype: bool\n '
return self.hybrid_shape_curve_smooth.CurvatureThresholdActivity | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CurvatureThresholdActivity() As boolean
|
| Returns or sets the CurvatureThresholdActivity.
|
| Example: This example retrieves the CurvatureThresholdActivity of the
| hybShpCurveSmooth in CurvatureActivity .
|
| Dim CurvatureActivity as boolean
| CurvatureActivity = hybShpCurvePar.CurvatureThresholdActivity
:return: bool
:rtype: bool | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | curvature_threshold_activity | Luanee/pycatia | 1 | python | @property
def curvature_threshold_activity(self) -> bool:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurvatureThresholdActivity() As boolean\n | \n | Returns or sets the CurvatureThresholdActivity.\n | \n | Example: This example retrieves the CurvatureThresholdActivity of the\n | hybShpCurveSmooth in CurvatureActivity .\n | \n | Dim CurvatureActivity as boolean \n | CurvatureActivity = hybShpCurvePar.CurvatureThresholdActivity\n\n :return: bool\n :rtype: bool\n '
return self.hybrid_shape_curve_smooth.CurvatureThresholdActivity | @property
def curvature_threshold_activity(self) -> bool:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurvatureThresholdActivity() As boolean\n | \n | Returns or sets the CurvatureThresholdActivity.\n | \n | Example: This example retrieves the CurvatureThresholdActivity of the\n | hybShpCurveSmooth in CurvatureActivity .\n | \n | Dim CurvatureActivity as boolean \n | CurvatureActivity = hybShpCurvePar.CurvatureThresholdActivity\n\n :return: bool\n :rtype: bool\n '
return self.hybrid_shape_curve_smooth.CurvatureThresholdActivity<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CurvatureThresholdActivity() As boolean
|
| Returns or sets the CurvatureThresholdActivity.
|
| Example: This example retrieves the CurvatureThresholdActivity of the
| hybShpCurveSmooth in CurvatureActivity .
|
| Dim CurvatureActivity as boolean
| CurvatureActivity = hybShpCurvePar.CurvatureThresholdActivity
:return: bool
:rtype: bool<|endoftext|> |
4b767c2dc2fbab696ed35ba311d2f9061b90001ff2853161458d8f0354c9b471 | @curvature_threshold_activity.setter
def curvature_threshold_activity(self, value: bool):
'\n :param bool value:\n '
self.hybrid_shape_curve_smooth.CurvatureThresholdActivity = value | :param bool value: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | curvature_threshold_activity | Luanee/pycatia | 1 | python | @curvature_threshold_activity.setter
def curvature_threshold_activity(self, value: bool):
'\n \n '
self.hybrid_shape_curve_smooth.CurvatureThresholdActivity = value | @curvature_threshold_activity.setter
def curvature_threshold_activity(self, value: bool):
'\n \n '
self.hybrid_shape_curve_smooth.CurvatureThresholdActivity = value<|docstring|>:param bool value:<|endoftext|> |
941861f459e5287bc054332fa208e806a8dcad5dc7e87f09130d3e8c840a9f1e | @property
def curve_to_smooth(self) -> Reference:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurveToSmooth() As Reference\n | \n | Returns or sets the curve to smooth.\n | \n | Example: This example retrieves the curve to smooth object of the\n | hybShpCurveSmooth in Curve.\n | \n | Dim Curve as CATIAReference \n | Curve = hybShpCurvePar.CurveToSmooth\n\n :return: Reference\n :rtype: Reference\n '
return Reference(self.hybrid_shape_curve_smooth.CurveToSmooth) | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CurveToSmooth() As Reference
|
| Returns or sets the curve to smooth.
|
| Example: This example retrieves the curve to smooth object of the
| hybShpCurveSmooth in Curve.
|
| Dim Curve as CATIAReference
| Curve = hybShpCurvePar.CurveToSmooth
:return: Reference
:rtype: Reference | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | curve_to_smooth | Luanee/pycatia | 1 | python | @property
def curve_to_smooth(self) -> Reference:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurveToSmooth() As Reference\n | \n | Returns or sets the curve to smooth.\n | \n | Example: This example retrieves the curve to smooth object of the\n | hybShpCurveSmooth in Curve.\n | \n | Dim Curve as CATIAReference \n | Curve = hybShpCurvePar.CurveToSmooth\n\n :return: Reference\n :rtype: Reference\n '
return Reference(self.hybrid_shape_curve_smooth.CurveToSmooth) | @property
def curve_to_smooth(self) -> Reference:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property CurveToSmooth() As Reference\n | \n | Returns or sets the curve to smooth.\n | \n | Example: This example retrieves the curve to smooth object of the\n | hybShpCurveSmooth in Curve.\n | \n | Dim Curve as CATIAReference \n | Curve = hybShpCurvePar.CurveToSmooth\n\n :return: Reference\n :rtype: Reference\n '
return Reference(self.hybrid_shape_curve_smooth.CurveToSmooth)<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property CurveToSmooth() As Reference
|
| Returns or sets the curve to smooth.
|
| Example: This example retrieves the curve to smooth object of the
| hybShpCurveSmooth in Curve.
|
| Dim Curve as CATIAReference
| Curve = hybShpCurvePar.CurveToSmooth
:return: Reference
:rtype: Reference<|endoftext|> |
4249b501c2d28c2ac57e90478efb04903545027264d8d22edeb1ff426d6d76bf | @curve_to_smooth.setter
def curve_to_smooth(self, reference_curve: Reference):
'\n :param Reference reference_curve:\n '
self.hybrid_shape_curve_smooth.CurveToSmooth = reference_curve.com_object | :param Reference reference_curve: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | curve_to_smooth | Luanee/pycatia | 1 | python | @curve_to_smooth.setter
def curve_to_smooth(self, reference_curve: Reference):
'\n \n '
self.hybrid_shape_curve_smooth.CurveToSmooth = reference_curve.com_object | @curve_to_smooth.setter
def curve_to_smooth(self, reference_curve: Reference):
'\n \n '
self.hybrid_shape_curve_smooth.CurveToSmooth = reference_curve.com_object<|docstring|>:param Reference reference_curve:<|endoftext|> |
3198fb7249fe35c1c0edac1a05b6fa4629190d07cf627ac1fd93444f2d9be4ee | @property
def end_extremity_continuity(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property EndExtremityContinuity() As long\n | \n | Returns or sets the continuity condition (curvature, tangency or point)\n | applied to the smoothed curve with regard to the input curve at the end\n | extremity of the input curve.\n | Legal values:\n | \n | 0\n | CATGSMContinuity_Point. continuity in point (C0). \n | 1\n | CATGSMContinuity_Tangency. continuity in tangency\n | (C1).\n | 2\n | CATGSMContinuity_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oContinuity the continuity at the end extremity\n | for the hybShpCurveSmooth hybrid shape feature.\n | \n | oContinuity = hybShpCurveSmooth.EndExtremityContinuity\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.EndExtremityContinuity | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property EndExtremityContinuity() As long
|
| Returns or sets the continuity condition (curvature, tangency or point)
| applied to the smoothed curve with regard to the input curve at the end
| extremity of the input curve.
| Legal values:
|
| 0
| CATGSMContinuity_Point. continuity in point (C0).
| 1
| CATGSMContinuity_Tangency. continuity in tangency
| (C1).
| 2
| CATGSMContinuity_Curvature. continuity in curvature
| (C2).
|
| Example:
| This example retrieves in oContinuity the continuity at the end extremity
| for the hybShpCurveSmooth hybrid shape feature.
|
| oContinuity = hybShpCurveSmooth.EndExtremityContinuity
:return: int
:rtype: int | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | end_extremity_continuity | Luanee/pycatia | 1 | python | @property
def end_extremity_continuity(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property EndExtremityContinuity() As long\n | \n | Returns or sets the continuity condition (curvature, tangency or point)\n | applied to the smoothed curve with regard to the input curve at the end\n | extremity of the input curve.\n | Legal values:\n | \n | 0\n | CATGSMContinuity_Point. continuity in point (C0). \n | 1\n | CATGSMContinuity_Tangency. continuity in tangency\n | (C1).\n | 2\n | CATGSMContinuity_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oContinuity the continuity at the end extremity\n | for the hybShpCurveSmooth hybrid shape feature.\n | \n | oContinuity = hybShpCurveSmooth.EndExtremityContinuity\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.EndExtremityContinuity | @property
def end_extremity_continuity(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property EndExtremityContinuity() As long\n | \n | Returns or sets the continuity condition (curvature, tangency or point)\n | applied to the smoothed curve with regard to the input curve at the end\n | extremity of the input curve.\n | Legal values:\n | \n | 0\n | CATGSMContinuity_Point. continuity in point (C0). \n | 1\n | CATGSMContinuity_Tangency. continuity in tangency\n | (C1).\n | 2\n | CATGSMContinuity_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oContinuity the continuity at the end extremity\n | for the hybShpCurveSmooth hybrid shape feature.\n | \n | oContinuity = hybShpCurveSmooth.EndExtremityContinuity\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.EndExtremityContinuity<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property EndExtremityContinuity() As long
|
| Returns or sets the continuity condition (curvature, tangency or point)
| applied to the smoothed curve with regard to the input curve at the end
| extremity of the input curve.
| Legal values:
|
| 0
| CATGSMContinuity_Point. continuity in point (C0).
| 1
| CATGSMContinuity_Tangency. continuity in tangency
| (C1).
| 2
| CATGSMContinuity_Curvature. continuity in curvature
| (C2).
|
| Example:
| This example retrieves in oContinuity the continuity at the end extremity
| for the hybShpCurveSmooth hybrid shape feature.
|
| oContinuity = hybShpCurveSmooth.EndExtremityContinuity
:return: int
:rtype: int<|endoftext|> |
59351dd1dd9948598173b6618c91f09f1fb55d8ca3a6135c99053e467653e539 | @end_extremity_continuity.setter
def end_extremity_continuity(self, value: int):
'\n :param int value:\n '
self.hybrid_shape_curve_smooth.EndExtremityContinuity = value | :param int value: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | end_extremity_continuity | Luanee/pycatia | 1 | python | @end_extremity_continuity.setter
def end_extremity_continuity(self, value: int):
'\n \n '
self.hybrid_shape_curve_smooth.EndExtremityContinuity = value | @end_extremity_continuity.setter
def end_extremity_continuity(self, value: int):
'\n \n '
self.hybrid_shape_curve_smooth.EndExtremityContinuity = value<|docstring|>:param int value:<|endoftext|> |
42d1b1192e065d7875347aac6dba4a152f42ebe33efbd8c0c31d29813080ddfa | @property
def maximum_deviation(self) -> Length:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property MaximumDeviation() As Length (Read Only)\n | \n | Returns the MaximumDeviation.\n | \n | Example: This example retrieves the MaximumDeviation of the\n | hybShpCurveSmooth in MaximumDeviationVal.\n | \n | Dim MaximumDeviationVal as CATIALength\n | MaximumDeviationVal = hybShpCurvePar.MaximumDeviation\n\n :return: Length\n :rtype: Length\n '
return Length(self.hybrid_shape_curve_smooth.MaximumDeviation) | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property MaximumDeviation() As Length (Read Only)
|
| Returns the MaximumDeviation.
|
| Example: This example retrieves the MaximumDeviation of the
| hybShpCurveSmooth in MaximumDeviationVal.
|
| Dim MaximumDeviationVal as CATIALength
| MaximumDeviationVal = hybShpCurvePar.MaximumDeviation
:return: Length
:rtype: Length | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | maximum_deviation | Luanee/pycatia | 1 | python | @property
def maximum_deviation(self) -> Length:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property MaximumDeviation() As Length (Read Only)\n | \n | Returns the MaximumDeviation.\n | \n | Example: This example retrieves the MaximumDeviation of the\n | hybShpCurveSmooth in MaximumDeviationVal.\n | \n | Dim MaximumDeviationVal as CATIALength\n | MaximumDeviationVal = hybShpCurvePar.MaximumDeviation\n\n :return: Length\n :rtype: Length\n '
return Length(self.hybrid_shape_curve_smooth.MaximumDeviation) | @property
def maximum_deviation(self) -> Length:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property MaximumDeviation() As Length (Read Only)\n | \n | Returns the MaximumDeviation.\n | \n | Example: This example retrieves the MaximumDeviation of the\n | hybShpCurveSmooth in MaximumDeviationVal.\n | \n | Dim MaximumDeviationVal as CATIALength\n | MaximumDeviationVal = hybShpCurvePar.MaximumDeviation\n\n :return: Length\n :rtype: Length\n '
return Length(self.hybrid_shape_curve_smooth.MaximumDeviation)<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property MaximumDeviation() As Length (Read Only)
|
| Returns the MaximumDeviation.
|
| Example: This example retrieves the MaximumDeviation of the
| hybShpCurveSmooth in MaximumDeviationVal.
|
| Dim MaximumDeviationVal as CATIALength
| MaximumDeviationVal = hybShpCurvePar.MaximumDeviation
:return: Length
:rtype: Length<|endoftext|> |
1944aba9c646c675d723255357a0b4bb9075fc64cf51da4c351a585fa9850731 | @property
def maximum_deviation_activity(self) -> bool:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property MaximumDeviationActivity() As boolean\n | \n | Returns or sets the MaximumDeviationActivity.\n | \n | Example: This example retrieves the MaximumDeviationActivity of the\n | hybShpCurveSmooth in MaxActivity .\n | \n | Dim MaxActivity as boolean\n | MaxActivity = hybShpCurvePar.MaximumDeviationActivity\n\n :return: bool\n :rtype: bool\n '
return self.hybrid_shape_curve_smooth.MaximumDeviationActivity | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property MaximumDeviationActivity() As boolean
|
| Returns or sets the MaximumDeviationActivity.
|
| Example: This example retrieves the MaximumDeviationActivity of the
| hybShpCurveSmooth in MaxActivity .
|
| Dim MaxActivity as boolean
| MaxActivity = hybShpCurvePar.MaximumDeviationActivity
:return: bool
:rtype: bool | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | maximum_deviation_activity | Luanee/pycatia | 1 | python | @property
def maximum_deviation_activity(self) -> bool:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property MaximumDeviationActivity() As boolean\n | \n | Returns or sets the MaximumDeviationActivity.\n | \n | Example: This example retrieves the MaximumDeviationActivity of the\n | hybShpCurveSmooth in MaxActivity .\n | \n | Dim MaxActivity as boolean\n | MaxActivity = hybShpCurvePar.MaximumDeviationActivity\n\n :return: bool\n :rtype: bool\n '
return self.hybrid_shape_curve_smooth.MaximumDeviationActivity | @property
def maximum_deviation_activity(self) -> bool:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property MaximumDeviationActivity() As boolean\n | \n | Returns or sets the MaximumDeviationActivity.\n | \n | Example: This example retrieves the MaximumDeviationActivity of the\n | hybShpCurveSmooth in MaxActivity .\n | \n | Dim MaxActivity as boolean\n | MaxActivity = hybShpCurvePar.MaximumDeviationActivity\n\n :return: bool\n :rtype: bool\n '
return self.hybrid_shape_curve_smooth.MaximumDeviationActivity<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property MaximumDeviationActivity() As boolean
|
| Returns or sets the MaximumDeviationActivity.
|
| Example: This example retrieves the MaximumDeviationActivity of the
| hybShpCurveSmooth in MaxActivity .
|
| Dim MaxActivity as boolean
| MaxActivity = hybShpCurvePar.MaximumDeviationActivity
:return: bool
:rtype: bool<|endoftext|> |
f7d5a76027704660718d5175ff2b6deda1b5a1c769d459bca2294c7d1fa4079b | @maximum_deviation_activity.setter
def maximum_deviation_activity(self, value: bool):
'\n :param bool value:\n '
self.hybrid_shape_curve_smooth.MaximumDeviationActivity = value | :param bool value: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | maximum_deviation_activity | Luanee/pycatia | 1 | python | @maximum_deviation_activity.setter
def maximum_deviation_activity(self, value: bool):
'\n \n '
self.hybrid_shape_curve_smooth.MaximumDeviationActivity = value | @maximum_deviation_activity.setter
def maximum_deviation_activity(self, value: bool):
'\n \n '
self.hybrid_shape_curve_smooth.MaximumDeviationActivity = value<|docstring|>:param bool value:<|endoftext|> |
be938229a982aab206cf14f76db161635bec1c77ace91adaa211e5b99906caee | @property
def start_extremity_continuity(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property StartExtremityContinuity() As long\n | \n | Returns or sets the continuity condition (curvature, tangency or point)\n | applied to the smoothed curve with regard to the input curve at the start\n | extremity of the input curve.\n | Legal values:\n | \n | 0\n | CATGSMContinuity_Point. continuity in point (C0). \n | 1\n | CATGSMContinuity_Tangency. continuity in tangency\n | (C1).\n | 2\n | CATGSMContinuity_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oContinuity the continuity at the start extremity\n | for the hybShpCurveSmooth hybrid shape feature.\n | \n | oContinuity = hybShpCurveSmooth.StartExtremityContinuity\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.StartExtremityContinuity | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property StartExtremityContinuity() As long
|
| Returns or sets the continuity condition (curvature, tangency or point)
| applied to the smoothed curve with regard to the input curve at the start
| extremity of the input curve.
| Legal values:
|
| 0
| CATGSMContinuity_Point. continuity in point (C0).
| 1
| CATGSMContinuity_Tangency. continuity in tangency
| (C1).
| 2
| CATGSMContinuity_Curvature. continuity in curvature
| (C2).
|
| Example:
| This example retrieves in oContinuity the continuity at the start extremity
| for the hybShpCurveSmooth hybrid shape feature.
|
| oContinuity = hybShpCurveSmooth.StartExtremityContinuity
:return: int
:rtype: int | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | start_extremity_continuity | Luanee/pycatia | 1 | python | @property
def start_extremity_continuity(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property StartExtremityContinuity() As long\n | \n | Returns or sets the continuity condition (curvature, tangency or point)\n | applied to the smoothed curve with regard to the input curve at the start\n | extremity of the input curve.\n | Legal values:\n | \n | 0\n | CATGSMContinuity_Point. continuity in point (C0). \n | 1\n | CATGSMContinuity_Tangency. continuity in tangency\n | (C1).\n | 2\n | CATGSMContinuity_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oContinuity the continuity at the start extremity\n | for the hybShpCurveSmooth hybrid shape feature.\n | \n | oContinuity = hybShpCurveSmooth.StartExtremityContinuity\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.StartExtremityContinuity | @property
def start_extremity_continuity(self) -> int:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property StartExtremityContinuity() As long\n | \n | Returns or sets the continuity condition (curvature, tangency or point)\n | applied to the smoothed curve with regard to the input curve at the start\n | extremity of the input curve.\n | Legal values:\n | \n | 0\n | CATGSMContinuity_Point. continuity in point (C0). \n | 1\n | CATGSMContinuity_Tangency. continuity in tangency\n | (C1).\n | 2\n | CATGSMContinuity_Curvature. continuity in curvature\n | (C2).\n | \n | Example:\n | This example retrieves in oContinuity the continuity at the start extremity\n | for the hybShpCurveSmooth hybrid shape feature.\n | \n | oContinuity = hybShpCurveSmooth.StartExtremityContinuity\n\n :return: int\n :rtype: int\n '
return self.hybrid_shape_curve_smooth.StartExtremityContinuity<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property StartExtremityContinuity() As long
|
| Returns or sets the continuity condition (curvature, tangency or point)
| applied to the smoothed curve with regard to the input curve at the start
| extremity of the input curve.
| Legal values:
|
| 0
| CATGSMContinuity_Point. continuity in point (C0).
| 1
| CATGSMContinuity_Tangency. continuity in tangency
| (C1).
| 2
| CATGSMContinuity_Curvature. continuity in curvature
| (C2).
|
| Example:
| This example retrieves in oContinuity the continuity at the start extremity
| for the hybShpCurveSmooth hybrid shape feature.
|
| oContinuity = hybShpCurveSmooth.StartExtremityContinuity
:return: int
:rtype: int<|endoftext|> |
c2c7f19714f4940db9e7555cd1e0451900446395723d67af86760945b1a30423 | @start_extremity_continuity.setter
def start_extremity_continuity(self, value: int):
'\n :param int value:\n '
self.hybrid_shape_curve_smooth.StartExtremityContinuity = value | :param int value: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | start_extremity_continuity | Luanee/pycatia | 1 | python | @start_extremity_continuity.setter
def start_extremity_continuity(self, value: int):
'\n \n '
self.hybrid_shape_curve_smooth.StartExtremityContinuity = value | @start_extremity_continuity.setter
def start_extremity_continuity(self, value: int):
'\n \n '
self.hybrid_shape_curve_smooth.StartExtremityContinuity = value<|docstring|>:param int value:<|endoftext|> |
efc937737dbbaff9f5595f2d9420ee90c64b9da6975712850ec54528b614b366 | @property
def support(self) -> Reference:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property Support() As Reference\n | \n | Returns or sets the support of the curve.\n | if Suppport == nothing no support associated to the curve\n | \n | Example: This example retrieves the support of curve to smooth object of\n | the hybShpCurveSmooth in Support.\n | \n | Dim Support as CATIAReference \n | Support = ybShpCurveSmooth.Support\n\n :return: Reference\n :rtype: Reference\n '
return Reference(self.hybrid_shape_curve_smooth.Support) | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Support() As Reference
|
| Returns or sets the support of the curve.
| if Suppport == nothing no support associated to the curve
|
| Example: This example retrieves the support of curve to smooth object of
| the hybShpCurveSmooth in Support.
|
| Dim Support as CATIAReference
| Support = ybShpCurveSmooth.Support
:return: Reference
:rtype: Reference | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | support | Luanee/pycatia | 1 | python | @property
def support(self) -> Reference:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property Support() As Reference\n | \n | Returns or sets the support of the curve.\n | if Suppport == nothing no support associated to the curve\n | \n | Example: This example retrieves the support of curve to smooth object of\n | the hybShpCurveSmooth in Support.\n | \n | Dim Support as CATIAReference \n | Support = ybShpCurveSmooth.Support\n\n :return: Reference\n :rtype: Reference\n '
return Reference(self.hybrid_shape_curve_smooth.Support) | @property
def support(self) -> Reference:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property Support() As Reference\n | \n | Returns or sets the support of the curve.\n | if Suppport == nothing no support associated to the curve\n | \n | Example: This example retrieves the support of curve to smooth object of\n | the hybShpCurveSmooth in Support.\n | \n | Dim Support as CATIAReference \n | Support = ybShpCurveSmooth.Support\n\n :return: Reference\n :rtype: Reference\n '
return Reference(self.hybrid_shape_curve_smooth.Support)<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property Support() As Reference
|
| Returns or sets the support of the curve.
| if Suppport == nothing no support associated to the curve
|
| Example: This example retrieves the support of curve to smooth object of
| the hybShpCurveSmooth in Support.
|
| Dim Support as CATIAReference
| Support = ybShpCurveSmooth.Support
:return: Reference
:rtype: Reference<|endoftext|> |
4a5b08d2515a54114b35a2ee5e9c15ecb9483a79720a23871b8e5328f7b94d2e | @support.setter
def support(self, reference_support: Reference):
'\n :param Reference reference_support:\n '
self.hybrid_shape_curve_smooth.Support = reference_support.com_object | :param Reference reference_support: | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | support | Luanee/pycatia | 1 | python | @support.setter
def support(self, reference_support: Reference):
'\n \n '
self.hybrid_shape_curve_smooth.Support = reference_support.com_object | @support.setter
def support(self, reference_support: Reference):
'\n \n '
self.hybrid_shape_curve_smooth.Support = reference_support.com_object<|docstring|>:param Reference reference_support:<|endoftext|> |
5bc4a1b8d732b54bb3e903b50c71d9c0569b566b6abc9fcfba9eaddced3dd6eb | @property
def tangency_threshold(self) -> Angle:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property TangencyThreshold() As Angle (Read Only)\n | \n | Returns the TangencyThreshold.\n | \n | Example: This example retrieves the curve to smooth object of the\n | hybShpCurveSmooth in AngleThH.\n | \n | Dim Curve as CATIAAngle \n | AngleThH = ybShpCurveSmooth.TangencyThreshold\n\n :return: Angle\n :rtype: Angle\n '
return Angle(self.hybrid_shape_curve_smooth.TangencyThreshold) | .. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property TangencyThreshold() As Angle (Read Only)
|
| Returns the TangencyThreshold.
|
| Example: This example retrieves the curve to smooth object of the
| hybShpCurveSmooth in AngleThH.
|
| Dim Curve as CATIAAngle
| AngleThH = ybShpCurveSmooth.TangencyThreshold
:return: Angle
:rtype: Angle | pycatia/hybrid_shape_interfaces/hybrid_shape_curve_smooth.py | tangency_threshold | Luanee/pycatia | 1 | python | @property
def tangency_threshold(self) -> Angle:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property TangencyThreshold() As Angle (Read Only)\n | \n | Returns the TangencyThreshold.\n | \n | Example: This example retrieves the curve to smooth object of the\n | hybShpCurveSmooth in AngleThH.\n | \n | Dim Curve as CATIAAngle \n | AngleThH = ybShpCurveSmooth.TangencyThreshold\n\n :return: Angle\n :rtype: Angle\n '
return Angle(self.hybrid_shape_curve_smooth.TangencyThreshold) | @property
def tangency_threshold(self) -> Angle:
'\n .. note::\n :class: toggle\n\n CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)\n | o Property TangencyThreshold() As Angle (Read Only)\n | \n | Returns the TangencyThreshold.\n | \n | Example: This example retrieves the curve to smooth object of the\n | hybShpCurveSmooth in AngleThH.\n | \n | Dim Curve as CATIAAngle \n | AngleThH = ybShpCurveSmooth.TangencyThreshold\n\n :return: Angle\n :rtype: Angle\n '
return Angle(self.hybrid_shape_curve_smooth.TangencyThreshold)<|docstring|>.. note::
:class: toggle
CAA V5 Visual Basic Help (2020-07-06 14:02:20.222384)
| o Property TangencyThreshold() As Angle (Read Only)
|
| Returns the TangencyThreshold.
|
| Example: This example retrieves the curve to smooth object of the
| hybShpCurveSmooth in AngleThH.
|
| Dim Curve as CATIAAngle
| AngleThH = ybShpCurveSmooth.TangencyThreshold
:return: Angle
:rtype: Angle<|endoftext|> |
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