{
  "__type": "IngestedDoc",
  "__tag": 4010,
  "_content": {
    "Notes": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "The weights "
            },
            {
              "__type": "InlineRole",
              "__tag": 4003,
              "value": "wd",
              "domain": null,
              "role": null,
              "inventory": null
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " and "
            },
            {
              "__type": "InlineRole",
              "__tag": 4003,
              "value": "we",
              "domain": null,
              "role": null,
              "inventory": null
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " are computed from provided values as follows:"
            }
          ]
        },
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "sx"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " and "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "sy"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " are converted to weights by dividing 1.0 by their squares. For example, "
            },
            {
              "__type": "InlineCode",
              "__tag": 4051,
              "value": "wd = 1./np.power(`sx`, 2)"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "."
            }
          ]
        },
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "covx"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " and "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "covy"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " are arrays of covariance matrices and are converted to weights by performing a matrix inversion on each observation's covariance matrix. For example, "
            },
            {
              "__type": "InlineCode",
              "__tag": 4051,
              "value": "we[i] = np.linalg.inv(covy[i])"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "."
            }
          ]
        },
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "These arguments follow the same structured argument conventions as wd and we only restricted by their natures: "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "sx"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " and "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "sy"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " can't be rank-3, but "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "covx"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " and "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "covy"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " can be."
            }
          ]
        },
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "Only set "
            },
            {
              "__type": "Emphasis",
              "__tag": 4047,
              "children": [
                {
                  "__type": "Text",
                  "__tag": 4046,
                  "value": "either"
                }
              ]
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "sx"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " or "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "covx"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " (not both). Setting both will raise an exception. Same with "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "sy"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": " and "
            },
            {
              "__type": "ParamRef",
              "__tag": 4071,
              "name": "covy"
            },
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "."
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Warns": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Raises": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Yields": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Methods": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Returns": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Summary": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Paragraph",
          "__tag": 4045,
          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "The data, with weightings as actual standard deviations and/or covariances."
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Receives": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Warnings": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Attributes": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    },
    "Parameters": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Parameters",
          "__tag": 4026,
          "children": [
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "x",
              "annotation": "array_like",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Observed data for the independent variable of the regression"
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "y",
              "annotation": "array_like, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "If array-like, observed data for the dependent variable of the regression. A scalar input implies that the model to be used on the data is implicit."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "sx",
              "annotation": "array_like, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Standard deviations of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "x"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": ". "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "sx"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " are standard deviations of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "x"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " and are converted to weights by dividing 1.0 by their squares."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "sy",
              "annotation": "array_like, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Standard deviations of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "y"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": ". "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "sy"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " are standard deviations of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "y"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " and are converted to weights by dividing 1.0 by their squares."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "covx",
              "annotation": "array_like, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Covariance of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "x"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "covx"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " is an array of covariance matrices of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "x"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " and are converted to weights by performing a matrix inversion on each observation's covariance matrix."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "covy",
              "annotation": "array_like, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Covariance of "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "y"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "covy"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " is an array of covariance matrices and are converted to weights by performing a matrix inversion on each observation's covariance matrix."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "fix",
              "annotation": "array_like, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "The argument and member fix is the same as Data.fix and ODR.ifixx: It is an array of integers with the same shape as "
                    },
                    {
                      "__type": "ParamRef",
                      "__tag": 4071,
                      "name": "x"
                    },
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": " that determines which input observations are treated as fixed. One can use a sequence of length m (the dimensionality of the input observations) to fix some dimensions for all observations. A value of 0 fixes the observation, a value > 0 makes it free."
                    }
                  ]
                }
              ]
            },
            {
              "__type": "DocParam",
              "__tag": 4016,
              "name": "meta",
              "annotation": "dict, optional",
              "desc": [
                {
                  "__type": "Paragraph",
                  "__tag": 4045,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "Free-form dictionary for metadata."
                    }
                  ]
                }
              ]
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Extended Summary": {
      "__type": "Section",
      "__tag": 4015,
      "children": [
        {
          "__type": "Admonition",
          "__tag": 4056,
          "kind": "deprecated",
          "base_type": "neutral",
          "children": [
            {
              "__type": "AdmonitionTitle",
              "__tag": 4055,
              "children": [
                {
                  "__type": "Text",
                  "__tag": 4046,
                  "value": "deprecated 1.17.0"
                }
              ]
            },
            {
              "__type": "Paragraph",
              "__tag": 4045,
              "children": [
                {
                  "__type": "CrossRef",
                  "__tag": 4002,
                  "value": "scipy.odr",
                  "reference": {
                    "__type": "LocalRef",
                    "__tag": 4022,
                    "kind": "module",
                    "path": "scipy.odr"
                  },
                  "kind": "module"
                },
                {
                  "__type": "Text",
                  "__tag": 4046,
                  "value": " is deprecated and will be removed in SciPy 1.19.0. Please use "
                },
                {
                  "__type": "Link",
                  "__tag": 4049,
                  "children": [
                    {
                      "__type": "Text",
                      "__tag": 4046,
                      "value": "pypi.org/project/odrpack/"
                    }
                  ],
                  "url": "https://pypi.org/project/odrpack/",
                  "title": ""
                },
                {
                  "__type": "Text",
                  "__tag": 4046,
                  "value": " instead."
                }
              ]
            }
          ]
        }
      ],
      "title": [],
      "level": 0,
      "target": null
    },
    "Other Parameters": {
      "__type": "Section",
      "__tag": 4015,
      "children": [],
      "title": [],
      "level": 0,
      "target": null
    }
  },
  "_ordered_sections": [
    "Summary",
    "Extended Summary",
    "Parameters",
    "Attributes",
    "Methods",
    "Returns",
    "Yields",
    "Receives",
    "Other Parameters",
    "Raises",
    "Warns",
    "Warnings",
    "Notes"
  ],
  "item_file": "/scipy/odr/_odrpack.py",
  "item_line": 320,
  "item_type": "class",
  "aliases": [
    "scipy.odr.RealData"
  ],
  "example_section_data": {
    "__type": "Section",
    "__tag": 4015,
    "children": [],
    "title": [],
    "level": 0,
    "target": null
  },
  "see_also": [],
  "signature": {
    "__type": "SignatureNode",
    "__tag": 4029,
    "kind": "function",
    "parameters": [
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "x",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": {
          "__type": "Empty",
          "__tag": 4031
        }
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "y",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "sx",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "sy",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "covx",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "covy",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "fix",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      },
      {
        "__type": "SigParam",
        "__tag": 4030,
        "name": "meta",
        "annotation": {
          "__type": "Empty",
          "__tag": 4031
        },
        "kind": "POSITIONAL_OR_KEYWORD",
        "default": "None"
      }
    ],
    "return_annotation": {
      "__type": "Empty",
      "__tag": 4031
    },
    "target_name": "RealData"
  },
  "references": null,
  "qa": "scipy.odr._odrpack:RealData",
  "arbitrary": [],
  "local_refs": [
    "covx",
    "covy",
    "fix",
    "meta",
    "sx",
    "sy",
    "x",
    "y"
  ]
}