corrplot/resources/templates/plugin-schema.json.mustache

{
  "title": "Correlation Plot",
  "maintainer": "Jingcheng Yang",
  "description": "Correlation plots can be used to quickly find insights. It is used to investigate the dependence between multiple variables at the same time and to highlight the most correlated variables in a data table.",
  "logo": "https://store-images.s-microsoft.com/image/apps.30079.0034b9fb-e1fa-4c69-b5b7-de0750ba3098.c645c7e3-2d23-4418-9288-0bd1322b1070.9112ecd7-1c16-4a37-ab49-a5b2c2b61542.png",
  "version": "v0.1.0",
  "readme": "http: //nordata-cdn.oss-cn-shanghai.aliyuncs.com/test.md",
  "tags": [
    "R",
    "Chart"
  ],
  "fields": [
    {
      "key": "corr_vars",
      "dataIndex": "corr_vars",
      "valueType": "select",
      "title": "Correlation Variables",
      "tooltip": "Which variables do you want to analyze?",
      "valueEnum": {{ columns }},
      "fieldProps": {
        "mode": "multiple",
      },
      "formItemProps": {
        "rules": [
          {
            "required": true,
            "message": "Please select several variables."
          }
        ]
      }
    },
    {
      "key": "method",
      "dataIndex": "method",
      "valueType": "select",
      "title": "Method",
      "tooltip": "The visualization method of correlation matrix to be used. Allowed values are square (default), circle.",
      "valueEnum": {
        "square": {
          "text": "Square"
        },
        "circle": {
          "text": "Circle"
        }
      },
      "formItemProps": {
        "initialValue": "square"
      }
    },
    {
      "key": "corr_type",
      "dataIndex": "corr_type",
      "valueType": "select",
      "title": "Correlation Type",
      "tooltip": "full (default), lower or upper display.",
      "valueEnum": {
        "full": {
          "text": "Full"
        },
        "lower": {
          "text": "Lower"
        },
        "upper": {
          "text": "Upper"
        }
      },
      "formItemProps": {
        "initialValue": "full"
      }
    },
    {
      "key": "hc_method",
      "dataIndex": "hc_method",
      "valueType": "select",
      "title": "Cluster Method",
      "tooltip": "The agglomeration method to be used in hclust (see ?hclust).",
      "valueEnum": {
        "ward.D": {
          "text": "ward.D"
        },
        "ward.D2": {
          "text": "ward.D2"
        },
        "single": {
          "text": "single"
        },
        "complete": {
          "text": "complete"
        },
        "average": {
          "text": "average"
        },
        "mcquitty": {
          "text": "mcquitty"
        },
        "median": {
          "text": "median"
        },
        "centroid": {
          "text": "centroid"
        }
      },
      "formItemProps": {
        "initialValue": "complete"
      }
    },
    {
      "key": "hc_order",
      "dataIndex": "hc_order",
      "valueType": "switch",
      "title": "Cluster Ordered",
      "tooltip": "Logical value. If TRUE, correlation matrix will be hc.ordered using hclust function.",
      "formItemProps": {
        "initialValue": true
      }
    },
    {
      "key": "sig_level",
      "dataIndex": "sig_level",
      "valueType": "switch",
      "title": "Cluster Ordered",
      "tooltip": "Significant level, greater than 0 and less than 1."
      "fieldProps": {
        "step": 0.01
      },
      "formItemProps": {
        "initialValue": 0.05
      }
    }
  ],
  "dataKey": {
    "annoData": "Anno",
    "data": "Data"
  },
  "examples": [
    {
      "title": "Example 1",
      "key": "example-1",
      "datafile": "",
      "arguments": {
        "corr_vars": [
          "mpg",
          "cyl",
          "disp",
          "hp",
          "drat",
          "wt",
          "qsec",
          "vs",
          "am",
          "gear",
          "carb"
        ],
        "sig_level": 0.05,
        "hc_order": true,
        "hc_method": "complete",
        "corr_type": "full",
        "method": "square"
      }
    }
  ]
}