Web interface for uploading results

GradientOne has two types of result entries:

• Result entries typically come from  contain time-series plottable data in a channels object, as well as individual pieces of metadata, such as the instrument type, config values and timebase range:

{
  "info": {
    "instrument_type": "RigolDS1054Z",
    "channels": [
      {
        "name": "chan1",
        "start_time": 0,
        "enabled": true,
        "trigger_level": 1.52,
        "offset": 0.48,
        "time_step": 4e-07,
        "y_values": [
          0.0438,
          0,
          0.0438,
          ...
        ],
        "coupling": "dc"
      },
      ...
    ],
    "config_excerpt": {
      "timebase": {
        "position": 0
      },
      "enabled_list": [
        "chan1",
        "chan2"
      ],
      "channels": [
        {
          "name": "chan1",
          "enabled": true,
          "range": 8,
          "offset": 0.48,
          "input_impedance": 1000000,
          "coupling": "dc"
        },
        ...
      ],
      "trigger_edge_slope": "positive",
      "trigger": {
        "source": "chan1",
        "type": "edge",
        "coupling": "dc",
        "level": 1.52
      },
      "acquisition": {
        "record_length": 6000,
        "start_time": -0.0012,
        "time_per_record": 0.0024,
        "type": "normal",
        "number_of_averages": 2
      }
    },
    "timebase_scale": 0.0002,
    "h_divs": 12,
    "slice_length": 6000,
    "timebase_range": 0.0024,
    "num_of_slices": 1
  },
  "slice_length": 6000,
  "timebase_range": 0.0024,
  "num_of_slices": 1,
  "date_created": "2017-12-15T17:50:36.042800Z",
  ...
}

• Meta Result entries are generated by running a Meta Analysis. Metadata will be compiled into a dataframe object, where metadata are grouped into lists:

{
  "info": {
    "dataframe": {
      "instrument_type": [
        "RigolDS1054Z",
        "RigolDS1054Z",
        ...
      ],
      "slice_length": [
        6000,
        5000,
        ...
      ],
      "date_created": [
        "2017-12-15T17:50:36.042800Z",
        "2017-12-15T12:30:26.000000Z",
        ...
      ],
      ...
    }
  }
}

With the Result entities, you can visualize and perform measurements in the timeseries data, such as looking forpatterns in data, measuring rise/fall times, and pass/fail criteria.

With the Meta Results entries, you can look for explanations as to how the presence of these patterns, or the rise/fall times, or the configuration information affects whether the result passed or failed by some other criteria. For example, it might be that the presence of a peak at a specific location in the timeseries is correlated with failure, or that failed results are more likely to come from a specific test rig.

In addition to collecting data from GradientOne-integrated testrigs, you can upload data through the GradientOne web interface. To access it, go to /uploads. We support data in JSON, xls, xlsx and csv format. In JSON, the data must be either in the info/channels format, either as a single object or in an array of multiple objects. 

After adding a supported file, the page will attempt to interpret the data:

By default, the file will be iterpreted as being a table where every row is a the metadata of a single entry. In this example, Result 1 will be uploaded as:

"info": {
    "Average Cell Current (mA)": 4.8,
    "Average Cell Gain (dB)": 3.1,
    "Result": "Pass",
    "Max Cell Temperature (C)": 0.2,
    "Average Cell Temperature (C)": 1.6
},

If you instead select Rows are channels of a single result, the data will be uploaded as a single result, where Channel 1 is row 1:

{
  "info": {
    "channels": [
      {
        "name": 0,
        "y_values": [
          1.4,
          5.1,
          0.2,
          ...
        ]
      },
      {
        "name": 1,
        "y_values": [
          1.4,
          4.9,
          0.2,
          ...
        ]
      },
      ...
    ]
  }
}

If you instead select Rows are single channels of multiple results, the data will be uploaded as multiple results, where Result 1 is row 1:

{
  "info": {
    "channels": [
      {
        "name": 0,
        "y_values": [
          1.4,
          5.1,
          0.2,
          ...
        ]
      }
    ]
  }
}

Result 2 will be: 

  "info": {
    "channels": [
      {
        "name": 0,
        "y_values": [
          1.4,
          4.9,
          0.2,
          ...
        ]
      }
    ]
  }
}

If you select any of the Columns options, the columns will be painted the same instead of the rows:

If you select Columns are result metadata entries, Result 1 will be:

{
    "info": {
        0: 1.4,
        1: 1.4,
        2: 1,3,
        ...
    }
}

If you select Columns are channels of a single result, only one result will be created:

{
    "info": {
        "channels": [
            {"name": "Number", 
             "y_values": [0, 1, 2, ...]},
            {"name": "Average Cell Temperature", 
             "y_values": [1.4, 1.4, 1.3, ...]},
            ...
        ]
    }
}

If you select Columns are the single channels of multiple results, then Result 1 will be:

{
    "info": {
        "channels": [
            {"name": "Number", 
             "y_values": [0, 1, 2, ...]},
        ]
    }
}

and Result 2 will be:

{
    "info": {
        "channels": [
            {"name": "Average Cell Temperature", 
             "y_values": [1.4, 1.4, 1.3, ...]}
        ]
    }
}

Make sure that you add a config name so that you can find your uploaded results later. Click Submit when ready. After uploading, links to the generated results will appear in the Link column.