GetUnitConversions

Export the Young's Modulus in the Metric system for a record

import pandas

import GRANTA_MIScriptingToolkit as gdl

session = gdl.GRANTA_MISession("http://my.server.name/mi_servicelayer/", autoLogon=True, receiveTimeout=5000)
db_key = "MI_Training"
table_name = "Tensile Test Data"

import_service = session.dataImportService
browse_service = session.browseService
export_service = session.dataExportService

partial_table_ref = gdl.PartialTableReference(tableName=table_name)

modfied_record_guid = "4269f1bc-df6b-4a6d-870c-ef931728f37b"
modified_record_ref = gdl.RecordReference(DBKey=db_key, recordGUID=modfied_record_guid)

attribute_name = "Young's Modulus (11-axis)"
unit_context_metric = gdl.UnitConversionContext(unitSystem="Metric")

modulus_attribute_ref = gdl.AttributeReference(
    name=attribute_name,
    DBKey=db_key,
    partialTableReference=partial_table_ref,
)
export_request = gdl.GetRecordAttributesByRefRequest(
    recordReferences=[modified_record_ref],
    attributeReferences=[modulus_attribute_ref],
)

exported_data = export_service.GetRecordAttributesByRef(export_request).recordData
modulus_value = [[a.pointDataType.points[0].value for a in r.attributeValues] for r in exported_data][0][0]
modulus_metric_symbol = [[a.pointDataType.unitSymbol for a in r.attributeValues] for r in exported_data][0][0]
print(f"Young's modulus = {modulus_value} {modulus_metric_symbol}")

Previous cell output:

Young's modulus = 174.0004272460938 GPa

Now let's convert its value with all available conversions in Granta MI

unit_conversions_request = gdl.GetUnitConversionsRequest(
    DBKey=db_key,
    unitSymbols=[modulus_metric_symbol],
)

source_units = browse_service.GetUnitConversions(unit_conversions_request).sourceUnits
conversion_targets = [c.conversions for c in source_units]
factors_and_offsets = [[(c.factor, c.offset) for c in c_target] for c_target in conversion_targets][0]
symbols = [[c.targetSymbol for c in c_target] for c_target in conversion_targets][0]
results = [modulus_value * factor + offset for factor, offset in factors_and_offsets]
equations = [f"{modulus_value} * {factor} + {offset}" for factor, offset in factors_and_offsets]

factors, offsets = zip(*factors_and_offsets)
df = pandas.DataFrame([factors, offsets, equations, results])
df_flipped = df.transpose()
df_flipped.columns = ["factor", "offset", "equation", "converted result"]
df_flipped.index = symbols
df_flipped.style