def setUp(self):
# Set up a mock set of tableData similar to the Qt table with 3 rows
self.tableData = [
['0.6', '0.3', '0.9', '5750', '23'],
['', '', '', '5930', '24'],
['', '', '', '5850', '24'],
['', '', '', '5950', '25'],
['1', '0.5', '1.5', '3650', '30'],
['', '', '', '3690', '30'],
['', '', '', '3670', '30'],
['', '', '', '3710', '30'],
['1.6', '0.8', '2.4', '1462', '31'],
['', '', '', '1820', '31'],
['', '', '', '1787', '31'],
['', '', '', '1840', '31']
]
self.rowCount = len(self.tableData)
# Set up test for both types of arrays to calculate apparentResistivity
voltageSpacing, meanVoltage, meanCurrent = aggregateTable(
self.tableData, self.rowCount)
self.voltageSpacing = voltageSpacing
self.meanVoltage = meanVoltage
self.meanCurrent = meanCurrent
self.Vm = self.meanVoltage
self.I = self.meanCurrent
def aggregateTableForPlot(self):
"""Apply the aggregation function and assign the outputs to the class
Notes
-----
This method assures that the voltageSpacing, meanVoltage, and
meanCurrent properties are up to date with the table
"""
voltageSpacing, meanVoltage, meanCurrent = aggregateTable(
self.model.table)
self.voltageSpacing = voltageSpacing
self.meanVoltage = meanVoltage
self.meanCurrent = meanCurrent
from aggregate import aggregateTable
schlumberferFilterCoefficients, wennerFilterCoefficients = coefficients
sampleInterval = np.log(10) / 3.
# Print out the table that is the "input" table from the field survey
print('Schlumberger example:')
time.sleep(sleep_time)
print('This is the starting table:')
for row in tableData:
print(row)
# Aggregate the table to get the mean voltage and current
voltageSpacing, meanVoltage, meanCurrent = aggregateTable(
tableData)
# Print out the aggregated values
print('\nVoltage Spacing: {}\nMean Voltage: {}'.format(
voltageSpacing, meanVoltage))
print('Mean Current: {}'.format(meanCurrent))
# Use the modified Schlumberger equation like that used in the spreadsheet
apparentResistivity = schlumbergerResistivityModified(
voltageSpacing, meanVoltage, meanCurrent)
print('\nApparent resistivity (same formula as ' +
'spreadsheet for Schlum):\n{}'.format(apparentResistivity))
# Interpolate the field data to get values at Gosh's suggested intervals
voltageSpacingExtrapolated, newRestivity = interpolateFieldData(
voltageSpacing, apparentResistivity, 'schlumberger')
print('\nNew Resitivity values:\n{}'.format(newRestivity))
