def makeTestSection(test, details, images):
section = ""
section += mdHeader(3, "Test: " + test)
section += mdBlock(details)
section += mdBlock(
images.generateTable(columns=2, directory=str(project)))
return section
def output_table(args):
# if True: return
project = Path(RAWDATA) / args.project
print('\n\n## Summary Table \n\n')
summary_table = args.state.summaryTable.generateTable().format()
print(summary_table)
## Make summary markdown
summaryFile = "test_summary_table.md"
summarySections = (
mdHeader(1, "Meniscus Fatigue Expr 1 - Pretrial"),
mdBlock('\n\n\n'),
mdHeader(2, "Summary Table"),
mdBlock(summary_table),
mdBlock('\n\nDone...\n\n'),
)
# writeImageTable(project, summaryFile, summarySections, writemode='w')
## Make images markdown
# imagesMarkdown = os.sep.join(RAWDATA,args.project,"test_all_images.md")
# writeImageTable(args, imagesMarkdown)
testDetails, testImages = args.state.testDetails, args.state.testImages
def makeTestSection(test, details, images):
section = ""
section += mdHeader(3, "Test: " + test)
section += mdBlock(details)
section += mdBlock(
images.generateTable(columns=2, directory=str(project)))
return section
testSections = (makeTestSection(test, details, images) for (
test,
details), (_, images) in zip(testDetails.items(), testImages.items()))
import itertools
writeImageTable(project,
summaryFile,
itertools.chain(summarySections, testSections),
writemode='w')
print(subprocess.call(['open', '-a', 'Marked',
str(project / summaryFile)]))
def handler(testconf, excelfile, args):
def updateMetaData(data):
## Handle Names
data['name'] = testconf.info.name
data['id'] = testconf.info.short
data['info'] = testconf.info._asdict()
assert excelfile.exists()
## Update with Excel Values
data = parse_data_from_worksheet(
parser_data_sheet_excel=args.parser_data_sheet_excel,
testpath=excelfile,
testconf=testconf,
args=args,
)
print(mdBlock("Excel Sheet Data:"))
rows = [(k, v) for k, v in flatten(data).items()]
rows = sorted(rows)
# print()
# print(HTML(tabulate.tabulate( rows, [ "Key", "Value", ], tablefmt ='html' )))
# print(mdBlock("<pre>\n"+json.dumps(data,indent=4)+"\n</pre>"))
updateMetaData(data)
# excel_data = DataTree(notes=data.pop("notes"), other=data.pop("other"))
json_data = collections.OrderedDict(sorted(data.items()))
testconf.folder.save_calculated_json_raw(test=testconf,
name='excel',
json_data=json_data,
overwrite=True)
def handler(testconf, excelfile, args):
def updateMetaData(data):
## Handle Names
data['name'] = testconf.info.name
data['id'] = testconf.info.short
data['info'] = testconf.info._asdict()
assert excelfile.exists()
## Update with Excel Values
data = parse_data_from_worksheet(
parser_data_sheet_excel=args.parser_data_sheet_excel,
testpath=excelfile,
testconf=testconf,
args=args,
)
print(mdBlock("Excel Sheet Data:"))
rows = [ (k,v) for k,v in flatten(data).items() ]
rows = sorted(rows)
# print()
# print(HTML(tabulate.tabulate( rows, [ "Key", "Value", ], tablefmt ='html' )))
# print(mdBlock("<pre>\n"+json.dumps(data,indent=4)+"\n</pre>"))
updateMetaData(data)
# excel_data = DataTree(notes=data.pop("notes"), other=data.pop("other"))
json_data = collections.OrderedDict(sorted(data.items()))
testconf.folder.save_calculated_json_raw(test=testconf, name='excel',json_data=json_data, overwrite=True)
def guitestprocess(testinfodict, fs, args, logFileNames):
with setupStdFiles(*logFileNames) as logging: # setup for logging output!
try:
from scilab.tools.project import DataTree, debug
from scilab.tools import testingtools
import scilab.datahandling.dataprocessor as dataprocessor
from scilab.expers.configuration import FileStructure, generatetestinfoclass
print("### Processing ")
TestInfo = generatetestinfoclass(
**fs.projdesc["experiment_config"]["testinfo"])
testinfo = TestInfo(**testinfodict)
debug(testinfo)
test = DataTree()
test.data = DataTree()
test.info = testinfo
test.folder = fs.testfolder(testinfo=test.info,
ensure_folders_exists=False)
debug(list(test.keys()), fs, args)
expertype = fs.projdesc["experiment_config"]["type"]
if expertype == "cycles":
import scilab.expers.mechanical.fatigue.cycles as exper
elif expertype == "uts":
import scilab.expers.mechanical.fatigue.uts as exper
else:
raise ValueError("Do not know how to process test type.",
expertype)
args.parser_data_sheet_excel = exper.parser_data_sheet_excel
args.parser_image_measurements = exper.parser_image_measurements
args.codehandlers = exper.getcodehandlers()
if not fs or not test or not args:
debug(fs, test, args)
logging.warning("Cannot execute test! Empty arguments ")
return
if not 'data' in test:
test.data = DataTree()
dataprocessor.execute(fs=fs,
name=test.info.name,
testconf=test,
args=args)
print(mdBlock("<p>\n# Done #</p>"))
except Exception as err:
print("\n<br>\n[Error]\n<br>\n", flush=True)
print("Exception:\n", repr(err))
print("Traceback:\n", traceback.format_exc())
logging.exception(err)
def guitestprocess(testinfodict, fs, args, logFileNames):
with setupStdFiles(*logFileNames) as logging: # setup for logging output!
try:
from scilab.tools.project import DataTree, debug
from scilab.tools import testingtools
import scilab.datahandling.dataprocessor as dataprocessor
from scilab.expers.configuration import FileStructure, generatetestinfoclass
print("### Processing ")
TestInfo = generatetestinfoclass(**fs.projdesc["experiment_config"]["testinfo"])
testinfo = TestInfo(**testinfodict)
debug(testinfo)
test = DataTree()
test.data = DataTree()
test.info = testinfo
test.folder = fs.testfolder(testinfo=test.info, ensure_folders_exists=False)
debug(list(test.keys()), fs, args)
expertype = fs.projdesc["experiment_config"]["type"]
if expertype == "cycles":
import scilab.expers.mechanical.fatigue.cycles as exper
elif expertype == "uts":
import scilab.expers.mechanical.fatigue.uts as exper
else:
raise ValueError("Do not know how to process test type.", expertype)
args.parser_data_sheet_excel = exper.parser_data_sheet_excel
args.parser_image_measurements = exper.parser_image_measurements
args.codehandlers = exper.getcodehandlers()
if not fs or not test or not args:
debug(fs, test, args)
logging.warning("Cannot execute test! Empty arguments ")
return
if not 'data' in test:
test.data = DataTree()
dataprocessor.execute(fs=fs, name=test.info.name, testconf=test, args=args )
print(mdBlock("<p>\n# Done #</p>"))
except Exception as err:
print("\n<br>\n[Error]\n<br>\n", flush=True)
print("Exception:\n", repr(err))
print("Traceback:\n", traceback.format_exc())
logging.exception(err)
def handler(testconf, excelfile, args):
# print(mdHeader(3, ": {}",testconf.info.name))
def updateMetaData(data):
## Handle Names
data['name'] = testconf.info.name
data['id'] = testconf.info.short
data['info'] = testconf.info.as_dict()
debug(testconf.folder.jsoncalc.as_posix())
# print(str(testconf.info), file=args.report)
## Update with Excel Values
data = parse_data_from_worksheet(
testpath=excelfile,
testconf=testconf,
args=args,
)
print(mdBlock("Excel Sheet Data:"))
rows = [(k, v) for k, v in flatten(data).items()]
rows = sorted(rows)
print()
print(HTML(tabulate.tabulate(rows, [
"Key",
"Value",
], tablefmt='html')))
# print(mdBlock("<pre>\n"+json.dumps(data,indent=4)+"\n</pre>"))
updateMetaData(data)
# excel_data = DataTree(notes=data.pop("notes"), other=data.pop("other"))
json_data = collections.OrderedDict(sorted(data.items()))
testconf.folder.save_calculated_json_raw(test=testconf,
name='excel',
json_data=json_data,
overwrite=True)
## Update with Image Measurements
data = parse_from_image_measurements(testconf=testconf, args=args)
updateMetaData(data)
testconf.folder.save_calculated_json_raw(test=testconf,
name='measurements',
json_data=data,
overwrite=True)
return
def handler(testconf, excelfile, args):
# print(mdHeader(3, ": {}",testconf.info.name))
def updateMetaData(data):
## Handle Names
data['name'] = testconf.info.name
data['id'] = testconf.info.short
data['info'] = testconf.info.as_dict()
debug(testconf.folder.jsoncalc.as_posix())
# print(str(testconf.info), file=args.report)
## Update with Excel Values
data = parse_data_from_worksheet(
testpath=excelfile,
testconf=testconf,
args=args,
)
print(mdBlock("Excel Sheet Data:"))
rows = [ (k,v) for k,v in flatten(data).items() ]
rows = sorted(rows)
print()
print(HTML(tabulate.tabulate( rows, [ "Key", "Value", ], tablefmt ='html' )))
# print(mdBlock("<pre>\n"+json.dumps(data,indent=4)+"\n</pre>"))
updateMetaData(data)
# excel_data = DataTree(notes=data.pop("notes"), other=data.pop("other"))
json_data = collections.OrderedDict(sorted(data.items()))
testconf.folder.save_calculated_json_raw(test=testconf, name='excel',json_data=json_data, overwrite=True)
## Update with Image Measurements
data = parse_from_image_measurements(
testconf=testconf,
args=args)
updateMetaData(data)
testconf.folder.save_calculated_json_raw(test=testconf, name='measurements',json_data=data, overwrite=True)
return
def print_csv_data(testinfo, testfolder, details, report):
fatigue_data = """
Short Name,set,location,sample,Test Name,Level,Area,DM3,Pred UTS,Orient,Cycles (1st Quartile),Cycles (4th Quartile),UTS Load,Max Strain
1002-1LG-1001,1002,1LG,1001,,90%,0.788,120.33,12.635,,29,39,,
1002-1LG-701,1002,1LG,701,,60%,1.13,160.73,17.66,LG,972,975,,
1002-1LG-702,1002,1LG,702,,70%,1.466,141.22,15.716,,,,25,
1002-1LG-902,1002,1LG,902,,80%,0.931,136.98,15.293,LG,104,105,,
1002-1TR-601,1002,1TR,601,,60%,0.16894,5.563,0.5,,,,2.1,
1002-1TR-602,1002,1TR,602,,70%,1.1296,12.035,5.4,,11,12,,
1002-1TR-603,1002,1TR,603,,70%,1.02,5.433,1.056,,,,1.7,
1002-1TR-801,1002,1TR,801,,80%,0.7912,5.319,1.016,,3790,3791,,
1006-1TR-501,1006,1TR,501,,90%,0.713,4.942,0.884,,,,,
1006-1TR-502,1006,1TR,502,,80%,0.555,4.72,0.644,,1,21,,
1006-1TR-701,1006,1TR,701,,70%,0.786,8.083,1.39,,1597,1598,,
1006-1TR-702,1006,1TR,702,,60%,0.701,10.939,2.988,,6620,6630,,
1009-1LG-1002,1009,1LG,1002,jan10(gf10.9-llm)-wa-lg-l10-x2,60%,1.02,133.97,14.994,LG,,,14,
1009-1LG-1003,1009,1LG,1003,jan10(gf10.9-llm)-wa-lg-l10-x3,70%,0.72,156.2,17.208,LG,98,99,,
1009-1LG-1201,1009,1LG,1201,jan10(gf10.9-llm)-wa-lg-l12-x1,80%,1.2,192.6,20.83,LG,,,38,
1009-1LG-1202,1009,1LG,1202,jan10(gf10.9-llm)-wa-lg-l12-x2,90%,1.36,118.05,13.407,LG,184,185,,
1009-1LG-1203,1009,1LG,1203,jan10(gf10.9-llm)-wa-lg-l12-x3,80%,1.1,97.07,11.317,LG,559,560,,
1009-1TR-1101,1009,1TR,1101,,70%,0.79,9.742,2.568,,,,5,
1009-1TR-1102,1009,1TR,1102,,60%,1.02,9.632,2.529,,,,6.7,
1009-1TR-902,1009,1TR,902,,90%,0.87,7.029,1.615,,,,3.4,
1009-1TR-903,1009,1TR,903,,90%,0.88,14.487,4.233,,1,1,,
1104-1LG-501,1104,1LG,501,jan11(gf11.4-llm)-wa-lg-l5-x1,90%,1.1,113.96,12.99,LG,1,17,,
1104-1LG-502,1104,1LG,502,jan11(gf11.4-llm)-wa-lg-l5-x2,80%,1.56,64.166,8.03,LG,102,126,,
1104-1LG-701,1104,1LG,701,jan11(gf11.4-llm)-wa-lg-l7-x1,70%,1.26,207.92,22.361,LG,,,12,
1104-1LG-702,1104,1LG,702,jan11(gf11.4-llm)-wa-lg-l7-x2,60%,1.26,113.76,12.98,LG,,,12,
1105-1LG-601,1105,1LG,601,jan11(gf11.5-llm)-wa-lg-l6-x1,60%,0.88,250.89,26.642,LG,,,24,
1105-1LG-602,1105,1LG,602,jan11(gf11.5-llm)-wa-lg-l6-x2,70%,0.93,171.9,18.772,LG,198,199,,
1105-1LG-801,1105,1LG,801,jan11(gf11.5-llm)-wa-lg-l8-x1,80%,1.23,19.789,19.789,LG,751,752,,
1105-1LG-802,1105,1LG,802,jan11(gf11.5-llm)-wa-lg-l8-x2,90%,1.81,143.35,15.928,LG,25,26,,
1105-1TR-501,1105,1TR,501,,90%,0.52,8.92,2.279,,104,105,,
1105-1TR-502,1105,1TR,502,,80%,0.38,7.899,1.921,,7,8,,
1105-1TR-701,1105,1TR,701,,70%,0.67,11.912,3.329,,16,18,,
1105-1TR-702,1105,1TR,702,,60%,0.629,8.977,2.3,,143,145,,
"""
def values(v):
try:
return int(v)
except:
try:
return float(v)
except:
return v
fatigue_header, *fatigue_rows = [ l.strip().split(',') for l in fatigue_data.strip().split('\n') ]
# debug(fatigue_header)
fatigue_dicts = [ { k:values(i) for k,i in zip(fatigue_header, r) } for r in fatigue_rows ]
fatigue_dicts = DataTree(**{ r['Short Name']:r for r in fatigue_dicts })
# debug(fatigue_dicts)
print(mdHeader(3, "CSV Data" ), file=report)
# KeyError: "Key 'elapsedStep' not found in: step, loadLinearLoad1Maximum, displacementLinearDigitalPositionMinimum, rotationRotaryRotationMinimum, torqueRotaryTorqueMinimum, rotationRotaryRotationMaximum, torqueRotaryTorqueMaximum, indices, positionLinearPositionMaximum, rotaryDisplacementRotaryDigitalRotationMaximum, rotaryDisplacementRotaryDigitalRotationMinimum, loadLinearLoadMaximum, loadLinearLoad1Minimum, elapsedCycles, pc|frequency, _matrix, _InstronMatrixData__slices, displacementLinearDigitalPositionMaximum, totalCycles, loadLinearLoadMinimum, positionLinearPositionMinimum, pc|cycleStartTime"
if testinfo.orientation == 'lg':
trendsfolder = testfolder.raws.cycles_lg_csv
loads = ['loadLinearLoadMaximum','loadLinearLoadMinimum']
loadsTracking = 'loadLinearLoad'
elif testinfo.orientation == 'tr':
trendsfolder = testfolder.raws.cycles_tr_csv
loads = ['loadLinearLoad1Maximum','loadLinearLoad1Maximum']
loadsTracking = 'loadLinearLoad1'
debug(testinfo.short, trendsfolder)
if not trendsfolder.trends or not trendsfolder.trends.exists():
print("Error: couldn't find trend files! (%s)"%(str(testinfo),), file=report)
return
trends = csvread(str(trendsfolder.trends))
indicies = trends._getslices('step')
debug(indicies)
sl_fatigue = indicies[5]
# sl_uts = indicies[7]
def fmt(name, N=-25, O=-1):
if hasattr(name, '__call__'):
return name(trends, N, O)[1]
return trends[name].array[N:O]
columns = [
'elapsedCycles',
'step',
'displacementLinearDigitalPositionMinimum',
'displacementLinearDigitalPositionMaximum',
lambda x,N,O: ('Min Strain', x['displacementLinearDigitalPositionMinimum'].array[N:O]/details.gauge.value),
lambda x,N,O: ('Max Strain', x['displacementLinearDigitalPositionMaximum'].array[N:O]/details.gauge.value),
]+loads
def short(name, N=-1, O=-1):
if hasattr(name, '__call__'):
return name(trends, N, O)[0]
return name.replace('Linear', '').replace('displacement', 'disp').replace('DigitalPosition','')
fatigue_dict = fatigue_dicts.get(testinfo.short,None)
quartile1 = 'Cycles (1st Quartile)'
quartile4 = 'Cycles (4th Quartile)'
print(mdBlock("Fatigue Data:"+str(fatigue_dict)), file=report)
if fatigue_dict and fatigue_dict[quartile4]:
startEndCycleIdx = find_index(fatigue_dict[quartile1], trends['elapsedCycles'].array[sl_fatigue])
lastCycleIdx = find_index(fatigue_dict[quartile4], trends['elapsedCycles'].array[sl_fatigue])
N, O = startEndCycleIdx-1, lastCycleIdx
if not lastCycleIdx:
debug(trends['elapsedCycles'].array[sl_fatigue])
debug(startEndCycleIdx, lastCycleIdx, N, O)
lastCycleMaxPosition = (trends['displacementLinearDigitalPositionMaximum'].array[sl_fatigue])[lastCycleIdx]
debug(lastCycleMaxPosition, fatigue_dict)
print(mdBlock("**Fatigue Cycle**: {'id': '%s', 'loc': '%s', 'max disp': %.3f, 'max strain':%.3f, 'lastCycle': %d, 'timeLast': %.3f} "%(
fatigue_dict['Short Name'],
fatigue_dict['location'],
lastCycleMaxPosition,
lastCycleMaxPosition/details.gauge.value,
fatigue_dict[quartile4],
trends['pc|cycleStartTime'].array[sl_fatigue][lastCycleIdx]
),
), file=report)
else:
N, O = -25, -1
if fatigue_dict and fatigue_dict['UTS Load']:
tracking = csvread(str(trendsfolder.tracking))
track_indicies = trends._getslices('step')
sl_uts = track_indicies[7]
debug(track_indicies, sl_uts)
maxload = data_find_max(tracking[loadsTracking].array[sl_uts])
debug(maxload)
maxes = DataTree()
maxes.load = maxload.value
maxes.stress = maxes.load / details.measurements.area.value
maxes.displacement = tracking.displacement.array[sl_uts][maxload.idx]
maxes.strain = maxes.displacement / details.gauge.value
debug(maxes)
print(mdBlock("**UTS Load**: %s: %s, %s, %.3f, %.3f, %.3f, %.3f, , %.3f, %.3f, %d, %.3f "%(
'Name, Orient, UTS Load (manual), UTS Stress (manual), disp, strain, load, stress, idx, time',
fatigue_dict['Short Name'],
fatigue_dict['location'],
fatigue_dict['UTS Load'],
fatigue_dict['UTS Load']/details.gauge.value,
maxes.displacement,
maxes.strain,
maxes.load,
maxes.stress,
maxload.idx,
tracking.totalTime.array[sl_uts][maxload.idx],
)), file=report)
tabledata = OrderedDict([(short(col), fmt(col, N, O)) for col in columns ])
print(tabulate(tabledata, headers="keys", numalign="right", floatfmt=".2f"), file=report)
print(mdBlock("Steps: "), set(trends['step'].array.tolist()), file=report)
def handler(test: Path, args: dict):
data_json = Json.load_data_path(test)
## Details
### lookup details
detailValues = [
part.strip() if type(part) is str else part
for column in args.state.jsonColumns.values()
for part in [attributesAccessor(data_json, column)]
]
testName = "Test {}".format(test.stems())
if 'n/a' in detailValues:
debug(detailValues)
logging.error("Skipping:" + testName + " due to missing details: " +
repr(detailValues))
return
### details table
detailsTable = MarkdownTable(headers=['Detail', 'Value'])
detailsTable.add_rows(zip(args.state.jsonColumns.keys(), detailValues))
details = detailsTable.generateTable(headers=['Name', 'Value']).format()
args.state.testDetails[testName] = details
## Overview Images
### test overview images
testOverviewImages = ImageTable()\
.addImageGlob(str(test.parent), 'img', '*.png')\
.addImageGlob(str(test.parent), "img","overview","*Stress*last*.png")\
.addImageGlob(str(test.parent), "img","overview","*Stress*all*.png")\
.addImageGlob(str(test.parent), "img","trends","*Stress*all*.png")\
.addImageGlob(str(test.parent), "img","trends","*Stress*last*.png")
### add details and images to test section
args.state.testImages[testName] = testOverviewImages
# args.state.tests[testFolder] = [details, images]
### summary details
# debug(detailValues)
attribs, testId = parse_test_name(test.parent.stems())
args.state.summaryTable.add_row(
[testId, test.parent.stems(), attribs.orientation] + detailValues)
## all test images
allImagesTable = ImageTable().addImageGlob(str(test.parent), 'img',
'**/*.png')
allImages = allImagesTable.generateTable(columns=2,
directory=str(
test.parent)).format()
testDetails = [
mdHeader(2, 'Test: ' + testName),
mdBlock(details),
mdHeader(2, 'All Images'), allImages
]
writeImageTable(test.parent, 'Test Images ({}).md'.format(testName),
testDetails)
# print
print("## CSV Data")
print('>', ','.join(map(str, detailValues)))
return
def print_csv_data(testinfo, testfolder, details, report):
fatigue_data = """
Short Name,set,location,sample,Test Name,Level,Area,DM3,Pred UTS,Orient,Cycles (1st Quartile),Cycles (4th Quartile),UTS Load,Max Strain
1002-1LG-1001,1002,1LG,1001,,90%,0.788,120.33,12.635,,29,39,,
1002-1LG-701,1002,1LG,701,,60%,1.13,160.73,17.66,LG,972,975,,
1002-1LG-702,1002,1LG,702,,70%,1.466,141.22,15.716,,,,25,
1002-1LG-902,1002,1LG,902,,80%,0.931,136.98,15.293,LG,104,105,,
1002-1TR-601,1002,1TR,601,,60%,0.16894,5.563,0.5,,,,2.1,
1002-1TR-602,1002,1TR,602,,70%,1.1296,12.035,5.4,,11,12,,
1002-1TR-603,1002,1TR,603,,70%,1.02,5.433,1.056,,,,1.7,
1002-1TR-801,1002,1TR,801,,80%,0.7912,5.319,1.016,,3790,3791,,
1006-1TR-501,1006,1TR,501,,90%,0.713,4.942,0.884,,,,,
1006-1TR-502,1006,1TR,502,,80%,0.555,4.72,0.644,,1,21,,
1006-1TR-701,1006,1TR,701,,70%,0.786,8.083,1.39,,1597,1598,,
1006-1TR-702,1006,1TR,702,,60%,0.701,10.939,2.988,,6620,6630,,
1009-1LG-1002,1009,1LG,1002,jan10(gf10.9-llm)-wa-lg-l10-x2,60%,1.02,133.97,14.994,LG,,,14,
1009-1LG-1003,1009,1LG,1003,jan10(gf10.9-llm)-wa-lg-l10-x3,70%,0.72,156.2,17.208,LG,98,99,,
1009-1LG-1201,1009,1LG,1201,jan10(gf10.9-llm)-wa-lg-l12-x1,80%,1.2,192.6,20.83,LG,,,38,
1009-1LG-1202,1009,1LG,1202,jan10(gf10.9-llm)-wa-lg-l12-x2,90%,1.36,118.05,13.407,LG,184,185,,
1009-1LG-1203,1009,1LG,1203,jan10(gf10.9-llm)-wa-lg-l12-x3,80%,1.1,97.07,11.317,LG,559,560,,
1009-1TR-1101,1009,1TR,1101,,70%,0.79,9.742,2.568,,,,5,
1009-1TR-1102,1009,1TR,1102,,60%,1.02,9.632,2.529,,,,6.7,
1009-1TR-902,1009,1TR,902,,90%,0.87,7.029,1.615,,,,3.4,
1009-1TR-903,1009,1TR,903,,90%,0.88,14.487,4.233,,1,1,,
1104-1LG-501,1104,1LG,501,jan11(gf11.4-llm)-wa-lg-l5-x1,90%,1.1,113.96,12.99,LG,1,17,,
1104-1LG-502,1104,1LG,502,jan11(gf11.4-llm)-wa-lg-l5-x2,80%,1.56,64.166,8.03,LG,102,126,,
1104-1LG-701,1104,1LG,701,jan11(gf11.4-llm)-wa-lg-l7-x1,70%,1.26,207.92,22.361,LG,,,12,
1104-1LG-702,1104,1LG,702,jan11(gf11.4-llm)-wa-lg-l7-x2,60%,1.26,113.76,12.98,LG,,,12,
1105-1LG-601,1105,1LG,601,jan11(gf11.5-llm)-wa-lg-l6-x1,60%,0.88,250.89,26.642,LG,,,24,
1105-1LG-602,1105,1LG,602,jan11(gf11.5-llm)-wa-lg-l6-x2,70%,0.93,171.9,18.772,LG,198,199,,
1105-1LG-801,1105,1LG,801,jan11(gf11.5-llm)-wa-lg-l8-x1,80%,1.23,19.789,19.789,LG,751,752,,
1105-1LG-802,1105,1LG,802,jan11(gf11.5-llm)-wa-lg-l8-x2,90%,1.81,143.35,15.928,LG,25,26,,
1105-1TR-501,1105,1TR,501,,90%,0.52,8.92,2.279,,104,105,,
1105-1TR-502,1105,1TR,502,,80%,0.38,7.899,1.921,,7,8,,
1105-1TR-701,1105,1TR,701,,70%,0.67,11.912,3.329,,16,18,,
1105-1TR-702,1105,1TR,702,,60%,0.629,8.977,2.3,,143,145,,
"""
def values(v):
try:
return int(v)
except:
try:
return float(v)
except:
return v
fatigue_header, *fatigue_rows = [
l.strip().split(',') for l in fatigue_data.strip().split('\n')
]
# debug(fatigue_header)
fatigue_dicts = [{k: values(i)
for k, i in zip(fatigue_header, r)}
for r in fatigue_rows]
fatigue_dicts = DataTree(**{r['Short Name']: r for r in fatigue_dicts})
# debug(fatigue_dicts)
print(mdHeader(3, "CSV Data"), file=report)
# KeyError: "Key 'elapsedStep' not found in: step, loadLinearLoad1Maximum, displacementLinearDigitalPositionMinimum, rotationRotaryRotationMinimum, torqueRotaryTorqueMinimum, rotationRotaryRotationMaximum, torqueRotaryTorqueMaximum, indices, positionLinearPositionMaximum, rotaryDisplacementRotaryDigitalRotationMaximum, rotaryDisplacementRotaryDigitalRotationMinimum, loadLinearLoadMaximum, loadLinearLoad1Minimum, elapsedCycles, pc|frequency, _matrix, _InstronMatrixData__slices, displacementLinearDigitalPositionMaximum, totalCycles, loadLinearLoadMinimum, positionLinearPositionMinimum, pc|cycleStartTime"
if testinfo.orientation == 'lg':
trendsfolder = testfolder.raws.cycles_lg_csv
loads = ['loadLinearLoadMaximum', 'loadLinearLoadMinimum']
loadsTracking = 'loadLinearLoad'
elif testinfo.orientation == 'tr':
trendsfolder = testfolder.raws.cycles_tr_csv
loads = ['loadLinearLoad1Maximum', 'loadLinearLoad1Maximum']
loadsTracking = 'loadLinearLoad1'
debug(testinfo.short, trendsfolder)
if not trendsfolder.trends or not trendsfolder.trends.exists():
print("Error: couldn't find trend files! (%s)" % (str(testinfo), ),
file=report)
return
trends = csvread(str(trendsfolder.trends))
indicies = trends._getslices('step')
debug(indicies)
sl_fatigue = indicies[5]
# sl_uts = indicies[7]
def fmt(name, N=-25, O=-1):
if hasattr(name, '__call__'):
return name(trends, N, O)[1]
return trends[name].array[N:O]
columns = [
'elapsedCycles',
'step',
'displacementLinearDigitalPositionMinimum',
'displacementLinearDigitalPositionMaximum',
lambda x, N, O:
('Min Strain', x['displacementLinearDigitalPositionMinimum'].array[N:O]
/ details.gauge.value),
lambda x, N, O:
('Max Strain', x['displacementLinearDigitalPositionMaximum'].array[N:O]
/ details.gauge.value),
] + loads
def short(name, N=-1, O=-1):
if hasattr(name, '__call__'):
return name(trends, N, O)[0]
return name.replace('Linear',
'').replace('displacement',
'disp').replace('DigitalPosition', '')
fatigue_dict = fatigue_dicts.get(testinfo.short, None)
quartile1 = 'Cycles (1st Quartile)'
quartile4 = 'Cycles (4th Quartile)'
print(mdBlock("Fatigue Data:" + str(fatigue_dict)), file=report)
if fatigue_dict and fatigue_dict[quartile4]:
startEndCycleIdx = find_index(
fatigue_dict[quartile1], trends['elapsedCycles'].array[sl_fatigue])
lastCycleIdx = find_index(fatigue_dict[quartile4],
trends['elapsedCycles'].array[sl_fatigue])
N, O = startEndCycleIdx - 1, lastCycleIdx
if not lastCycleIdx:
debug(trends['elapsedCycles'].array[sl_fatigue])
debug(startEndCycleIdx, lastCycleIdx, N, O)
lastCycleMaxPosition = (
trends['displacementLinearDigitalPositionMaximum'].
array[sl_fatigue])[lastCycleIdx]
debug(lastCycleMaxPosition, fatigue_dict)
print(mdBlock(
"**Fatigue Cycle**: {'id': '%s', 'loc': '%s', 'max disp': %.3f, 'max strain':%.3f, 'lastCycle': %d, 'timeLast': %.3f} "
% (fatigue_dict['Short Name'], fatigue_dict['location'],
lastCycleMaxPosition, lastCycleMaxPosition /
details.gauge.value, fatigue_dict[quartile4],
trends['pc|cycleStartTime'].array[sl_fatigue][lastCycleIdx]), ),
file=report)
else:
N, O = -25, -1
if fatigue_dict and fatigue_dict['UTS Load']:
tracking = csvread(str(trendsfolder.tracking))
track_indicies = trends._getslices('step')
sl_uts = track_indicies[7]
debug(track_indicies, sl_uts)
maxload = data_find_max(tracking[loadsTracking].array[sl_uts])
debug(maxload)
maxes = DataTree()
maxes.load = maxload.value
maxes.stress = maxes.load / details.measurements.area.value
maxes.displacement = tracking.displacement.array[sl_uts][maxload.idx]
maxes.strain = maxes.displacement / details.gauge.value
debug(maxes)
print(mdBlock(
"**UTS Load**: %s: %s, %s, %.3f, %.3f, %.3f, %.3f, , %.3f, %.3f, %d, %.3f "
% (
'Name, Orient, UTS Load (manual), UTS Stress (manual), disp, strain, load, stress, idx, time',
fatigue_dict['Short Name'],
fatigue_dict['location'],
fatigue_dict['UTS Load'],
fatigue_dict['UTS Load'] / details.gauge.value,
maxes.displacement,
maxes.strain,
maxes.load,
maxes.stress,
maxload.idx,
tracking.totalTime.array[sl_uts][maxload.idx],
)),
file=report)
tabledata = OrderedDict([(short(col), fmt(col, N, O)) for col in columns])
print(tabulate(tabledata, headers="keys", numalign="right",
floatfmt=".2f"),
file=report)
print(mdBlock("Steps: "), set(trends['step'].array.tolist()), file=report)