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SAT9/SAT9_SCADA/com.inductiveautomation.perspective/views/Windows/Statistics/view.json

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"config": {
"script": "\tdata \u003d []\n\ttable \u003d []\n\timport datetime\n\tcurrent_datetime\u003ddatetime.datetime.now()\n\tstr_date \u003d current_datetime.strftime(\"%m-%d-%Y %I-%M\")\n\n\n\tif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 0:\n\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Induct Details\").getChild(\"Induct Details\").props.filter.results.data\n\t\tif(len(results) \u003e 0):\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Induct\",\"Total (#)\",\"Single Carrier (#)\",\"Double Carrier (#)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027InductName\u0027],result[\u0027Total_count\u0027],result[\u0027singlecarrier_count\u0027],result[\u0027doublecarrier_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Induct\",\"Total (%)\",\"Single Carrier (%)\",\"Double Carrier (%)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027InductName\u0027],result[\u0027Total_perc\u0027],result[\u0027SingleCarrier_perc\u0027],result[\u0027DoubleCarrier_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Induct\",\"Total (pph)\",\"Single Carrier (pph)\",\"Double Carrier (pph)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027InductName\u0027],result[\u0027Total_rate\u0027],result[\u0027SingleCarrier_rate\u0027],result[\u0027DoubleCarrier_rate\u0027]])\n\t\n\t\telse:\n\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Induct Details\").getChild(\"Induct Details\").props.data)\n\t\t\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Induct\",\"Total (#)\",\"Single Carrier (#)\",\"Double Carrier (#)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027InductName\u0027],result[\u0027Total_count\u0027],result[\u0027singlecarrier_count\u0027],result[\u0027doublecarrier_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Induct\",\"Total (%)\",\"Single Carrier (%)\",\"Double Carrier (%)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027InductName\u0027],result[\u0027Total_perc\u0027],result[\u0027SingleCarrier_perc\u0027],result[\u0027DoubleCarrier_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Induct\",\"Total (pph)\",\"Single Carrier (pph)\",\"Double Carrier (pph)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027InductName\u0027],result[\u0027Total_rate\u0027],result[\u0027SingleCarrier_rate\u0027],result[\u0027DoubleCarrier_rate\u0027]])\n\t\t\n\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Induct Details.csv\u0027, data \u003d csv)\t\n\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 1:\n\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Scanner_Details\").getChild(\"Scanner Details\").props.filter.results.data\n\t\tif(len(results) \u003e 0):\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Scanner\",\"Total (#)\",\"Good Read (#)\",\"No Read (#)\",\"Multi Read (#)\",\"No Code (#)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027ScannerName\u0027],result[\u0027Total_count\u0027],result[\u0027GoodRead_count\u0027],result[\u0027NoRead_count\u0027],result[\u0027MultiLabelRead_count\u0027],result[\u0027NoCode_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Scanner\",\"Total (%)\",\"Good Read (%)\",\"No Read (%)\",\"Multi Read (%)\",\"No Code (%)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027ScannerName\u0027],result[\u0027Total_perc\u0027],result[\u0027GoodRead_perc\u0027],result[\u0027NoRead_perc\u0027],result[\u0027MultiLabelRead_perc\u0027],result[\u0027NoCode_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Scanner\",\"Total (pph)\",\"Good Read (pph)\",\"No Read (pph)\",\"Multi Read (pph)\",\"No Code (pph)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027ScannerName\u0027],result[\u0027Total_rate\u0027],result[\u0027GoodRead_rate\u0027],result[\u0027NoRead_rate\u0027],result[\u0027MultiLabelRead_rate\u0027],result[\u0027NoCode_rate\u0027]])\n\t\n\t\telse:\n\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Scanner_Details\").getChild(\"Scanner Details\").props.data)\n\t\t\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Scanner\",\"Total (#)\",\"Good Read (#)\",\"No Read (#)\",\"Multi Read (#)\",\"No Code (#)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027ScannerName\u0027],result[\u0027Total_count\u0027],result[\u0027GoodRead_count\u0027],result[\u0027NoRead_count\u0027],result[\u0027MultiLabelRead_count\u0027],result[\u0027NoCode_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Scanner\",\"Total (%)\",\"Good Read (%)\",\"No Read (%)\",\"Multi Read (%)\",\"No Code (%)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027ScannerName\u0027],result[\u0027Total_perc\u0027],result[\u0027GoodRead_perc\u0027],result[\u0027NoRead_perc\u0027],result[\u0027MultiLabelRead_perc\u0027],result[\u0027NoCode_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Scanner\",\"Total (pph)\",\"Good Read (pph)\",\"No Read (pph)\",\"Multi Read (pph)\",\"No Code (pph)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027ScannerName\u0027],result[\u0027Total_rate\u0027],result[\u0027GoodRead_rate\u0027],result[\u0027NoRead_rate\u0027],result[\u0027MultiLabelRead_rate\u0027],result[\u0027NoCode_rate\u0027]])\n\t\t\t\n\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Scanner Details.csv\u0027, data \u003d csv)\n\t\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 2:\n\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Sorter Summary\").getChild(\"Sorter Summary\").props.filter.results.data\n\t\tif(len(results) \u003e 0):\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (#)\",\"Sorted (#)\",\"Awcs Recirc (#)\",\"Operational Recirc (#)\",\"Machine Recirc (#)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Induct_count\u0027],result[\u0027Sorted_count\u0027],result[\u0027AWCSRecirc_count\u0027],result[\u0027OperRecirc_count\u0027],result[\u0027MachineRecirc_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (%)\",\"Sorted (%)\",\"Awcs Recirc (%)\",\"Operational Recirc (%)\",\"Machine Recirc (%)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Induct_perc\u0027],result[\u0027Sorted_perc\u0027],result[\u0027AWCSRecirc_perc\u0027],result[\u0027OperRecirc_perc\u0027],result[\u0027MachineRecirc_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (pph)\",\"Sorted (pph)\",\"Awcs Recirc (pph)\",\"Operational Recirc (pph)\",\"Machine Recirc (pph)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Induct_rate\u0027],result[\u0027Sorted_rate\u0027],result[\u0027AWCSRecirc_rate\u0027],result[\u0027OperRecirc_rate\u0027],result[\u0027MachineRecirc_rate\u0027]])\n\t\n\t\telse:\n\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Sorter Summary\").getChild(\"Sorter Summary\").props.data)\n\t\t\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (#)\",\"Sorted (#)\",\"Awcs Recirc (#)\",\"Operational Recirc (#)\",\"Machine Recirc (#)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Induct_count\u0027],result[\u0027Sorted_count\u0027],result[\u0027AWCSRecirc_count\u0027],result[\u0027OperRecirc_count\u0027],result[\u0027MachineRecirc_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (%)\",\"Sorted (%)\",\"Awcs Recirc (%)\",\"Operational Recirc (%)\",\"Machine Recirc (%)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Induct_perc\u0027],result[\u0027Sorted_perc\u0027],result[\u0027AWCSRecirc_perc\u0027],result[\u0027OperRecirc_perc\u0027],result[\u0027MachineRecirc_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (pph)\",\"Sorted (pph)\",\"Awcs Recirc (pph)\",\"Operational Recirc (pph)\",\"Machine Recirc (pph)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Induct_rate\u0027],result[\u0027Sorted_rate\u0027],result[\u0027AWCSRecirc_rate\u0027],result[\u0027OperRecirc_rate\u0027],result[\u0027MachineRecirc_rate\u0027]])\n\t\t\t\n\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Sorter Summary.csv\u0027, data \u003d csv)\n\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 3:\n\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Sorter Details\").getChild(\"Sorter Details\").props.filter.results.data\n\t\tif(len(results) \u003e 0):\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (#)\",\"Sorted (#)\",\"Assigned (#)\",\"Dest Inv (#)\",\"Dest None (#)\",\"Dest Dis (#)\",\"Dest Full (#)\",\"Unexpected (#)\",\"Dest Fault (#)\",\"Div Fail (#)\",\"Gap Err (#)\",\"Lost (#)\",\"Track Err (#)\",\"Unknown (#)\",\"Unsafe (#)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027inducted_count\u0027],result[\u0027sorted_count\u0027],result[\u0027assigned_count\u0027],result[\u0027destinv_count\u0027],result[\u0027destnone_count\u0027],result[\u0027destdis_count\u0027],result[\u0027destfull_count\u0027],result[\u0027unexpected_count\u0027],result[\u0027destfault_count\u0027],result[\u0027divfail_count\u0027],result[\u0027gaperr_count\u0027],result[\u0027lost_count\u0027],result[\u0027trackerr_count\u0027],result[\u0027unknownn_count\u0027],result[\u0027unsafe_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (%)\",\"Sorted (%)\",\"Assigned (%)\",\"Dest Inv (%)\",\"Dest None (%)\",\"Dest Dis (%)\",\"Dest Full (%)\",\"Unexpected (%)\",\"Dest Fault (%)\",\"Div Fail (%)\",\"Gap Err (%)\",\"Lost (%)\",\"Track Err (%)\",\"Unknown (%)\",\"Unsafe (%)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027inducted_perc\u0027],result[\u0027sorted_perc\u0027],result[\u0027assigned_perc\u0027],result[\u0027destinv_perc\u0027],result[\u0027destnone_perc\u0027],result[\u0027destdis_perc\u0027],result[\u0027destfull_perc\u0027],result[\u0027unexpected_perc\u0027],result[\u0027destfault_perc\u0027],result[\u0027divfail_perc\u0027],result[\u0027gaperr_perc\u0027],result[\u0027lost_perc\u0027],result[\u0027trackerr_perc\u0027],result[\u0027unknown_perc\u0027],result[\u0027unsafe_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (pph)\",\"Sorted (pph)\",\"Assigned (pph)\",\"Dest Inv (pph)\",\"Dest None (pph)\",\"Dest Dis (pph)\",\"Dest Full (pph)\",\"Unexpected (pph)\",\"Dest Fault (pph)\",\"Div Fail (pph)\",\"Gap Err (pph)\",\"Lost (pph)\",\"Track Err (pph)\",\"Unknown (pph)\",\"Unsafe (pph)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027inducted_rate\u0027],result[\u0027sorted_rate\u0027],result[\u0027assigned_rate\u0027],result[\u0027destinv_rate\u0027],result[\u0027destnone_rate\u0027],result[\u0027destdis_rate\u0027],result[\u0027destfull_rate\u0027],result[\u0027unexpected_rate\u0027],result[\u0027destfault_rate\u0027],result[\u0027divfail_rate\u0027],result[\u0027gaperr_rate\u0027],result[\u0027lost_rate\u0027],result[\u0027trackerr_rate\u0027],result[\u0027unknown_rate\u0027],result[\u0027unsafe_rate\u0027]])\n\t\t\n\t\telse:\n\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Sorter Details\").getChild(\"Sorter Details\").props.data)\n\t\t\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (#)\",\"Sorted (#)\",\"Assigned (#)\",\"Dest Inv (#)\",\"Dest None (#)\",\"Dest Dis (#)\",\"Dest Full (#)\",\"Unexpected (#)\",\"Dest Fault (#)\",\"Div Fail (#)\",\"Gap Err (#)\",\"Lost (#)\",\"Track Err (#)\",\"Unknown (#)\",\"Unsafe (#)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027inducted_count\u0027],result[\u0027sorted_count\u0027],result[\u0027sorted_count\u0027],result[\u0027destinv_count\u0027],result[\u0027destnone_count\u0027],result[\u0027destdis_count\u0027],result[\u0027destfull_count\u0027],result[\u0027unexpected_count\u0027],result[\u0027destfault_count\u0027],result[\u0027divfail_count\u0027],result[\u0027gaperr_count\u0027],result[\u0027lost_count\u0027],result[\u0027trackerr_count\u0027],result[\u0027unknownn_count\u0027],result[\u0027unsafe_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (%)\",\"Sorted (%)\",\"Assigned (%)\",\"Dest Inv (%)\",\"Dest None (%)\",\"Dest Dis (%)\",\"Dest Full (%)\",\"Unexpected (%)\",\"Dest Fault (%)\",\"Div Fail (%)\",\"Gap Err (%)\",\"Lost (%)\",\"Track Err (%)\",\"Unknown (%)\",\"Unsafe (%)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027inducted_perc\u0027],result[\u0027sorted_perc\u0027],result[\u0027assigned_perc\u0027],result[\u0027destinv_perc\u0027],result[\u0027destnone_perc\u0027],result[\u0027destdis_perc\u0027],result[\u0027destfull_perc\u0027],result[\u0027unexpected_perc\u0027],result[\u0027destfault_perc\u0027],result[\u0027divfail_perc\u0027],result[\u0027gaperr_perc\u0027],result[\u0027lost_perc\u0027],result[\u0027trackerr_perc\u0027],result[\u0027unknown_perc\u0027],result[\u0027unsafe_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Inducted (pph)\",\"Sorted (pph)\",\"Assigned (pph)\",\"Dest Inv (pph)\",\"Dest None (pph)\",\"Dest Dis (pph)\",\"Dest Full (pph)\",\"Unexpected (pph)\",\"Dest Fault (pph)\",\"Div Fail (pph)\",\"Gap Err (pph)\",\"Lost (pph)\",\"Track Err (pph)\",\"Unknown (pph)\",\"Unsafe (pph)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027inducted_rate\u0027],result[\u0027sorted_rate\u0027],result[\u0027assigned_rate\u0027],result[\u0027destinv_rate\u0027],result[\u0027destnone_rate\u0027],result[\u0027destdis_rate\u0027],result[\u0027destfull_rate\u0027],result[\u0027unexpected_rate\u0027],result[\u0027destfault_rate\u0027],result[\u0027divfail_rate\u0027],result[\u0027gaperr_rate\u0027],result[\u0027lost_rate\u0027],result[\u0027trackerr_rate\u0027],result[\u0027unknown_rate\u0027],result[\u0027unsafe_rate\u0027]])\n\t\t\t\n\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Sorter Details.csv\u0027, data \u003d csv)\n\t\t\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 4:\n\t\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Lane Details\").getChild(\"Lane Details\").props.filter.results.data\n\t\t\tif(len(results) \u003e 0):\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Lane\",\"Total (#)\",\"Diverted (#)\",\"Dest Full (#)\",\"Dest Jam (#)\",\"Dest Disabled (#)\",\"Dest Fault (#)\",\"Divert Fail (#)\",\"Lost (#)\",\"Unsafe (#)\",\"Dim Error (#)\",\"Gap Error (#)\",\"Unknown (#)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Lane\u0027],result[\u0027Total_count\u0027],result[\u0027Diverted_count\u0027],result[\u0027Destfull_count\u0027],result[\u0027DestJam_count\u0027],result[\u0027DestDis_count\u0027],result[\u0027DestFault_count\u0027],result[\u0027DivertFail_count\u0027],result[\u0027Lost_count\u0027],result[\u0027Unsafe_count\u0027],result[\u0027Dim_count\u0027],result[\u0027GapErr_count\u0027],result[\u0027Unknown_count\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Lane\",\"Total (%)\",\"Diverted (%)\",\"Dest Full (%)\",\"Dest Jam (%)\",\"Dest Disabled (%)\",\"Dest Fault (%)\",\"Divert Fail (%)\",\"Lost (%)\",\"Unsafe (%)\",\"Dim Error (%)\",\"Gap Error (%)\",\"Unknown (%)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Lane\u0027],result[\u0027total_perc\u0027],result[\u0027Diverted_perc\u0027],result[\u0027destfull_perc\u0027],result[\u0027destjam_perc\u0027],result[\u0027destdisabled_perc\u0027],result[\u0027destfault_perc\u0027],result[\u0027DivertFail_perc\u0027],result[\u0027lost_perc\u0027],result[\u0027unsafe_perc\u0027],result[\u0027dim_perc\u0027],result[\u0027gaperr_perc\u0027],result[\u0027unknown_perc\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Lane\",\"Total (pph)\",\"Diverted (pph)\",\"Dest Full (pph)\",\"Dest Jam (pph)\",\"Dest Disabled (pph)\",\"Dest Fault (pph)\",\"Divert Fail (pph)\",\"Lost (pph)\",\"Unsafe (pph)\",\"Dim Error (pph)\",\"Gap Error (pph)\",\"Unknown (pph)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Lane\u0027],result[\u0027total_rate\u0027],result[\u0027Diverted_rate\u0027],result[\u0027destfull_rate\u0027],result[\u0027destjam_rate\u0027],result[\u0027destdisabled_rate\u0027],result[\u0027destfault_rate\u0027],result[\u0027DivertFail_rate\u0027],result[\u0027lost_rate\u0027],result[\u0027unsafe_rate\u0027],result[\u0027dim_rate\u0027],result[\u0027gaperr_rate\u0027],result[\u0027unknown_rate\u0027]])\n\t\t\t\n\t\t\telse:\n\t\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Lane Details\").getChild(\"Lane Details\").props.data)\n\t\t\t\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Lane\",\"Total (#)\",\"Diverted (#)\",\"Dest Full (#)\",\"Dest Jam (#)\",\"Dest Disabled (#)\",\"Dest Fault (#)\",\"Divert Fail (#)\",\"Lost (#)\",\"Unsafe (#)\",\"Dim Error (#)\",\"Gap Error (#)\",\"Unknown (#)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Lane\u0027],result[\u0027Total_count\u0027],result[\u0027Diverted_count\u0027],result[\u0027Destfull_count\u0027],result[\u0027DestJam_count\u0027],result[\u0027DestDis_count\u0027],result[\u0027DestFault_count\u0027],result[\u0027DivertFail_count\u0027],result[\u0027Lost_count\u0027],result[\u0027Unsafe_count\u0027],result[\u0027Dim_count\u0027],result[\u0027GapErr_count\u0027],result[\u0027Unknown_count\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Lane\",\"Total (%)\",\"Diverted (%)\",\"Dest Full (%)\",\"Dest Jam (%)\",\"Dest Disabled (%)\",\"Dest Fault (%)\",\"Divert Fail (%)\",\"Lost (%)\",\"Unsafe (%)\",\"Dim Error (%)\",\"Gap Error (%)\",\"Unknown (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Lane\u0027],result[\u0027total_perc\u0027],result[\u0027Diverted_perc\u0027],result[\u0027destfull_perc\u0027],result[\u0027destjam_perc\u0027],result[\u0027destdisabled_perc\u0027],result[\u0027destfault_perc\u0027],result[\u0027DivertFail_perc\u0027],result[\u0027lost_perc\u0027],result[\u0027unsafe_perc\u0027],result[\u0027dim_perc\u0027],result[\u0027gaperr_perc\u0027],result[\u0027unknown_perc\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"End Timestamp\", \"Sorter\",\"Lane\",\"Total (pph)\",\"Diverted (pph)\",\"Dest Full (pph)\",\"Dest Jam (pph)\",\"Dest Disabled (pph)\",\"Dest Fault (pph)\",\"Divert Fail (pph)\",\"Lost (pph)\",\"Unsafe (pph)\",\"Dim Error (pph)\",\"Gap Error (pph)\",\"Unknown (pph)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027SorterName\u0027],result[\u0027Lane\u0027],result[\u0027total_rate\u0027],result[\u0027Diverted_rate\u0027],result[\u0027destfull_rate\u0027],result[\u0027destjam_rate\u0027],result[\u0027destdisabled_rate\u0027],result[\u0027destfault_rate\u0027],result[\u0027DivertFail_rate\u0027],result[\u0027lost_rate\u0027],result[\u0027unsafe_rate\u0027],result[\u0027dim_rate\u0027],result[\u0027gaperr_rate\u0027],result[\u0027unknown_rate\u0027]])\n\t\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Lane Details.csv\u0027, data \u003d csv)\n\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 5:\n\t\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Hourly_Induct\").getChild(\"Hourly_Induct\").props.filter.results.data\n\t\t\tif(len(results) \u003e 0):\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (#)\",\"Single Carrier (#)\",\"Double Carrier (#)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (#)\u0027],result[\u0027Single Carrier (#)\u0027],result[\u0027Double Carrier (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Total (%)\",\"Single Carrier (%)\",\"Double Carrier (%)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (%\u0027],result[\u0027Single Carrier (%)\u0027],result[\u0027Double Carrier (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (pph)\",\"Single Carrier (pph)\",\"Double Carrier (pph)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (pph)\u0027],result[\u0027Single Carrier (pph)\u0027],result[\u0027Double Carrier (pph)\u0027]])\n\t\t\t\n\t\t\telse:\n\t\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Hourly_Induct\").getChild(\"Hourly_Induct\").props.data)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (#)\",\"Single Carrier (#)\",\"Double Carrier (#)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (#)\u0027],result[\u0027Single Carrier (#)\u0027],result[\u0027Double Carrier (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Total (%)\",\"Single Carrier (%)\",\"Double Carrier (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (%)\u0027],result[\u0027Single Carrier (%)\u0027],result[\u0027Double Carrier (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (pph)\",\"Single Carrier (pph)\",\"Double Carrier (pph)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (pph)\u0027],result[\u0027Single Carrier (pph)\u0027],result[\u0027Double Carrier (pph)\u0027]])\n\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Hourly Induct.csv\u0027, data \u003d csv)\n\t\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 6:\n\t\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Hourly_Scanner\").getChild(\"Hourly_Scanner\").props.filter.results.data\n\t\t\tif(len(results) \u003e 0):\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (#)\",\"Good Read (#)\",\"No Read (#)\",\"Multi Read (#)\",\"No code (#)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (#)\u0027],result[\u0027Good Read (#)\u0027],result[\u0027No Read (#)\u0027],result[\u0027Multi Read (#)\u0027],result[\u0027No code (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (%)\",\"Good Read (%)\",\"No Read (%)\",\"Multi Read (%)\",\"No Code (%)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (%)\u0027],result[\u0027Good Read (%)\u0027],result[\u0027No Read (%)\u0027],result[\u0027Multi Read (%)\u0027],result[\u0027No Code (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Total (pph)\",\"Good Read (pph)\",\"No Read (pph)\",\"Multi Read (pph)\",\"No Code (pph)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (pph)\u0027],result[\u0027Good Read (pph)\u0027],result[\u0027No Read (pph)\u0027],result[\u0027Multi Read (pph)\u0027],result[\u0027No Code (pph)\u0027]])\n\t\t\t\n\t\t\telse:\n\t\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Hourly_Scanner\").getChild(\"Hourly_Scanner\").props.data)\n\t\t\t\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (#)\",\"Good Read (#)\",\"No Read (#)\",\"Multi Read (#)\",\"No code (#)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (#)\u0027],result[\u0027Good Read (#)\u0027],result[\u0027No Read (#)\u0027],result[\u0027Multi Read (#)\u0027],result[\u0027No code (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\", \"Total (%)\",\"Good Read (%)\",\"No Read (%)\",\"Multi Read (%)\",\"No Code (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (%)\u0027],result[\u0027Good Read (%)\u0027],result[\u0027No Read (%)\u0027],result[\u0027Multi Read (%)\u0027],result[\u0027No Code (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Total (pph)\",\"Good Read (pph)\",\"No Read (pph)\",\"Multi Read (pph)\",\"No Code (pph)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (pph)\u0027],result[\u0027Good Read (pph)\u0027],result[\u0027No Read (pph)\u0027],result[\u0027Multi Read (pph)\u0027],result[\u0027No Code (pph)\u0027]])\n\t\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Hourly Scanner.csv\u0027, data \u003d csv)\n\t\t\t\n\t\t\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 7:\n\t\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Hourly_Sorter_Summary\").getChild(\"Hourly_Sorter_Summary\").props.filter.results.data\n\t\t\tif(len(results) \u003e 0):\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (#)\",\"Sorted (#)\",\"Awcs Recirc (#)\",\"Operational Recirc (#)\",\"Machine Recirc (#)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (#)\u0027],result[\u0027Sorted (#)\u0027],result[\u0027Awcs Recirc (#)\u0027],result[\u0027Operational Recirc (#)\u0027],result[\u0027Machine Recirc (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (%)\",\"Sorted (%)\",\"Awcs Recirc (%)\",\"Operational Recirc (%)\",\"Machine Recirc (%)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (%)\u0027],result[\u0027Sorted (%)\u0027],result[\u0027Awcs Recirc (%)\u0027],result[\u0027Operational Recirc (%)\u0027],result[\u0027Machine Recirc (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (pph)\",\"Sorted (pph)\",\"Awcs Recirc (pph)\",\"Operational Recirc (pph)\",\"Machine Recirc (pph)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (pph)\u0027],result[\u0027Sorted (pph)\u0027],result[\u0027Awcs Recirc (pph)\u0027],result[\u0027Operational Recirc (pph)\u0027],result[\u0027Machine Recirc (pph)\u0027]])\n\t\t\n\t\t\telse:\n\t\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Hourly_Sorter_Summary\").getChild(\"Hourly_Sorter_Summary\").props.data)\n\t\t\t\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (#)\",\"Sorted (#)\",\"Awcs Recirc (#)\",\"Operational Recirc (#)\",\"Machine Recirc (#)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (#)\u0027],result[\u0027Sorted (#)\u0027],result[\u0027Awcs Recirc (#)\u0027],result[\u0027Operational Recirc (#)\u0027],result[\u0027Machine Recirc (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (%)\",\"Sorted (%)\",\"Awcs Recirc (%)\",\"Operational Recirc (%)\",\"Machine Recirc (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (%)\u0027],result[\u0027Sorted (%)\u0027],result[\u0027Awcs Recirc (%)\u0027],result[\u0027Operational Recirc (%)\u0027],result[\u0027Machine Recirc (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (pph)\",\"Sorted (pph)\",\"Awcs Recirc (pph)\",\"Operational Recirc (pph)\",\"Machine Recirc (pph)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (pph)\u0027],result[\u0027Sorted (pph)\u0027],result[\u0027Awcs Recirc (pph)\u0027],result[\u0027Operational Recirc (pph)\u0027],result[\u0027Machine Recirc (pph)\u0027]])\n\t\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Hourly Sorter Summary.csv\u0027, data \u003d csv)\n\t\n\t\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 8:\n\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Hourly_Sorter_Details\").getChild(\"Hourly_Sorter_Details\").props.filter.results.data\n\t\tif(len(results) \u003e 0):\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (#)\",\"Sorted (#)\",\"Dest Inv (#)\",\"Dest None (#)\",\"Dest Dis (#)\",\"Dest Full (#)\",\"Unexpected (#)\",\"Dest Fault (#)\",\"Div Fail (#)\",\"Gap Err (#)\",\"Lost (#)\",\"Track Err (#)\",\"Unknown (#)\",\"Unsafe (#)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (#)\u0027],result[\u0027Sorted (#)\u0027],result[\u0027Dest Inv (#)\u0027],result[\u0027Dest None (#)\u0027],result[\u0027Dest Dis (#)\u0027],result[\u0027Dest Full (#)\u0027],result[\u0027Unexpected (#)\u0027],result[\u0027Dest Fault (#)\u0027],result[\u0027Div Fail (#)\u0027],result[\u0027Gap Err (#)\u0027],result[\u0027Lost (#)\u0027],result[\u0027Track Err (#)\u0027],result[\u0027Unknown (#)\u0027],result[\u0027Unsafe (#)\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (%)\",\"Sorted (%)\",\"Dest Inv (%)\",\"Dest None (%)\",\"Dest Dis (%)\",\"Dest Full (%)\",\"Unexpected (%)\",\"Dest Fault (%)\",\"Div Fail (%)\",\"Gap Err (%)\",\"Lost (%)\",\"Track Err (%)\",\"Unknown (%)\",\"Unsafe (%)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (%)\u0027],result[\u0027Sorted (%)\u0027],result[\u0027Dest Inv (%)\u0027],result[\u0027Dest None (%)\u0027],result[\u0027Dest Dis (%)\u0027],result[\u0027Dest Full (%)\u0027],result[\u0027Unexpected (%)\u0027],result[\u0027Dest Fault (%)\u0027],result[\u0027Div Fail (%)\u0027],result[\u0027Gap Err (%)\u0027],result[\u0027Lost (%)\u0027],result[\u0027Track Err (%)\u0027],result[\u0027Unknown (%)\u0027],result[\u0027Unsafe (%)\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (pph)\",\"Sorted (pph)\",\"Dest Inv (pph)\",\"Dest None (pph)\",\"Dest Dis (pph)\",\"Dest Full (pph)\",\"Unexpected (pph)\",\"Dest Fault (pph)\",\"Div Fail (pph)\",\"Gap Err (pph)\",\"Lost (pph)\",\"Track Err (pph)\",\"Unknown (pph)\",\"Unsafe (pph)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (pph)\u0027],result[\u0027Sorted (pph)\u0027],result[\u0027Dest Inv (pph)\u0027],result[\u0027Dest None (pph)\u0027],result[\u0027Dest Dis (pph)\u0027],result[\u0027Dest Full (pph)\u0027],result[\u0027Unexpected (pph)\u0027],result[\u0027Dest Fault (pph)\u0027],result[\u0027Div Fail (pph)\u0027],result[\u0027Gap Err (pph)\u0027],result[\u0027Lost (pph)\u0027],result[\u0027Track Err (pph)\u0027],result[\u0027Unknown (pph)\u0027],result[\u0027Unsafe (pph)\u0027]])\n\t\t\n\t\telse:\n\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Hourly_Sorter_Details\").getChild(\"Hourly_Sorter_Details\").props.data)\n\t\t\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (#)\",\"Sorted (#)\",\"Dest Inv (#)\",\"Dest None (#)\",\"Dest Dis (#)\",\"Dest Full (#)\",\"Unexpected (#)\",\"Dest Fault (#)\",\"Div Fail (#)\",\"Gap Err (#)\",\"Lost (#)\",\"Track Err (#)\",\"Unknown (#)\",\"Unsafe (#)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (#)\u0027],result[\u0027Sorted (#)\u0027],result[\u0027Dest Inv (#)\u0027],result[\u0027Dest None (#)\u0027],result[\u0027Dest Dis (#)\u0027],result[\u0027Dest Full (#)\u0027],result[\u0027Unexpected (#)\u0027],result[\u0027Dest Fault (#)\u0027],result[\u0027Div Fail (#)\u0027],result[\u0027Gap Err (#)\u0027],result[\u0027Lost (#)\u0027],result[\u0027Track Err (#)\u0027],result[\u0027Unknown (#)\u0027],result[\u0027Unsafe (#)\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (%)\",\"Sorted (%)\",\"Dest Inv (%)\",\"Dest None (%)\",\"Dest Dis (%)\",\"Dest Full (%)\",\"Unexpected (%)\",\"Dest Fault (%)\",\"Div Fail (%)\",\"Gap Err (%)\",\"Lost (%)\",\"Track Err (%)\",\"Unknown (%)\",\"Unsafe (%)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (%)\u0027],result[\u0027Sorted (%)\u0027],result[\u0027Dest Inv (%)\u0027],result[\u0027Dest None (%)\u0027],result[\u0027Dest Dis (%)\u0027],result[\u0027Dest Full (%)\u0027],result[\u0027Unexpected (%)\u0027],result[\u0027Dest Fault (%)\u0027],result[\u0027Div Fail (%)\u0027],result[\u0027Gap Err (%)\u0027],result[\u0027Lost (%)\u0027],result[\u0027Track Err (%)\u0027],result[\u0027Unknown (%)\u0027],result[\u0027Unsafe (%)\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Inducted (pph)\",\"Sorted (pph)\",\"Dest Inv (pph)\",\"Dest None (pph)\",\"Dest Dis (pph)\",\"Dest Full (pph)\",\"Unexpected (pph)\",\"Dest Fault (pph)\",\"Div Fail (pph)\",\"Gap Err (pph)\",\"Lost (pph)\",\"Track Err (pph)\",\"Unknown (pph)\",\"Unsafe (pph)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Inducted (pph)\u0027],result[\u0027Sorted (pph)\u0027],result[\u0027Dest Inv (pph)\u0027],result[\u0027Dest None (pph)\u0027],result[\u0027Dest Dis (pph)\u0027],result[\u0027Dest Full (pph)\u0027],result[\u0027Unexpected (pph)\u0027],result[\u0027Dest Fault (pph)\u0027],result[\u0027Div Fail (pph)\u0027],result[\u0027Gap Err (pph)\u0027],result[\u0027Lost (pph)\u0027],result[\u0027Track Err (pph)\u0027],result[\u0027Unknown (pph)\u0027],result[\u0027Unsafe (pph)\u0027]])\n\t\t\t\n\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Hourly Sorter Details.csv\u0027, data \u003d csv)\n\t\t\n\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 9:\n\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Hourly_Lane\").getChild(\"Hourly_Lane\").props.filter.results.data\n\t\tif(len(results) \u003e 0):\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Total (#)\",\"Diverted (#)\",\"Dest Full (#)\",\"Dest Jam (#)\",\"Dest Disabled (#)\",\"Dest Fault (#)\",\"Divert Fail (#)\",\"Lost (#)\",\"Unsafe (#)\",\"Dim Error (#)\",\"Gap Error (#)\",\"Unknown (#)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027endt\u0027],result[\u0027rownumber\u0027],result[\u0027Total_count\u0027],result[\u0027Diverted_count\u0027],result[\u0027Destfull_count\u0027],result[\u0027DestJam_count\u0027],result[\u0027DestDis_count\u0027],result[\u0027DestFault_count\u0027],result[\u0027DivertFail_count\u0027],result[\u0027Lost_count\u0027],result[\u0027Unsafe_count\u0027],result[\u0027Dim_count\u0027],result[\u0027GapErr_count\u0027],result[\u0027Unknown_count\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Total (%)\",\"Diverted (%)\",\"Dest Full (%)\",\"Dest Jam (%)\",\"Dest Disabled (%)\",\"Dest Fault (%)\",\"Divert Fail (%)\",\"Lost (%)\",\"Unsafe (%)\",\"Dim Error (%)\",\"Gap Error (%)\",\"Unknown (%)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027endt\u0027],result[\u0027rownumber\u0027],result[\u0027total_perc\u0027],result[\u0027Diverted_perc\u0027],result[\u0027destfull_perc\u0027],result[\u0027destjam_perc\u0027],result[\u0027destdisabled_perc\u0027],result[\u0027destfault_perc\u0027],result[\u0027DivertFail_perc\u0027],result[\u0027lost_perc\u0027],result[\u0027unsafe_perc\u0027],result[\u0027dim_perc\u0027],result[\u0027gaperr_perc\u0027],result[\u0027unknown_perc\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Total (pph)\",\"Diverted (pph)\",\"Dest Full (pph)\",\"Dest Jam (pph)\",\"Dest Disabled (pph)\",\"Dest Fault (pph)\",\"Divert Fail (pph)\",\"Lost (pph)\",\"Unsafe (pph)\",\"Dim Error (pph)\",\"Gap Error (pph)\",\"Unknown (pph)\"]\n\t\t\t\tfor result in results:\n\t\t\t\t\tdata.append([result[\u0027endt\u0027],result[\u0027rownumber\u0027],result[\u0027total_rate\u0027],result[\u0027Diverted_rate\u0027],result[\u0027destfull_rate\u0027],result[\u0027destjam_rate\u0027],result[\u0027destdisabled_rate\u0027],result[\u0027destfault_rate\u0027],result[\u0027DivertFail_rate\u0027],result[\u0027lost_rate\u0027],result[\u0027unsafe_rate\u0027],result[\u0027dim_rate\u0027],result[\u0027gaperr_rate\u0027],result[\u0027unknown_rate\u0027]])\n\t\t\t\n\t\telse:\n\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Hourly_Lane\").getChild(\"Hourly_Lane\").props.data)\n\t\t\t\n\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Total (#)\",\"Diverted (#)\",\"Dest Full (#)\",\"Dest Jam (#)\",\"Dest Disabled (#)\",\"Dest Fault (#)\",\"Divert Fail (#)\",\"Lost (#)\",\"Unsafe (#)\",\"Dim Err (#)\",\"Gap Error (#)\",\"Unknown (#)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (#)\u0027],result[\u0027Diverted (#)\u0027],result[\u0027Dest Full (#)\u0027],result[\u0027Dest Jam (#)\u0027],result[\u0027Dest Disabled (#)\u0027],result[\u0027Dest Fault (#)\u0027],result[\u0027Divert Fail (#)\u0027],result[\u0027Lost (#)\u0027],result[\u0027Unsafe (#)\u0027],result[\u0027Dim Err (#)\u0027],result[\u0027Gap Err (#)\u0027],result[\u0027Unknown (#)\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Total (%)\",\"Diverted (%)\",\"Dest Full (%)\",\"Dest Jam (%)\",\"Dest Disabled (%)\",\"Dest Fault (%)\",\"Divert Fail (%)\",\"Lost (%)\",\"Unsafe (%)\",\"Dim Err (%)\",\"Gap Error (%)\",\"Unknown (%)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (%)\u0027],result[\u0027Diverted (%)\u0027],result[\u0027Dest Full (%)\u0027],result[\u0027Dest Jam (%)\u0027],result[\u0027Dest Disabled (%)\u0027],result[\u0027Dest Fault (%)\u0027],result[\u0027Divert Fail (%)\u0027],result[\u0027Lost (%)\u0027],result[\u0027Unsafe (%)\u0027],result[\u0027Dim Err (%)\u0027],result[\u0027Gap Err (%)\u0027],result[\u0027Unknown (%)\u0027]])\n\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\theaders \u003d [\"Start Timestamp\", \"Hour\",\"Total (pph)\",\"Diverted (pph)\",\"Dest Full (pph)\",\"Dest Jam (pph)\",\"Dest Disabled (pph)\",\"Dest Fault (pph)\",\"Divert Fail (pph)\",\"Lost (pph)\",\"Unsafe (pph)\",\"Dim Err (pph)\",\"Gap Error (pph)\",\"Unknown (pph)\"]\n\t\t\t\tfor result in test_table:\n\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Total (pph)\u0027],result[\u0027Diverted (pph)\u0027],result[\u0027Dest Full (pph)\u0027],result[\u0027Dest Jam (pph)\u0027],result[\u0027Dest Disabled (pph)\u0027],result[\u0027Dest Fault (pph)\u0027],result[\u0027Divert Fail (pph)\u0027],result[\u0027Lost (pph)\u0027],result[\u0027Unsafe (pph)\u0027],result[\u0027Dim Err (pph)\u0027],result[\u0027Gap Err (pph)\u0027],result[\u0027Unknown (pph)\u0027]])\n\t\t\t\t\n\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Hourly Lane.csv\u0027, data \u003d csv)\n\t\t\t\n\t\t\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 12:\n\t\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Dumper cycles\").getChild(\"Dumper cycles\").props.filter.results.data\n\t\t\tif(len(results) \u003e 0):\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1\",\"Cycles of ULGL2\",\"Cycles of ULGL3\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1\u0027],result[\u0027Cycles of ULGL2\u0027],result[\u0027Cycles of ULGL3\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1 (%)\",\"Cycles of ULGL2 (%)\",\"Cycles of ULGL3 (%)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1 (%)\u0027],result[\u0027Cycles of ULGL2 (%)\u0027],result[\u0027Cycles of ULGL3 (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1 (cph)\",\"Cycles of ULGL2 (cph)\",\"Cycles of ULGL3 (cph)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1 (cph)\u0027],result[\u0027Cycles of ULGL2 (cph)\u0027],result[\u0027Cycles of ULGL3 (cph)\u0027]])\n\t\t\t\t\t\n\t\t\telse:\n\t\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Dumper cycles\").getChild(\"Dumper cycles\").props.data)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1\",\"Cycles of ULGL2\",\"Cycles of ULGL3\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1\u0027],result[\u0027Cycles of ULGL2\u0027],result[\u0027Cycles of ULGL3\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1 (%)\",\"Cycles of ULGL2 (%)\",\"Cycles of ULGL3 (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1 (%)\u0027],result[\u0027Cycles of ULGL2 (%)\u0027],result[\u0027Cycles of ULGL3 (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1 (cph)\",\"Cycles of ULGL2 (cph)\",\"Cycles of ULGL3 (cph)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1 (cph)\u0027],result[\u0027Cycles of ULGL2 (cph)\u0027],result[\u0027Cycles of ULGL3 (cph)\u0027]])\t\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Dumper cycles.csv\u0027, data \u003d csv)\n\t\t\t\t\t\n\t\t\t\t\t\n\telif self.getSibling(\"Statistics\").props.currentTabIndex \u003d\u003d 10:\n\n\t\t\tresults \u003d self.parent.getChild(\"Statistics\").getChild(\"Total Full1\").getChild(\"Total Full1\").props.filter.results.data\n\t\t\tif(len(results) \u003e 0):\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1\",\"Cycles of ULGL2\",\"Cycles of ULGL3\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1\u0027],result[\u0027Cycles of ULGL2\u0027],result[\u0027Cycles of ULGL3\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1 (%)\",\"Cycles of ULGL2 (%)\",\"Cycles of ULGL3 (%)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1 (%)\u0027],result[\u0027Cycles of ULGL2 (%)\u0027],result[\u0027Cycles of ULGL3 (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Start Timestamp\",\"Hour\",\"Cycles of ULGL1 (cph)\",\"Cycles of ULGL2 (cph)\",\"Cycles of ULGL3 (cph)\"]\n\t\t\t\t\tfor result in results:\n\t\t\t\t\t\tdata.append([result[\u0027Start Timestamp\u0027],result[\u0027Hour\u0027],result[\u0027Cycles of ULGL1 (cph)\u0027],result[\u0027Cycles of ULGL2 (cph)\u0027],result[\u0027Cycles of ULGL3 (cph)\u0027]])\n\t\t\t\n\t\t\telse:\n\t\t\t\ttest_table \u003d system.dataset.toPyDataSet(self.parent.getChild(\"Statistics\").getChild(\"Total Full1\").getChild(\"Total Full1\").props.data)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\tif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Count\":\n\t\t\t\t\theaders \u003d [\"Lane\",\"Total (#)\",\"DestFull (#)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Lane\u0027],result[\u0027Total (#)\u0027],result[\u0027DestFull (#)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Lane\",\"Total (%)\",\"DestFull (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Lane\u0027],result[\u0027Total (%)\u0027],result[\u0027DestFull (%)\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Rate\":\n\t\t\t\t\theaders \u003d [\"Lane\",\"Total (pph)\",\"DestFull (pph)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Lane\u0027],result[\u0027Total (pph)\u0027],result[\u0027DestFull (pph)\u0027]])\t\t\t\t\t\t\t\n\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Lane Total Full.csv\u0027, data \u003d csv)\n\t\t\t\n\telif 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test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027Total_Jam\u0027],result[\u0027Dumpers_jam\u0027],result[\u0027Inbound_jam\u0027],result[\u0027Runout_jam\u0027],result[\u0027Sorter_Recirc_jam\u0027]])\n\t\t\t\telif self.parent.getChild(\"Aggregation_Mode\").getChild(\"Dropdown_Aggregation_mode\").props.value \u003d\u003d \"Percentage\":\n\t\t\t\t\theaders \u003d [\"Start Stamp\",\"End Stamp\",\"Total Jam (%)\",\"Dumpers Jam (%)\", \"Inbound Jam (%)\",\"Runout Jam (%)\",\"Sorter Recirc Jam (%)\"]\n\t\t\t\t\tfor result in test_table:\n\t\t\t\t\t\tdata.append([result[\u0027Startstamp\u0027],result[\u0027Endtstamp\u0027],result[\u0027Total_perc\u0027],result[\u0027Dumpers_perc\u0027],result[\u0027Inbound_perc\u0027],result[\u0027Runout_perc\u0027],result[\u0027Sorter_Recirc_perc\u0027]])\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\n\t\t\ttable \u003d system.dataset.toDataSet(headers, data)\t\n\t\t\tcsv \u003d system.dataset.toCSV(table,1,0,1)\n\t\t\tsystem.perspective.download(filename \u003d str_date+\u0027 Jam Areas.csv\u0027, data \u003d csv)\t\t\t\t\t\t\n\t\t\t\t\t"
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},
"meta": {
"name": "ExportToCSV",
"tooltip": {
"enabled": true,
"location": "bottom",
"style": {
"backgroundColor": "#2B2B2BBF",
"color": "#FFFFFF",
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"meta": {
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"label": "Past 30 Min",
"value": "Past 30 Min"
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{
"label": "Past Hour",
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"binding": {
"config": {
"expression": "{../Period.props.value} \u003d \"Custom\""
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"input": "\"Current Day\"",
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"input": "\"Wrap Down\"",
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{
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"type": "map"
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"formattedValue": "Aug 4, 2025 6:08 PM",
"formattedValues": {
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"position": {
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"type": "ia.display.label"
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{
"meta": {
"name": "End Date"
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"position": {
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{
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"output": "todate(dateFormat(dateArithmetic(now(),0, \"hour\"), \"yyyy-MM-dd HH:mm:ss\"))"
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{
"input": "Past 2 Hour",
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},
{
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},
{
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{
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"input": "Night",
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{
"input": "Wrap Down",
"output": "if (dateFormat(dateArithmetic(now(),0, \"Day\"), \"HH:mm:ss\")\u003c\"23:30:00\",\r todate(dateFormat(dateArithmetic(now(0),0, \"Day\"), \"yyyy-MM-dd 2:30:00\")),\r if (dateFormat(dateArithmetic(now(),0, \"Day\"), \"HH:mm:ss\")\u003c\"2:30:00\",\r todate(dateFormat(dateArithmetic(now(),0, \"Day\"), \"yyyy-MM-dd HH:mm:ss\")), todate(dateFormat(dateArithmetic(now(0),0, \"Day\"), \"yyyy-MM-dd 2:30:00\"))))"
},
{
"input": "Current Sort",
"output": "todate(dateFormat(dateArithmetic(now(),0, \"hour\"), \"yyyy-MM-dd HH:mm:ss\"))"
}
],
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"type": "map"
}
],
"type": "property"
},
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"enabled": null,
"script": "\t\n\tif self.getSibling(\"Period\").props.value !\u003d \"Custom\":\n\t\tself.props.value \u003d self.props.endDate"
}
},
"props.maxDate": {
"binding": {
"config": {
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},
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}
},
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"binding": {
"config": {
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},
"type": "expr"
}
}
},
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"dismissOnSelect": false,
"formattedValue": "Aug 4, 2025 7:08 PM",
"formattedValues": {
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"datetime": "Mar 29, 2021 1:37 PM",
"time": "1:37 PM"
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},
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}
],
"meta": {
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},
"position": {
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"x": 0.0025,
"y": 0.0059
},
"propConfig": {
"custom.EndDate": {
"binding": {
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},
"type": "property"
}
},
"custom.StartDate": {
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"config": {
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},
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}
}
},
"props": {
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"fontFamily": "Arial"
}
},
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},
{
"meta": {
"name": "Info",
"tooltip": {
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"textAlign": "left",
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"binding": {
"config": {
"expression": "if ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 0,\r\n\t\"About: Induct Details\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time of the first value determined by the selected period.\"+\r\n\t\"\\n\"+\"End Timestamp - time of the last value determined by the selected period.\"+\r\n\t\"\\n\"+\"Sorter Number - sorter name.\"+\r\n\t\"\\n\"+\"Induct Number - induct name.\"+\r\n\t\"\\n\"+\"Total Count - the total number of parcels.\"+\r\n\t\"\\n\"+\"Single Carrier Count - the number of single parcels.\"+\r\n\t\"\\n\"+\"Double Carrier Count - the number of paired parcels.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 1,\r\n\t\"About: Scanner Details\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time of the first value determined by the selected period.\"+\r\n\t\"\\n\"+\"End Timestamp - time of the last value determined by the selected period.\"+\r\n\t\"\\n\"+\"Sorter Number - sorter name.\"+\r\n\t\"\\n\"+\"Scanner Number - scanner name.\"+\r\n\t\"\\n\"+\"Total Count - total number of scanned parcels.\"+\r\n\t\"\\n\"+\"Good Read Count - number of good reads.\"+\r\n\t\"\\n\"+\"No Read Count - number of noreads.\"+\r\n\t\"\\n\"+\"Multi Read Count - number of multireads.\"+\r\n\t\"\\n\"+\"No Code Count - number of no codes.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 2,\r\n\t\"About: Sorter Summary\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time of the first value determined by the selected period.\"+\r\n\t\"\\n\"+\"End Timestamp - time of the last value determined by the selected period.\"+\r\n\t\"\\n\"+\"Sorter Number - sorter name.\"+\r\n\t\"\\n\"+\"Inducted - the total number of received parcels.\"+\r\n\t\"\\n\"+\"Sorted - the number of parcels sorted.\"+\r\n\t\"\\n\"+\"AWCS Recirc - the number of parcels sent for recirc.\"+\r\n\t\"\\n\"+\"Operational Recirc - \"+\r\n\t\"\\n\"+\"Machine Recirc - \",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 3,\r\n\t\"About: Sorter Details\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time of the first value determined by the selected period.\"+\r\n\t\"\\n\"+\"End Timestamp - time of the last value determined by the selected period.\"+\r\n\t\"\\n\"+\"Sorter Number - sorter name.\"+\r\n\t\"\\n\"+\"Inducted Count - the total number of received parcels.\"+\r\n\t\"\\n\"+\"Sorted Count - the number of parcels sorted.\"+\r\n\t\"\\n\"+\"Assigned Count - not applicable.\"+\r\n\t\"\\n\"+\"Destination Inv Count - the total number of the requested destination \\n\\t\\tassigned by AWCS is not valid for the current scan point or sorter.\"+\r\n\t\"\\n\"+\"Dest None Count - not applicable.\"+\r\n\t\"\\n\"+\"Dest Dis Count - not applicable.\"+\r\n\t\"\\n\"+\"Destination Full Count - the total number of the requested destination for \\n\\t\\tthe container was full. \"+\r\n\t\"\\n\"+\"Unexpected Count - the total number of an unexpected container was \\n\\t\\tidentified during sortation.\"+\r\n\t\"\\n\"+\"Destination Fault Count - the total number of the requested destination \\n\\t\\tfor the container was non-operational due to a fault\"+\r\n\t\"\\n\"+\"Divert Fail Count - the total number of the sorter attempted to divert \\n\\t\\tthe container to the requested destination\tbut failed. \"+\r\n\t\"\\n\"+\"Gap Error Count - the total number of containers were inducted into the \\n\\t\\tsorter with less than the minimum gap between containers the \\n\\t\\tsorter supports.\"+\r\n\t\"\\n\"+\"Lost Count - the total number of the container was lost on the sorter after \\n\\t\\tit was scanned at a scan point.\"+\r\n\t\"\\n\"+\"Track Error - the total number of the container was lost on the sorter after \\n\\t\\tit was scanned at a scan point.\"+\r\n\t\"\\n\"+\"Unknown Count - the total number of\"+\r\n\t\"\\n\"+\"Unsafe Count - the total number of the sorter did not attempt to divert \\n\\t\\tthe container to the requested destination because the container \\n\\t\\twas unable to be diverted accurately or safely\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 4,\r\n\t\"About: Lane Details\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time of the first value determined by the selected period.\"+\r\n\t\"\\n\"+\"End Timestamp - time of the last value determined by the selected period.\"+\r\n\t\"\\n\"+\"Sorter Number - sorter name.\"+\r\n\t\"\\n\"+\"Lane/Chute Number - lane/chute name.\"+\r\n\t\"\\n\"+\"Total Count - total number of diverted parcels on this chute.\"+\r\n\t\"\\n\"+\"Diverted Count - the number of successfully diverted parcels to this chute.\"+\r\n\t\"\\n\"+\"Destination Full Count - the number of full states.\"+\r\n\t\"\\n\"+\"Destination Jam Count - the number of jam states.\"+\r\n\t\"\\n\"+\"Destination Disabled Count - the number of Disabled states.\"+\r\n\t\"\\n\"+\"Destination Fault Count - not applicable.\"+\r\n\t\"\\n\"+\"Divert Fail Count - the number of unsuccessfully diverted parcels to this chute.\"+\r\n\t\"\\n\"+\"Lost Count - not applicable.\"+\r\n\t\"\\n\"+\"Unsafe Count - not applicable.\"+\r\n\t\"\\n\"+\"Dim Error - not applicable.\"+\r\n\t\"\\n\"+\"Gap Error Count - not applicable.\"+\r\n\t\"\\n\"+\"Unknown Count - not applicable.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 5,\r\n\t\"About: Hourly Induct\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time value for counting on hourly values.\"+\r\n\t\"\\n\"+\"Hour – Hour of the day (H1-H24) - time in the selected period \\n\\t\\tdivided by whole hours. The choice of the time period \\n\\t\\tthat will be viewed for the Hourly tables should be \\n\\t\\tin whole hours (example: 7:00).\"+\r\n\t\"\\n\"+\"Total (#) - the total number of parcels.\"+\r\n\t\"\\n\"+\"Single Carrier (#) - the number of single parcels.\"+\r\n\t\"\\n\"+\"Double Carrier (#) - the number of paired parcels.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 6,\r\n\t\"About: Hourly Scanner\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time value for counting on hourly values.\"+\r\n\t\"\\n\"+\"Hour – Hour of the day (H1-H24) - time in the selected period \\n\\t\\tdivided by whole hours. The choice of the time period \\n\\t\\tthat will be viewed for the Hourly tables should be \\n\\t\\tin whole hours (example: 7:00).\"+\r\n\t\"\\n\"+\"Total (#) - total number of scanned parcels.\"+\r\n\t\"\\n\"+\"Good read (#) - number of good reads.\"+\r\n\t\"\\n\"+\"No Read (#) - number of noreads.\"+\r\n\t\"\\n\"+\"Multi Read (#) - number of multireads.\"+\r\n\t\"\\n\"+\"No Code (#) - number of no codes.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 7,\r\n\t\"About: Hourly Sorter Summary\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time value for counting on hourly values.\"+\r\n\t\"\\n\"+\"Hour – Hour of the day (H1-H24) - time in the selected period \\n\\t\\tdivided by whole hours. The choice of the time period \\n\\t\\tthat will be viewed for the Hourly tables should be \\n\\t\\tin whole hours (example: 7:00).\"+\r\n\t\"\\n\"+\"Total Inducted(#) - the total number of received parcels.\"+\r\n\t\"\\n\"+\"Total Sorted(#) - the number of parcels sorted.\"+\r\n\t\"\\n\"+\"AWCS Recirculate (#) - the number of parcels sent for recirc.\"+\r\n\t\"\\n\"+\"Operational Recirculate(#) - \"+\r\n\t\"\\n\"+\"Machine Recirculate(#) - \",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 8,\r\n\t\"About: Hourly Sorter Details\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time value for counting on hourly values.\"+\r\n\t\"\\n\"+\"Hour – Hour of the day (H1-H24) - time in the selected period \\n\\t\\tdivided by whole hours. The choice of the time period \\n\\t\\tthat will be viewed for the Hourly tables should be \\n\\t\\tin whole hours (example: 7:00).\"+\r\n\t\"\\n\"+\"Inducted (#) - the total number of received parcels.\"+\r\n\t\"\\n\"+\"Sorted (#) - the number of parcels sorted.\"+\r\n\t\"\\n\"+\"Assigned (#) - not applicable.\"+\r\n\t\"\\n\"+\"Destination Inv (#) - the total number of the requested destination \\n\\t\\tassigned by AWCS is not valid for the current scan point or sorter.\"+\r\n\t\"\\n\"+\"Dest None (#) - not applicable.\"+\r\n\t\"\\n\"+\"Dest Dis Count - not applicable.\"+\r\n\t\"\\n\"+\"Destination Full (#) - the total number of the requested destination for \\n\\t\\tthe container was full.\"+\r\n\t\"\\n\"+\"Unexpected (#) - the total number of an unexpected container was \\n\\t\\tidentified during sortation.\"+\r\n\t\"\\n\"+\"Destination Fault (#) - the total number of the requested destination \\n\\t\\tfor the container was non-operational due to a fault.\"+\r\n\t\"\\n\"+\"Divert Fail (#) - - the total number of the sorter attempted to divert \\n\\t\\tthe container to the requested destination but failed.\"+\r\n\t\"\\n\"+\"Gap Error (#) - the total number of containers were inducted into the \\n\\t\\tsorter with less than the minimum gap between containers the \\n\\t\\tsorter supports.\"+\r\n\t\"\\n\"+\"Lost (#) - the total number of the container was lost on the sorter after \\n\\t\\tit was scanned at a scan point.\"+\r\n\t\"\\n\"+\"Track Error (#) - the total number of the container was lost on the sorter after \\n\\t\\tit was scanned at a scan point.\"+\r\n\t\"\\n\"+\"Unknown Count (#) - \"+\r\n\t\"\\n\"+\"Unsafe Count (#) - the total number of the sorter did not attempt to divert \\n\\t\\tthe container to the requested destination because the container \\n\\t\\twas unable to be diverted accurately or safely\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 9,\r\n\t\"About: Hourly Lane Details\"+ \r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Start Timestamp - time value for counting on hourly values.\"+\r\n\t\"\\n\"+\"Hour – Hour of the day (H1-H24) - time in the selected period \\n\\t\\tdivided by whole hours. The choice of the time period \\n\\t\\tthat will be viewed for the Hourly tables should be \\n\\t\\tin whole hours (example: 7:00).\"+\r\n\t\"\\n\"+\"Total (#) - total number of diverted parcels on this chute.\"+\r\n\t\"\\n\"+\"Diverted (#) - the number of successfully diverted parcels to this chute.\"+\r\n\t\"\\n\"+\"Destination Full (#) - the number of full states.\"+\r\n\t\"\\n\"+\"Destination Jam (#) - the number of jam states.\"+\r\n\t\"\\n\"+\"Destination Disabled (#) - the number of Disabled states.\"+\r\n\t\"\\n\"+\"Destination Fault Count - not applicable.\"+\r\n\t\"\\n\"+\"Divert Fail (#) - the number of unsuccessfully diverted parcels to this chute.\"+\r\n\t\"\\n\"+\"Lost (#) - not applicable.\"+\r\n\t\"\\n\"+\"Unsafe (#) - not applicable.\"+\r\n\t\"\\n\"+\"Dim (#) - not applicable.\"+\r\n\t\"\\n\"+\"Gap Error (#) - not applicable.\"+\r\n\t\"\\n\"+\"Unknown (#) - not applicable.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 10,\r\n\t\"About: Lane Total Full\"+\t\r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Lane Number - lane name.\"+\r\n\t\"\\n\"+\"Total Count - total number of diverted parcels on this chute.\"+\r\n\t\"\\n\"+\"Destination Full Count - the number of full states.\",\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 11,\r\n\t\"About: Jam by Area\"+\t\r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Jam counts by areas\",\r\n\t\r\nif ({view.params.Table} \u003d \"Statistics\" \u0026\u0026 {view.params.Tab_ID} \u003d 12,\r\n\t\"About: Dumper cycles\"+\t\r\n\t\"\\n\"+\r\n\t\"\\n\"+\"Cycles counts by dumpers\",\t\t\r\n\r\n\"not response\")))))))))))))"
},
"type": "expr"
}
}
},
"props": {
"fit": {
"mode": "fill"
},
"source": "/system/images/MyIcon/question64x64.png",
"style": {
"cursor": "pointer"
}
},
"type": "ia.display.image"
},
{
"meta": {
"name": "Label"
},
"position": {
"height": 0.0344,
"width": 0.2536,
"x": 0.5195,
"y": 0.0041
},
"propConfig": {
"props.text": {
"binding": {
"config": {
"designerUseLimit": false,
"parameters": {
"endtime": "{../Period_not_Global_0.custom.EndDate}",
"starttime": "{../Period_not_Global_0.custom.StartDate}"
},
"polling": {
"enabled": true,
"rate": "300"
},
"queryPath": "Statistics/Max PPH 5 Min"
},
"transforms": [
{
"code": "\t\n\tmax_pph \u003d system.dataset.toPyDataSet(value)\n\treturn \"Highest Sorted PPH at 5 min Interval: \" + str(int(max_pph[0][0])) + \" pph\"\n\t\n\t",
"type": "script"
}
],
"type": "query"
}
}
},
"props": {
"style": {
"color": "#FFFFFF",
"fontFamily": "Arial",
"fontSize": 20
}
},
"type": "ia.display.label"
},
{
"children": [
{
"meta": {
"name": "Label_Lane"
},
"position": {
"basis": "70px"
},
"props": {
"style": {
"color": "#000000"
},
"text": "Dumper:"
},
"type": "ia.display.label"
},
{
"meta": {
"name": "Dumper"
},
"position": {
"basis": "171px"
},
"props": {
"options": [
{
"label": "ULGL1-1",
"value": "ULGL1-1"
},
{
"label": "ULGL2-1",
"value": "ULGL2-1"
},
{
"label": "ULGL3-1",
"value": "ULGL3-1"
}
],
"value": "S0101"
},
"type": "ia.input.dropdown"
}
],
"meta": {
"name": "Dumper Drop Down_0",
"visible": false
},
"position": {
"height": 0.0269,
"width": 0.1219,
"x": 0.8469,
"y": 0.0922
},
"propConfig": {
"meta.visible": {
"binding": {
"config": {
"expression": "if ({../Statistics.props.currentTabIndex} \u003d 12 ,\r\ntrue,\r\nfalse)"
},
"enabled": false,
"type": "expr"
}
}
},
"props": {
"style": {
"fontFamily": "Arial"
}
},
"type": "ia.container.flex"
}
],
"meta": {
"name": "root"
},
"position": {
"x": -0.0073,
"y": -0.0011
},
"props": {
"mode": "percent",
"style": {
"backgroundColor": "#1A4A5E"
}
},
"type": "ia.container.coord"
}
}
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