Transaction
ID: 87ec690f72...b5f5
Inputs (28)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.215 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.18 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.58 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.76 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.54 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.12 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.19 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.34 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.182 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.611 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.59 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.46 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.85 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.34 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.128 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.15 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
5.41 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.29 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
4.17 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.47 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.27 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.359 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.88 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.636 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.01 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.5 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.92 ERG
Outputs (29)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.21 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.17 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.58 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.75 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.53 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.12 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.19 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.33 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.177 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.606 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.59 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.46 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.84 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.33 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.123 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.04 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.15 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
5.41 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.29 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.16 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.46 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.27 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.354 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.88 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.631 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.5 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.91 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.14 ERG
Transaction Details
Confirmations: 1,028,224
Total coins transferred: 63.18 ERG
Fees: 0.14 ERG
Fees per byte: 0.000003176 ERG
Raw Transaction Data
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],
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "387a0103939ec6dbed241f24fe0efc384062d76c3fb8183ebd05216f54cafd66",
"mainChain": true
},
{
"boxId": "107b18aff11c9b1b96a893ff965a77a251c914b40dbca76ff1d33ec5213013b0",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 1174000000,
"index": 1,
"globalIndex": 15936413,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "ea3b1be239043c8ee95eb3e5ea343e3400195ef44ddeaa29a296f87d80a6f877",
"mainChain": true
},
{
"boxId": "e09bea6f686e1b38be2f21529bc19e3926b12e128947d2aa45d13326e1366317",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 3575000000,
"index": 2,
"globalIndex": 15936414,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "b95b7b0a4f2fb997c5a6911a4317f06315571cfd743d347521818a1fcfbc8938",
"mainChain": true
},
{
"boxId": "ecee0232f669bc2edf9ce776871106609b08d7b7bf0c1fd2b58de214c1ea3472",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2751000000,
"index": 3,
"globalIndex": 15936415,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "1cbb0b1a3570bb81c74b11a85c17fbb0076335b7fa2f2299e5d86451e896e7cd",
"mainChain": true
},
{
"boxId": "bf531a32bbf9de5f284c505a1e9cbcadda23312074078c8040086c63299686b0",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 1533000000,
"index": 4,
"globalIndex": 15936416,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "b39e9b07a27005c2e90a4d7cf099a241751d027c85062a35662d5fd958d8d8a9",
"mainChain": true
},
{
"boxId": "e020d7015bdc806bb66166e9ac4745c0f82b8439359b3f0b1a46f2b116b9f2ad",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 3118000000,
"index": 5,
"globalIndex": 15936417,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "35449ab7b533501d7912b0d019c3ad1fa79f8586df9d7ec1813c21e025748403",
"mainChain": true
},
{
"boxId": "1c26a10141a2602855b707761334b4e0adc6d0ed25b156eaec38a6eb88574cbf",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2189000000,
"index": 6,
"globalIndex": 15936418,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "412d31747a14e4c8c996ff292876d7aa759a23ac690dd23ecde44a2135ded879",
"mainChain": true
},
{
"boxId": "6cedc1cdecd7b8f19d29122e53b1582671eeac17d6b90a6735ce3f75565c91c3",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2330000000,
"index": 7,
"globalIndex": 15936419,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "8ce8fb26b560492cdab45c222b7e64f8fd13a888d51b944bae7513f9f693c249",
"mainChain": true
},
{
"boxId": "2352e737060d3112aa11d4ef0fa797c82776bff1ee5268a4e6038379d127b457",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 177000000,
"index": 8,
"globalIndex": 15936420,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "4f085924fff43594eec0975bc1de0cbf2b917950a36597bc5dba556e8515eebc",
"mainChain": true
},
{
"boxId": "1e65813b6ea83456365f1ea7d452bb19368b9925ae6a0c55db453256f0c42baa",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 606000000,
"index": 9,
"globalIndex": 15936421,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "5d7e246fa13d6823a2dff2417994c78e6260d09aaf7823526c143dc0be8c7013",
"mainChain": true
},
{
"boxId": "c73d892413fa9dd7363d82eb59dde2e2ff773b26e23c937a800b102f7612716c",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 1586000000,
"index": 10,
"globalIndex": 15936422,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "f533095af98e0ac4c791e81b3ad08366505f83b032c9309a676555ad5d8255db",
"mainChain": true
},
{
"boxId": "b1ec29767cb95b2d9de7a3d128d722a3eff9d490cdf8098a2be268e15e77f9d2",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 3455000000,
"index": 11,
"globalIndex": 15936423,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "59b06f246ba11a7b26f9bddc2a844fd8896161bdcd2d8cfe0f9f42c85ca91609",
"mainChain": true
},
{
"boxId": "54bd209a45dbecef164eb9d0129791724fe5a6d6ebf5a4b8ba5baaaeb3e89483",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 3841000000,
"index": 12,
"globalIndex": 15936424,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "c8c15fd1e4ded8454624d099ea779b3ea4e3cf41dc53909866c62f666b15deda",
"mainChain": true
},
{
"boxId": "6a9835deb7c6aa824f30cc48b0badd60203bca8f051b80d454a159bf952f8346",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2333000000,
"index": 13,
"globalIndex": 15936425,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "1eb643809a79e752a2c05f685c9c544d405f3d07f7c30a975b167f200b13040c",
"mainChain": true
},
{
"boxId": "092ef4e2e4ab60b8d15c2354f2203f1852aa0e2f0b07c90adba5d73d554306bf",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 123000000,
"index": 14,
"globalIndex": 15936426,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "26c1f084f1a26d2058573fd16fe168dfe9a7cb0e047cef00a3840f3a35cb8ac5",
"mainChain": true
},
{
"boxId": "58eb5ef372a9b690927b6e083ff0ebcb6814911d6f87a1a2051a96e919c48e8e",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2042000000,
"index": 15,
"globalIndex": 15936427,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "88c3e6a947e16fd036b05b76d4c4cd09a6479620c049b8e4f7f2d4934b9fc0d4",
"mainChain": true
},
{
"boxId": "27885d309ae9108b1e27be42bb460e46c4ef9c9c043c67fd1b869d6db3845c35",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2148000000,
"index": 16,
"globalIndex": 15936428,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "da0455d6a28bcafb6321af36acfc169678402b2840f504e0e42c2600ec40179a",
"mainChain": true
},
{
"boxId": "43a3ba02e807810531ad36d87cf0aeb7ce38fb53100f2b5bb5fb4ae0aeddecff",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 5405000000,
"index": 17,
"globalIndex": 15936429,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "912cc7e5544ee62918d2a30b65a6311f47ba1ffe1bd6ec8b19581d3330199b59",
"mainChain": true
},
{
"boxId": "73aa6b13682046a59725ebe81be2c394e038f3bdcef41f5046fa91a30ff93cc1",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2289000000,
"index": 18,
"globalIndex": 15936430,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "710dd8fe4f223143705bb289e9000f3f259a6e179861d0e5132b3297124fedb8",
"mainChain": true
},
{
"boxId": "d41c0fc2b987ee4a6c5de5c9466bbd78a724421c32b534aa01ad333f7a660dd8",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 4160000000,
"index": 19,
"globalIndex": 15936431,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "103604000e20c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c004020400010104020101010004020500040404020500040405d00f0580897a040404020500040404000580897a050004000580897a0400040204000404040104040401050001000401040105000100040105000400040101000101050001010400050004000400040001000ec204101c0400040204000402010001000400040101000402010004000402040005020402040404040500040004000400040004000400010001000101d809d601c6a70711d602c6a7080c3c0e0ed60396830601e6c6a7040c3c0e11e6c6a7050c3c0e0ee6c6a7060c4c0ee67201e6720293b2a4730000a7d604b2a4730100d605c67204050c3c0e0ed606c67204040c3c0e11d607b2a5730200d608c672070711d609db63087207957203d195ed9595957203aee47202d9010a3c0e0e938c720a01c2b2a4730300730496830501e6c67204040c3c0e11e6c67204050c3c0e0ee6c67204060c4c0ee6c672040711e6c67204080c3c0e0e7305afe47205d9010a3c0e0e94dc0c1aade47206d9010c3c0e118c720c01028c720a01730673077308959593c27207c2a796830701e6c67207040c3c0e11e6c67207050c3c0e0ee6c67207060c4c0ee6c672070711e6c67207080c3c0e0e93c17207c1a793b1db630872077309730ad804d60ae47208d60be47201d60cb2720b730b00d60db2720a730c00ededed93b2720a730d009a720c730eed90720d7ea30591720db2720b730f0093b2720a731000b2720b7311009594720c7312938cb2db6308a7731300018cb2720973140001d801d60edb6308a79591b1720e7315938cb2720e731600018cb2720973170001938cb2720973180001c5a773199683050193e4c67207040c3c0e11e4720693e4c67207050c3c0e0ee4720593e4c67207060c4c0ee4c67204060c4c0e93e47208e4c67204071193e4c67207080c3c0e0ee4c67204080c3c0e0e731ad1731b0101d805d601c2a7d602b5a4d901026393c272027201d603b17202d604b2a4730000d605730195ef95ed917203730293c5b27202730300c5a7730495937203730573067307d1dad9010601957206d807d608e4c6b2a4730800040c3c0e11d609e4c67204040c3c0e11d60a99b072027309d9010a41639a8c720a01c18c720a02b0b57209d9010a3c0e11d801d60c8c720a028fb2720c730a00b2720c730b00730cd9010a413c0e119a8c720a01b28c8c720a0202730d00d60bade4c67204060c4c0ed9010b4c0ed801d60d9d9c7e8c720b0205720a730e86028c720b0199720d9e720d730fd60cada5d9010c63c2720cd60dada5d9010d63c1720dd60eb0b57208d9010e3c0e11d801d6108c720e028fb27210731000b272107311007312d9010e413c0e119a8c720e01b28c8c720e0202731300edededaf7208d9010f3c0e11d807d6118c720f01d612dc0c1aad7209d901123c0e118c7212010272117314d6138c720f02d614dad9011405d801d6169d9c99b0720b720ad90116414d0e998c7216018c8c721602029c73157eb17208057214b072087316d90116413c0e119a8c721601b28c8c721602027317009972169e7216731801b27213731900d615b27213731a00d616dc0c1a720c027211731bd617b27213731c0095947212731dd801d6189ab2b2ad7209d901183c0e118c721802721200731e00721495927218721595947216731fed93b2720d721600721893721773207321ed93721673229372177218959272147215959472167323ed93b2720d721600721493721773247325ed93721673269372177214af720bd9010f4d0ed801d6118c720f02959172117327d801d612dc0c1a720c028c720f01732895947212732993c1b2a57212007211732a732b9591720e732caea5d9010f63ed93c1720f720e93c2720f7201732d9594b2e4c672040711732e00732f938cb2db63087204733000017205d801d60fdb630872049591b1720f7331938cb2720f73320001720593c57204720573330193c272047334d17335",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "1b1fa91e5df8877bab53cf67d8c3744a164bea3d3242521eb009acde27b0b271",
"mainChain": true
},
{
"boxId": "89f23e23aeb8428494a3499ad5515e25690c54794cbfa8c262a9fbf240a42768",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2461000000,
"index": 20,
"globalIndex": 15936432,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "7fc05fdf3ed2a7472144ad255387ae7e30f53f584c496dd72462d3e1c162cf97",
"mainChain": true
},
{
"boxId": "b1242205a32447f01e79e8d3e8a0dbcc251d961fb3193e7561bb1f46231f5443",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 3265000000,
"index": 21,
"globalIndex": 15936433,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "5dfe210146f3113500606d97b0f4207268a757d7c1b8d09c4bc1159eec2a0ef7",
"mainChain": true
},
{
"boxId": "a2ab73e2925b89d0d434e8f5195c58a093bf0461bcb41c2d31fac2d1f583826b",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 354000000,
"index": 22,
"globalIndex": 15936434,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "e705c94a6685799c7f31b64e583d5411a33634277b7aaa3fffa341379ae6498c",
"mainChain": true
},
{
"boxId": "ce808ba4103873728e28fb2590c207a96f6bdc8c71708c571479179a51651e8f",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2875000000,
"index": 23,
"globalIndex": 15936435,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "8425e779ccdd468d530c1e4a57f5e03f145241383c84104385681b792931439f",
"mainChain": true
},
{
"boxId": "4b12fb5b98fa2196e88855f1f0af6a7c437758a982fe4ed39dc7a646b668b45f",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 631000000,
"index": 24,
"globalIndex": 15936436,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "d7107686cc4b0f3668e923919ff989659c4d1011613bd4029423f5196e7e75c9",
"mainChain": true
},
{
"boxId": "e76a996a5eb23399272dad1b2e42caf57340e1ca587c79098b2d37f5c915498d",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 3001000000,
"index": 25,
"globalIndex": 15936437,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "047ca6ce16a84439fc412f38e376ba29796485d2f2030ff8aade7ffbc528f3dd",
"mainChain": true
},
{
"boxId": "453caa3e1db123615488c7ccd78843ff7bda01d94a37f81073f3dd85a825c518",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2499000000,
"index": 26,
"globalIndex": 15936438,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "1c7afe85d2dc39e55e8a65917cbc37948aeef951d6a672e5bd939afbfae83c01",
"mainChain": true
},
{
"boxId": "a46df4845c9dc7c663cce1bdf63b7498979ec677bb437ae5cdec5f0696359c4d",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 2911000000,
"index": 27,
"globalIndex": 15936439,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "64c620fc21849869ee0bedbf235e5a0b5676ca3ee16cfa44f48aec2d09b63ed2",
"mainChain": true
},
{
"boxId": "3a77050aa54b2dda4be90da7595e1a122b5d53b04e44db761ac6e20d37a6807e",
"transactionId": "87ec690f7254af3df9f08222c53c065dff8fc04f0d2c1cc84e4944841ebcb5f5",
"blockId": "c42505cdea168f109d3abfdf31a786840ccfb57ef201370517c8625c98c11f7c",
"value": 140000000,
"index": 28,
"globalIndex": 15936440,
"creationHeight": 735535,
"settlementHeight": 735537,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "ca20d09f061abbe85ccf2dcdec83ed5a674f2190be7a53e02208638fe25aae3e",
"mainChain": true
}
],
"size": 44075,
"isUnconfirmed": false
}