Transaction
ID: 2597d5205a...695e
Inputs (28)
Spent
Address:
Output transaction:
Settlement height:
Value:
2.69 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
4.96 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.52 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.43 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.5 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.99 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.95 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.871 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
5.08 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.594 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.229 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.115 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.08 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.51 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.59 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.01 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.37 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.74 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.44 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.47 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.17 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.47 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
3.71 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.496 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
4.8 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.19 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
2.44 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.97 ERG
Outputs (29)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.69 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.95 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.51 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.42 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.49 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.98 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.94 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.866 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
5.08 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.589 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.224 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.11 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.07 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.51 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.58 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.01 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.37 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.73 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.43 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.47 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.16 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.46 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.71 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.491 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.8 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.185 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.44 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.97 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.14 ERG
Transaction Details
Confirmations: 1,041,001
Total coins transferred: 63.38 ERG
Fees: 0.14 ERG
Fees per byte: 0.000003176 ERG
Raw Transaction Data
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{
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{
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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": "488c78c1d30074bb13c6da28d350faa43f96ae59bc035b8594b7c5fafd541aa4",
"mainChain": true
},
{
"boxId": "87a04887fa23a0ad7c7f31b8e9156d6e574eff52a7714ef17e49e8b74f5820d1",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 4953000000,
"index": 1,
"globalIndex": 15538267,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "ea5271daf1952bdc89afc45d33d5cc8eef39960bf2dd8a08e73baad28868b475",
"mainChain": true
},
{
"boxId": "b1f260afa8f078be88e33698a0f9ecb4429cfbdd9c5f921ece38e9fe140a87d4",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2513000000,
"index": 2,
"globalIndex": 15538268,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "d29678f3afee7ca79b21c25e24443fa546b3041befc27d4032d2b6bd6e64f700",
"mainChain": true
},
{
"boxId": "629048900693fc6b2df3604c54b824381ad82f374483a5c0f8e83c669e46ecad",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2424000000,
"index": 3,
"globalIndex": 15538269,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "d836114324c75a927f1caf05958858a752f86c8f9ba129668041b2b2c807e066",
"mainChain": true
},
{
"boxId": "12f93ec6dfd9599ab9890bcaa35c03fdd2b97866f3d3347a1dd78975260e8442",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 3494000000,
"index": 4,
"globalIndex": 15538270,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "fb901db2b7effa319187e588b863afde4bc2f65f61f71ec80f6e0bad08b8309f",
"mainChain": true
},
{
"boxId": "763f8e85e452cd771233232214e35505cb8cea5f84fe50c216073466998f2769",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2984000000,
"index": 5,
"globalIndex": 15538271,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "cc1f57ef85aa897f227ecd5636eec703cd25fd4901853f4173ea58439ccc1443",
"mainChain": true
},
{
"boxId": "f2287baffc888edafbc9fc8615ae2233dddda0b164823a52b3fadf3f123e9e04",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2943000000,
"index": 6,
"globalIndex": 15538272,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "773b79c2cd92f2ab87289dae31b93e696bd2d8a3303ccce7563fb3a7fc732d70",
"mainChain": true
},
{
"boxId": "1fcf952a1f1321a38b675d63adab7bb5e2cffa91cd1477e3706432645b284756",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 866000000,
"index": 7,
"globalIndex": 15538273,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "103cfd99629faef47a93284eadb0cab6cd70c4fce7750392db0f9737385be485",
"mainChain": true
},
{
"boxId": "84b0f8eb841fc75afa6c9afaf1f58594b8e4e102ddd02ee61ea40043d40d7347",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 5076000000,
"index": 8,
"globalIndex": 15538274,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "a1fa89a11c53293b099d10d0d7a13773caac12bf8f1f529fca794eb0189cc1b3",
"mainChain": true
},
{
"boxId": "450214253c27e19729632a4a56811efc1e40c565862153e51b9d9c94f35d520f",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 589000000,
"index": 9,
"globalIndex": 15538275,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "3e6b6bcf0417010d573beaf3a625e279aa07969b1b8e25a6fb63a3448b916137",
"mainChain": true
},
{
"boxId": "d6bdf769550e936de4e92e3e35680bf2dc0e36718ed7d4889f0efdf8d4304a2e",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 224000000,
"index": 10,
"globalIndex": 15538276,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "0e993e5449886f028e8a2aa21bae777bcffede2a895a8d71270988f24b46339d",
"mainChain": true
},
{
"boxId": "f1f504f5b5044e8c2b2a5bee4998d8cca4e2f69f4ebdf0f06272ee8d77a36b14",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 110000000,
"index": 11,
"globalIndex": 15538277,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "f1df1679a70d0f76db428271327bd31d025848dbc38653b4811cba112db7b9ee",
"mainChain": true
},
{
"boxId": "8d5f26090a7deec6bc15257c1482ae4c3c361a00e5940e5c458727464bff1031",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 1072000000,
"index": 12,
"globalIndex": 15538278,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "f415aed46bc97cc626fdddbdd43de89c980e143c301139b2d66ac5fe94927858",
"mainChain": true
},
{
"boxId": "ae9fecd96424591bcef9b3558f0939220604d8f057915e9755603e59bf575617",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 1509000000,
"index": 13,
"globalIndex": 15538279,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "afd6992955270055fc99c5435dbe6232e5c02ef790b64f06ab3e680b1417976e",
"mainChain": true
},
{
"boxId": "2977c9b628a1bec3d35b0317a5ccc1cef3bef9853421351c2836d079b9f5673e",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 1582000000,
"index": 14,
"globalIndex": 15538280,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "bd75feae9e407009c04c5320adfe3de5716aa9acc4efe673ce045ac1e5529f34",
"mainChain": true
},
{
"boxId": "b1e70870565fcbb021b3c589ede7beaee12c957873c1dc999e983efc07d8898d",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 3008000000,
"index": 15,
"globalIndex": 15538281,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "6282b9c529f30fa834ded266079cf0d182e7790cedd618fc046376a6ab8e3ac9",
"mainChain": true
},
{
"boxId": "1daa9edce256ebc3ef48cbdc80b8443e4375cd8186febdceee06fbb02550f6fc",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 1369000000,
"index": 16,
"globalIndex": 15538282,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "4163cb44b6bd0ccdcc32a494ddc1f4a0d05a8605032cd6fb4d53b0b2f383c4a3",
"mainChain": true
},
{
"boxId": "2e650af1a4441e6d324a0204ee55ffb6161b7876d8ad41752d316287fd57e9c2",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 3731000000,
"index": 17,
"globalIndex": 15538283,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "bcb45ab116ff243ee18462cd4178fac695b26e1ebdb1bd70fb3a1f2227227773",
"mainChain": true
},
{
"boxId": "b5bbe0504db64d0762d6fce523c34f4bf37f743b455a74f860a378403583885a",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2431000000,
"index": 18,
"globalIndex": 15538284,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "2b8202cde605b05711dd445cff843139e46deb6e3303343e23abf1446a0adab9",
"mainChain": true
},
{
"boxId": "45679a99fd48bd8b38dcdaccdaafdc7db7fc40f1324339a75cd9859e1976e055",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2465000000,
"index": 19,
"globalIndex": 15538285,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "19126ca5f7180bc45cca0db9112db5ca3f731bcc6b41edcc8975ee11994c1238",
"mainChain": true
},
{
"boxId": "0214b68d8db73e064114cc72f602bd7737618a3736b9e280d7ca950a82428ac4",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2160000000,
"index": 20,
"globalIndex": 15538286,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "993610f0e6faf70cec2fb4f0665682ba563ca01b5ac29c156cda920b0c71a505",
"mainChain": true
},
{
"boxId": "5f3870e6e81dfd6ae4259c5e16697b3e73b41da409525a813821fdedff6fad87",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 1464000000,
"index": 21,
"globalIndex": 15538287,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "70fd6e227109b11474cdb81bcfb173a30523dadbca72b291b915aee8ebf81781",
"mainChain": true
},
{
"boxId": "5c4da14e2e2401fc9e7ba1c56070f33588cfa0a37e5dd1b958a83b9d85694692",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 3708000000,
"index": 22,
"globalIndex": 15538288,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "1e6c2bc5b3f57081a278377a53c3c3550b87769407ea73530fc6e2de0f812eab",
"mainChain": true
},
{
"boxId": "77249c8689da9c4f6e830fc1519a0219e7021a9e5d31388ae103fd854b74b500",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 491000000,
"index": 23,
"globalIndex": 15538289,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "bbdd2b74f47323edf7fcc19b7af357d281dd228b618de40a37ab1db23c02cd5d",
"mainChain": true
},
{
"boxId": "0bc5d27ea7c344ce6e5efdcf86b57f5dbc1765e7eda01f5976b7585017f1b72c",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 4796000000,
"index": 24,
"globalIndex": 15538290,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "c51ae2d222698a8f0e4a1512a7d724dfd3405d845aa0b84638841f60e131d3c7",
"mainChain": true
},
{
"boxId": "3abd19742306e8d658bf46702ab57cdfdfa6287285706c761b236df6fdc98513",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 185000000,
"index": 25,
"globalIndex": 15538291,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "058bb48114b9b81b360d19ce10cfdb688764c0f23d03025332684ec4ce70215b",
"mainChain": true
},
{
"boxId": "e60609a13b944e79d0bda74b5dcbce0dd70921cbd7525b167763de192cc7053c",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 2439000000,
"index": 26,
"globalIndex": 15538292,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "0b557729b461f435373d4212a184617eed09638d3bef684eed79a37889df733f",
"mainChain": true
},
{
"boxId": "10d6e7e491c96dff2c014043993c02442cc41adb025443419c5b7c580398d89c",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 1965000000,
"index": 27,
"globalIndex": 15538293,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "169d46691a1c88d9e3fb5c9d85b7622102dabdbe248a9e77461d351ca8ea290f",
"mainChain": true
},
{
"boxId": "0e444c4c2f78bf97e84723af4970a8e27e8b6ec5cd2bf5d5362e737a147509ca",
"transactionId": "2597d5205a920301deeb3ffa21098669697363c6a9d931e796ddd5a1454e695e",
"blockId": "3cb01829cbc47281dc3e961c4ddbb5d522545cd60544b27409c838505b5e1842",
"value": 140000000,
"index": 28,
"globalIndex": 15538294,
"creationHeight": 727942,
"settlementHeight": 727945,
"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": "ce6e0cd5a0ebc12f68447a77ac3247a2489f20c84104e5eb43316aa99898ebd0",
"mainChain": true
}
],
"size": 44075,
"isUnconfirmed": false
}