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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: ortools/sat/cp_model.proto
package com.google.ortools.sat;
/**
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*/
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/**
*
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* It will be referred to by an int32 corresponding to its index in a
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* Depending on the context, a reference to a variable whose domain is in [0, 1]
* can also be seen as a Boolean that will be true if the variable value is 1
* and false if it is 0. When used in this context, the field name will always
* contain the word "literal".
* Negative reference (advanced usage): to simplify the creation of a model and
* for efficiency reasons, all the "literal" or "variable" fields can also
* contain a negative index. A negative index i will refer to the negation of
* the integer variable at index -i -1 or to NOT the literal at the same index.
* Ex: A variable index 4 will refer to the integer variable model.variables(4)
* and an index of -5 will refer to the negation of the same variable. A literal
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* The most common example being just [min, max].
* If min == max, then this is a constant variable.
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* Note that we check at validation that a variable domain is small enough so
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* The most common example being just [min, max].
* If min == max, then this is a constant variable.
* We have:
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* - min == domain.front();
* - max == domain.back();
* - for all i < n : min_i <= max_i
* - for all i < n-1 : max_i + 1 < min_{i+1}.
* Note that we check at validation that a variable domain is small enough so
* that we don't run into integer overflow in our algorithms. Because of that,
* you cannot just have "unbounded" variable like [0, kint64max] and should
* try to specify tighter domains.
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* The variable domain given as a sorted list of n disjoint intervals
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* The most common example being just [min, max].
* If min == max, then this is a constant variable.
* We have:
* - domain_size() is always even.
* - min == domain.front();
* - max == domain.back();
* - for all i < n : min_i <= max_i
* - for all i < n-1 : max_i + 1 < min_{i+1}.
* Note that we check at validation that a variable domain is small enough so
* that we don't run into integer overflow in our algorithms. Because of that,
* you cannot just have "unbounded" variable like [0, kint64max] and should
* try to specify tighter domains.
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* The most common example being just [min, max].
* If min == max, then this is a constant variable.
* We have:
* - domain_size() is always even.
* - min == domain.front();
* - max == domain.back();
* - for all i < n : min_i <= max_i
* - for all i < n-1 : max_i + 1 < min_{i+1}.
* Note that we check at validation that a variable domain is small enough so
* that we don't run into integer overflow in our algorithms. Because of that,
* you cannot just have "unbounded" variable like [0, kint64max] and should
* try to specify tighter domains.
*
*
* repeated int64 domain = 2;
* @param index The index to set the value at.
* @param value The domain to set.
* @return This builder for chaining.
*/
public Builder setDomain(
int index, long value) {
ensureDomainIsMutable();
domain_.setLong(index, value);
onChanged();
return this;
}
/**
*
* The variable domain given as a sorted list of n disjoint intervals
* [min, max] and encoded as [min_0, max_0, ..., min_{n-1}, max_{n-1}].
* The most common example being just [min, max].
* If min == max, then this is a constant variable.
* We have:
* - domain_size() is always even.
* - min == domain.front();
* - max == domain.back();
* - for all i < n : min_i <= max_i
* - for all i < n-1 : max_i + 1 < min_{i+1}.
* Note that we check at validation that a variable domain is small enough so
* that we don't run into integer overflow in our algorithms. Because of that,
* you cannot just have "unbounded" variable like [0, kint64max] and should
* try to specify tighter domains.
*
*
* repeated int64 domain = 2;
* @param value The domain to add.
* @return This builder for chaining.
*/
public Builder addDomain(long value) {
ensureDomainIsMutable();
domain_.addLong(value);
onChanged();
return this;
}
/**
*
* The variable domain given as a sorted list of n disjoint intervals
* [min, max] and encoded as [min_0, max_0, ..., min_{n-1}, max_{n-1}].
* The most common example being just [min, max].
* If min == max, then this is a constant variable.
* We have:
* - domain_size() is always even.
* - min == domain.front();
* - max == domain.back();
* - for all i < n : min_i <= max_i
* - for all i < n-1 : max_i + 1 < min_{i+1}.
* Note that we check at validation that a variable domain is small enough so
* that we don't run into integer overflow in our algorithms. Because of that,
* you cannot just have "unbounded" variable like [0, kint64max] and should
* try to specify tighter domains.
*
*
* repeated int64 domain = 2;
* @param values The domain to add.
* @return This builder for chaining.
*/
public Builder addAllDomain(
java.lang.Iterable values) {
ensureDomainIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, domain_);
onChanged();
return this;
}
/**
*
* The variable domain given as a sorted list of n disjoint intervals
* [min, max] and encoded as [min_0, max_0, ..., min_{n-1}, max_{n-1}].
* The most common example being just [min, max].
* If min == max, then this is a constant variable.
* We have:
* - domain_size() is always even.
* - min == domain.front();
* - max == domain.back();
* - for all i < n : min_i <= max_i
* - for all i < n-1 : max_i + 1 < min_{i+1}.
* Note that we check at validation that a variable domain is small enough so
* that we don't run into integer overflow in our algorithms. Because of that,
* you cannot just have "unbounded" variable like [0, kint64max] and should
* try to specify tighter domains.
*
*
* repeated int64 domain = 2;
* @return This builder for chaining.
*/
public Builder clearDomain() {
domain_ = emptyLongList();
bitField0_ = (bitField0_ & ~0x00000001);
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:operations_research.sat.IntegerVariableProto)
}
// @@protoc_insertion_point(class_scope:operations_research.sat.IntegerVariableProto)
private static final com.google.ortools.sat.IntegerVariableProto DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new com.google.ortools.sat.IntegerVariableProto();
}
public static com.google.ortools.sat.IntegerVariableProto getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
@java.lang.Override
public IntegerVariableProto parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new IntegerVariableProto(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public com.google.ortools.sat.IntegerVariableProto getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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