江端智一のホームページ
Host sea-anemone.tech
HostName sea-anemone.tech
IdentityFile ~/.ssh/DefaultKey-ap-northeast-1.pem
User ubuntu(pemは、AWSから貰ったものを使うだけ)
/////////////////////////////////////////
// gcc -g life_0813.c -o life_0813
/////////////////////////////////////////
#include <stdio.h>
#include <stdlib.h>
/// グローバル変数で強行する
struct date
{
int day;
int month;
int year;
};
enum sex {woman, man};
enum marrige {unmarried, married, divorce, remarriage};
struct person {
int age; //年齢
enum sex sex; // 性別
enum marrige marrige; // 成婚
struct person *prev; /* 前の構造体を示すポインタ */
struct person *next; /* 次の構造体を示すポインタ */
};
double men[100],women[100]; // 年齢別人口 平成22年データ 単位は1000人
double men_death_rate[100],women_death_rate[100]; //死亡率 平成22年データ
double men_unmarried_rate[100],women_unmarried_rate[100]; //未婚率 平成22年データ
double men_existance_matching_rate[100]; // 有配偶率 (平成22年)
double women_existance_matching_rate[100]; // 有配偶率 (平成22年)
// 初婚、再婚関係なく、その世代に対して。
// 結婚している比率
double men_divorce_rate[100]; // 有配偶離婚率
double women_divorce_rate[100]; // 有配偶離婚率
// ○ 結婚している人に対する離婚率
double men_remarrige_ratio[100];
double women_remarrige_ratio[100]; // 再婚率 (2010年)
int initial_data();// 死亡率 平成22年データ (資料 厚生労働省大臣官房統計情報部人口動態・保健統計課「人口動態統計」)
void delete_person(
struct person **p_person,
struct person **p_first_person,
struct person **p_last_person) // メモリを消す処理e
{
struct person *temp_p_person;
if (*p_first_person == *p_last_person){
//printf("p_first_person == p_last_person\n");
exit(0);
}
if (*p_person == *p_first_person){ // 最初の場合
*p_first_person = (*p_person)->next;
(*p_first_person)->prev = NULL;
//printf("C1");
free(*p_person);
*p_person = *p_first_person;
}
else if (*p_person == *p_last_person){ //最後の場合
*p_last_person = (*p_person)->prev;
(*p_last_person)->next = NULL;
//printf("C2");
free(*p_person);
*p_person = *p_last_person;
}
else {
(*p_person)->next->prev = (*p_person)->prev;
(*p_person)->prev->next = (*p_person)->next;
temp_p_person = (*p_person)->prev; // 一つ前のポインタに退避
//printf("C3");
free(*p_person);
*p_person = temp_p_person;
}
}
population_counter(struct person *p_first_person)
{
struct person *p_person;
int count;
p_person = p_first_person; //最初の一人
count = 0;
while (p_person != NULL){
count++;
p_person = p_person->next;
}
//printf("count=%d \n", count);
}
int main ()
{
int i, k, count;
struct person *p_person, *p_prev_person, *p_next_person;
struct person *p_first_person, *p_last_person;
int women_pop, men_pop;
double dd;
// 日本国民一億人のデータを作る
//printf("checked -1.\r\n");
initial_data(); // 初期データ入力
//printf("checked 0.\r\n");
srand(10); // 乱数のシード
//////////// 現状データの入力 ////////////
// 最初の一人(0人目) 99歳の女性と仮定する。
p_person= (struct person *)malloc(sizeof(struct person));
if(p_person == NULL) {
printf("メモリが確保できません\n");
exit(EXIT_FAILURE);
}
p_person->sex = woman;
p_person->age = 99;
p_first_person = p_person; //最初の一人
// (最後に)ポインタをリンクする
p_person->prev = NULL;
p_prev_person = p_person;
for(i=99; i>=0; i--){
women_pop = women[i] * 1000;
men_pop = men[i] * 1000;
for(k=0; k<women_pop; k++){
p_person= (struct person *)malloc(sizeof(struct person));
if(p_person == NULL) {
printf("メモリが確保できません %d\n",i);
exit(EXIT_FAILURE);
}
p_person->sex = woman;
p_person->age = i;
// (最後に)ポインタをリンクする
p_prev_person->next = p_person;
p_person->prev = p_prev_person;
p_person->next = NULL;
p_prev_person = p_person;
}
for(k=0; k<men_pop; k++){
p_person= (struct person *)malloc(sizeof(struct person));
if(p_person == NULL) {
printf("メモリが確保できません %d\n",i);
exit(EXIT_FAILURE);
}
p_person->sex = man;
p_person->age = i;
// (最後に)ポインタをリンクする
p_prev_person->next = p_person;
p_person->prev = p_prev_person;
p_person->next = NULL;
p_prev_person = p_person;
}
}
p_last_person = p_person;
//printf("checked 1.\n");
// 既婚(離婚も含む)・未婚の入力 (乱数で入力する) (離婚人口も含む)
p_person = p_first_person; //最初の一人
while (p_person != NULL){
if (p_person->sex == woman){ // 女性の場合
if (women_unmarried_rate[p_person->age] >= rand()/32768.0){
p_person->marrige = unmarried;
}
else {
p_person->marrige = married;
}
}
else{// 男性の場合
if (men_unmarried_rate[p_person->age] >= rand()/32768.0){
p_person->marrige = unmarried;
}
else {
p_person->marrige = married;
}
}
p_person = p_person->next;
}
//printf("count=%d \n", count);
// 離婚させる (ここは男女で分ける必要ないが、詳細データが手に入った時に反映)
p_person = p_first_person; //最初の一人
while (p_person != NULL){
if (p_person->sex == woman){ // 女性の場合
if ((p_person->marrige == married) || (p_person->marrige == remarriage)){ // 結婚している
if( women_divorce_rate[p_person->age] >= rand()/32768.0){
p_person->marrige = divorce; // 離婚させる
}
}
}
else{// 男性の場合
if ((p_person->marrige == married) || (p_person->marrige == remarriage)){ // 結婚している
if( men_divorce_rate[p_person->age] >= rand()/32768.0){
p_person->marrige = divorce; // 離婚させる
}
}
}
p_person = p_person->next;
}
// 再婚させる
// 離婚している人に対する再婚率 (に変換する式)
// =
// 再婚率 x その世代の人口数 / 離婚(×未婚、結婚)人口
// としなければなない
// 上記の解釈間違いの可能性あり
// 離婚した人を再婚させる (ここは男女で分ける必要がある)
p_person = p_first_person; //最初の一人
while (p_person != NULL){
if (p_person->sex == woman){ // 女性の場合
if (p_person->marrige == divorce){ // 離婚している
if( women_remarrige_ratio[p_person->age] >= rand()/32768.0){
p_person->marrige = remarriage; // 再婚させる
}
}
}
else{// 男性の場合
if (p_person->marrige == divorce){ // 離婚している
if( men_remarrige_ratio[p_person->age] >= rand()/32768.0){
p_person->marrige = remarriage; // 再婚させる
}
}
}
p_person = p_person->next;
}
// (T.B.D.)
//初期値チェックルーチン
#if 1
p_person = p_first_person; //最初の一人
printf("性別,年齢,成婚\n");
while (p_person != NULL){
if (p_person->sex == woman)
printf("女性,");
else
printf("男性,");
printf("%d,",p_person->age);
if (p_person->marrige == unmarried)
printf("未婚\n");
else if (p_person->marrige == married)
printf("結婚\n");
else if (p_person->marrige == divorce)
printf("離婚\n");
else if (p_person->marrige == remarriage)
printf("再婚\n");
p_person = p_person->next;
}
//printf("count=%d \n", count);
#endif
//初期値チェックルーチン 終り
//////////// 現状データの入力 終わり ////////////
p_person = p_first_person; //最初の一人
count = 0;
while (p_person != NULL){
count++;
p_person = p_person->next;
}
//printf("count=%d \n", count);
// (1)100歳以上は、いない(死んだ)ことにする。
// → person->age が100になったらオブジェクトを開放
#if 0
//時間計測の為、コメントアウト
for(i=0; i<100; i++){//100年分を回す
//printf("%d\n",i);
p_person = p_first_person; //最初の一人
while (p_person != NULL){
p_person->age++;
if (p_person->age == 100){ //100歳以上は削除
delete_person(&p_person,&p_first_person,&p_last_person);
}
p_person = p_person->next;
}
population_counter(p_first_person);
}
p_person = p_first_person; //最初の一人
count = 0;
while (p_person != NULL){
count++;
p_person = p_person->next;
}
//printf("count=%d \n", count);
#endif // 時間計測の為、コメントアウト
}
int initial_data()
{
men[ 0]=549 ; men_death_rate[ 0]=0.0025 ;
men[ 1]=535 ; men_death_rate[ 1]=0.0004 ;
men[ 2]=535 ; men_death_rate[ 2]=0.0002 ;
men[ 3]=550 ; men_death_rate[ 3]=0.0002 ;
men[ 4]=548 ; men_death_rate[ 4]=0.0002 ;
men[ 5]=544 ; men_death_rate[ 5]=0.0001 ;
men[ 6]=542 ; men_death_rate[ 6]=0.0001 ;
men[ 7]=562 ; men_death_rate[ 7]=0.0001 ;
men[ 8]=574 ; men_death_rate[ 8]=0.0001 ;
men[ 9]=589 ; men_death_rate[ 9]=0.0001 ;
men[10]=597 ; men_death_rate[10]=0.0001 ;
men[11]=604 ; men_death_rate[11]=0.0001 ;
men[12]=604 ; men_death_rate[12]=0.0001 ;
men[13]=613 ; men_death_rate[13]=0.0001 ;
men[14]=610 ; men_death_rate[14]=0.0001 ;
men[15]=607 ; men_death_rate[15]=0.0003 ;
men[16]=627 ; men_death_rate[16]=0.0003 ;
men[17]=632 ; men_death_rate[17]=0.0003 ;
men[18]=621 ; men_death_rate[18]=0.0003 ;
men[19]=631 ; men_death_rate[19]=0.0003 ;
men[20]=623 ; men_death_rate[20]=0.0006 ;
men[21]=632 ; men_death_rate[21]=0.0006 ;
men[22]=648 ; men_death_rate[22]=0.0006 ;
men[23]=668 ; men_death_rate[23]=0.0006 ;
men[24]=683 ; men_death_rate[24]=0.0006 ;
men[25]=697 ; men_death_rate[25]=0.0007 ;
men[26]=723 ; men_death_rate[26]=0.0007 ;
men[27]=745 ; men_death_rate[27]=0.0007 ;
men[28]=754 ; men_death_rate[28]=0.0007 ;
men[29]=754 ; men_death_rate[29]=0.0007 ;
men[30]=764 ; men_death_rate[30]=0.0008 ;
men[31]=797 ; men_death_rate[31]=0.0008 ;
men[32]=818 ; men_death_rate[32]=0.0008 ;
men[33]=852 ; men_death_rate[33]=0.0008 ;
men[34]=873 ; men_death_rate[34]=0.0008 ;
men[35]=917 ; men_death_rate[35]=0.0010 ;
men[36]=960 ; men_death_rate[36]=0.0010 ;
men[37]=1012 ; men_death_rate[37]=0.0010 ;
men[38]=1028 ; men_death_rate[38]=0.0010 ;
men[39]=1010 ; men_death_rate[39]=0.0010 ;
men[40]=982 ; men_death_rate[40]=0.0015 ;
men[41]=954 ; men_death_rate[41]=0.0015 ;
men[42]=937 ; men_death_rate[42]=0.0015 ;
men[43]=916 ; men_death_rate[43]=0.0015 ;
men[44]=915 ; men_death_rate[44]=0.0015 ;
men[45]=713 ; men_death_rate[45]=0.0024 ;
men[46]=882 ; men_death_rate[46]=0.0024 ;
men[47]=826 ; men_death_rate[47]=0.0024 ;
men[48]=805 ; men_death_rate[48]=0.0024 ;
men[49]=778 ; men_death_rate[49]=0.0024 ;
men[50]=765 ; men_death_rate[50]=0.0038 ;
men[51]=770 ; men_death_rate[51]=0.0038 ;
men[52]=783 ; men_death_rate[52]=0.0038 ;
men[53]=761 ; men_death_rate[53]=0.0038 ;
men[54]=740 ; men_death_rate[54]=0.0038 ;
men[55]=776 ; men_death_rate[55]=0.0063 ;
men[56]=803 ; men_death_rate[56]=0.0063 ;
men[57]=803 ; men_death_rate[57]=0.0063 ;
men[58]=850 ; men_death_rate[58]=0.0063 ;
men[59]=896 ; men_death_rate[59]=0.0063 ;
men[60]=949 ; men_death_rate[60]=0.0093 ;
men[61]=1018 ; men_death_rate[61]=0.0093 ;
men[62]=1111 ; men_death_rate[62]=0.0093 ;
men[63]=1099 ; men_death_rate[63]=0.0093 ;
men[64]=1042 ; men_death_rate[64]=0.0093 ;
men[65]=645 ; men_death_rate[65]=0.0146 ;
men[66]=684 ; men_death_rate[66]=0.0146 ;
men[67]=825 ; men_death_rate[67]=0.0146 ;
men[68]=794 ; men_death_rate[68]=0.0146 ;
men[69]=809 ; men_death_rate[69]=0.0146 ;
men[70]=780 ; men_death_rate[70]=0.0227 ;
men[71]=698 ; men_death_rate[71]=0.0227 ;
men[72]=599 ; men_death_rate[72]=0.0227 ;
men[73]=627 ; men_death_rate[73]=0.0227 ;
men[74]=631 ; men_death_rate[74]=0.0227 ;
men[75]=616 ; men_death_rate[75]=0.0396 ;
men[76]=571 ; men_death_rate[76]=0.0396 ;
men[77]=521 ; men_death_rate[77]=0.0396 ;
men[78]=501 ; men_death_rate[78]=0.0396 ;
men[79]=470 ; men_death_rate[79]=0.0396 ;
men[80]=430 ; men_death_rate[80]=0.0705 ;
men[81]=385 ; men_death_rate[81]=0.0705 ;
men[82]=350 ; men_death_rate[82]=0.0705 ;
men[83]=316 ; men_death_rate[83]=0.0705 ;
men[84]=281 ; men_death_rate[84]=0.0705 ;
men[85]=247 ; men_death_rate[85]=0.1200 ;
men[86]=202 ; men_death_rate[86]=0.1200 ;
men[87]=158 ; men_death_rate[87]=0.1200 ;
men[88]=122 ; men_death_rate[88]=0.1200 ;
men[89]=98 ; men_death_rate[89]=0.1200 ;
men[90]=78 ; men_death_rate[90]=0.2025 ;
men[91]=67 ; men_death_rate[91]=0.2025 ;
men[92]=44 ; men_death_rate[92]=0.2025 ;
men[93]=36 ; men_death_rate[93]=0.2025 ;
men[94]=28 ; men_death_rate[94]=0.2025 ;
men[95]=21 ; men_death_rate[95]=0.3188 ;
men[96]=15 ; men_death_rate[96]=0.3188 ;
men[97]=11 ; men_death_rate[97]=0.3188 ;
men[98]=7 ; men_death_rate[98]=0.3188 ;
men[99]=5 ; men_death_rate[99]=0.3188 ;
women[ 0]=520; women_death_rate[ 0]=0.0021 ;
women[ 1]=510; women_death_rate[ 1]=0.0004 ;
women[ 2]=511; women_death_rate[ 2]=0.0002 ;
women[ 3]=525; women_death_rate[ 3]=0.0001 ;
women[ 4]=522; women_death_rate[ 4]=0.0001 ;
women[ 5]=518; women_death_rate[ 5]=0.0001 ;
women[ 6]=517; women_death_rate[ 6]=0.0001 ;
women[ 7]=538; women_death_rate[ 7]=0.0001 ;
women[ 8]=545; women_death_rate[ 8]=0.0001 ;
women[ 9]=561; women_death_rate[ 9]=0.0001 ;
women[10]=568; women_death_rate[10]=0.0001 ;
women[11]=573; women_death_rate[11]=0.0001 ;
women[12]=576; women_death_rate[12]=0.0001 ;
women[13]=585; women_death_rate[13]=0.0001 ;
women[14]=583; women_death_rate[14]=0.0001 ;
women[15]=578; women_death_rate[15]=0.0002 ;
women[16]=595; women_death_rate[16]=0.0002 ;
women[17]=597; women_death_rate[17]=0.0002 ;
women[18]=589; women_death_rate[18]=0.0002 ;
women[19]=599; women_death_rate[19]=0.0002 ;
women[20]=596; women_death_rate[20]=0.0003 ;
women[21]=605; women_death_rate[21]=0.0003 ;
women[22]=622; women_death_rate[22]=0.0003 ;
women[23]=638; women_death_rate[23]=0.0003 ;
women[24]=655; women_death_rate[24]=0.0003 ;
women[25]=667; women_death_rate[25]=0.0003 ;
women[26]=697; women_death_rate[26]=0.0003 ;
women[27]=719; women_death_rate[27]=0.0003 ;
women[28]=729; women_death_rate[28]=0.0003 ;
women[29]=734; women_death_rate[29]=0.0003 ;
women[30]=742; women_death_rate[30]=0.0004 ;
women[31]=774; women_death_rate[31]=0.0004 ;
women[32]=794; women_death_rate[32]=0.0004 ;
women[33]=828; women_death_rate[33]=0.0004 ;
women[34]=849; women_death_rate[34]=0.0004 ;
women[35]=890; women_death_rate[35]=0.0006 ;
women[36]=931; women_death_rate[36]=0.0006 ;
women[37]=982; women_death_rate[37]=0.0006 ;
women[38]=1001; women_death_rate[38]=0.0006 ;
women[39]=981; women_death_rate[39]=0.0006 ;
women[40]=958; women_death_rate[40]=0.0008 ;
women[41]=931; women_death_rate[41]=0.0008 ;
women[42]=920; women_death_rate[42]=0.0008 ;
women[43]=902; women_death_rate[43]=0.0008 ;
women[44]=898; women_death_rate[44]=0.0008 ;
women[45]=705; women_death_rate[45]=0.0013 ;
women[46]=872; women_death_rate[46]=0.0013 ;
women[47]=815; women_death_rate[47]=0.0013 ;
women[48]=798; women_death_rate[48]=0.0013 ;
women[49]=772; women_death_rate[49]=0.0013 ;
women[50]=760; women_death_rate[50]=0.0019 ;
women[51]=768; women_death_rate[51]=0.0019 ;
women[52]=783; women_death_rate[52]=0.0019 ;
women[53]=765; women_death_rate[53]=0.0019 ;
women[54]=744; women_death_rate[54]=0.0019 ;
women[55]=783; women_death_rate[55]=0.0028 ;
women[56]=810; women_death_rate[56]=0.0028 ;
women[57]=813; women_death_rate[57]=0.0028 ;
women[58]=868; women_death_rate[58]=0.0028 ;
women[59]=918; women_death_rate[59]=0.0028 ;
women[60]=975; women_death_rate[60]=0.0039 ;
women[61]=1051; women_death_rate[61]=0.0039 ;
women[62]=1152; women_death_rate[62]=0.0039 ;
women[63]=1146; women_death_rate[63]=0.0039 ;
women[64]=1090; women_death_rate[64]=0.0039 ;
women[65]=685; women_death_rate[65]=0.0060 ;
women[66]=741; women_death_rate[66]=0.0060 ;
women[67]=903; women_death_rate[67]=0.0060 ;
women[68]=875; women_death_rate[68]=0.0060 ;
women[69]=899; women_death_rate[69]=0.0060 ;
women[70]=873; women_death_rate[70]=0.0098 ;
women[71]=793; women_death_rate[71]=0.0098 ;
women[72]=690; women_death_rate[72]=0.0098 ;
women[73]=738; women_death_rate[73]=0.0098 ;
women[74]=755; women_death_rate[74]=0.0098 ;
women[75]=753; women_death_rate[75]=0.0179 ;
women[76]=718; women_death_rate[76]=0.0179 ;
women[77]=675; women_death_rate[77]=0.0179 ;
women[78]=671; women_death_rate[78]=0.0179 ;
women[79]=646; women_death_rate[79]=0.0179 ;
women[80]=614; women_death_rate[80]=0.0343 ;
women[81]=573; women_death_rate[81]=0.0343 ;
women[82]=547; women_death_rate[82]=0.0343 ;
women[83]=515; women_death_rate[83]=0.0343 ;
women[84]=482; women_death_rate[84]=0.0343 ;
women[85]=454; women_death_rate[85]=0.0691 ;
women[86]=405; women_death_rate[86]=0.0691 ;
women[87]=349; women_death_rate[87]=0.0691 ;
women[88]=313; women_death_rate[88]=0.0691 ;
women[89]=276; women_death_rate[89]=0.0691 ;
women[90]=236; women_death_rate[90]=0.1312 ;
women[91]=213; women_death_rate[91]=0.1312 ;
women[92]=146; women_death_rate[92]=0.1312 ;
women[93]=128; women_death_rate[93]=0.1312 ;
women[94]=106; women_death_rate[94]=0.1312 ;
women[95]=87 ; women_death_rate[95]=0.2381 ;
women[96]=63 ; women_death_rate[96]=0.2381 ;
women[97]=49 ; women_death_rate[97]=0.2381 ;
women[98]=35 ; women_death_rate[98]=0.2381 ;
women[99]=25 ; women_death_rate[99]=0.2381 ;
/////////////////////////////////////////////
// 未婚率 (平成22年)
men_unmarried_rate[ 0]=1.000 ;
men_unmarried_rate[ 1]=1.000 ;
men_unmarried_rate[ 2]=1.000 ;
men_unmarried_rate[ 3]=1.000 ;
men_unmarried_rate[ 4]=1.000 ;
men_unmarried_rate[ 5]=1.000 ;
men_unmarried_rate[ 6]=1.000 ;
men_unmarried_rate[ 7]=1.000 ;
men_unmarried_rate[ 8]=1.000 ;
men_unmarried_rate[ 9]=1.000 ;
men_unmarried_rate[10]=1.000 ;
men_unmarried_rate[11]=1.000 ;
men_unmarried_rate[12]=1.000 ;
men_unmarried_rate[13]=1.000 ;
men_unmarried_rate[14]=1.000 ;
men_unmarried_rate[15]=1.000 ;
men_unmarried_rate[16]=1.000 ;
men_unmarried_rate[17]=1.000 ;
men_unmarried_rate[18]=0.975 ;
men_unmarried_rate[19]=0.975 ;
men_unmarried_rate[20]=0.910 ;
men_unmarried_rate[21]=0.910 ;
men_unmarried_rate[22]=0.910 ;
men_unmarried_rate[23]=0.910 ;
men_unmarried_rate[24]=0.910 ;
men_unmarried_rate[25]=0.645 ;
men_unmarried_rate[26]=0.645 ;
men_unmarried_rate[27]=0.645 ;
men_unmarried_rate[28]=0.645 ;
men_unmarried_rate[29]=0.645 ;
men_unmarried_rate[30]=0.413 ;
men_unmarried_rate[31]=0.413 ;
men_unmarried_rate[32]=0.413 ;
men_unmarried_rate[33]=0.413 ;
men_unmarried_rate[34]=0.413 ;
men_unmarried_rate[35]=0.370 ;
men_unmarried_rate[36]=0.370 ;
men_unmarried_rate[37]=0.370 ;
men_unmarried_rate[38]=0.370 ;
men_unmarried_rate[39]=0.370 ;
men_unmarried_rate[40]=0.229 ;
men_unmarried_rate[41]=0.229 ;
men_unmarried_rate[42]=0.229 ;
men_unmarried_rate[43]=0.229 ;
men_unmarried_rate[44]=0.229 ;
men_unmarried_rate[45]=0.166 ;
men_unmarried_rate[46]=0.166 ;
men_unmarried_rate[47]=0.166 ;
men_unmarried_rate[48]=0.166 ;
men_unmarried_rate[49]=0.166 ;
men_unmarried_rate[50]=0.189 ;
men_unmarried_rate[51]=0.189 ;
men_unmarried_rate[52]=0.189 ;
men_unmarried_rate[53]=0.189 ;
men_unmarried_rate[54]=0.189 ;
men_unmarried_rate[55]=0.139 ;
men_unmarried_rate[56]=0.139 ;
men_unmarried_rate[57]=0.139 ;
men_unmarried_rate[58]=0.139 ;
men_unmarried_rate[59]=0.139 ;
men_unmarried_rate[60]=0.068 ;
men_unmarried_rate[61]=0.068 ;
men_unmarried_rate[62]=0.068 ;
men_unmarried_rate[63]=0.068 ;
men_unmarried_rate[64]=0.068 ;
men_unmarried_rate[65]=0.042 ;
men_unmarried_rate[66]=0.042 ;
men_unmarried_rate[67]=0.042 ;
men_unmarried_rate[68]=0.042 ;
men_unmarried_rate[69]=0.042 ;
men_unmarried_rate[70]=0.015 ;
men_unmarried_rate[71]=0.015 ;
men_unmarried_rate[72]=0.015 ;
men_unmarried_rate[73]=0.015 ;
men_unmarried_rate[74]=0.015 ;
men_unmarried_rate[75]=0.012 ;
men_unmarried_rate[76]=0.012 ;
men_unmarried_rate[77]=0.012 ;
men_unmarried_rate[78]=0.012 ;
men_unmarried_rate[79]=0.012 ;
men_unmarried_rate[80]=0.012 ;
men_unmarried_rate[81]=0.012 ;
men_unmarried_rate[82]=0.012 ;
men_unmarried_rate[83]=0.012 ;
men_unmarried_rate[84]=0.012 ;
men_unmarried_rate[85]=0.011 ;
men_unmarried_rate[86]=0.011 ;
men_unmarried_rate[87]=0.011 ;
men_unmarried_rate[88]=0.011 ;
men_unmarried_rate[89]=0.011 ;
men_unmarried_rate[90]=0.011 ;
men_unmarried_rate[91]=0.011 ;
men_unmarried_rate[92]=0.011 ;
men_unmarried_rate[93]=0.011 ;
men_unmarried_rate[94]=0.011 ;
men_unmarried_rate[95]=0.011 ;
men_unmarried_rate[96]=0.011 ;
men_unmarried_rate[97]=0.011 ;
men_unmarried_rate[98]=0.011 ;
men_unmarried_rate[99]=0.011 ;
women_unmarried_rate[ 0]=1.000 ;
women_unmarried_rate[ 1]=1.000 ;
women_unmarried_rate[ 2]=1.000 ;
women_unmarried_rate[ 3]=1.000 ;
women_unmarried_rate[ 4]=1.000 ;
women_unmarried_rate[ 5]=1.000 ;
women_unmarried_rate[ 6]=1.000 ;
women_unmarried_rate[ 7]=1.000 ;
women_unmarried_rate[ 8]=1.000 ;
women_unmarried_rate[ 9]=1.000 ;
women_unmarried_rate[10]=1.000 ;
women_unmarried_rate[11]=1.000 ;
women_unmarried_rate[12]=1.000 ;
women_unmarried_rate[13]=1.000 ;
women_unmarried_rate[14]=1.000 ;
women_unmarried_rate[15]=1.000 ;
women_unmarried_rate[16]=0.984 ;
women_unmarried_rate[17]=0.984 ;
women_unmarried_rate[18]=0.984 ;
women_unmarried_rate[19]=0.984 ;
women_unmarried_rate[20]=0.898 ;
women_unmarried_rate[21]=0.898 ;
women_unmarried_rate[22]=0.898 ;
women_unmarried_rate[23]=0.898 ;
women_unmarried_rate[24]=0.898 ;
women_unmarried_rate[25]=0.607 ;
women_unmarried_rate[26]=0.607 ;
women_unmarried_rate[27]=0.607 ;
women_unmarried_rate[28]=0.607 ;
women_unmarried_rate[29]=0.607 ;
women_unmarried_rate[30]=0.374 ;
women_unmarried_rate[31]=0.374 ;
women_unmarried_rate[32]=0.374 ;
women_unmarried_rate[33]=0.374 ;
women_unmarried_rate[34]=0.374 ;
women_unmarried_rate[35]=0.250 ;
women_unmarried_rate[36]=0.250 ;
women_unmarried_rate[37]=0.250 ;
women_unmarried_rate[38]=0.250 ;
women_unmarried_rate[39]=0.250 ;
women_unmarried_rate[40]=0.224 ;
women_unmarried_rate[41]=0.224 ;
women_unmarried_rate[42]=0.224 ;
women_unmarried_rate[43]=0.224 ;
women_unmarried_rate[44]=0.224 ;
women_unmarried_rate[45]=0.154 ;
women_unmarried_rate[46]=0.154 ;
women_unmarried_rate[47]=0.154 ;
women_unmarried_rate[48]=0.154 ;
women_unmarried_rate[49]=0.154 ;
women_unmarried_rate[50]=0.114 ;
women_unmarried_rate[51]=0.114 ;
women_unmarried_rate[52]=0.114 ;
women_unmarried_rate[53]=0.114 ;
women_unmarried_rate[54]=0.114 ;
women_unmarried_rate[55]=0.073 ;
women_unmarried_rate[56]=0.073 ;
women_unmarried_rate[57]=0.073 ;
women_unmarried_rate[58]=0.073 ;
women_unmarried_rate[59]=0.073 ;
women_unmarried_rate[60]=0.055 ;
women_unmarried_rate[61]=0.055 ;
women_unmarried_rate[62]=0.055 ;
women_unmarried_rate[63]=0.055 ;
women_unmarried_rate[64]=0.055 ;
women_unmarried_rate[65]=0.053 ;
women_unmarried_rate[66]=0.053 ;
women_unmarried_rate[67]=0.053 ;
women_unmarried_rate[68]=0.053 ;
women_unmarried_rate[69]=0.053 ;
women_unmarried_rate[70]=0.033 ;
women_unmarried_rate[71]=0.033 ;
women_unmarried_rate[72]=0.033 ;
women_unmarried_rate[73]=0.033 ;
women_unmarried_rate[74]=0.033 ;
women_unmarried_rate[75]=0.044 ;
women_unmarried_rate[76]=0.044 ;
women_unmarried_rate[77]=0.044 ;
women_unmarried_rate[78]=0.044 ;
women_unmarried_rate[79]=0.044 ;
women_unmarried_rate[80]=0.078 ;
women_unmarried_rate[81]=0.078 ;
women_unmarried_rate[82]=0.078 ;
women_unmarried_rate[83]=0.078 ;
women_unmarried_rate[84]=0.078 ;
women_unmarried_rate[85]=0.033 ;
women_unmarried_rate[86]=0.033 ;
women_unmarried_rate[87]=0.033 ;
women_unmarried_rate[88]=0.033 ;
women_unmarried_rate[89]=0.033 ;
women_unmarried_rate[90]=0.033 ;
women_unmarried_rate[91]=0.033 ;
women_unmarried_rate[92]=0.033 ;
women_unmarried_rate[93]=0.033 ;
women_unmarried_rate[94]=0.033 ;
women_unmarried_rate[95]=0.033 ;
women_unmarried_rate[96]=0.033 ;
women_unmarried_rate[97]=0.033 ;
women_unmarried_rate[98]=0.033 ;
women_unmarried_rate[99]=0.033 ;
// 有配偶率 (平成22年)
// 初婚、再婚関係なく、その世代に対して。
// 結婚している比率
//国勢調査の男女別の有配偶者の数はなぜ違うのか
men_existance_matching_rate[ 0]=0.000 ;
men_existance_matching_rate[ 1]=0.000 ;
men_existance_matching_rate[ 2]=0.000 ;
men_existance_matching_rate[ 3]=0.000 ;
men_existance_matching_rate[ 4]=0.000 ;
men_existance_matching_rate[ 5]=0.000 ;
men_existance_matching_rate[ 6]=0.000 ;
men_existance_matching_rate[ 7]=0.000 ;
men_existance_matching_rate[ 8]=0.000 ;
men_existance_matching_rate[ 9]=0.000 ;
men_existance_matching_rate[10]=0.000 ;
men_existance_matching_rate[11]=0.000 ;
men_existance_matching_rate[12]=0.000 ;
men_existance_matching_rate[13]=0.000 ;
men_existance_matching_rate[14]=0.000 ;
men_existance_matching_rate[15]=0.011 ;
men_existance_matching_rate[16]=0.011 ;
men_existance_matching_rate[17]=0.011 ;
men_existance_matching_rate[18]=0.011 ;
men_existance_matching_rate[19]=0.011 ;
men_existance_matching_rate[20]=0.036 ;
men_existance_matching_rate[21]=0.036 ;
men_existance_matching_rate[22]=0.036 ;
men_existance_matching_rate[23]=0.036 ;
men_existance_matching_rate[24]=0.036 ;
men_existance_matching_rate[25]=0.241 ;
men_existance_matching_rate[26]=0.241 ;
men_existance_matching_rate[27]=0.241 ;
men_existance_matching_rate[28]=0.241 ;
men_existance_matching_rate[29]=0.241 ;
men_existance_matching_rate[30]=0.497 ;
men_existance_matching_rate[31]=0.497 ;
men_existance_matching_rate[32]=0.497 ;
men_existance_matching_rate[33]=0.497 ;
men_existance_matching_rate[34]=0.497 ;
men_existance_matching_rate[35]=0.530 ;
men_existance_matching_rate[36]=0.530 ;
men_existance_matching_rate[37]=0.530 ;
men_existance_matching_rate[38]=0.530 ;
men_existance_matching_rate[39]=0.530 ;
men_existance_matching_rate[40]=0.694 ;
men_existance_matching_rate[41]=0.694 ;
men_existance_matching_rate[42]=0.694 ;
men_existance_matching_rate[43]=0.694 ;
men_existance_matching_rate[44]=0.694 ;
men_existance_matching_rate[45]=0.741 ;
men_existance_matching_rate[46]=0.741 ;
men_existance_matching_rate[47]=0.741 ;
men_existance_matching_rate[48]=0.741 ;
men_existance_matching_rate[49]=0.741 ;
men_existance_matching_rate[50]=0.700 ;
men_existance_matching_rate[51]=0.700 ;
men_existance_matching_rate[52]=0.700 ;
men_existance_matching_rate[53]=0.700 ;
men_existance_matching_rate[54]=0.700 ;
men_existance_matching_rate[55]=0.765 ;
men_existance_matching_rate[56]=0.765 ;
men_existance_matching_rate[57]=0.765 ;
men_existance_matching_rate[58]=0.765 ;
men_existance_matching_rate[59]=0.765 ;
men_existance_matching_rate[60]=0.842 ;
men_existance_matching_rate[61]=0.842 ;
men_existance_matching_rate[62]=0.842 ;
men_existance_matching_rate[63]=0.842 ;
men_existance_matching_rate[64]=0.842 ;
men_existance_matching_rate[65]=0.824 ;
men_existance_matching_rate[66]=0.824 ;
men_existance_matching_rate[67]=0.824 ;
men_existance_matching_rate[68]=0.824 ;
men_existance_matching_rate[69]=0.824 ;
men_existance_matching_rate[70]=0.838 ;
men_existance_matching_rate[71]=0.838 ;
men_existance_matching_rate[72]=0.838 ;
men_existance_matching_rate[73]=0.838 ;
men_existance_matching_rate[74]=0.838 ;
men_existance_matching_rate[75]=0.817 ;
men_existance_matching_rate[76]=0.817 ;
men_existance_matching_rate[77]=0.817 ;
men_existance_matching_rate[78]=0.817 ;
men_existance_matching_rate[79]=0.817 ;
men_existance_matching_rate[80]=0.730 ;
men_existance_matching_rate[81]=0.730 ;
men_existance_matching_rate[82]=0.730 ;
men_existance_matching_rate[83]=0.730 ;
men_existance_matching_rate[84]=0.730 ;
men_existance_matching_rate[85]=0.708 ;
men_existance_matching_rate[86]=0.708 ;
men_existance_matching_rate[87]=0.708 ;
men_existance_matching_rate[88]=0.708 ;
men_existance_matching_rate[89]=0.708 ;
men_existance_matching_rate[90]=0.708 ;
men_existance_matching_rate[91]=0.708 ;
men_existance_matching_rate[92]=0.708 ;
men_existance_matching_rate[93]=0.708 ;
men_existance_matching_rate[94]=0.708 ;
men_existance_matching_rate[95]=0.708 ;
men_existance_matching_rate[96]=0.708 ;
men_existance_matching_rate[97]=0.708 ;
men_existance_matching_rate[98]=0.708 ;
men_existance_matching_rate[99]=0.708 ;
women_existance_matching_rate[ 0]=0.000 ;
women_existance_matching_rate[ 1]=0.000 ;
women_existance_matching_rate[ 2]=0.000 ;
women_existance_matching_rate[ 3]=0.000 ;
women_existance_matching_rate[ 4]=0.000 ;
women_existance_matching_rate[ 5]=0.000 ;
women_existance_matching_rate[ 6]=0.000 ;
women_existance_matching_rate[ 7]=0.000 ;
women_existance_matching_rate[ 8]=0.000 ;
women_existance_matching_rate[ 9]=0.000 ;
women_existance_matching_rate[10]=0.000 ;
women_existance_matching_rate[11]=0.000 ;
women_existance_matching_rate[12]=0.000 ;
women_existance_matching_rate[13]=0.000 ;
women_existance_matching_rate[14]=0.000 ;
women_existance_matching_rate[15]=0.008 ;
women_existance_matching_rate[16]=0.008 ;
women_existance_matching_rate[17]=0.008 ;
women_existance_matching_rate[18]=0.008 ;
women_existance_matching_rate[19]=0.008 ;
women_existance_matching_rate[20]=0.052 ;
women_existance_matching_rate[21]=0.052 ;
women_existance_matching_rate[22]=0.052 ;
women_existance_matching_rate[23]=0.052 ;
women_existance_matching_rate[24]=0.052 ;
women_existance_matching_rate[25]=0.312 ;
women_existance_matching_rate[26]=0.312 ;
women_existance_matching_rate[27]=0.312 ;
women_existance_matching_rate[28]=0.312 ;
women_existance_matching_rate[29]=0.312 ;
women_existance_matching_rate[30]=0.569 ;
women_existance_matching_rate[31]=0.569 ;
women_existance_matching_rate[32]=0.569 ;
women_existance_matching_rate[33]=0.569 ;
women_existance_matching_rate[34]=0.569 ;
women_existance_matching_rate[35]=0.667 ;
women_existance_matching_rate[36]=0.667 ;
women_existance_matching_rate[37]=0.667 ;
women_existance_matching_rate[38]=0.667 ;
women_existance_matching_rate[39]=0.667 ;
women_existance_matching_rate[40]=0.229 ;
women_existance_matching_rate[41]=0.229 ;
women_existance_matching_rate[42]=0.229 ;
women_existance_matching_rate[43]=0.229 ;
women_existance_matching_rate[44]=0.229 ;
women_existance_matching_rate[45]=0.712 ;
women_existance_matching_rate[46]=0.712 ;
women_existance_matching_rate[47]=0.712 ;
women_existance_matching_rate[48]=0.712 ;
women_existance_matching_rate[49]=0.712 ;
women_existance_matching_rate[50]=0.755 ;
women_existance_matching_rate[51]=0.755 ;
women_existance_matching_rate[52]=0.755 ;
women_existance_matching_rate[53]=0.755 ;
women_existance_matching_rate[54]=0.755 ;
women_existance_matching_rate[55]=0.789 ;
women_existance_matching_rate[56]=0.789 ;
women_existance_matching_rate[57]=0.789 ;
women_existance_matching_rate[58]=0.789 ;
women_existance_matching_rate[59]=0.789 ;
women_existance_matching_rate[60]=0.733 ;
women_existance_matching_rate[61]=0.733 ;
women_existance_matching_rate[62]=0.733 ;
women_existance_matching_rate[63]=0.733 ;
women_existance_matching_rate[64]=0.733 ;
women_existance_matching_rate[65]=0.663 ;
women_existance_matching_rate[66]=0.663 ;
women_existance_matching_rate[67]=0.663 ;
women_existance_matching_rate[68]=0.663 ;
women_existance_matching_rate[69]=0.663 ;
women_existance_matching_rate[70]=0.650 ;
women_existance_matching_rate[71]=0.650 ;
women_existance_matching_rate[72]=0.650 ;
women_existance_matching_rate[73]=0.650 ;
women_existance_matching_rate[74]=0.650 ;
women_existance_matching_rate[75]=0.462 ;
women_existance_matching_rate[76]=0.462 ;
women_existance_matching_rate[77]=0.462 ;
women_existance_matching_rate[78]=0.462 ;
women_existance_matching_rate[79]=0.462 ;
women_existance_matching_rate[80]=0.326 ;
women_existance_matching_rate[81]=0.326 ;
women_existance_matching_rate[82]=0.326 ;
women_existance_matching_rate[83]=0.326 ;
women_existance_matching_rate[84]=0.326 ;
women_existance_matching_rate[85]=0.093 ;
women_existance_matching_rate[86]=0.093 ;
women_existance_matching_rate[87]=0.093 ;
women_existance_matching_rate[88]=0.093 ;
women_existance_matching_rate[89]=0.093 ;
women_existance_matching_rate[90]=0.093 ;
women_existance_matching_rate[91]=0.093 ;
women_existance_matching_rate[92]=0.093 ;
women_existance_matching_rate[93]=0.093 ;
women_existance_matching_rate[94]=0.093 ;
women_existance_matching_rate[95]=0.093 ;
women_existance_matching_rate[96]=0.093 ;
women_existance_matching_rate[97]=0.093 ;
women_existance_matching_rate[98]=0.093 ;
women_existance_matching_rate[99]=0.093 ;
//有配偶離婚率 Divorce rates for married population
// 平成22年データ
// ○ 結婚している人に対する離婚率
// × 人口に対する離婚率
men_divorce_rate[0] = 0.0000 ;//結婚できないから、
men_divorce_rate[1] = 0.0000 ;//離婚もできない
men_divorce_rate[2] = 0.0000 ;
men_divorce_rate[3] = 0.0000 ;
men_divorce_rate[4] = 0.0000 ;
men_divorce_rate[5] = 0.0000 ;
men_divorce_rate[6] = 0.0000 ;
men_divorce_rate[7] = 0.0000 ;
men_divorce_rate[8] = 0.0000 ;
men_divorce_rate[9] = 0.0000 ;
men_divorce_rate[10] = 0.0000 ;
men_divorce_rate[11] = 0.0000 ;
men_divorce_rate[12] = 0.0000 ;
men_divorce_rate[13] = 0.0000 ;
men_divorce_rate[14] = 0.0000 ;
men_divorce_rate[15] = 0.0000 ;
men_divorce_rate[16] = 0.0000 ;
men_divorce_rate[17] = 0.0000 ;
men_divorce_rate[18] = 0.4809 ;
men_divorce_rate[19] = 0.4809 ;
men_divorce_rate[20] = 0.4705 ;
men_divorce_rate[21] = 0.4705 ;
men_divorce_rate[22] = 0.4705 ;
men_divorce_rate[23] = 0.4705 ;
men_divorce_rate[24] = 0.4705 ;
men_divorce_rate[25] = 0.2283 ;
men_divorce_rate[26] = 0.2283 ;
men_divorce_rate[27] = 0.2283 ;
men_divorce_rate[28] = 0.2283 ;
men_divorce_rate[29] = 0.2283 ;
men_divorce_rate[30] = 0.1521 ;
men_divorce_rate[31] = 0.1521 ;
men_divorce_rate[32] = 0.1521 ;
men_divorce_rate[33] = 0.1521 ;
men_divorce_rate[34] = 0.1521 ;
men_divorce_rate[35] = 0.1165 ;
men_divorce_rate[36] = 0.1165 ;
men_divorce_rate[37] = 0.1165 ;
men_divorce_rate[38] = 0.1165 ;
men_divorce_rate[39] = 0.1165 ;
men_divorce_rate[40] = 0.0939 ;
men_divorce_rate[41] = 0.0939 ;
men_divorce_rate[42] = 0.0939 ;
men_divorce_rate[43] = 0.0939 ;
men_divorce_rate[44] = 0.0939 ;
men_divorce_rate[45] = 0.0703 ;
men_divorce_rate[46] = 0.0703 ;
men_divorce_rate[47] = 0.0703 ;
men_divorce_rate[48] = 0.0703 ;
men_divorce_rate[49] = 0.0703 ;
men_divorce_rate[50] = 0.0495 ;
men_divorce_rate[51] = 0.0495 ;
men_divorce_rate[52] = 0.0495 ;
men_divorce_rate[53] = 0.0495 ;
men_divorce_rate[54] = 0.0495 ;
men_divorce_rate[55] = 0.0309 ;
men_divorce_rate[56] = 0.0309 ;
men_divorce_rate[57] = 0.0309 ;
men_divorce_rate[58] = 0.0309 ;
men_divorce_rate[59] = 0.0309 ;
men_divorce_rate[60] = 0.0194 ;
men_divorce_rate[61] = 0.0194 ;
men_divorce_rate[62] = 0.0194 ;
men_divorce_rate[63] = 0.0194 ;
men_divorce_rate[64] = 0.0194 ;
men_divorce_rate[65] = 0.0110 ;
men_divorce_rate[66] = 0.0110 ;
men_divorce_rate[67] = 0.0110 ;
men_divorce_rate[68] = 0.0110 ;
men_divorce_rate[69] = 0.0110 ;
men_divorce_rate[70] = 0.0040 ;
men_divorce_rate[71] = 0.0040 ;
men_divorce_rate[72] = 0.0040 ;
men_divorce_rate[73] = 0.0040 ;
men_divorce_rate[74] = 0.0040 ;
men_divorce_rate[75] = 0.0040 ;
men_divorce_rate[76] = 0.0040 ;
men_divorce_rate[77] = 0.0040 ;
men_divorce_rate[78] = 0.0040 ;
men_divorce_rate[79] = 0.0040 ;
men_divorce_rate[80] = 0.0040 ;
men_divorce_rate[81] = 0.0040 ;
men_divorce_rate[82] = 0.0040 ;
men_divorce_rate[83] = 0.0040 ;
men_divorce_rate[84] = 0.0040 ;
men_divorce_rate[85] = 0.0040 ;
men_divorce_rate[86] = 0.0040 ;
men_divorce_rate[87] = 0.0040 ;
men_divorce_rate[88] = 0.0040 ;
men_divorce_rate[89] = 0.0040 ;
men_divorce_rate[90] = 0.0040 ;
men_divorce_rate[91] = 0.0040 ;
men_divorce_rate[92] = 0.0040 ;
men_divorce_rate[93] = 0.0040 ;
men_divorce_rate[94] = 0.0040 ;
men_divorce_rate[95] = 0.0040 ;
men_divorce_rate[96] = 0.0040 ;
men_divorce_rate[97] = 0.0040 ;
men_divorce_rate[98] = 0.0040 ;
men_divorce_rate[99] = 0.0040 ;
women_divorce_rate[0] = 0.0000 ;//結婚できないから、
women_divorce_rate[1] = 0.0000 ;//離婚もできない
women_divorce_rate[2] = 0.0000 ;
women_divorce_rate[3] = 0.0000 ;
women_divorce_rate[4] = 0.0000 ;
women_divorce_rate[5] = 0.0000 ;
women_divorce_rate[6] = 0.0000 ;
women_divorce_rate[7] = 0.0000 ;
women_divorce_rate[8] = 0.0000 ;
women_divorce_rate[9] = 0.0000 ;
women_divorce_rate[10] = 0.0000 ;
women_divorce_rate[11] = 0.0000 ;
women_divorce_rate[12] = 0.0000 ;
women_divorce_rate[13] = 0.0000 ;
women_divorce_rate[14] = 0.0000 ;
women_divorce_rate[15] = 0.0000 ;
women_divorce_rate[16] = 0.8274 ;
women_divorce_rate[17] = 0.8274 ;
women_divorce_rate[18] = 0.8274 ;
women_divorce_rate[19] = 0.8274 ;
women_divorce_rate[20] = 0.4834 ;
women_divorce_rate[21] = 0.4834 ;
women_divorce_rate[22] = 0.4834 ;
women_divorce_rate[23] = 0.4834 ;
women_divorce_rate[24] = 0.4834 ;
women_divorce_rate[25] = 0.2288 ;
women_divorce_rate[26] = 0.2288 ;
women_divorce_rate[27] = 0.2288 ;
women_divorce_rate[28] = 0.2288 ;
women_divorce_rate[29] = 0.2288 ;
women_divorce_rate[30] = 0.1480 ;
women_divorce_rate[31] = 0.1480 ;
women_divorce_rate[32] = 0.1480 ;
women_divorce_rate[33] = 0.1480 ;
women_divorce_rate[34] = 0.1480 ;
women_divorce_rate[35] = 0.1090 ;
women_divorce_rate[36] = 0.1090 ;
women_divorce_rate[37] = 0.1090 ;
women_divorce_rate[38] = 0.1090 ;
women_divorce_rate[39] = 0.1090 ;
women_divorce_rate[40] = 0.0833 ;
women_divorce_rate[41] = 0.0833 ;
women_divorce_rate[42] = 0.0833 ;
women_divorce_rate[43] = 0.0833 ;
women_divorce_rate[44] = 0.0833 ;
women_divorce_rate[45] = 0.0560 ;
women_divorce_rate[46] = 0.0560 ;
women_divorce_rate[47] = 0.0560 ;
women_divorce_rate[48] = 0.0560 ;
women_divorce_rate[49] = 0.0560 ;
women_divorce_rate[50] = 0.0322 ;
women_divorce_rate[51] = 0.0322 ;
women_divorce_rate[52] = 0.0322 ;
women_divorce_rate[53] = 0.0322 ;
women_divorce_rate[54] = 0.0322 ;
women_divorce_rate[55] = 0.0172 ;
women_divorce_rate[56] = 0.0172 ;
women_divorce_rate[57] = 0.0172 ;
women_divorce_rate[58] = 0.0172 ;
women_divorce_rate[59] = 0.0172 ;
women_divorce_rate[60] = 0.0113 ;
women_divorce_rate[61] = 0.0113 ;
women_divorce_rate[62] = 0.0113 ;
women_divorce_rate[63] = 0.0113 ;
women_divorce_rate[64] = 0.0113 ;
women_divorce_rate[65] = 0.0073 ;
women_divorce_rate[66] = 0.0073 ;
women_divorce_rate[67] = 0.0073 ;
women_divorce_rate[68] = 0.0073 ;
women_divorce_rate[69] = 0.0073 ;
women_divorce_rate[70] = 0.0028 ;
women_divorce_rate[71] = 0.0028 ;
women_divorce_rate[72] = 0.0028 ;
women_divorce_rate[73] = 0.0028 ;
women_divorce_rate[74] = 0.0028 ;
women_divorce_rate[75] = 0.0028 ;
women_divorce_rate[76] = 0.0028 ;
women_divorce_rate[77] = 0.0028 ;
women_divorce_rate[78] = 0.0028 ;
women_divorce_rate[79] = 0.0028 ;
women_divorce_rate[80] = 0.0028 ;
women_divorce_rate[81] = 0.0028 ;
women_divorce_rate[82] = 0.0028 ;
women_divorce_rate[83] = 0.0028 ;
women_divorce_rate[84] = 0.0028 ;
women_divorce_rate[85] = 0.0028 ;
women_divorce_rate[86] = 0.0028 ;
women_divorce_rate[87] = 0.0028 ;
women_divorce_rate[88] = 0.0028 ;
women_divorce_rate[89] = 0.0028 ;
women_divorce_rate[90] = 0.0028 ;
women_divorce_rate[91] = 0.0028 ;
women_divorce_rate[92] = 0.0028 ;
women_divorce_rate[93] = 0.0028 ;
women_divorce_rate[94] = 0.0028 ;
women_divorce_rate[95] = 0.0028 ;
women_divorce_rate[96] = 0.0028 ;
women_divorce_rate[97] = 0.0028 ;
women_divorce_rate[98] = 0.0028 ;
women_divorce_rate[99] = 0.0028 ;
// 再婚率 (2010年)
// × 離婚している人に対する再婚率
// ○ 世代人口(未婚、結婚、離婚関係なし)に対する再婚率
// ということで、計算式に注意しなければならない。
// (というか、なんで、最初からそういう数値にしないんだ!)
// 離婚している人に対する再婚率 (に変換する式)
// =
// 再婚率 x その世代の人口数 / 離婚(×未婚、結婚)人口
// としなければなない
//表６－６ 性，年齢（５歳階級）別再婚率：1930～2010年
//（‰）
//年 齢 2010年
men_remarrige_ratio[0] = 0.0000;
men_remarrige_ratio[1] = 0.0000;
men_remarrige_ratio[2] = 0.0000;
men_remarrige_ratio[3] = 0.0000;
men_remarrige_ratio[4] = 0.0000;
men_remarrige_ratio[5] = 0.0000;
men_remarrige_ratio[6] = 0.0000;
men_remarrige_ratio[7] = 0.0000;
men_remarrige_ratio[8] = 0.0000;
men_remarrige_ratio[9] = 0.0000;
men_remarrige_ratio[10] = 0.0000;
men_remarrige_ratio[11] = 0.0000;
men_remarrige_ratio[12] = 0.0000;
men_remarrige_ratio[13] = 0.0000;
men_remarrige_ratio[14] = 0.0000;
men_remarrige_ratio[15] = 0.0000;
men_remarrige_ratio[16] = 0.0000;
men_remarrige_ratio[17] = 0.0000;
men_remarrige_ratio[18] = 0.0001;
men_remarrige_ratio[19] = 0.0001;
men_remarrige_ratio[20] = 0.0048;
men_remarrige_ratio[21] = 0.0048;
men_remarrige_ratio[22] = 0.0048;
men_remarrige_ratio[23] = 0.0048;
men_remarrige_ratio[24] = 0.0048;
men_remarrige_ratio[25] = 0.0226;
men_remarrige_ratio[26] = 0.0226;
men_remarrige_ratio[27] = 0.0226;
men_remarrige_ratio[28] = 0.0226;
men_remarrige_ratio[29] = 0.0226;
men_remarrige_ratio[30] = 0.0448;
men_remarrige_ratio[31] = 0.0448;
men_remarrige_ratio[32] = 0.0448;
men_remarrige_ratio[33] = 0.0448;
men_remarrige_ratio[34] = 0.0448;
men_remarrige_ratio[35] = 0.0476;
men_remarrige_ratio[36] = 0.0476;
men_remarrige_ratio[37] = 0.0476;
men_remarrige_ratio[38] = 0.0476;
men_remarrige_ratio[39] = 0.0476;
men_remarrige_ratio[40] = 0.0371;
men_remarrige_ratio[41] = 0.0371;
men_remarrige_ratio[42] = 0.0371;
men_remarrige_ratio[43] = 0.0371;
men_remarrige_ratio[44] = 0.0371;
men_remarrige_ratio[45] = 0.0261;
men_remarrige_ratio[46] = 0.0261;
men_remarrige_ratio[47] = 0.0261;
men_remarrige_ratio[48] = 0.0261;
men_remarrige_ratio[49] = 0.0261;
men_remarrige_ratio[50] = 0.0180;
men_remarrige_ratio[51] = 0.0180;
men_remarrige_ratio[52] = 0.0180;
men_remarrige_ratio[53] = 0.0180;
men_remarrige_ratio[54] = 0.0180;
men_remarrige_ratio[55] = 0.0123;
men_remarrige_ratio[56] = 0.0123;
men_remarrige_ratio[57] = 0.0123;
men_remarrige_ratio[58] = 0.0123;
men_remarrige_ratio[59] = 0.0123;
men_remarrige_ratio[60] = 0.0091;
men_remarrige_ratio[61] = 0.0091;
men_remarrige_ratio[62] = 0.0091;
men_remarrige_ratio[63] = 0.0091;
men_remarrige_ratio[64] = 0.0091;
men_remarrige_ratio[65] = 0.0056;
men_remarrige_ratio[66] = 0.0056;
men_remarrige_ratio[67] = 0.0056;
men_remarrige_ratio[68] = 0.0056;
men_remarrige_ratio[69] = 0.0056;
men_remarrige_ratio[70] = 0.0025;
men_remarrige_ratio[71] = 0.0025;
men_remarrige_ratio[72] = 0.0025;
men_remarrige_ratio[73] = 0.0025;
men_remarrige_ratio[74] = 0.0025;
men_remarrige_ratio[75] = 0.0025;
men_remarrige_ratio[76] = 0.0025;
men_remarrige_ratio[77] = 0.0025;
men_remarrige_ratio[78] = 0.0025;
men_remarrige_ratio[79] = 0.0025;
men_remarrige_ratio[80] = 0.0025;
men_remarrige_ratio[81] = 0.0025;
men_remarrige_ratio[82] = 0.0025;
men_remarrige_ratio[83] = 0.0025;
men_remarrige_ratio[84] = 0.0025;
men_remarrige_ratio[85] = 0.0025;
men_remarrige_ratio[86] = 0.0025;
men_remarrige_ratio[87] = 0.0025;
men_remarrige_ratio[88] = 0.0025;
men_remarrige_ratio[89] = 0.0025;
men_remarrige_ratio[90] = 0.0025;
men_remarrige_ratio[91] = 0.0025;
men_remarrige_ratio[92] = 0.0025;
men_remarrige_ratio[93] = 0.0025;
men_remarrige_ratio[94] = 0.0025;
men_remarrige_ratio[95] = 0.0025;
men_remarrige_ratio[96] = 0.0025;
men_remarrige_ratio[97] = 0.0025;
men_remarrige_ratio[98] = 0.0025;
men_remarrige_ratio[99] = 0.0025;
women_remarrige_ratio[0] = 0.0000;
women_remarrige_ratio[1] = 0.0000;
women_remarrige_ratio[2] = 0.0000;
women_remarrige_ratio[3] = 0.0000;
women_remarrige_ratio[4] = 0.0000;
women_remarrige_ratio[5] = 0.0000;
women_remarrige_ratio[6] = 0.0000;
women_remarrige_ratio[7] = 0.0000;
women_remarrige_ratio[8] = 0.0000;
women_remarrige_ratio[9] = 0.0000;
women_remarrige_ratio[10] = 0.0000;
women_remarrige_ratio[11] = 0.0000;
women_remarrige_ratio[12] = 0.0000;
women_remarrige_ratio[13] = 0.0000;
women_remarrige_ratio[14] = 0.0000;
women_remarrige_ratio[15] = 0.0000;
women_remarrige_ratio[16] = 0.0004;
women_remarrige_ratio[17] = 0.0004;
women_remarrige_ratio[18] = 0.0004;
women_remarrige_ratio[19] = 0.0004;
women_remarrige_ratio[20] = 0.0103;
women_remarrige_ratio[21] = 0.0103;
women_remarrige_ratio[22] = 0.0103;
women_remarrige_ratio[23] = 0.0103;
women_remarrige_ratio[24] = 0.0103;
women_remarrige_ratio[25] = 0.0345;
women_remarrige_ratio[26] = 0.0345;
women_remarrige_ratio[27] = 0.0345;
women_remarrige_ratio[28] = 0.0345;
women_remarrige_ratio[29] = 0.0345;
women_remarrige_ratio[30] = 0.0501;
women_remarrige_ratio[31] = 0.0501;
women_remarrige_ratio[32] = 0.0501;
women_remarrige_ratio[33] = 0.0501;
women_remarrige_ratio[34] = 0.0501;
women_remarrige_ratio[35] = 0.0438;
women_remarrige_ratio[36] = 0.0438;
women_remarrige_ratio[37] = 0.0438;
women_remarrige_ratio[38] = 0.0438;
women_remarrige_ratio[39] = 0.0438;
women_remarrige_ratio[40] = 0.0269;
women_remarrige_ratio[41] = 0.0269;
women_remarrige_ratio[42] = 0.0269;
women_remarrige_ratio[43] = 0.0269;
women_remarrige_ratio[44] = 0.0269;
women_remarrige_ratio[45] = 0.0176;
women_remarrige_ratio[46] = 0.0176;
women_remarrige_ratio[47] = 0.0176;
women_remarrige_ratio[48] = 0.0176;
women_remarrige_ratio[49] = 0.0176;
women_remarrige_ratio[50] = 0.0115;
women_remarrige_ratio[51] = 0.0115;
women_remarrige_ratio[52] = 0.0115;
women_remarrige_ratio[53] = 0.0115;
women_remarrige_ratio[54] = 0.0115;
women_remarrige_ratio[55] = 0.0069;
women_remarrige_ratio[56] = 0.0069;
women_remarrige_ratio[57] = 0.0069;
women_remarrige_ratio[58] = 0.0069;
women_remarrige_ratio[59] = 0.0069;
women_remarrige_ratio[60] = 0.0043;
women_remarrige_ratio[61] = 0.0043;
women_remarrige_ratio[62] = 0.0043;
women_remarrige_ratio[63] = 0.0043;
women_remarrige_ratio[64] = 0.0043;
women_remarrige_ratio[65] = 0.0025;
women_remarrige_ratio[66] = 0.0025;
women_remarrige_ratio[67] = 0.0025;
women_remarrige_ratio[68] = 0.0025;
women_remarrige_ratio[69] = 0.0025;
women_remarrige_ratio[70] = 0.0007;
women_remarrige_ratio[71] = 0.0007;
women_remarrige_ratio[72] = 0.0007;
women_remarrige_ratio[73] = 0.0007;
women_remarrige_ratio[74] = 0.0007;
women_remarrige_ratio[75] = 0.0007;
women_remarrige_ratio[76] = 0.0007;
women_remarrige_ratio[77] = 0.0007;
women_remarrige_ratio[78] = 0.0007;
women_remarrige_ratio[79] = 0.0007;
women_remarrige_ratio[80] = 0.0007;
women_remarrige_ratio[81] = 0.0007;
women_remarrige_ratio[82] = 0.0007;
women_remarrige_ratio[83] = 0.0007;
women_remarrige_ratio[84] = 0.0007;
women_remarrige_ratio[85] = 0.0007;
women_remarrige_ratio[86] = 0.0007;
women_remarrige_ratio[87] = 0.0007;
women_remarrige_ratio[88] = 0.0007;
women_remarrige_ratio[89] = 0.0007;
women_remarrige_ratio[90] = 0.0007;
women_remarrige_ratio[91] = 0.0007;
women_remarrige_ratio[92] = 0.0007;
women_remarrige_ratio[93] = 0.0007;
women_remarrige_ratio[94] = 0.0007;
women_remarrige_ratio[95] = 0.0007;
women_remarrige_ratio[96] = 0.0007;
women_remarrige_ratio[97] = 0.0007;
women_remarrige_ratio[98] = 0.0007;
women_remarrige_ratio[99] = 0.0007;
}
に記載された通りの設定をした後
この設定を以下のようにしてみた。
でもって、再起動
なんか、物理メモリの量が減っているし、こころなし、重くなったような気がしたので、元に戻しました。
HDDレコーダに録画しておいた、映画"Fukushima 50"を、毎日10分間くらいに分けて見続けて、先日、終了しました。
The other day, I finished watching the movie "Fukushima 50," which I had recorded on my HDD recorder, in 10-minute segments every day.
良い映画だったと思います。
I think it was a good movie.
特に、『事故現場(原子炉)に接近しなければ事故を収拾できないのに、接近することができない』という ――
In particular, the fact that "they needed to get close to the accident site (reactor) to get it under control, but we could not"
そういう、やっかいなモノに頼って、私達は生きているという事実に気がつくことは、大切だと思います。
I think it is important to realize the fact that we depend on such troublesome things in our lives.
その他、色々思うところはあるのですが、本日は、差し控えさせて頂きたいと思います。
I have many other thoughts on the subject, but I would like to refrain from discussing them today.
とはいえ、『フクシマ50』を見て、事故のことがわかったような気になってしまうのはもったいない。
Nevertheless, it would be a shame to let "Fukushima 50" make you think that you understand the accident.
ここは一つ、私が、「原発事故オリエンテーション」を試みたいと思います。
I would like to attempt a "nuclear accident orientation" here.
-----
先ずは、定番、三原順先生の漫画『Die Energie 5.2☆11.8』
First up is the classic manga "Die Energie 5.2☆11.8" by Jun Mihara.
そして、これまで何度も引用させていただいた、原子力発電所の襲撃方法の教本、高村薫さんの『神の火』です。
And then there is Kaoru Takamura's "God's Fire", a teaching book on how to attack nuclear power plants, which I have quoted many times before.
さらに、原子炉への物理攻撃では、東野圭吾さんの『天空の蜂』です。
And for a physical attack on a nuclear reactor, it's Keigo Higashino's "Bees in the Sky".
ここまで読んで頂ければ、『原発を人質に取られた瞬間、私たちの負けが確定する』ということは、比較的簡単に分かります。
If you have read them it is relatively easy to understand that 'the moment the nuclear power plant is taken hostage, we are sure to lose.
------
原発の事故対応の話では、
According to "response to the nuclear accident",
You read my column, and ,
総括は、やはり、船橋洋一さんの『カウントダウン・メルトダウン』です。
the summary is also "Countdown Meltdown" by Yoichi Funabashi.
もちろん、それ以外にも、「軽水炉型と重水炉型の違い」とか「高速増殖炉もんじゅ」の話など、挙げればキリがありませんので、とりあえず、これくらいで十分です。
Of course, there are many other things I could mention, such as the difference between light water reactor type and heavy water reactor type, or the story of the fast breeder reactor Monju, but the above contents are enough for now.
------
で、実は、ここまでが前置きです。
So, actually, that's all the preamble.
ここ数日間で、大騒ぎになっている(という感じは、正直あまりしませんが)
In the last few days, there's been a lot of fuss (although I honestly don't feel like there's much fuss).
―― 柏崎刈羽原子力発電所で、一体、何があったのか
"What the hell happened at the Kashiwazaki-Kariwa Nuclear Power Plant?"
―― 原子力規制委員会は、何であんなに激怒しているのか
"Why is the Nuclear Regulatory Commission so furious?"
ここからが本論です。
This is where it starts.
(To be continued)
https://unlocker.jp.uptodown.com/windows/download
(Continuation from yesterday)
ただ、今の私は、現在、信頼できるお医者さんからの情報や、自分なりの全力の文献調査や数値分析の結果として
However, form the information from a doctor that I have trusted, and as a result of my own all-out papers research and numerical analysis,
『マスクは、新型コロナ感染防止に、絶対的な効果がある』
"Masks are absolutely effective in preventing new coronary infections"
ことを、絶対的なレベルで確信しています。
I am absolutely convinced that.
その根拠は、
The reasonings behind this are,
for this, and
for this, and
for this, and
for this, and
for this, and
for this,
構成と校正と調査と執筆です。
they are composition, proofreading, research, and writing.
-----
人の言うことを鵜呑みにするのではなく、教えて頂き、自分で調べて考えた結果として、自分で記述した結論なのだから、
I don't just believe what people tell me, I've been taught, I've done my own research, I've done my own thinking, and I've written my own conclusions.
『その結果が、未来で笑われるなら、それでもいい』
"If the result is laughed at in the future, I don't mind it"
と、開き直れる自信があります
I will defiantly declare in the future.
逆に、過去の私を嗤う未来の人間たちに対して、
On the other hand, to the people of the future who laugh at me in the past,
『お前たちの、今の常識だって、未来では笑われることになるかもしれない』
"Even your present common sense may be laughed at in the future"
『お前たちは、"常に、自分で考えて行動をした結果だから、それでいい"、と言い切れるだけのことをやっているのか？』
"Are you doing enough to be able to say, "It's always the result of my own thinking and action", so it's okay'?"
と、論争をふっかける準備すらあります。
I am going to be even prepared to argue with them.
-----
今回のコロナ禍においては、私は「圧倒的にマスクの利用をお勧め」しています。
In the case of the corona disaster, I "overwhelmingly recommend" the use of a mask.
なぜか。
Why am I doing ?
費用対効果がお話にならないくらい高く、サンクコストが果てしなく小さいからです。
This is because the cost-effectiveness is unbelievably high and the sunk costs are endlessly low.
マスクをして得られるメリットと、マスクをしないで失うデメリットが、14万7000光年くらい差があるからです。
This is because there is a difference of about 147,000 light years between the advantages gained by wearing a mask and the disadvantages lost by not wearing a mask.
すなわち、「激烈な苦痛、重篤、最悪死亡」 v.s 「10年後の未来の瞬時(数秒)の嘲笑」です。
In other words, "intense pain, serious illness, and worst death" v.s "instant (seconds) ridicule 10 years in the future".
-----
まあ、マスクの使用を選ぶのは「あなた」ですが ――
Well, it's "you" who chooses to use the mask, or not -- however,
だからといって、『あなたが、どこでも、自由に、マスクをしない権利がある』という話にはなりません。
that doesn't mean that "you have the right to not wear a mask, anywhere, at your will"
上記の費用対効果の話には、「あなた以外の第三者」が含まれていないからです。
This is because the above cost-benefit discussion does not include "third parties other than you".
-----
自然な考え方として、
As a natural thought,
『自分はマスクの効果を1mmも信じていないけど、マスクの効果を信じている人の為にマスクをする』という行為は、
The act of "I don't believe in masks at all, however I wear masks for people who do believe in them" is
■別段、自己矛盾でも、自己欺瞞でもなく、
- neithor self-contradictory, nor self-deceptive,
■社会通念上の常識的な行為であり、
- a common act in the socially accepted sense,
■お互いに気持ちの良い社会を構築する、超・超・超低コストなアプローチ
- a super, super, super low-cost approach to building a mutually pleasant society
です。
-----
とまあ ――
And well...
この程度のロジック(コストと社会通念の計算)もできない「絶望的かつ壊滅的なバカ」が、まだまだ残っているんだなー、と、心底呆れ返っています。
I am truly dismayed that there are still some "hopeless and devastated idiots" left who can't even do this level of logic (calculating costs and social conventions).
(Continuation from yesterday)
では、中学二年生の時に何があったか ―― 私は、中学の生徒会会長に就任したのです。
So what happened in the eighth grade -- I became the president of the student council of my middle school.
私は、世間が描いている「生徒会会長」が、その通りのキャラクターでないことを知っています。
I know that the "student council president" is not the character that the public envisions them to be.
そもそも、そんなことをやろうとする奴は、「上手いこと教師におだてられて」「回りに押しつけられて」「その気になってしまうほど単純」で ――
First of all, anyone trying to do something like this is "flattered by a good teacher", "pushed", and "simple enough to get into the mood".
そして、教師たちにとって都合の良い人物 ―― そこそこ判断力が早く、教師の言うことに従順で、御しやすい生徒、 ―― であることを知っています。
And I know that the student is a good fit for the teachers -- a student who is quick to judge, obedient to the teacher, and easy to control.
つまり、「私」です。
In other words, it was "me.
それでも、私は、「生徒会会長」という身分を手に入れることで、『自分自身であり続けることを、ギリギリの線で諦めない』ことを守ったのだと、今なら思えます。
Even if there were, I can see now that by obtaining the status of "Student Council President," I protected myself from giving up at the last minute to continue being myself.
ともあれ、これ(生徒会会長の肩書)は、いわゆる、「ピアノ」という武器との等価交換となりました。
Anyway, this (the title of student council president) became the equivalent exchange for the so-called "piano" weapon.
こうして、ようやく私は、「大っ嫌いなピアノ」を捨てることができたのです。
Thus, I was finally able to discard the piano, which I hated.
-----
私が、ようやく「ラクに息ができるようになったなぁ」と実感したのは、大学に入ってから、「クラス」という概念から解き放たれた時です。
After entering university, I was freed from the concept of "class," and finally felt that I could breathe easily.
■「仲間」だの「友人」だのとかいう、そういう"記号"を必要とせず、
- I didn't need symbols like "buddies" and "friends.
■人間関係を、その人間への「好き」と「嫌い」の気持だけで決定することができて、
- I could make decisions about relationships based solely on how much I like or dislike a person.
■他人からコントロールされない/他人をコントロールしない、
- I didn't have to be controlled by others / control others
■「自己責任」で、自分の生き方を「自己決定」できる
- I could "decide" how to live your life with "self-responsibility"
という日々の中で、私は、ようやく苦しい時代を終えた、と実感できました。
It was during these days that I realized that the hard times were finally over.
-----
最近、「過去の自分に戻る」というコミックやアニメが多いです。
Lately, there have been a lot of comics and anime about "going back to the past".
しかし、私の場合、「過去の自分に戻る」ことは希望しません。
However, in my case, I would not wish to "return to my past.
特に、小学校から中学校にかけては、ゴメンです。
Especially from elementary school to junior high school, it is joking.
(Continuation from yesterday)
最近、この子ども時代の矛盾した行動に、一定の説明ができることに気がつきました。
Recently, I realized that there is a certain explanation for this contradictory behavior in my childhood.
子どものころの私は、本質的にキャラクターが"陰"だった ―― というよりは"暗"でした。
When I was a child, my characters were essentially "negative" -- or rather, "dark".
私は、物事を表向きのままで見ないで、その"裏"を見つけようとし、"悪意"で解釈する、という癖がありました。
I had a habit of not seeing things as they appear on the surface, but trying to find the "other side" of them, and interpreting them in a "malicious" way.
(これは、今の、私のコラムやブログを読んで頂ければ明らかです)。
(This is obvious if you read my columns and blogs, now)
子どもの「勝ち組」というのは、明るく、元気で、友達が多く、物事に疑問を持たず、大人の言うことを聞く、今で言うところの「陽キャ」、当時で言うところの「根明(ネアカ)」というやつらでした。
The children's "winners" were what we now call "extrovert" or "lively", had many friends, didn't question things, and listened to adults.
(今は、そいつらが『幼稚』だった、ということを知っていますが)
(I know now that they were "childish.")
これに対立する「負け組」は、今で言うところの「陰キャ」、当時で言うところの「根暗(ネクラ)」でした。
The opposing "losers" were what we now call "introvert" or "gloomy" as they were called then.
当時の私でも、回りから「根暗」のレッテルを張られることは、恐しいことでした。
Even back then, I was afraid of being labeled as "gloomy" by those around me.
当然ですが、「根暗」は、仲間外れ(今で言う「イジメ」)の対象にもなったからです。
Naturally, being "gloomy" also meant being ostracized (what we now call "bullied").
学級(クラス)という管理単位の中で生きる子どもにとって、「仲間外れ」は、学校生活での"死"を意味します。
For children who are controlled within the unit of a class, being left out means death in school life.
基本的に、法律(刑事罰)の概念が及ばない「学校」という治外法権(無法地帯)の中にあって、「根暗」とレッテルと張られた子どもたちに、自分を守る手段はありません。
Basically, in the extraterritoriality (lawlessness) of "school," where the concept of law (criminal punishment) does not apply, children who are labeled as "dark-skinned" have no way to protect themselves.
外面はどうあれ、私の内実は、「負け組」「陰キャ」「根暗(ネクラ)」で、そんな私にとって、学校は『地獄そのもの』だったのです。
Regardless of what I looked like on the outside, I was in fact a "loser","introvert" or "gloomy" and schools were "hell itself" for me.
-----
そんな環境にあって、たまたま私が携帯していたものが、「ピアノ」という『武器』でした。
In such an environment, what I happened to carry with me was a "weapon" called "piano".
ピアノは ―― モテます。主に女子から。
Playing the piano made me popular, mostly with girls.
もう、問答無用の最終兵器でした。
It was already the ultimate weapon, no questions asked.
ピアノを習ったことがある人なら、当然知っていますが、ピアノを2～3年間、毎日続けていればで、「耳コピ」なんぞ簡単にできるようになります。
If you've ever taken piano lessons, you know that if you play the piano every day for two to three years, you can easily learn to play by ear by yourself.
さらに、アニメの主題歌、流行歌、なんぞ、両手を使って ―― つまり主旋律ではなく、演奏の方を ―― ピアノで弾けるようになります。
In addition, you will be able to play anime theme songs, popular songs, etc. on the piano using both hands -- not the main melody, but the performance.
これで、モテないわけがありません。
With this, there is no way you won't be popular.
私が弾いているピアノは、常に数人の女の子が取り囲んでいました。
The piano I was playing was always surrounded by several girls.
------
『江端・・・常々、お前は、いけすかねえ野郎と思っていたが、ここに至っても、まだ自慢話か』
"Ebata... I've always thought you were the worst unpleasant person, however you are still bragging it again"
と、思われているかもしれません。
You might be thinking.
私だってそう思います。
I think so too.
でもね、私、この話を、他人にしたことないんですよ。
But, you know, I've never told this story to anyone else.
嫁さんにも娘にもしたことがありません。
I have never done this to my wife or my daughter.
この"私"が、こんな"美味しい自慢ネタ"を黙っている ―― そんなことありえると思いますか？
Do you think it's possible that I'm not telling you about this delicious boast?
いや、ない。ありえない。
No, no. It's not possible.
今の私に、思い当たることは一つです。
There is one thing that comes to mind for me right now.
私ですら信じられないのですが、多分、私は「必死」だったんです。
Even I couldn't believe it, but maybe I was "desperate".
「負け組」「陰キャ」「根暗(ネクラ)」が、学校という『地獄』で生き抜くことに。
The "loser", "introvert" or "gloomy" had to survive in the "hell" of school.
えらそうに学校のシステムの不備をつき、教師の不勉強を批判し、子どもたちの狭窄視野を指摘している私は、子どものころは、イジメを怖がって、そこから逃れる手段を考えるだけの、
Though I am pointing out the inadequacies of the school system, criticizing teachers for their lack of knowledge, and worrying about children's narrow view, I was just afraid of bullies and thinking of ways to escape from them, and was
―― 凡庸な子ども
"An ordinary child"
だったのです。
だから、私は、死ぬほど大嫌いだった「ピアノ」という『武器』を、手放すことができなかったのです ―― 中学2年生になるまで。
That's why I couldn't let go of my weapon of choice, the piano, which I hated to death -- until I was in the eighth grade.
なるほど、こんな恥かしい話、できる訳がありませんし、私が無意識下に封印してきたのも道理というものです。
I see. There is no way I can talk about such a shameful thing. It's no wonder I've unconsciously sealed it away.
(To be continued)
最近、「過去の自分に戻る」というコミックやアニメが多いです。
Lately, there have been a lot of comics and anime about "going back to the past".
この手のコンテンツに共通することは『過去の記憶を保持している』と『過去の事象が再現される』という前提条件です。
What all these contents have in common is the prerequisite of 'retaining memories of the past' and 'recreating the events of the past'.
まあ、こういう設定がないと、コンテンツとして成立しないので、仕方がないのかもしれません。
Well, without this kind of arrangement, the content would be unsustainable, so it may be inevitable.
-----
しかし、私の場合、仮にこの2つの前提条件があったとしても、「過去の自分に戻る」ことは希望しません。
However, in my case, even if I had these two prerequisites, I would not wish to "return to my past.
特に、小学校から中学校にかけては、ゴメンです。
Especially from elementary school to junior high school, it is joking.
あの「息苦しさ」を忘れることはできません。
I will never forget that "suffocating feeling".
勿論、誰のどんな人生だって、「息苦しい」とは思いますが、大人の方が、対処方法が選べる分、ラクな気がします。
Of course, everyone's life is "suffocating," but I think it's easier for adults because they can choose how to deal with it.
―― 最悪でも、組織を巻き込んで自爆してやる
"At the very worst, we could have a suicide bomber involving the organization"
という選択肢があるだけでも、大人の方が、ずっとマシです。
Adults should get that option.
子どもの頃は、大人とか教師とか学校とか言うシステムを「破壊する」という発想は、できませんでした。
When I was a child, the idea of "destroying" the system of adults, teachers, and schools was not possible.
今なら、その発想は簡単にできるのですが。
Now, that idea is easy for me to do.
子どもが大人に頼れれば良いのですが、そもそも、子どもにとって「大人は敵」ですから、頼れようがありません。
It would be great if children could rely on adults, but for children, adults are the enemy, so there is no way to rely on them.
それはさておき。
Aside from that.
-----
私、小学校のころから、ピアノを続けていました ―― 死ぬほど、ピアノの練習が嫌いだったにも関わらずです。
I've been taking piano lessons since I was in elementary school -- even though I hated practicing piano to death.
今のピアノのレッスンというものが、どのようになっているかは知りませんが、私の子どものころは、それはもう、下らないくらいに「教条主義」でした。
I don't know how piano classes are today, but when I was a kid, they were so "dogmatic" that they were trivial.
今なら、はっきりと「バッカじゃねーの」と言い切れます。
Now, I can clearly say, "They were idiot".
バイエル、ブルクミュラー、ツェルニー・・・、あの「絶望的なまでに退屈な曲の演奏」を強いられる日々は、本当にうんざりでした。
Beyer, Burgmuller, Czerny... I was really fed up with those days of being forced to "play hopelessly boring music".
『ピアノの上達のためには、弾く手のフォームを美しく整えることが欠かせません』が、ウソであるとは言いませんが ――
I'm not saying that "To improve your piano playing, it's essential to have a beautiful finger form" is all bullshit.
しかし、『ピアノの上達のためには、フォームなんぞ瑣末なことを忘れて、ピアノを弾くことを心から楽しむこと』こそが、絶対的な真理です。
However, the absolute truth is that "in order to improve your piano playing, you must forget about such trivial matters as form and truly enjoy playing the piano".
-----
こういう、「狂った教条主義」の一例が、テニス部に入っても「1年生はボールを打たず、走り込みと筋トレをするものである」という、下らない「しきたり」です。
One example of this kind of "crazy dogmatism" is the stupid "ritual" of joining the tennis club, "freshmen are not supposed to hit the ball, but run and do strength training.
私は、自腹を切って、とっととテニススクールやスキースクールに入って、ロジカルに、最速かつ最短に、"技を"教えて貰いました。
I paid my own way and quickly joined a tennis school or a ski school to learn the "techniques" in the fastest and most logical way.
今の私は、テニスとスキーの一通りの技を使えて、普通に楽しめるレベルにあります。
I am now at a level where I can use a whole range of tennis and skiing techniques and enjoy them normally.
そして、私が、テニスとスキーを上達するために走り込んだ距離は「0メートル」です。
And, the distance I have run to improve my tennis and skiing is "0 meters".
-----
さて、それらを見直してみて、今の私に分からないことは、『なぜ、当時の私は、とっととピアノなんぞを止めなかったか』ということなのです。
Now, after reviewing them, what I don't understand now is why I didn't stop playing the piano as soon as I could.
(To be continued)
/codes/20201224/
====================================
root# apt install postgresql-13-pgrouting
// 必要なDBのテーブルを作成
///// 江端追加ここから
root# cd /go/src
root# chmod a+rx -R work
root# cd work
root# chmod a+rx -R environment
///// 江端追加ここまで
root# su - postgres
postgres# cd /go/src/work/environment
====================================
修正(コメントアウト)は2箇所
(1)
root@8f02d02f5b8e:/go/src/agent# cat User.cpp | grep 12/24
// LOG_D << ss_info; 江端が実施 12/24 15:43
(2)該当のファイルは、「client_init.go」です。
>71行目
> paramF, _ := strconv.Atoi(x)
>
>を削除（コメントアウト）いただきたく、よろしくお願いいたします。
>（再度のgo installは不要です。）
====================================