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authorjustanothercatgirl <sotov2070@gmail.com>2024-12-04 10:02:11 +0300
committerjustanothercatgirl <sotov2070@gmail.com>2024-12-04 10:02:11 +0300
commitc031795880d2ff2d3b64864a4ba68280a91d21c3 (patch)
treed3d3c930cb16a6ff16b5501c977ea1701fe5bd72 /110/__main.cpp
parent35f687f6a4e306585a263b2611f9a5c8b3c2a3a8 (diff)
Finished 110
Diffstat (limited to '110/__main.cpp')
-rw-r--r--110/__main.cpp117
1 files changed, 117 insertions, 0 deletions
diff --git a/110/__main.cpp b/110/__main.cpp
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+++ b/110/__main.cpp
@@ -0,0 +1,117 @@
+#include <iostream>
+
+#include "include/praktable.hpp"
+
+using table = prak::table<double>;
+using vecarg = const std::vector<f64> &;
+using f64p = prak::pvalue<f64>;
+table data;
+
+const f64p g = {9.815710602, 0.001};
+
+f64 get(std::string key) {
+ return data[key, 0];
+}
+
+// [0] = x0
+f64 getsqrt(vecarg v) {
+ return std::sqrt(std::abs(get("x0_1") - v[0]));
+}
+
+f64 a_A(vecarg a) {
+ return 2/a[0]/a[0];
+}
+
+f64 J_mrga(vecarg a) {
+ return a[0] * a[1] * a[1] * (a[2]/a[3] - 1);
+}
+
+f64 ξ_x012(vecarg x) {
+ return (x[1] - x[0]) / (2*x[2] - x[0] - x[1]);
+}
+
+f64 Mfr_mgRξ(vecarg a) {
+ return a[0] * a[1] * a[2] * a[3];
+}
+
+f64 J_mrgtx034(vecarg a) {
+ return a[0]*a[1]*a[1]*(a[2]*a[3]*a[3] / 2 / std::pow(std::sqrt(a[4]-a[6]) - std::sqrt(a[4]-a[5]), 2) - 1);
+}
+
+table ex1(std::string s) {
+ table ret(s);
+ ret.add_column("x1", std::vector<f64>(ret.rows, NAN))
+ .add_column("t", std::vector<f64>(ret.rows, NAN))
+ .add_column("st", std::vector<f64>(ret.rows, NAN))
+ .add_column("sqrt", std::vector<f64>(ret.rows, NAN))
+ .apply(prak::avg<f64>, {"x11", "x12", "x13"}, "x1")
+ .apply(prak::avg<f64>, {"t1", "t2", "t3"}, "t")
+ .apply(prak::stddev<f64>, {"t1", "t2", "t3"}, "st")
+ .apply(getsqrt, {"x3"}, "sqrt")
+ .delete_cols({"x11", "x12", "x13", "t1", "t2", "t3"});
+ auto [A, B] = ret.least_squares_linear("sqrt", "t", "st", std::nullopt);
+
+ f64p m1 = {get("m1"), 0.00001},
+ R = {get("R2"), 0.00005},
+ x0 = {get("x0_1"), 0.01},
+ x1 = {ret.col_avg("x1"), 0.01 * std::sqrt(ret.rows)},
+ x2 = {get("x2_1"), 0.01};
+
+ /*std::cout << x0 << '\n' << x1 << '\n' << x2 << '\n';*/
+ f64p a = prak::function<f64>(a_A, {A});
+ f64p J = prak::function<f64>(J_mrga, {m1, R, g, a});
+ f64p ξ = prak::function<f64>(ξ_x012, {x0, x1, x2});
+ f64p Mfr = prak::function<f64>(Mfr_mgRξ, {m1, g, R, ξ});
+ std::cout << ret
+ << "\na = " << a
+ << "\nJ = " << J
+ << "\nξ = " << ξ
+ << "\nМомент трения Mfr = " << Mfr
+ << std::endl;
+ return ret;
+}
+
+void ex2(std::string data) {
+ table table(data);
+ f64p R0 = {get("R2_0"), 0.00005},
+ R1 = {get("R2_1"), 0.00005},
+ m0 = {get("m2_0"), 0.00001},
+ m1 = {get("m2_1"), 0.00001},
+ x0 = {get("x0_2"), 0.01},
+ x3 = {get("x3_2"), 0.01},
+ x4 = {get("x4_2"), 0.01};
+
+ table .add_column("t", std::vector<f64>(table.rows, NAN))
+ .add_column("st", std::vector<f64>(table.rows, NAN))
+ .add_column("Ji", std::vector<f64>(table.rows, NAN))
+ .add_column("sJi", std::vector<f64>(table.rows, NAN))
+ .add_column("0", std::vector<f64>(table.rows, 0.0))
+ .apply(prak::avg<f64>, {"t1", "t2", "t3"}, "t")
+ .apply(prak::stddev<f64>, {"t1", "t2", "t3"}, "st")
+ .delete_cols({"t1", "t2", "t3"})
+ ;
+ for (size_t i = 0; i < table.rows; ++i) {
+ /* mrgtx034 */
+ std::vector<f64p> args = {
+ table["M", i] == 0 ? m0 : m1,
+ table["R", i] == 0 ? R0 : R1,
+ g, {table["t", i], table["st", i]},
+ // я проебался и только на первом измерении у меня x4 = 4см, на остальных 10см
+ x0, x3, table["M", i] == 0 && table["R", i] == 0 ? f64p{0.04, 0.01} : x4,
+ };
+ auto [val, err] = prak::function<f64>(J_mrgtx034, args);
+ table["Ji", i] = val;
+ table["sJi", i] = err;
+ }
+ table.write_plot("ex2_1.plot", "Ji", "0", "sJi");
+ table.multiply_column("sJi", 1 / std::sqrt(1 - 0.75));
+ table.write_plot("ex2_2.plot", "Ji", "0", "sJi");
+ std::cout << table;
+}
+
+int main() {
+ data = table("common");
+ ex1("data1");
+ ex2("data2");
+ return 0;
+}