From aa6656d11cee4b16b2699f6958059c84db6666cb Mon Sep 17 00:00:00 2001
From: Philippe <philippe.montandon@etu.hesge.ch>
Date: Sun, 5 Dec 2021 13:41:34 +0100
Subject: [PATCH] Je me sens super seul
---
Makefile | 2 +-
opti.c | 93 +++++++++++++++-
opti.h | 6 +-
plot-c-arrays-with-matplotlib-master.zip | Bin 0 -> 4775 bytes
.../.gitignore | 5 +
.../C/main.c | 32 ++++++
.../C/makefile | 12 ++
.../C/vector.c | 105 ++++++++++++++++++
.../C/vector.h | 62 +++++++++++
.../Python/example.py | 19 ++++
.../Python/load_vec.py | 50 +++++++++
11 files changed, 379 insertions(+), 7 deletions(-)
create mode 100644 plot-c-arrays-with-matplotlib-master.zip
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/.gitignore
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/main.c
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/makefile
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.c
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.h
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/example.py
create mode 100644 plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/load_vec.py
diff --git a/Makefile b/Makefile
index 437c3ab..496a372 100644
--- a/Makefile
+++ b/Makefile
@@ -1,4 +1,4 @@
-CC=gcc -Wall -Wextra
+CC=gcc -Wall -Wextra -lm
opti: opti.o
$(CC) $^ -o $@
opti.o: opti.c
diff --git a/opti.c b/opti.c
index 3aa38ad..56400ec 100644
--- a/opti.c
+++ b/opti.c
@@ -9,7 +9,7 @@ double RANDOMNESS = 0.01;
Point* line(double a, double b){
Point * points = (Point*)malloc(sizeof(Point)*LINE_POINTS);
double x = 0.0;
- for(int i=0;i<LINE_POINTS-1;i++){
+ for(int i=0;i<LINE_POINTS;i++){
Point d;
d.x = x;
d.y = (a*x)+b;
@@ -20,6 +20,14 @@ Point* line(double a, double b){
return points;
}
+double popow(double v, double w){
+ double u=v;
+ for(int i=1;i<w;i++){
+ v*=u;
+ }
+ return v;
+}
+
double double_random(double min, double max)
{
double my_random;
@@ -29,9 +37,10 @@ double double_random(double min, double max)
return my_random;
}
-Point* cloud(Point* a_line){
+// version 1 du nuage, se doit d'appeler line indirectement
+Point* cloud1(Point* a_line){
Point * my_cloud = (Point*)malloc(sizeof(Point)*CLOUD_POINTS);
- for(int i=0;i<CLOUD_POINTS-1;i++){
+ for(int i=0;i<CLOUD_POINTS;i++){
Point chosen_point = a_line[rand()%LINE_POINTS-1];
double new_y = double_random(chosen_point.y-RANDOMNESS, chosen_point.y+RANDOMNESS);
my_cloud[i].x=chosen_point.x;
@@ -41,10 +50,84 @@ Point* cloud(Point* a_line){
return my_cloud;
}
+// version 2 du nuage, peut être généré grâce aux a et b d'une droite
+// génère aléatoirement des points sur l'axe des x (qui ne sont donc pas espacés uniformément)
+Point* cloud2(double a, double b){
+ Point * my_cloud = (Point*)malloc(sizeof(Point)*CLOUD_POINTS);
+ for(int i=0;i<CLOUD_POINTS;i++){
+ Point chosen_point;
+ chosen_point.x = double_random(0,1);
+ for(int j=0;j<CLOUD_POINTS-1;j++){
+ while(chosen_point.x==my_cloud[j].x){
+ chosen_point.x = double_random(0,1);
+ }
+ }
+ double rj = double_random(-RANDOMNESS, RANDOMNESS);
+ chosen_point.y = (a*chosen_point.x)+b+rj;
+ my_cloud[i].x=chosen_point.x;
+ my_cloud[i].y=chosen_point.y;
+ printf("\nx = %f | y = %f\n", my_cloud[i].x,my_cloud[i].y);
+ }
+ return my_cloud;
+}
+
+// version 3 du nuage, plus simple, x espacés uniformément
+Point* cloud3(double a, double b){
+ Point * my_cloud = (Point*)malloc(sizeof(Point)*CLOUD_POINTS);
+ for(int i=0;i<CLOUD_POINTS;i++){
+ Point chosen_point;
+ chosen_point.x = double_random(0,1);
+ for(int j=0;j<CLOUD_POINTS-1;j++){
+ while(chosen_point.x==my_cloud[j].x){
+ chosen_point.x = double_random(0,1);
+ }
+ }
+ double rj = double_random(-RANDOMNESS, RANDOMNESS);
+ chosen_point.y = (a*chosen_point.x)+b+rj;
+ my_cloud[i].x=chosen_point.x;
+ my_cloud[i].y=chosen_point.y;
+ printf("\nx = %f | y = %f\n", my_cloud[i].x,my_cloud[i].y);
+ }
+ return my_cloud;
+}
+
+double* average(Point* my_cloud, int cloud_size){
+ double* avg = (double*)malloc(sizeof(double)*4);
+ double x_avg, y_avg, x2_avg, xy_avg;
+ for(int i=0; i<cloud_size-1;i++){
+ x_avg+=my_cloud[i].x;
+ y_avg+=my_cloud[i].y;
+ x2_avg+=popow((my_cloud[i].x),2);
+ xy_avg+=((my_cloud[i].x)*(my_cloud[i].y));
+ }
+ x_avg/=cloud_size; y_avg/=cloud_size; x2_avg/=cloud_size; xy_avg/=cloud_size;
+ avg[0]=x_avg; avg[1]=y_avg; avg[2]=x2_avg; avg[3]=xy_avg;
+ printf("x=%f - y=%f - x2=%f - xy=%f", avg[0],avg[1],avg[2],avg[3]);
+ return avg;
+}
+
+double* a_and_b(double* my_average){
+ double* a_n_b = (double*)malloc(sizeof(double)*2);
+ double x_avg = my_average[0];
+ double y_avg = my_average[1];
+ double x2_avg = my_average[2];
+ double xy_avg = my_average[3];
+ double a = (xy_avg-(x_avg*y_avg))/(x2_avg-popow(x_avg,2));
+ double b = y_avg-(a*x_avg);
+ a_n_b[0]=a;
+ a_n_b[1]=b;
+ return a_n_b;
+}
+
+double cost(){
+ return 0.0;
+}
+
int main (void){
srand ( time ( NULL));
- Point* first_line = line(7.0, 5.5);
- cloud(first_line);
+ //Point* first_line = line(7.0, 5.5);
+ Point* fluffy = cloud2(7.0, 5.5);
+ average(fluffy, CLOUD_POINTS);
printf("\ndone\n");
return 0;
}
\ No newline at end of file
diff --git a/opti.h b/opti.h
index 63113bc..4b3591b 100644
--- a/opti.h
+++ b/opti.h
@@ -1,9 +1,10 @@
#ifndef _OPTI_H_
#define _OPTI_H_
+#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
-#include <time.h>
+#include <math.h>
@@ -17,5 +18,8 @@ struct Point
Point* line(double a, double b);
double double_random(double min, double max);
Point* cloud(Point* a_line);
+Point* cloud2(double a, double b);
+double* average(Point* my_cloud, int cloud_size);
+double* a_and_b(double* my_average);
#endif
\ No newline at end of file
diff --git a/plot-c-arrays-with-matplotlib-master.zip b/plot-c-arrays-with-matplotlib-master.zip
new file mode 100644
index 0000000000000000000000000000000000000000..41607ac48a1b108fed5f2673b8729d04ad2f21d1
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diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/.gitignore b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/.gitignore
new file mode 100644
index 0000000..c3a8bb1
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/.gitignore
@@ -0,0 +1,5 @@
+*.vec
+.vscode
+__pycache__
+example
+*.o
\ No newline at end of file
diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/main.c b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/main.c
new file mode 100644
index 0000000..e1a7fcf
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/main.c
@@ -0,0 +1,32 @@
+#include <stdio.h>
+#include <math.h>
+
+#include "vector.h"
+
+/** @brief
+ * An exemple of mathematical function
+ * in 1 dimension.
+ *
+ * @param x A double variable.
+ * @return f(x) = 2.0*sin(x) - 3.0*cos(x)
+ */
+double my_function(double x)
+{
+ return 2.0 * sin(x) - 3.0 * cos(x);
+}
+
+int main()
+{
+ // Create a vector X = [0,1,2...99]
+ double_vector_t *X = iota(100);
+ // Create a vector Y = my_function(x)
+ double_vector_t *Y = apply_function(X, my_function);
+
+ // Export our vectors into files
+ export_vector("../X.vec", X);
+ export_vector("../Y.vec", Y);
+
+ // Free our vectors
+ destroy_vector(&Y);
+ destroy_vector(&X);
+}
\ No newline at end of file
diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/makefile b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/makefile
new file mode 100644
index 0000000..8dda09a
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/makefile
@@ -0,0 +1,12 @@
+
+CC=gcc -std=gnu11 -Wall -Wextra -g -fsanitize=leak -fsanitize=undefined
+LIBS=-lm
+
+example: vector.o vector.h main.c
+ $(CC) $^ $(LIBS) -o $@
+
+vector.o: vector.c vector.h
+ $(CC) -c $< -o $@
+
+clean:
+ rm -f *.vec *.o example
\ No newline at end of file
diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.c b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.c
new file mode 100644
index 0000000..ff4428b
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.c
@@ -0,0 +1,105 @@
+#include <stdio.h>
+#include <stdlib.h>
+
+#include "vector.h"
+
+/** @brief
+ * Compute the endianness used by
+ * the architecture.
+ *
+ * @return 1 if little-endian, 0 if big-endian
+ */
+uint8_t get_endianness()
+{
+ uint32_t endianness = 0x01020304;
+ // Return the endianness by accessing the first byte in memory
+ // which should be 1 if big-endian and 4 if little-endian
+ return *((uint8_t *)(&endianness)) == 4;
+}
+
+/** @brief
+ * Create a vector of a given dimension.
+ *
+ * @param N The number of dimensions.
+ * @return A dynamically allocated vector
+ */
+double_vector_t *init_vector(uint32_t N)
+{
+ double_vector_t *vec = malloc(sizeof(double_vector_t));
+ vec->components = malloc(N * sizeof(double));
+ vec->N = N;
+ if (vec == NULL)
+ {
+ perror("Can't allocate memory");
+ exit(EXIT_FAILURE);
+ }
+ return vec;
+}
+/** @brief
+ * Create a vector of a given dimension,
+ * with values from 0 to N excluded.
+ *
+ * @param N The number of dimensions.
+ * @return A dynamically allocated vector : [0,1..N-1]
+ */
+double_vector_t *iota(uint32_t N)
+{
+ double_vector_t *vec = init_vector(N);
+ for (uint32_t i = 0; i < N; i++)
+ {
+ vec->components[i] = i;
+ }
+ return vec;
+}
+/** @brief
+ * Apply a 1d function element-wise
+ * to a given vector, and return the
+ * result in a new vector.
+ *
+ * @param vec The argument vector
+ * @param f The 1d function to apply
+ * @return A dynamically allocated vector : f(X)
+ */
+double_vector_t *apply_function(double_vector_t *vec, double_function_t f)
+{
+ double_vector_t *res = init_vector(vec->N);
+ for (uint32_t i = 0; i < vec->N; i++)
+ {
+ res->components[i] = f(vec->components[i]);
+ }
+ return res;
+}
+/** @brief
+ * Export a vector into a file.
+ *
+ * @param filename The name of the output file
+ * @param vec The vector to export
+ */
+void export_vector(const char *filename, double_vector_t *vec)
+{
+ FILE *output = fopen(filename, "w");
+
+ vector_metadata_t metadata;
+ metadata.endianness = get_endianness();
+ metadata.size_of_a_component = sizeof(double);
+ metadata.number_of_component = vec->N;
+
+ fwrite(&metadata, sizeof(vector_metadata_t), 1, output);
+ fwrite(vec->components,
+ metadata.size_of_a_component,
+ metadata.number_of_component,
+ output);
+
+ fclose(output);
+}
+/** @brief
+ * Free a vector.
+ *
+ * @param vec A double pointer on a vector
+ */
+void destroy_vector(double_vector_t **vec)
+{
+ free((*vec)->components);
+ free(*vec);
+ *vec = NULL;
+}
\ No newline at end of file
diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.h b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.h
new file mode 100644
index 0000000..ceb461c
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.h
@@ -0,0 +1,62 @@
+#include <stdint.h>
+
+typedef struct double_vector
+{
+ uint32_t N; // The dimmension of the vector
+ double *components;
+} double_vector_t;
+// Function pointer, example : double f(double x);
+typedef double (*double_function_t)(double);
+
+/*
+* The attribute "packed" tells the compiler,
+* that the struct should be stored in memory
+* without padding. It's highly recommended,
+* if we want to serialize the structure.
+* (for example to store it in a file)
+*/
+typedef struct vector_metadata
+{
+ uint8_t endianness; // 1 = little, 0 = big
+ uint8_t size_of_a_component; // in bytes
+ uint32_t number_of_component;
+} __attribute__((packed)) vector_metadata_t;
+
+/** @brief
+ * Create a vector of a given dimension.
+ *
+ * @param N The number of dimensions.
+ * @return A dynamically allocated vector
+ */
+double_vector_t *init_vector(uint32_t N);
+/** @brief
+ * Create a vector of a given dimension,
+ * with values from 0 to N excluded.
+ *
+ * @param N The number of dimensions.
+ * @return A dynamically allocated vector : [0,1..N-1]
+ */
+double_vector_t *iota(uint32_t N);
+/** @brief
+ * Apply a 1d function element-wise
+ * to a given vector, and return the
+ * result in a new vector.
+ *
+ * @param vec The argument vector
+ * @param f The 1d function to apply
+ * @return A dynamically allocated vector : f(X)
+ */
+double_vector_t *apply_function(double_vector_t *vec, double_function_t f);
+/** @brief
+ * Export a vector into a file.
+ *
+ * @param filename The name of the output file
+ * @param vec The vector to export
+ */
+void export_vector(const char *filename, double_vector_t *vec);
+/** @brief
+ * Free a vector.
+ *
+ * @param vec A double pointer on a vector
+ */
+void destroy_vector(double_vector_t **vec);
\ No newline at end of file
diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/example.py b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/example.py
new file mode 100644
index 0000000..e40a556
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/example.py
@@ -0,0 +1,19 @@
+from matplotlib import pyplot as plt
+from load_vec import load_vector
+
+X = load_vector("../X.vec")
+Y = load_vector("../Y.vec")
+
+type_of_data = 'curve'
+
+if type_of_data == 'curve':
+ plt.plot(X, Y, label="my curve")
+else:
+ plt.scatter(X, Y, marker='x', label="my points")
+
+plt.title("My data")
+plt.xlabel("X")
+plt.ylabel("Y")
+plt.legend(loc="upper right")
+
+plt.show()
diff --git a/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/load_vec.py b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/load_vec.py
new file mode 100644
index 0000000..17880a1
--- /dev/null
+++ b/plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/load_vec.py
@@ -0,0 +1,50 @@
+import numpy as np
+from typing import Tuple
+METADATA_SIZE = 6
+
+
+def _parse_metadata(metadata: bytes) -> Tuple[type, int]:
+ """
+ Parse the metadata for a vec file.
+
+ Parameters:
+ metadata (bytes): The metadata bytes
+
+ Returns:
+ (type, int): The type and the number of component of the vector
+ """
+
+ little_endian = bool(metadata[0])
+ endianness = 'little' if little_endian else 'big'
+
+ size_of_components = int(metadata[1])
+ # For now we only consider two types
+ datatype = np.float64 if size_of_components == 8 else np.float
+
+ # Recover our 32 bit integer specifying the endianness
+ nb_components = int.from_bytes(metadata[2:], endianness)
+
+ return datatype, nb_components
+
+
+def load_vector(filename: str) -> np.ndarray:
+ """
+ Load a vector from a file.
+
+ Parameters:
+ filename (str): The name of the file containing the vector
+
+ Returns:
+ np.ndarray: The vector
+
+ """
+ file = open(filename, 'rb')
+ # Read our metadata struct
+ metadata = file.read(METADATA_SIZE)
+
+ datatype, nb_components = _parse_metadata(metadata)
+
+ array = np.fromfile(file, dtype=datatype, count=nb_components)
+
+ file.close()
+ return array
--
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