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Commit 70d727f6 authored by sgegito's avatar sgegito
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*.o
*.x
*.pgm
*.a
*.b
*.c
*.aa
*.bb
*.cc
*.lines
opti
Python/__pycache__/load_vec.cpython-38.pyc deleted 100644 → 0
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Python/__pycache__/load_vec.cpython-39.pyc deleted 100644 → 0
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Python/example.py deleted 100644 → 0
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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()
Python/load_vec.py deleted 100644 → 0
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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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0.404912 0.337045
0.874113 0.362145
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0.516266 0.080001
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plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/.gitignore deleted 100644 → 0
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*.vec
.vscode
__pycache__
example
*.o
\ No newline at end of file
plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/main.c deleted 100644 → 0
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#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
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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
plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.c deleted 100644 → 0
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#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
plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/C/vector.h deleted 100644 → 0
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#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
plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/example.py deleted 100644 → 0
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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()
plot-c-arrays-with-matplotlib-master/plot-c-arrays-with-matplotlib-master/Python/load_vec.py deleted 100644 → 0
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View file @ ed093534
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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