def main():
course_content = None
student_info = None
courses_file_name = "data/car-f-92.crs"
student_file_name = "data/car-f-92.stu"
course_dict = {}
student_dict = {}
# leemos el archivo con la informacion de los cursos (id, cantidad de estudiantes)
with open(courses_file_name, "r+") as f:
course_content = [course.split() for course in [line.rstrip('\n') for line in f]]
#print(studen_info)
# leemos el archivo con la información de los estudiantes (lista de cursos a los que está inscrito)
with open(student_file_name, "r+") as f:
student_info = [student.split() for student in [line.rstrip('\n') for line in f]]
#print(course_content)
# generamos diccionarios de objetos que representan a los cursos y a los estudiantes con todos sus atributos
course_dict, student_dict = Formatter(course_content, student_info).format()
total_students = len(student_dict)
total_courses = len(course_dict)
conflict_matrix = np.zeros(total_courses * total_courses).reshape(total_courses, total_courses)
conflicts = 0
for course_id, course in course_dict.items():
students = course.student_list
for course_id2, course2 in course_dict.items():
students2 = course2.student_list
for student in students:
for student2 in students2:
if student.student_id == student2.student_id:
conflict_matrix[course.get_numeric_id() - 1][course2.get_numeric_id() - 1] = 1
conflicts += 1
print(conflicts)
print(conflict_matrix)
print("Conflict density:", conflicts/(total_courses*total_courses))
"""
# imprime contenido de diccionario de cursos para probar
for course_id, course in course_dict.items():
print(course.course_id)
print(course.no_students)
for student in course.student_list:
print(student.student_id)
"""
"""
def build_dashboard(self,
input_data={},
aligment={},
params={},
title="Stock Closing Prices",
ylabel='Price',
ylabel_right={},
show=True,
column='adj_close',
height=[],
**kwargs_to_bokeh):
plots = []
_data, x_range, _names = Formatter().format_input_data(
input_data, column)
_params = Formatter().format_params(_data, params, _names)
_aligment = Formatter().format_aligment(aligment, _names)
_y_label_right = Formatter().format_y_label_right(
ylabel_right, ylabel, _names)
kwargs_to_bokeh['y_axis_label'] = ylabel
if 'x_range' not in kwargs_to_bokeh:
kwargs_to_bokeh['x_range'] = Range1d(x_range[0], x_range[-1])
if not height:
height = [(1. / len(_data))] * len(_data)
else:
assert len(height) == len(_data), (
"Number of heights should be equal to the number of plots. " +
"expected: %s, " % len(_data) +
"found: %s, len(height)= %s. " % (height, len(height)))
assert sum(height) == 1, ("All heights should sum up to 1, " +
"found: %s, sum(height)=%s" %
(height, sum(height)))
for i, (plot_title, data) in enumerate(_data.items()):
plots.append(
self._plot_stock(data=data,
names=_names[plot_title],
title=plot_title,
params=_params[plot_title],
aligment=_aligment[plot_title],
ylabel_right=_y_label_right[plot_title],
height=height[i],
**kwargs_to_bokeh))
layout = gridplot(plots, plot_width=self.width, ncols=self.ncols)
self.layout = layout
if show:
curdoc().add_root(layout)
curdoc().title = title
return curdoc
