def generate_chart_image(chart_data_dict: dict) -> Path:
"""
Create the chart image with given input, return image Path.
:param chart_data_dict: dict
:return: Path object
"""
fig = plt.figure(figsize=(19.20,
10.80)) # set proportion/size in inches, 1080p
ax = plt.subplot(xlim=(-0, 105), ylim=(-0, 100))
plt.subplots_adjust(left=0.05,
right=0.95,
top=0.9,
bottom=0.1,
wspace=0.01,
hspace=0.01)
# TODO: hide vertical axis, top and right border lines.
set_axis()
ax.grid(False) # No grid
# if custom chart parameters affecting avatar layout,
# pass chart_data_dict['chart_params'] to generate_avatar_coords
avatar_coord_dict = generate_avatar_coords(
chart_data_dict['score-students_dict'], chart_data_dict['class_id'])
add_avatars_to_plot(ax, avatar_coord_dict)
image_location = definitions.DATABASE.save_chart_image(
chart_data_dict, plt)
return image_location
def generate_chart_image(chart_data_dict: dict):
"""
Create the chart image with given input.
:param chart_data_dict: dict
:return: None
"""
fig = plt.figure(figsize=(16, 9)) # set proportion/size in inches,
ax = plt.subplot(xlim=(-0, 105), ylim=(-0, 100))
plt.subplots_adjust(left=0.05,
right=0.95,
top=0.9,
bottom=0.1,
wspace=0.01,
hspace=0.01)
# TODO: hide vertical axis, top and right border lines.
set_axis()
ax.grid(False) # No grid
# if custom chart parameters affecting avatar layout, pass chart_data_dict['chart_params'] to generate_avatar_coords
# nominally, avatar_coord_dict will be chart_data_dict['score-avatar_dict']
avatar_coord_dict = generate_avatar_coords(
chart_data_dict['score-avatar_dict'])
add_avatars_to_plot(ax, avatar_coord_dict)
image_location = save_chart_image(chart_data_dict)
return image_location
def generate_chart_image(chart_data_dict: dict):
"""
:param chart_data_dict: dict
:return: None
"""
fig = plt.figure(figsize=(16, 9)) # set proportion/size in inches,
ax = plt.subplot(xlim=(-0, 105), ylim=(-0, 100))
plt.subplots_adjust(left=0.05,
right=0.95,
top=0.9,
bottom=0.1,
wspace=0.01,
hspace=0.01)
# TODO: hide vertical axis, top and right border lines.
set_axis()
ax.grid(False) # No grid
# if custom chart parameters affecting avatar layout, pass chart_data_dict['chart_params'] to generate_avatar_coords
# nominally, avatar_coord_dict will be chart_data_dict['score-avatar_dict']
avatar_coord_dict = generate_avatar_coords(
chart_data_dict['score-avatar_dict'])
add_avatars_to_plot(ax, avatar_coord_dict)
# Maximise displayed image.
mng = plt.get_current_fig_manager()
mng.window.state("zoomed")
# Show image.
plt.show()
save_chart_image(chart_data_dict)
def test_generate_avatar_coords(self):
test_generate_avatar_coords_result = {
'foo': [(0.0, 5), (10.0, 35)],
'spam': [(0.0, 15), (10.0, 45)],
'dead': [(0.0, 25), (10.0, 55)],
'parrot': [(0.0, 35), (10.0, 65)],
'halibut': [(0.0, 45), (10.0, 75)],
'patties': [(0.0, 55), (10.0, 85)],
'original': [(10.0, 5)],
'recipe': [(10.0, 15)],
'chicken': [(10.0, 25)],
}
assert generate_avatar_coords(
self.test_score_avatar_dict) == test_generate_avatar_coords_result
def test_generate_avatar_coords_backends(self, request, monkeypatch,
database_backend):
test_database = request.getfixturevalue(database_backend)
test_database.default_avatar_path = 'mocked_default_avatar_path'
test_existing_class = NewClass.from_dict(
test_full_class_data_set['json_dict_rep'])
for student in test_existing_class:
if student.avatar_id:
Path(test_existing_class.temp_avatars_dir,
student.avatar_id).write_text(student.avatar_id)
# Create class in db:
test_database.create_class(test_existing_class)
# Find class id to load:
classes = test_database.get_classes()
test_class_id = classes[0].id
# test_class = Class.from_dict(test_full_class_data_set['json_dict_rep'])
test_class = test_database.load_class(test_class_id)
monkeypatch.setattr(process_chart_data.definitions, 'DATABASE',
test_database)
# student_score_entry_sequence = [0, 1, 3, None, 50, 99, 100, 1, 2, 3, 4, None, 6, 7, 8]
test_student_scores_dict = {
0: [test_class.students[0]], # Cali
1: [
test_class.students[1], # Monty
test_class.students[7]
], # Regina
3: [
test_class.students[2], # Abby
test_class.students[9]
], # Alex
# No score, not returned: None: [test_class.students[3], # Zach
# test_class.students[11]], # Edgar
50: [test_class.students[4]], # Janell
99: [test_class.students[5]], # Matthew
100: [test_class.students[6]], # Olivia
2: [test_class.students[8]], # Ashley
4: [test_class.students[10]], # Melissa
6: [test_class.students[12]], # Danielle
7: [test_class.students[13]], # Kayla
8: [test_class.students[14]], # Jaleigh
}
# Vary calls for actual avatars based on backend.
test_generate_avatar_coords_result = {
**{
'mocked_default_avatar_path': [(0.0, 15), (0.0, 25), (0.0, 45),
(0.0, 55), (0.0, 65), (10.0, 15),
(10.0, 25), (50.0, 5), (100.0, 5),
(100.0, 15)],
},
**({
test_database.get_avatar_path_class_filename(
test_class.id, test_class.students[8].avatar_id): [(0.0, 35)], # Ashley
test_database.get_avatar_path_class_filename(
test_class.id, test_class.students[0].avatar_id): [(0.0, 5)], # Cali
test_database.get_avatar_path_class_filename(
test_class.id, test_class.students[12].avatar_id): [(10.0, 5)], # Danielle
} if isinstance(test_database, JSONDatabase) else {
test_database.get_avatar_path(test_class.students[8].avatar_id): [(0.0, 35)], # Ashley
test_database.get_avatar_path(test_class.students[0].avatar_id): [(0.0, 5)], # Cali
test_database.get_avatar_path(test_class.students[12].avatar_id): [(10.0, 5)], # Danielle
}),
}
assert generate_avatar_coords(
test_student_scores_dict,
test_class.id) == test_generate_avatar_coords_result
def test_generate_avatar_coords_generic_api(self, monkeypatch,
empty_generic_database):
test_database = empty_generic_database
test_database.default_avatar_path = 'mocked_default_avatar_path'
test_class = Class.from_dict(test_full_class_data_set['json_dict_rep'])
student_score_entry_sequence = [
0, 1, 3, None, 50, 99, 100, 1, 2, 3, 4, None, 6, 7, 8
]
# Mock out avatar_paths with readable strings.
avatar_paths = [
f'path to {student.avatar_id}' if student.avatar_id is not None
else test_database.default_avatar_path
for student in test_class.students
]
# Format those avatar_paths to remove students who did not submit a score:
mocked_get_avatar_path_return_values = [
avatar_paths[student_score_entry_sequence.index(score)]
for score in student_score_entry_sequence if score is not None
]
avatar_path = (path for path in mocked_get_avatar_path_return_values)
avatar_ids = [student.avatar_id for student in test_class]
def mocked_get_avatar_path(avatar_id):
"""
Strictly speaking does not need a mock, as should raise error, but
re-mocking method for clarity.
"""
assert avatar_id in avatar_ids
# deepcode ignore unguarded~next~call: No guard - let error propagate, should not reach StopIteration.
return next(avatar_path)
test_database.get_avatar_path = mocked_get_avatar_path
monkeypatch.setattr(process_chart_data.definitions, 'DATABASE',
test_database)
test_student_scores_dict = {
0: [test_class.students[0]], # Cali
1: [
test_class.students[1], # Monty
test_class.students[7]
], # Regina
3: [
test_class.students[2], # Abby
test_class.students[9]
], # Alex
# No score, not returned: None: [test_class.students[3], # Zach
# test_class.students[11]], # Edgar
50: [test_class.students[4]], # Janell
99: [test_class.students[5]], # Matthew
100: [test_class.students[6]], # Olivia
2: [test_class.students[8]], # Ashley
4: [test_class.students[10]], # Melissa
6: [test_class.students[12]], # Danielle
7: [test_class.students[13]], # Kayla
8: [test_class.students[14]], # Jaleigh
}
test_generate_avatar_coords_result = {
'mocked_default_avatar_path': [(0.0, 15), (0.0, 25), (0.0, 35),
(0.0, 45), (0.0, 55), (0.0, 65),
(10.0, 15), (10.0, 25), (50.0, 5),
(100.0, 5)],
'path to Ashley_avatar.png': [(100.0, 15)],
'path to Cali_avatar.png': [(0.0, 5)],
'path to Danielle_avatar.png': [(10.0, 5)]
}
assert generate_avatar_coords(
test_student_scores_dict,
test_class.id) == test_generate_avatar_coords_result