# si a est impair et b est pair
elif a % 2 != 0 and b % 2 == 0:
return (a - 1) * b
# sinon - c'est que a et b sont impairs
else:
return a * a - b * b
# @END@
def dispatch1_ko(a, b, *args):
return a * a + b * b
exo_dispatch1 = ExerciseFunction(dispatch1, inputs_dispatch1)
####################
samples_A = [(2, 4, 6), [2, 4, 6]]
samples_B = [{6, 8, 10}]
inputs_dispatch2 = [
Args(a, b, A, B) for a, A in zip(range(3, 5), samples_A)
for b in range(7, 10) for B in samples_B
]
# @BEG@ name=dispatch2
def dispatch2(a, b, A, B):
"""
dispatch2 comme spécifié
Idem mais avec une expression génératrice
"""
# on n'a pas encore vu cette forme - cf Semaine 5
# mais pour vous donner un avant-goût d'une expression
# génératrice:
# on peut faire aussi comme ceci
# observez l'absence de crochets []
# la différence c'est juste qu'on ne
# construit pas la liste des carrés,
# car on n'en a pas besoin
# et donc un itérateur nous suffit
return math.sqrt(sum(x**2 for x in args))
# @END@
distance_inputs = [
Args(),
Args(1),
Args(1, 1),
Args(1, 1, 1),
Args(1, 1, 1, 1),
Args(*range(10)),
]
exo_distance = ExerciseFunction(distance, distance_inputs, nb_examples=3)
def distance_ko(*args):
return sum([x**2 for x in args])
def mul3(x=1, y=1, z=1):
return x * y * z
doubler_premier_kwds_inputs = [
Args(add3, 1, 2, 3),
Args(add3, 1, 2, z=3),
Args(add3, 1, y=2, z=3),
# Args(add3, x=1, y=2, z=3),
Args(mul3, 1, 2, 3),
Args(mul3, 1, 2, z=3),
Args(mul3, 1, y=2, z=3),
# Args(mul3, x=1, y=2, z=3),
]
# remettre les datasets de doubler_premier
doubler_premier_kwds_inputs \
+= [ arg_obj for arg_obj in doubler_premier_inputs
if arg_obj.args[0] == distance ]
exo_doubler_premier_kwds = ExerciseFunction(
doubler_premier_kwds, doubler_premier_kwds_inputs,
nb_examples=5,
call_renderer=CallRenderer(show_function=False),
)
def doubler_premier_kwds_ko(f, first, *args, **keywords):
return f(3*first, *args, **keywords)
Args(" 20 40 + 10 * "),
Args("20 6 6 + /"),
Args("20 18 -6 + /"),
Args("10 -3 /"),
Args("10 +"),
Args("10 20 30 +"),
Args("10 20 30 oops"),
Args("40 20 / 10 +"),
Args("40 20 - 10 +"),
Args("+"),
Args("10 20 30 + - /"),
]
exo_postfix_eval = ExerciseFunction(
postfix_eval,
inputs,
nb_examples=8,
)
# @BEG@ name=postfix_eval_typed latex_size=footnotesize
def postfix_eval_typed(chaine, type):
"""
a postfix evaluator, using a parametric type
that can be either `int`, `float` or `Fraction` or similars
"""
def divide(a, b):
if issubclass(type, int):
return a // b
else:
return a / b
return(cx,cy)
inputs_composantes_a = [
Args(15,10,20,15),Args(12,5,22,10),Args(5,5,10,10),Args(5,5,5,10),Args(15,10,23,10),Args(15,15,10,12),Args(20,10,15,15)
]
inputs_soustraction_a_b = [
Args(15,10,20,15),Args(12,5,22,10),Args(5,5,10,10),Args(5,5,5,10),Args(15,10,23,10),Args(15,15,10,12),Args(20,10,15,15)
]
exo_composantes_a = ExerciseFunction(
composantes_a,
inputs_composantes_a,
# show function name in leftmost column
call_renderer=CallRenderer(show_function=True),
# use pprint to format results
result_renderer=PPrintRenderer(width=20),
font_size="90%",
header_font_size="120%",
)
exo_soustraction_a_b = ExerciseFunction(
soustraction_a_b,
inputs_soustraction_a_b,
# show function name in leftmost column
call_renderer=CallRenderer(show_function=True),
# use pprint to format results
result_renderer=PPrintRenderer(width=20),
font_size="90%",
header_font_size="120%",
)
def intersect_ko(A, B):
A_vals = {v for k, v in A}
B_vals = {v for k, v in B}
return A_vals & B_vals
intersect_inputs = []
A1 = {
(12, 'douze'),
(10, 'dixA'),
(8, 'huit'),
}
B1 = {
(5, 'cinq'),
(10, 'dixB'),
(15, 'quinze'),
}
intersect_inputs.append(Args(A1, B1))
A2 = {(1, 'unA'), (2, 'deux'), (3, 'troisA')}
B2 = {(1, 'unB'), (2, 'deux'), (4, 'quatreB')}
intersect_inputs.append(Args(A2, B2))
exo_intersect = ExerciseFunction(
intersect,
intersect_inputs,
nb_examples=2,
call_renderer=PPrintCallRenderer(width=20),
)
from nbautoeval import Args, ExerciseFunction, PPrintCallRenderer
# @BEG@ name=longest_gap
def longest_gap(liste):
result = 0
begins = {}
for index, item in enumerate(liste):
if item not in begins:
begins[item] = index
else:
result = max(result, index - begins[item])
return result
# @END@
inputs = [
Args([1, 2, 3, 1, 4, 10, 4, 3, -1, 4]),
Args(["yes", "no", None, "yes", "no"]),
Args([1, 2, 3, 4]),
]
exo_longest_gap = ExerciseFunction(
longest_gap,
inputs,
nb_examples=0,
call_renderer=PPrintCallRenderer(width=45),
)
scalaire = 0
# sachez reconnaitre ce vilain idiome:
for i in range(len(vec1)):
scalaire += vec1[i] * vec2[i]
return scalaire
# @END@
from fractions import Fraction
inputs_produit_scalaire = [
Args((1, 2), (3, 4)),
Args(range(3, 9), range(5, 11)),
Args([-2, 10], [20, 4]),
Args([Fraction(2, 15), Fraction(3, 4)],
[Fraction(-7, 19), Fraction(4, 13)]),
Args([], []),
]
exo_produit_scalaire = ExerciseFunction(
produit_scalaire,
inputs_produit_scalaire,
call_renderer=PPrintCallRenderer(width=25),
result_renderer=PPrintRenderer(width=25),
)
def produit_scalaire_ko(vec1, vec2):
return [x * y for x, y in zip(vec1, vec2)]
enrichment_data = pd.read_pickle('data/enrichment_data_T4.p')
inputs_calc_EF = [
Args(enrichment_data["tanimoto_maccs"], 4),
Args(enrichment_data["tanimoto_maccs"], 5),
Args(enrichment_data["tanimoto_maccs"], 6),
Args(enrichment_data["tanimoto_morgan"], 4),
Args(enrichment_data["tanimoto_morgan"], 5),
Args(enrichment_data["tanimoto_morgan"], 6),
]
exo_calc_EF = ExerciseFunction(calculate_enrichment_factor,
inputs_calc_EF,
call_renderer=PPrintCallRenderer(
show_function=False,
css_properties={
'word-wrap': 'break-word',
'max-width': '40em'
},
))
def calculate_enrichment_factor_optimal(molecules,
ranked_dataset_percentage_cutoff,
pic50_cutoff):
"""
Get the optimal random enrichment factor for a given percentage of the ranked dataset.
Parameters
----------
molecules : pandas.DataFrame
inputs_maximum = [
Args(1, 2, 3),
Args(3, 2, 1),
Args(3, 1, 2)
]
########## step 3
# finally we create the exercise object
# NOTE: this is the only name that should be imported from this module
#
exo_factorielle = ExerciseFunction(
# first argument is the 'correct' function
# it is recommended to use the same name as in the notebook, as the
# python function name is used in HTML rendering
factorielle,
# the inputs
inputs_factorielle,
result_renderer=PPrintRenderer(width=20),
)
exo_somme = ExerciseFunction(
somme_diff_quotient_reste,
inputs_somme,
result_renderer=PPrintRenderer(width=20),
)
exo_est_bisextile = ExerciseFunction(
est_bisextile,
inputs_bisextile,
result_renderer=PPrintRenderer(width=20),
def multi_tri(listes):
"""
trie toutes les sous-listes
et retourne listes
"""
for liste in listes:
# sort fait un effet de bord
liste.sort()
# et on retourne la liste de départ
return listes
# @END@
inputs_multi_tri = [
Args([[40, 12, 25], ['spam', 'egg', 'bacon']]),
Args([[32, 45], [200, 12], [-25, 37]]),
Args([[], list(range(6)) + [2.5], [4, 2, 3, 1]]),
]
exo_multi_tri = ExerciseFunction(
multi_tri,
inputs_multi_tri,
call_renderer=PPrintCallRenderer(width=30),
result_renderer=PPrintRenderer(width=20),
)
def multi_tri_ko(listes):
return listes
args("".join(random.sample(alphabet, random.randint(3, 6))),
"".join(random.sample(alphabet, random.randint(5, 8))))
for i in range(4)
]
# @BEG@ name=inconnue
# pour enlever à gauche et à droite une chaine de longueur x
# on peut faire composite[ x : -x ]
# or ici x vaut len(connue)
def inconnue(composite, connue):
return composite[len(connue):-len(connue)]
# @END@
# @BEG@ name=inconnue more=bis
# ce qui peut aussi s'écrire comme ceci si on préfère
def inconnue_bis(composite, connue):
return composite[len(connue):len(composite) - len(connue)]
# @END@
exo_inconnue = ExerciseFunction(inconnue, inconnue_inputs)
def inconnue_ko(big, small):
return big[len(small):-4]
# ceci ne devrait pas marcher avec des instances de Number
def power_ko(x, n):
return x ** n
inputs_power = [
Args(2, 1),
Args(2, 10),
Args(1j, 4),
Args(Number(1j), 4),
]
powers = (2, 3, 1024, 1025)
inputs_power += [
Args(3, n) for n in powers
]
i_powers = (2*128, 2**128+1, 2*128-1)
inputs_power += [
Args(1j, n) for n in i_powers
]
exo_power = ExerciseFunction(
power, inputs_power,
nb_examples = 4,
call_renderer=PPrintCallRenderer(width=30),
result_renderer=PPrintRenderer(width=40),
)
inputs_laccess = [
Args([]),
Args([1]),
Args(['spam', 100]),
Args(['spam', 100, 'bacon']),
Args([1, 2, 3, 100]),
Args([1, 2, 100, 4, 5]),
Args(['si', 'pair', 'alors', 'dernier']),
Args(['retourne', 'le', 'milieu', 'si', 'impair']),
]
exo_laccess = ExerciseFunction(
laccess, inputs_laccess, nb_examples=0
)
def laccess_ko(liste):
return liste[-1]
#################### le même code marche-t-il avec des strings ?
inputs_laccess_strings = [
Args(""),
Args("a"),
Args("ab"),
Args("abc"),
Args("abcd"),
Args("abcde"),
]
# (voir semaine 5); ça se présente comme
# une compréhension de liste mais on remplace
# les [] par des {}
def read_set_bis(filename):
with open(filename) as feed:
return {line.strip() for line in feed}
# @END@
read_set_inputs = [
Args("data/setref1.txt"),
Args("data/setref2.txt"),
]
exo_read_set = ExerciseFunction(
read_set, read_set_inputs,
result_renderer=PPrintRenderer(width=25),
)
# @BEG@ name=search_in_set
# ici aussi on suppose que les fichiers existent
def search_in_set(filename_reference, filename):
"""
cherche les mots-lignes de filename parmi ceux
qui sont presents dans filename_reference
"""
# on tire profit de la fonction précédente
reference_set = read_set(filename_reference)
return f"{prenom}.{nom} ({rang_ieme})"
# @END@ ##########
def libelle_ko(ligne):
try:
nom, prenom, rang = ligne.split(',')
return f"{prenom}.{nom} ({rang})"
except:
return None
inputs_libelle = [
Args("Joseph, Dupont, 4"),
Args("Jean"),
Args("Jules , Durand, 1"),
Args(" Ted, Mosby, 2,"),
Args(" Jacques , Martin, 3 \t"),
Args("Sheldon, Cooper ,5, "),
Args("\t John, Doe\t, "),
Args("John, Smith, , , , 3"),
]
exo_libelle = ExerciseFunction(
libelle,
inputs_libelle,
nb_examples=0,
)
def correction(self,
student_diff,
extended=extended,
abbreviated=abbreviated):
self.datasets = [Args(extended, abbreviated).clone('deep')]
return ExerciseFunction.correction(self, student_diff)
# @END@
wc_inputs = (
Args('''Python is a programming language
that lets you work quickly
and integrate systems more effectively.'''),
Args(''),
Args('abc'),
Args('abc \t'),
Args('a bc \t'),
Args(' \tabc \n'),
Args(" ".join("abcdefg") + "\n"),
Args('''The Zen of Python, by Tim Peters
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
...'''),
)
exo_wc = ExerciseFunction(wc,
wc_inputs,
call_renderer=PPrintCallRenderer(max_width=40,
show_function=True),
result_renderer=PPrintRenderer(width=15))
{'n': 'Forbes', 'p': 'Bob'},
{'n': 'Martin', 'p': 'Jeanneot'},
{'n': 'Martin', 'p': 'Jean', 'p2': 'Paul'},
{'n': 'Forbes', 'p': 'Charlie'},
{'n': 'Martin', 'p': 'Jean', 'p2': 'Pierre'},
{'n': 'Dupont', 'p': 'Alexandre'},
{'n': 'Dupont', 'p': 'Laura', 'p2': 'Marie'},
{'n': 'Forbes', 'p': 'John'},
{'n': 'Martin', 'p': 'Jean'},
{'n': 'Dupont', 'p': 'Alex', 'p2': 'Pierre'}]]
inputs_tri_custom = [
Args(input) for input in inputs
]
exo_tri_custom = ExerciseFunction(
tri_custom, inputs_tri_custom,
call_renderer=PPrintCallRenderer(width=24),
result_renderer=PPrintRenderer(width=30),
font_size='small',
)
def tri_custom_ko(liste):
sort(liste)
return liste
Args([1, 2]),
Args(["toto", "tata"]),
Args([0]),
Args(["anticonstitutionnellement"]),
Args(["élastique", "ceinture", "bretelles"])
]
########## step 3
# finally we create the exercise object
# NOTE: this is the only name that should be imported from this module
#
exo_aleatoire = ExerciseFunction(
aleatoire,
inputs_creation,
result_renderer=PPrintRenderer(width=50),
)
exo_croissant = ExerciseFunction(
croissant,
inputs_creation,
result_renderer=PPrintRenderer(width=50),
)
exo_ajout_queue = ExerciseFunction(
ajout_queue,
inputs_ajout,
result_renderer=PPrintRenderer(width=50),
)
# on n'a pas encore vu les opérateurs logiques, mais
# on peut aussi faire tout simplement comme ça
# sans faire de if du tout
return a % b == 0 or b % a == 0
# @END@
def divisible_ko(a, b):
return a % b == 0
inputs_divisible = [
Args(10, 30),
Args(10, -30),
Args(-10, 30),
Args(-10, -30),
Args(8, 12),
Args(12, -8),
Args(-12, 8),
Args(-12, -8),
Args(10, 1),
Args(30, 10),
Args(30, -10),
Args(-30, 10),
Args(-30, -10),
]
exo_divisible = ExerciseFunction(divisible, inputs_divisible)
def fact(n):
"une version de factoriel à base de reduce"
return reduce(mul, range(1, n + 1), 1)
from math import factorial
fact_inputs = [0, 1, 5]
compare_all_inputs.append(Args(fact, factorial, fact_inputs))
def broken_fact(n):
return 0 if n <= 0 \
else 1 if n == 1 \
else n*fact(n-1)
compare_all_inputs.append(Args(broken_fact, factorial, fact_inputs))
#################### the exercice instance
exo_compare_all = ExerciseFunction(
compare_all,
compare_all_inputs,
nb_examples=2,
call_renderer=CallRenderer(show_function=False),
)
def compare_all_ko(*args):
return [not x for x in compare_all(*args)]
def correction(self, student_comptage):
# call the decorator on the student code
return ExerciseFunction.correction(
self, exercice_compliant(student_comptage))
a, b = b, a % b
return a
# @END@
def pgcd_ko(a, b):
return a % b
inputs_pgcd = [
Args(0, 0),
Args(0, 1),
Args(1, 0),
Args(15, 10),
Args(10, 15),
Args(3, 10),
Args(10, 3),
Args(10, 1),
Args(1, 10),
]
inputs_pgcd += [
Args(36 * 2**i * 3**j * 5**k,
36 * 2**j * 3**k * 5**i)
for i in range(3) for j in range(3) for k in range(2)
]
exo_pgcd = ExerciseFunction(
pgcd, inputs_pgcd,
nb_examples = 6,
)
# Since we need a distance matrix, calculate 1-x for every element in similarity matrix
for sim in similarities:
dissimilarity_matrix.append(1 - sim)
return dissimilarity_matrix
inputs_tan_dist_mat = [
Args(fingerprints_str[0:3]),
Args(fingerprints_str[0:1000])
]
exo_tan_dist_mat = ExerciseFunction(Tanimoto_distance_matrix_from_str,
inputs_tan_dist_mat,
call_renderer=PPrintCallRenderer(
show_function=False,
css_properties={
'word-wrap': 'break-word',
'max-width': '40em'
},
))
def ClusterFps_from_str(fp_list_str, cutoff=0.2):
fp_list = [
DataStructs.cDataStructs.CreateFromBitString(fp_str)
for fp_str in fp_list_str
]
return ClusterFps(fp_list, cutoff=0.2)
# Input: Fingerprints and a threshold for the clustering
def correction(self, student_decode_zen):
args_obj = Args(this)
self.datasets = [ args_obj ]
return ExerciseFunction.correction(self, student_decode_zen)
while index > 26:
index = (index - 1) // 26
# idem ici bien sûr
result = int_to_char(index) + result
return result
# @END@
z = 26
zz = 26**2 + 26
zzz = 26**3 + 26**2 + 26
numeric_inputs = (
1, 15, z, z+1, zz-1, zz, zz+1, zz+2, zzz-1, zzz, zzz+1, zzz+2, 26**2-1,
30_000, 100_000, 1_000_000,
)
# l'objet Args permet de capturer les arguments
# pour un appel à la fonction
spreadsheet_inputs = [Args(n) for n in numeric_inputs]
exo_spreadsheet = ExerciseFunction(
spreadsheet, spreadsheet_inputs, nb_examples=7,
)
def spreadsheet_ko(n):
if 1 <= n <= 26:
return int_to_char(n)
else:
return spreadsheet_ko(n//26) + int_to_char(n)
# @BEG@ name=carre more=ter
def carre_ter(ligne):
# On extrait toutes les valeurs séparées par des points-
# virgules, on les nettoie avec la méthode strip
# et on stocke le résultat dans une liste
liste_valeurs = [t.strip() for t in ligne.split(';')]
# Il ne reste plus qu'à calculer les carrés pour les
# valeurs valides (non vides) et les remettre dans une str
return ":".join([str(int(v)**2) for v in liste_valeurs if v])
# @END@
inputs_carre = [
Args("1;2;3"),
Args(" 2 ; 5;6;"),
Args("; 12 ; -23;\t60; 1\t"),
Args("; -12 ; ; -23; 1 ;;\t"),
]
exo_carre = ExerciseFunction(carre,
inputs_carre,
nb_examples=0,
call_renderer=PPrintCallRenderer(
show_function=False, width=40))
def carre_ko(s):
return ":".join(str(i**2) for i in (int(token) for token in s.split(';')))
(50_001, 150_000, 40),
(150_001, math.inf, 45),
)
def taxes_ter(income):
due = 0
for floor, ceiling, rate in TaxRate2:
due += (min(income, ceiling) - floor + 1) * rate / 100
if income <= ceiling:
return int(due)
def taxes_ko(income):
return (income - 12_500) * 20 / 100
taxes_values = [
0, 50_000, 12_500, 5_000, 16_500, 30_000, 100_000, 150_000, 200_000, 12_504
]
taxes_inputs = [Args(v) for v in taxes_values]
exo_taxes = ExerciseFunction(taxes, taxes_inputs, nb_examples=3)
if __name__ == '__main__':
for value in taxes_values:
tax = taxes(value)
print(f"{value} -> {tax}")
(C(=O)N(C(C(=O)N(C(C(=O)N(C(C(=O)N(C(C(=O)N1)C(C(C)CC=CC)O)C)C(C)C)C)CC(C)C)C)CC(C)C)\
C)C)C)CC(C)C)C)C(C)C)CC(C)C)C)C')
smiles_4 = MolFromSmiles(
'CC1=C(C(CCC1)(C)C)C=CC(=CC=CC(=CC=CC=C(C)C=CC=C(C)C=CC2=C(CCCC2(C)C)C)C)C'
)
smiles_5 = MolFromSmiles('CCCCCC1=CC(=C(C(=C1)O)C2C=C(CCC2C(=C)C)C)O')
smiles_6 = MolFromSmiles('CC(=O)OC1=CC=CC=C1C(=O)O')
smiles_7 = MolFromSmiles('CN1CCC23C4C1CC5=C2C(=C(C=C5)O)OC3C(C=C4)O')
inputs_calculate_fp = [
Args(smiles_1),
Args(smiles_2, method='ecfp4'),
Args(smiles_3, method='ecfp4', n_bits=1024),
Args(smiles_4, method='ecfp6'),
Args(smiles_5, method='torsion'),
Args(smiles_6, method='rdk5'),
Args(smiles_7, method='ecfp6', n_bits=1024),
]
exo_calculate_fp = ExerciseFunction(print_fp,
inputs_calculate_fp,
call_renderer=PPrintCallRenderer(
show_function=True,
css_properties={
'word-wrap': 'break-word',
'max-width': '40em'
},
))
# ________________________________________________________________________________
