Matrix multiplication bụ isi ọrụ na linear algebra.
Anyị na-eji ya n'ọtụtụ ngwa dị ka nhazi onyonyo, mmụta igwe, na ọtụtụ ndị ọzọ. NumPy bụ ngwugwu Python ama ama maka mgbakọ sayensị.
Agbanyeghị, na post a, anyị ga-elele ụzọ dị iche iche maka ịme ọtụtụ matrix na Python na-ejighi NumPy.
Anyị ga-eji kpara akpa, arụ ọrụ maapụ () arụnyere, yana nghota ndepụta.
Na mgbakwunye, anyị ga-eleba anya na uru na ihe ndọghachi azụ nke atụmatụ ọ bụla, yana mgbe etinyere nke ọ bụla n'ime ha. Ọ bụrụ na ị bụ onye ọhụrụ na algebra linear ma chọọ ịmatakwu gbasara mmụba matriks; nọgide na-agụ.
Ebee ka Anyị na-eji Matrix Multiplication?
A na-eji mmụba nke Matrix na eserese kọmputa iji gbanwee ihe ngosi 2D na 3D. Dịka ọmụmaatụ, ị nwere ike ịtụgharị, nha, ma tụgharịa ihe na ihuenyo. A na-eji matriks eme ihe na nhazi onyonyo iji nọchite anya foto dị ka nhazi pikselụ. E wezụga nke ahụ, enwere ike iji matriks rụọ ọrụ dịka nzacha onyonyo.
Anyị na-ejikwa matriks n'ime ngwa igwe. Ha nwere ike inyere anyị aka ịnọchite anya data na parampat nlereanya. Anyị nwere ike ịme ọtụtụ ọrụ, dị ka ngwaahịa ntụpọ mgbako na ngwaahịa matrix-vector.
N'ezie, ọrụ a dịkwa oke uru na ọrụ sayensị. Anyị nwere ike iji ya na physics na injinịa kọwaa ọnụọgụ anụ ahụ. N'ihi ya, anyị nwere ike ịrụ ọrụ na vectors na tenors.
Kedu ihe kpatara na anyị enweghị ike ịhọrọ iji NumPy?
Mgbe NumPy bụ a Ọbá akwụkwọ Python, ọ bụghị mgbe niile dị mma nhọrọ maka matrix multiplication. Anyị nwere ike ọ gaghị ahọrọ iji NumPy maka ebumnuche dịka nha na ndabere, mmụta, na sistemụ nketa.
Iji ọrụ arụnyere Python ma ọ bụ imepe koodu omenala nwere ike ịdị na-arụ ọrụ nke ọma n'ụfọdụ oge. Ọ dị mkpa ịmara na NumPy bụ ọbá akwụkwọ siri ike. E wezụga nke ahụ, ị nwekwara ike iji ya maka ịba ụba matriks.
Ugbu a, ka anyị leba anya ka anyị ga-esi nweta mmụba matriks na-enweghị NumPy.
Usoro loops akwụghị ụgwọ
Usoro loops akwụghị ụgwọ na-eji loops akwụ ụgwọ iji mejupụta matrix multiplication na Python. Ọrụ a na-atụgharị n'elu ihe matriks ọ bụla. Na, ọ na-amụba ha na-eji usoro nke akwu loops. Ọrụ ahụ weghachite nsonaazụ ya, nke echekwara na matriks ọhụrụ.
Usoro a dị mfe nghọta. Otú ọ dị, ọ nwere ike ọ gaghị adị irè dị ka ụzọ ndị ọzọ, karịsịa maka nnukwu matrices. N'agbanyeghị nke ahụ, ọ bụ nhọrọ magburu onwe ya maka gị ma ọ bụrụ na ị dị ọhụrụ na algebra linear.
def matrix_multiplication(A, B):
# Determine the matrices' dimensions.
rows_A = len(A)
cols_A = len(A[0])
rows_B = len(B)
cols_B = len(B[0])
# Tọọ nsonaazụ nsonaazụ ka ọ bụrụ efu.
result = [[0 for row in range(cols_B)] for col in
range(rows_A)]
# Iterate through rows of A
for s in range(rows_A):
# Iterate through columns of B
for j in range(cols_B):
# Iterate through rows of B
for k in range(cols_A):
result[s][j] += A[s][k] * B[k][j]
return result
Ka anyị nwee ihe atụ nke otu esi eme nke a. Ị nwere ike ịgbakwunye ahịrị koodu ndị a n'okpuru iji nwalee ihe atụ a.
# Sample matrices
A = [[1, 4, 3], [4, 9, 6]]
B = [[7, 8], [9, 10], [11, 12]]
# Perform matrix multiplication
result = matrix_multiplication(A, B)
# Print the result
print(result)
# Output: [[76, 84], [175, 194]]
uru:
- Ọ dị mfe nghọta.
- Ọ dị mma maka ndị ọhụrụ ma ọ bụ ndị na-achọ nghọta miri emi nke mmụba matriks.
ọghọm:
- Ọ bụghị dị irè dị ka usoro ọzọ, karịsịa maka nnukwu matrices.
- A naghị agụ ya dịka ụzọ ndị ọzọ si aga.
map () usoro ọrụ
Usoro ọrụ maapụ() na-enye ụzọ ọzọ maka ịme ọtụtụ matrix na Python. N'ime usoro a, anyị na-eji arụ ọrụ maapụ arụnyere arụnyere (). N'ihi ya, anyị na-eji ngwá ọrụ mmemme na-arụ ọrụ nke na-emetụta ọrụ enyere na mmewere ọ bụla nwere ike ime (ndepụta, tuple, wdg). Ọzọkwa, ọrụ maapụ() na-anabata paramita abụọ, ọrụ yana ihe enwere ike ime. Na, ọ na-eweghachite iterator nke na-etinye ọrụ ahụ na mmewere ọ bụla nwere ike ime.
N'ime usoro a, anyị na-aga site na onye ọ bụla so na matriks wee mee mmụgharị ahụ site na iji ọrụ map ().
A na-eji ọrụ zip() akọwapụta site na mmewere ọ bụla nke matrices n'otu oge.
N'ikpeazụ, a na-eji ọrụ nchikota () arụ ọrụ iji gbakwunye nsonaazụ ya.
def matrix_multiplication(A, B):
# To get the dimensions of the matrices
rows_A = len(A)
cols_A = len(A[0])
rows_B = len(B)
cols_B = len(B[0])
# We use map() function for multiplication.
result = [[sum(a * b for a, b in zip(row_a, col_b)) for
col_b in zip(*B)] for row_a in A]
return result
Ugbu a, ọzọ, anyị nwere ike iji ihe atụ nwalee koodu anyị.
# Example matrices
A = [[3, 2, 3], [4, 5, 6]]
B = [[7, 8], [9, 10], [11, 12]]
# Use map() function to perform matrix multiplication
result = list(map(lambda x: list(map(lambda y: sum(i*j
for i,j in zip(x,y)), zip(*B))), A))
# Print the result
print(result)
# Output: [[72, 80], [139, 154]]
uru
- Dị irè karịa ụzọ ahịrị loops ekpokọtara
- Ọ na-eji mmemme na-arụ ọrụ iji mee ka koodu ahụ dị mfe.
ọghọm
- Ụfọdụ ndị na-amachaghị maka mmemme na-arụ ọrụ nwere ike ịhụ na ọ naghị agụ ya.
- Ọ bụ obere nghọta karịa usoro loops akwụ akwụ.
Usoro nghota ndepụta
Nghọta ndepụta na-enyere gị aka ịmepụta ndepụta ọhụrụ n'otu ahịrị koodu. N'ihi ya, nke a bụ site n'itinye okwu na onye ọ bụla so na ndepụta dị adị.
N'ime usoro a, a na-eme mmụba site na ịmegharị ugboro ugboro site na onye otu matrix ọ bụla. Anyị na-eji nghota ndepụta oyiri.
# Sample matrices
A = [[1, 12, 3], [14, 5, 6]]
B = [[7, 8], [9, 10], [12, 12]]
# Matrix multiplication using list comprehension
result = [[sum(A[i][k] * B[k][j] for k in range(len(A[0])))
for j in range(len(B[0]))] for i in range(len(A))]
# Print the result
print(result)
[[151, 164], [215, 234]]
uru
- Tụnyere usoro ọrụ maapụ(), dị mkpụmkpụ yana enwere ike ịgụ ya.
ọghọm
- Ọ nwere ike ghara ịdị irè karịa iji ọrụ map(), ọkachasị maka nnukwu matrices.
- Ọ na-esi ike karịa ịbịaru nso loops akwụ akwụ.
mmechi
Na post a, anyị lere anya n'ụzọ ọzọ iji NumPy mgbe ị na-amụba matrices na Python. Anyị rụrụ ọtụtụ matriks na loops akwụ, arụrụ ọrụ maapụ () arụnyere, yana nghota ndepụta.
Usoro kachasị mma ga-adabere na mkpa nke ọrụ gị.
Usoro nke ọ bụla nwere uru na ọghọm nke ya. Iji jide n'aka na ọrụ ahụ na-arụ ọrụ nke ọma, ọ dị mma ịgbakwunye ụfọdụ ikpe nwere akụkụ matriks dị iche iche na ụkpụrụ.
I kwesịkwara ịgụnye ụfọdụ ule arụmọrụ iji tulee ka usoro ndị a si arụ ọrụ nke ọma.
Nkume a-aza