使用字典中的資料創建3D曲面圖

我無法弄清楚如何在 python 中使用 matplotlib 將我的資料轉換為曲面圖的 X、Y 和 Z 軸。資料來自一個包含 5 個字母單詞串列的檔案，我的程式運行該檔案并計算每個字母在單詞的每個位置出現的次數。它存盤在 5 個不同的字典中，每個位置一個。我在想我必須使用 .keys() 和 .values() 方法，但我并不積極。

我進入了 excel 并制作了圖表來展示我正在嘗試做的事情的一個例子。

這是我到目前為止的代碼：

import string
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
import numpy as np


#Creates a list of the alphabet in uppercase
alphabet = string.ascii_uppercase
letter_list = list(alphabet)

#Creates dictionary for lettercount. Keys = A-Z, Values = 0 
lettercount = {i: 0 for i in letter_list}

#Creates dictonaries for position frequency. Keys = A-Z, Values = 0 
position1_freq = {i: 0 for i in letter_list}
position2_freq = {i: 0 for i in letter_list}
position3_freq = {i: 0 for i in letter_list}
position4_freq = {i: 0 for i in letter_list}
position5_freq = {i: 0 for i in letter_list}


with open("answers.txt") as f:
    for i in f:
        i = i.rstrip()
        for word in i.split(" "):
            for letter in range(len(word)):
                #Iterates through alphabet
                for j in letter_list:
                    #If the letter in the word = j it will add 1 to lettercount and depending on what value the indicie letter is, 1 will be added to the proper position frequency
                    if word[letter] == j:
                        lettercount[j]  = 1
                        if letter == 0:
                            position1_freq[j]  = 1

                        if letter == 1:
                            position2_freq[j]  = 1

                        if letter == 2:
                            position3_freq[j]  = 1

                        if letter == 3:
                            position4_freq[j]  = 1

                        if letter == 4:
                            position5_freq[j]  = 1

#Sorts the lettercount dictionary to be high to low
sort_lettercount = sorted(lettercount.items(), key = lambda x: x[1], reverse= True)

fig = plt.figure()
ax = plt.axes(projection = '3d')



plt.show()

uj5u.com熱心網友回復：

這是一個完整的例子。我使用了串列和字典理解，因為它們在 python 中很常見（很好習慣！）和Counter標準庫中的類。因此，如果您不習慣代碼可能會有點難以閱讀，但這種風格在 python 中很常見，所以我建議學習它而不是使用顯式的 for 回圈。Counter物件是一種字典，因此可以將其視為字典。:)

然后我使用.values(). 計數器上的函式以提取結果。我將它放入一個 numpy 陣列中，因為這是 matplotlib 需要的。

最后，在 matplotlib 中創建 3d 圖有點做作。Matplotlib 對于分類資料（例如在 X 軸上有字母），也不適用于具有水平色帶的 3d 圖（例如在您的 excel 示例中）。

無論如何，這里是：

from string import ascii_uppercase
from collections import Counter


# a dictionary with all ascii lettters as keys, and only zeros as values
zero_counts = {c:0 for c in ascii_uppercase}

with open('answers.txt') as f:
    # read the file into a list, remove trailing newlines and make sure all is uppercase
    lines = [line.strip().upper() for line in f.readlines()]

    # transpose the list, so that instead of having N 5-letter words, we now have 5 N-letter words
    list_of_chars_per_pos = zip(*lines)

    # for each of these 5 "words", count the number of occurrances of each letter
    # then add these occurences into a copy of the "zero" dictionary from before
    # so now we have 5 dictionaries holding the count for letter 0,1,2,3 and 4
    char_counts_per_pos = [zero_counts | Counter(chars)  for chars in list_of_chars_per_pos]


# matplotlib only works with numpy data structures, so lets change into that!
import numpy as np
x = np.arange(len(ascii_uppercase)) # the x axis will correspond to the letters
y = np.arange(5)                    # the y axis will be the positions
X,Y = np.meshgrid(x,y)              # create 2D arrays with the X and Y coordinates

# here we extract the  data from the dictionaries using the .values() method
Z = np.array([list(dictionary.values()) for dictionary in char_counts_per_pos])

# now create the plot! create 3d axes on a new figure and draw the plot
# there is quite a bit of customization that can be done to the plot to make it look
# in whatever way you like.
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator, FixedLocator
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
surf= ax.plot_surface(X=X,Y=Y,Z=Z)
ax.xaxis.set_major_locator(FixedLocator(x))
ax.set_xticklabels(ascii_uppercase)
ax.set_box_aspect((26,5,5))
ax.zaxis.set_major_locator(MaxNLocator(integer=True))
ax.set_zlabel("Counts")
ax.set_ylabel("Position")

# finally, show the plot. :)
plt.show()

通過在以下文本檔案上運行它answers.txt

abbot
mince
grate
dodos
piggy
baron
party

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