Question

我正在使用从共振频率获取的数据来创建彩色图，作为x和y位置的函数。在浏览资源时（显示了随机的彩色图） here，使用meshgrid的彩色地图（如here等），我遇到了一个问题，我需要数据为网格格式，但我所需要的全部数据是我的 x值，y值和相应的共振频率。

我不擅长曲面创建，如果我没有连续的Z值来为x和x的每个值创建曲面，meshgrid对我来说就没有意义了y。

下面是2个完整的代码版本，每个版本都执行我不想要的事情。

版本1 ：绘制随机形状和颜色的正方形（由于我将color设置为等于{{1} }。我只是不知道该用什么替换。）

np.random.uniform(...)

版本2 ：没有要绘制的连续Z“表面”-我只有离散的值，我需要在每个值上显示颜色（x， y）位置。

import numpy as np import glob, os import codecs import re import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D from matplotlib.collections import PolyCollection from matplotlib import colors as mcolors from matplotlib.colors import LinearSegmentedColormap import numpy as np import math import pylab import sys #------------------------------------------------------------------------- directoryUsed = 'C:/Users/elarrick/Desktop/201807161056' os.chdir(directoryUsed) dataFolders = glob.glob('./*.ltda') LTXFiles = [file for file in os.listdir(directoryUsed) if (file.endswith('.ltda') and ("LT_X" in file))] #------------------------------------------------------------------------- # Function for getting coordinates in [x,y] form #------------------------------------------------------------------------- def getCoordinate(name): #e.g. name = LT_X_X0_Y0 name = name.strip(".\\") shortened = name.strip("LT_") #Takes the first 3 characters away whichAxis = shortened[0] if whichAxis == "X": coordinates = shortened.strip("X_") #e.g. X0_Y0 coordinates = coordinates.strip(".ltda") underscore_index = coordinates.find('_') x_value = int(coordinates[:underscore_index]) y_index = coordinates.find('Y') #y-value for the plot is whatever the y-position is if len(coordinates) == y_index+5: #If Y is at index 3, then if total len is 8, Y is a 4-digit number (including negative) y_value = int(coordinates[y_index+1:y_index+5]) elif len(coordinates) == y_index+4: #If Y is at index 3, then if total len is 7, Y is a 3-digit number (including negative) y_value = int(coordinates[y_index+1:y_index+4]) elif len(coordinates) == y_index+3: #If Y is at index 3, then if total len is 6, Y is a 2-digit number y_value = int(coordinates[y_index+1:y_index+3]) elif len(coordinates) == y_index+2: y_value = int(coordinates[y_index+1]) return [x_value,y_value] #------------------------------------------------------------------------- # Function for making color map #------------------------------------------------------------------------- def make_colormap(seq): """Return a LinearSegmentedColormap seq: a sequence of floats and RGB-tuples. The floats should be increasing and in the interval (0,1). """ seq = [(None,) * 3, 0.0] + list(seq) + [1.0, (None,) * 3] cdict = {'red': [], 'green': [], 'blue': []} for i, item in enumerate(seq): if isinstance(item, float): r1, g1, b1 = seq[i - 1] r2, g2, b2 = seq[i + 1] cdict['red'].append([item, r1, r2]) cdict['green'].append([item, g1, g2]) cdict['blue'].append([item, b1, b2]) return mcolors.LinearSegmentedColormap('CustomMap', cdict) #------------------------------------------------------------------------- # Get the data #------------------------------------------------------------------------- y_value_list = [] x_value_list = [] for item in LTXFiles: name, ext = os.path.splitext(item) if ext == '.ltda': try: coordinates = getCoordinate(name) #Returns [x,y] coordinates x_value_list.append(int(coordinates[0])) y_value_list.append(int(coordinates[1])) except TypeError: print "Name of the problematic file is ", name sys.exit() x_value_list = sorted(list(set(x_value_list))) #Gets the ordered values of X positions (e.g. -150, -120, -90, etc.) y_value_list = sorted(list(set(y_value_list))) #Gets the ordered values of Y positions (e.g. -150, -120, -90, etc.) #------------------------------------------------------------------------- # We now have the values of x and y in order. # Get the peak of the Mag vs. Freq curves #------------------------------------------------------------------------- x = [] y = [] dataLines = [] freq = [] OpenLoopMag = [] OpenLoopMagResFreq = [] OpenLoopPhase = [] OpenLoopPhaseResFreq = [] FirstMaximumOpenLoopMag = [] FirstMinimumOpenLoopMag = [] FirstMaximumOpenLoopPhase = [] FirstMinimumOpenLoopPhase = [] n_bins = 0 for x_val in x_value_list: #for each x value in order for y_val in y_value_list: n_bins += 1 print "\nThe x value currently being used is ", x_val print "\nThe y value currently being used is ", y_val for dataFile in LTXFiles: coordinate = getCoordinate(dataFile) #has form [x,y] if coordinate[0] == x_val and coordinate[1] == y_val: #If coordinates match f = codecs.open(dataFile, encoding='utf-8') for line in f: if '' in line: dataLines.append(line) #All lines with are an entry in dataLines for item in dataLines: item = re.sub("", "", item) item = re.sub("True", "", item) item = item.replace(",", "") splitItem = item.split() freq.append(float(splitItem[0])) #obtain the data for said [x,y] values OpenLoopMag.append(float(splitItem[1])) OpenLoopPhase.append(float(splitItem[2])) #-------------------------------------------------------------------------------------------- # We now have Freq, OpenLoopMag, and OpenLoopPhase # for each value of x,y. #-------------------------------------------------------------------------------------------- x.append(x_val) y.append(y_val) maxOpenLoopMag = max(OpenLoopMag) maxOpenLoopPhase = max(OpenLoopPhase) for i in range(0,len(OpenLoopMag)): if OpenLoopMag[i] == maxOpenLoopMag: OpenLoopMagResFreq.append(freq[i]) break for i in range(0,len(OpenLoopPhase)): if OpenLoopPhase[i] == maxOpenLoopPhase: OpenLoopPhaseResFreq.append(freq[i]) break minimumMagResFreq = min(OpenLoopMagResFreq) maximumMagResFreq = max(OpenLoopMagResFreq) c = mcolors.ColorConverter().to_rgb rvb = make_colormap( [c('red'), c('violet'), 0.33, c('violet'), c('blue'), 0.66, c('blue')]) N = len(x) print "x = ", x print "y = ", y colors = np.random.uniform(minimumMagResFreq, maximumMagResFreq, size=(N,)) plt.scatter(x,y,OpenLoopMagResFreq, c=colors, cmap=rvb, marker = "s") plt.xlabel('X position') plt.ylabel('Y position') plt.title('Resonant Frequency Visualization') plt.colorbar() plt.show()

版本1每次运行代码时都会给我这张图片不同的颜色：

第2版给我这个错误：

import numpy as np import matplotlib.pyplot as plt from matplotlib.colors import LinearSegmentedColormap import glob, os import codecs import re from mpl_toolkits.mplot3d import Axes3D from matplotlib.collections import PolyCollection from matplotlib import colors as mcolors import math import pylab import sys #-------------------------------------------------------------------------------------------- directoryUsed = 'C:/Users/elarrick/Desktop/201807161056' os.chdir(directoryUsed) dataFolders = glob.glob('./*.ltda') LTXFiles = [file for file in os.listdir(directoryUsed) if (file.endswith('.ltda') and ("LT_X" in file))] def getCoordinate(name): #e.g. name = LT_X_X0_Y0 name = name.strip(".\\") shortened = name.strip("LT_") #Takes the first 3 characters away whichAxis = shortened[0] if whichAxis == "X": coordinates = shortened.strip("X_") #e.g. X0_Y0 coordinates = coordinates.strip(".ltda") underscore_index = coordinates.find('_') x_value = int(coordinates[:underscore_index]) y_index = coordinates.find('Y') #y-value for the plot is whatever the y-position is if len(coordinates) == y_index+5: #If Y is at index 3, then if total len is 8, Y is a 4-digit number (including negative) y_value = int(coordinates[y_index+1:y_index+5]) elif len(coordinates) == y_index+4: #If Y is at index 3, then if total len is 7, Y is a 3-digit number (including negative) y_value = int(coordinates[y_index+1:y_index+4]) elif len(coordinates) == y_index+3: #If Y is at index 3, then if total len is 6, Y is a 2-digit number y_value = int(coordinates[y_index+1:y_index+3]) elif len(coordinates) == y_index+2: y_value = int(coordinates[y_index+1]) return [x_value,y_value] #-------------------------------------------------------------------------------------------- # Get the data #-------------------------------------------------------------------------------------------- y_value_list = [] x_value_list = [] for item in LTXFiles: name, ext = os.path.splitext(item) if ext == '.ltda': try: coordinates = getCoordinate(name) #Returns [x,y] coordinates x_value_list.append(int(coordinates[0])) y_value_list.append(int(coordinates[1])) except TypeError: print "Name of the problematic file is ", name sys.exit() x_value_list = sorted(list(set(x_value_list))) #Gets the ordered values of X positions (e.g. -150, -120, -90, etc.) y_value_list = sorted(list(set(y_value_list))) #Gets the ordered values of Y positions (e.g. -150, -120, -90, etc.) #-------------------------------------------------------------------------------------------- # We now have the values of x and y in order. # Get the peak of the Mag vs. Freq curves #-------------------------------------------------------------------------------------------- x = [] y = [] dataLines = [] freq = [] OpenLoopMag = [] OpenLoopMagResFreq = [] OpenLoopPhase = [] OpenLoopPhaseResFreq = [] FirstMaximumOpenLoopMag = [] FirstMinimumOpenLoopMag = [] FirstMaximumOpenLoopPhase = [] FirstMinimumOpenLoopPhase = [] n_bins = 0 for x_val in x_value_list: #for each x value in order for y_val in y_value_list: n_bins += 1 print "\nThe x value currently being used is ", x_val print "\nThe y value currently being used is ", y_val for dataFile in LTXFiles: coordinate = getCoordinate(dataFile) #has form [x,y] if coordinate[0] == x_val and coordinate[1] == y_val: #If coordinates match f = codecs.open(dataFile, encoding='utf-8') for line in f: if '' in line: dataLines.append(line) #All lines with are an entry in dataLines for item in dataLines: item = re.sub("", "", item) item = re.sub("True", "", item) item = item.replace(",", "") splitItem = item.split() freq.append(float(splitItem[0])) #obtain the data for said [x,y] values OpenLoopMag.append(float(splitItem[1])) OpenLoopPhase.append(float(splitItem[2])) #-------------------------------------------------------------------------------------------- # We now have Freq, OpenLoopMag, and OpenLoopPhase # for each value of x,y. #-------------------------------------------------------------------------------------------- x.append(x_val) y.append(y_val) maxOpenLoopMag = max(OpenLoopMag) maxOpenLoopPhase = max(OpenLoopPhase) for i in range(0,len(OpenLoopMag)): if OpenLoopMag[i] == maxOpenLoopMag: OpenLoopMagResFreq.append(freq[i]) break for i in range(0,len(OpenLoopPhase)): if OpenLoopPhase[i] == maxOpenLoopPhase: OpenLoopPhaseResFreq.append(freq[i]) break X, Y = np.meshgrid(x, y) #Z = np.cos(X) * np.sin(Y) * 10 a = np.zeros(len(x))+x b = np.zeros(len(y))+y Z = np.meshgrid(a,b) colors = [(1, 0, 0), (0, 1, 0), (0, 0, 1)] # R -> G -> B n_bins = [n_bins, n_bins, n_bins, n_bins] # Discretizes the interpolation into bins cmap_name = 'my_list' fig, axs = plt.subplots(2, 2, figsize=(6, 9)) fig.subplots_adjust(left=0.02, bottom=0.06, right=0.95, top=0.94, wspace=0.05) for n_bin, ax in zip(n_bins, axs.ravel()): # Create the colormap cm = LinearSegmentedColormap.from_list( cmap_name, colors, N=n_bin) # Fewer bins will result in "coarser" colomap interpolation im = ax.imshow(Z, interpolation='nearest', origin='lower', cmap=cm) ax.set_title("N bins: %s" % n_bin) fig.colorbar(im, ax=ax) plt.show()

x，y gridin的颜色图-Python

0 个答案: