python matplotlib 繪圖 和 dpi對應關係

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dpi表示圖內繪圖區域的尺寸不是圖片外邊框

dpi=1　　　　 600×400

dpi=2　　　　1200×800

dpi=3　　　　1800×1200

........

dpi=21　　　　(21×600)×(21×400) ---> 12600×8400

 

範例程式碼：

import timeimport scipy.signal as signallimport numpy as npimport matplotlibimport matplotlib.pyplot as plty_axis_last=np.linspace(0.0, 0.0, 21120)plt_x=0plt_arr=np.random.rand(1024, 1)def parse_output(start_freq, stop_freq,step ,donser_now_lable,donser, num_now, min_freq):    """Parse data from soapy_power"""    # define size    x_axis = np.linspace(start_freq, stop_freq, round((stop_freq - start_freq)))    y_axis=  np.linspace(0.0, 0.0, round((stop_freq - start_freq) ))    #print(len(x_axis))    donser_now_lable=donser_now_lable+len(x_axis)                    #y_axis deal    global  y_axis_last , plt_x , plt_arr    i=0    temp_lab=0    for num in range(donser_now_lable+1,len(donser),1 ):        if num>=len(donser):            y_axis[i]=0            temp_lab=len(donser)-donser_now_lable        if num_now==1:            y_axis[i]=donser[num]        else:            y_axis[i]=(donser[num]*0.65+y_axis_last[i]*0.35)        i=i+1        if i==len(x_axis):            break                            y_axis_last=y_axis    time_stop = time.time()                        #FFT change    if temp_lab!=0:        return -1    wave_data1=y_axis[0:len(x_axis)]    #print(len(x_axis))    wave_data2 = wave_data1 * signall.hann(len(x_axis))    c=np.fft.fft(wave_data2[0:len(x_axis)])*2/len(x_axis)    #print(len(c))    d=int(len(c)/2)    y_axis=abs(c[0:d])    x_axis.resize(d)            min=100    max=0    for i in range(0,len(y_axis),1 ):        if y_axis[i]>max:            max=y_axis[i]        if y_axis[i]<min:            min=y_axis[i]        #print(max)        #print(min)                    #x_axis y_axis to buffer & update buffer    if min_freq is None:        min_freq = start_freq    if start_freq == min_freq:        databuffer = {"timestamp": time_stop,                               "x": list(x_axis),                               "y": list(y_axis)}    else:        databuffer["x"].extend(x_axis)        databuffer["y"].extend(y_axis)                if stop_freq >0:        #data_storage.update(databuffer)        #self.plt_arr=np.random.rand(1024)        #self.plt_x=0        #print(self.plt_x)        if plt_x==0:            plt_arr=y_axis            plt_arr.resize(len(y_axis) , 1)            print("first time")        else:            plt_temp=y_axis            plt_temp.resize(len(y_axis) , 1)            plt_arr=np.concatenate((plt_arr,plt_temp ), axis=1)            #print(self.plt_arr)             if plt_x%1000==0:                print(plt_x)            if plt_x%1000==0:                cm=‘hot‘                norm = matplotlib.colors.Normalize(vmin=min, vmax=max)                  map=plt.imshow(plt_arr,interpolation=‘nearest‘,cmap=cm,norm=norm, origin=‘upper‘)                plt.xticks([])                plt.yticks([])                plt.axis(‘off‘)                #plt.colorbar(mappable=map,ax=None,shrink=0.5, pad=0)                plt.savefig("filename.png",  dpi=1320)                     #plt.show()                print("-------------------------->")                print(plt_x)        plt_x+=1                    temp_str=str(num_now)            return donser_now_labledef main():    num_now=1    donser_now_lable=0     sys_start_freq  =  87000000.0        #start fre   87MHZ    sys_stop_freq   = 108127168.0          #stop  fre  108MHZ    step            =  10316# 5158 # 2579.0             #Bin size  1KHZ          new    (108127168-87000000)/8192    bins            =  2048 #4096 #8192   #21120# 10560               #sampling number MHZ    #time_s        = 1                  # ?times    stop_freq       = sys_start_freq      #init    min_freq = None    plt_x=0    #donser=np.fromfile("C:\\Users\\Administrator\\Desktop\\bins\\123.b_le.bin", dtype=np.int16 )    donser=np.fromfile("C:\\Users\\Administrator\\Desktop\\bins\\1.b_le.bin", dtype=np.int16 ,count=629145600)  # 600M  629145600    while 1:        #time_start = time.time()        start_freq = stop_freq        if  start_freq>=sys_stop_freq:            break        stop_freq = start_freq+bins        #print("Start:", start_freq)        #print("Stop :", stop_freq)        donser_now_lable=parse_output(start_freq,stop_freq, step,donser_now_lable,donser, num_now, min_freq)        num_now=num_now+1        if donser_now_lable>=len(donser) :            breakif __name__ == "__main__":    main()

上代碼讀入一個二進位bin資料檔案1.08GB的一部分，資料格式為無包頭、小端模式、16位編碼的頻譜資料dpi=1320，產生名稱為filename.png的圖片

 

python matplotlib 繪圖 和 dpi對應關係