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Я новичок в python и пытаюсь увеличить масштаб отображения карт, чтобы уменьшить пустое пространство

Я пытался использовать plt.tight_layout() и plt.add_subplots, но это не сработало

Это мой необработанный код

 def flatten_header(header):
    """
        Attempt to turn an N-dimensional fits header into a 2-dimensional header
        Turns all CRPIX[>2] etc. into new keywords with suffix 'A'
        """
    orig_wcs = wcs.WCS(header)
    newheader = orig_wcs.celestial.to_header()
    newheader['NAXIS'] = 2
    newheader['NAXIS1'] = header['NAXIS{0}'.format(orig_wcs.wcs.lng   1)]
    newheader['NAXIS2'] = header['NAXIS{0}'.format(orig_wcs.wcs.lat   1)]
    newheader['BMAJ'] = header['BMAJ']
    newheader['BMIN'] = header['BMIN']
    newheader['BPA'] = header['BPA']  
    return newheader


def create_image(output_fitsname,mmb_name):
    #query = "select mmb_ra_decimal as mmb_ra_decimal,mmb_dec_decimal from mmb_full.mmb_dust_master where concat(round(mmb_gal_long,3),if(mmb_gal_lat > 0, ' ',''), round(mmb_gal_lat,3))  =  '" str(mmb_name) "' order by mmb_name limit 1"
    
    query = "select mmb_ra_decimal as mmb_ra_decimal,mmb_dec_decimal from mmb_dust_master where concat( right(left(mmb_name,8),7),if(mmb_gal_lat > 0, ' ','-'), right(mmb_name,5))  =  '" str(mmb_name) "' order by mmb_name limit 1"
    
    print(query)

    mmb_positions = pd.read_sql_query(query, con = mydb )
    #mmb_positions = pd.read_sql_query(query.format(mmb_name), con = conn )


    A1 =(mmb_positions['mmb_ra_decimal'])
    B1 =(mmb_positions['mmb_dec_decimal'])

    print(mmb_name)
    print('these are the positions', A1[0], B1[0])

    #plt.plot(A1,B1,  markersize = 2,  marker = '.',color='yellow', linestyle = 'none')
    
    figure = aplpy.FITSFigure(output_fitsname) # Create a figure using the first item in the hdulist
     
    figure.show_markers(A1[0], B1[0], edgecolor='lightblue', facecolor='none',
                marker='o', s=250, alpha=0.95,coords_frame='world', linewidth = 4)
    
    
    query = "select t2.ra_5ghz as ra_5ghz, t2.dec_5ghz as dec_5ghz from C2186_SOURCES t1, atlas_rms_radio_cat t2 where t1.source_name =  '" str(mmb_name) "' and power(power(t1.gal_long-t2.gal_long_5GHz,2) power(t1.gal_lat-t2.gal_lat_5GHz,2),0.5)*3600 < 100 and t2.ra_5ghz is not null"
    print(query)
    
    radio_positions = pd.read_sql_query(query, con = mydb )
    #mmb_positions = pd.read_sql_query(query.format(mmb_name), con = conn )


    A1 =(radio_positions['ra_5ghz'].dropna())
    B1 =(radio_positions['dec_5ghz'].dropna())

    print(mmb_name)
    #print('these are the positions', A1[0], B1[0])
    
    figure.show_markers(A1, B1, edgecolor='green', facecolor='none',
                marker='o', s=100, alpha=0.95,coords_frame='world', linewidth = 4)
    
    
    img_5ghz = f01[0].data
    min_5ghz = np.nanmin(img_5ghz)
    max_5ghz = np.nanmax(img_5ghz)
    plt.rc('font', family='serif')
    plt.rc('xtick', direction = 'in',labelsize='large')
    plt.rc('ytick', direction = 'in',labelsize='large')
    
    figure.show_colorscale(vmin= min_5ghz, vmax= max_5ghz,cmap='gist_heat',stretch = 'linear')
    #figure.show_grayscale() # Show greyscale of the image
    #figure.show_markers(ra[j], dec[j], edgecolor='red',marker='o', s =Major_axis[j], alpha=0.5, linewidth=3., facecolor='none')
 
    #figure.show_ellipses(ra, dec, width =0.0057, height=0.0026)
    #figure.show_circles(ra, dec,0.0057,edgecolor='green', facecolor='None', linewidth=3., alpha=0.7, coords_frame = 'world')
    figure.show_ellipses(ra[j],dec[j], Minor_axis[j], Major_axis[j], angle=float(pa[j]),coords_frame = 'world',  edgecolor='green', facecolor='None', linewidth=3., alpha=0.7)
    #figure.show_ellipses()
    #figure.add_beam(hatch='/////')
    figure.add_beam()
    figure.axis_labels.set_font(size=12, weight = 'bold')
    figure.add_colorbar()
    figure.colorbar.set_axis_label_text('Surface Brightness (Jy/beam)')
    figure.colorbar.set_axis_label_font(size=12, weight = 'bold')
      #figure.show_markers(xw=[catalogue.glon], yw=[catalogue.glat]) # Add markers from the catalogue
    figure.save(output_filename) # Save figure to output file
    
    return 1


for j in range(len(source_name)):
    fits_filename = '/Users/' str(date) '/target_fits/' str(source_name[j]) '_' str(freq[j]) '.restor.fits'
    output_fitsname = '/Users/C2186_Detections/' str(date) '/' str(source_name[j]) '_' str(freq[j]) '_' str(obs_date[j]) '.fits'
    # Change these three as necessary
   # catalogue_filename = "test.csv"
    output_filename = '/Users//C2186_Detections/' str(date) '/' str(source_name[j]) '_' str(freq[j]) '_' str(obs_date[j]) '.png'
  

    f01 = fits.open(fits_filename) 
    fheader01= f01[0].header
    new_header = flatten_header(fheader01)
    fits.writeto(output_fitsname,f01[0].data[0][0],header=new_header,overwrite=True)

    create_image(output_fitsname,source_name[j])
 

Я прикрепил изображение вывода, которое я хотел бы увеличить!

Любая помощь будет очень признательна