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Python colors.normalize函数代码示例

原作者: [db:作者] 来自: [db:来源] 收藏 邀请

本文整理汇总了Python中matplotlib.colors.normalize函数的典型用法代码示例。如果您正苦于以下问题:Python normalize函数的具体用法?Python normalize怎么用?Python normalize使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。



在下文中一共展示了normalize函数的20个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: plot_maps

def plot_maps(plot_params, anat_fn, anat_slice_def, fig_dir,
              orientation=['axial','sagittal'], crop_extension=None,
              plot_anat=True, plot_fontsize=25, fig_dpi=75):

    ldata = []
    for p in plot_params:
        c = xndarray.load(p['fn']).sub_cuboid(**p['slice_def'])
        c.set_orientation(orientation)
        ldata.append(c.data)

    c_anat = xndarray.load(anat_fn).sub_cuboid(**anat_slice_def)
    c_anat.set_orientation(orientation)

    resolution = c_anat.meta_data[1]['pixdim'][1:4]
    slice_resolution = resolution[MRI4Daxes.index(orientation[0])], \
      resolution[MRI4Daxes.index(orientation[1])]

    all_data = np.array(ldata)

    if 'prl' in plot_params[0]['fn']:
        norm = normalize(all_data.min(), all_data.max()*1.05)
        print 'norm:', (all_data.min(), all_data.max())
    else:
        norm = normalize(all_data.min(), all_data.max())

    print 'norm:', (all_data.min(), all_data.max())
    for data, plot_param in zip(all_data, plot_params):
        fn = plot_param['fn']
        plt.figure()
        print 'fn:', fn
        print '->', (data.min(), data.max())
        if plot_anat:
            anat_data = c_anat.data
        else:
            anat_data = None
        plot_func_slice(data, anatomy=anat_data,
                        parcellation=plot_param.get('mask'),
                        func_cmap=cmap,
                        parcels_line_width=1., func_norm=norm,
                        resolution=slice_resolution,
                        crop_extension=crop_extension)
        set_ticks_fontsize(plot_fontsize)

        fig_fn = op.join(fig_dir, '%s.png' %op.splitext(op.basename(fn))[0])
        output_fig_fn = plot_param.get('output_fig_fn', fig_fn)

        print 'Save to: %s' %output_fig_fn
        plt.savefig(output_fig_fn, dpi=fig_dpi)
        autocrop(output_fig_fn)
    return norm
开发者ID:ainafp,项目名称:pyhrf,代码行数:50,代码来源:real_data_jde_rfir_glm.py


示例2: __init__

  def __init__( self, data, ax, prefs, *args, **kw ):

    PlotBase.__init__( self, data, ax, prefs, *args, **kw )
    if type( data ) == types.DictType:
      self.gdata = GraphData( data )
    elif type( data ) == types.InstanceType and data.__class__ == GraphData:
      self.gdata = data
    if self.prefs.has_key( 'span' ):
      self.width = self.prefs['span']
    else:
      self.width = 1.0
      if self.gdata.key_type == "time":
        nKeys = self.gdata.getNumberOfKeys()
        self.width = ( max( self.gdata.all_keys ) - min( self.gdata.all_keys ) ) / nKeys

    # Setup the colormapper to get the right colors
    self.cmap = LinearSegmentedColormap( 'quality_colormap', cdict, 256 )
    #self.cmap = cm.RdYlGn
    self.norms = normalize( 0, 100 )
    mapper = cm.ScalarMappable( cmap = self.cmap, norm = self.norms )
    mapper = cm.ScalarMappable( cmap = cm.RdYlGn, norm = self.norms )
    def get_alpha( *args, **kw ):
      return 1.0
    mapper.get_alpha = get_alpha
    self.mapper = mapper
开发者ID:sbel,项目名称:bes3-jinr,代码行数:25,代码来源:QualityMapGraph.py


示例3: colorify

def colorify(data, vmin=None, vmax=None, cmap=plt.cm.Spectral):
    """ Associate a color map to a quantity vector

    Parameters
    ----------
    data: sequence
        values to index

    vmin: float, optional
        minimal value to index

    vmax: float, optional
        maximal value to index

    cmap: colormap instance
        colormap to use

    Returns
    -------
    colors: sequence
        color sequence corresponding to data

    scalarMap: colormap
        generated map
    """
    import matplotlib.colors as colors

    _vmin = vmin or min(data)
    _vmax = vmax or max(data)
    cNorm = colors.normalize(vmin=_vmin, vmax=_vmax)

    scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=cmap)
    colors = map(scalarMap.to_rgba, data)
    return colors, scalarMap
开发者ID:philrosenfield,项目名称:ResolvedStellarPops,代码行数:34,代码来源:plotting.py


示例4: __init__

    def __init__(self, cmapName="hsv", indexMin=0, indexMax=1):
        """
        cmapName: color map name
        indexMin, indexMax: mininal and maximal value of index used
                            used for normalization
        """

        #self.cmap = cm.cmap_d[cmapName] # color map instance
        self.cmap = cm.get_cmap(cmapName) # color map instance
        self.norm = colors.normalize(indexMin, indexMax) # normalize instance
开发者ID:gizela,项目名称:gizela,代码行数:10,代码来源:ColorMap.py


示例5: pproc

def pproc(filename, inArray, dir, max_value, padding, show_plot):
    array = dirArray(inArray[0], dir)
    #with open('1.dat', 'w') as f:
    #    for item in xArray:    
    #        f.write(str(item))
    mat = FilterMap(max_value, padding)
    mat.filter(array)
    #plt.imshow(mat.result)
    
    maxV =  max(map(max, mat.result))
    minV =  min(map(min, mat.result))
    if (maxV**2 > minV**2): mv = np.sqrt(maxV**2)
    else: mv = np.sqrt(minV**2)

    print "max value of field: ", mv
    print "half of max value of field: ", mv/2
    
    # ['Spectral', 'summer', 'RdBu', 'Set1', 'Set2', 'Set3', 'brg_r', 'Dark2', 
    # 'hot', 'PuOr_r', 'afmhot_r', 'terrain_r', 'PuBuGn_r', 'RdPu', 'gist_ncar_r', 
    # 'gist_yarg_r', 'Dark2_r', 'YlGnBu', 'RdYlBu', 'hot_r', 'gist_rainbow_r', 
    # 'gist_stern', 'gnuplot_r', 'cool_r', 'cool', 'gray', 'copper_r', 'Greens_r', 
    # 'GnBu', 'gist_ncar', 'spring_r', 'gist_rainbow', 'RdYlBu_r', 'gist_heat_r', 
    # 'OrRd_r', 'bone', 'gist_stern_r', 'RdYlGn', 'Pastel2_r', 'spring', 'terrain', 
    # 'YlOrRd_r', 'Set2_r', 'winter_r', 'PuBu', 'RdGy_r', 'spectral', 'flag_r', 
    # 'jet_r', 'RdPu_r', 'Purples_r', 'gist_yarg', 'BuGn', 'Paired_r', 'hsv_r', 'bwr', 
    # 'YlOrRd', 'Greens', 'PRGn', 'gist_heat', 'spectral_r', 'Paired', 'hsv', 'Oranges_r', 
    # 'prism_r', 'Pastel2', 'Pastel1_r', 'Pastel1', 'gray_r', 'PuRd_r', 'Spectral_r', 
    # 'gnuplot2_r', 'BuPu', 'YlGnBu_r', 'copper', 'gist_earth_r', 'Set3_r', 'OrRd', 
    # 'PuBu_r', 'ocean_r', 'brg', 'gnuplot2', 'jet', 'bone_r', 'gist_earth', 'Oranges', 
    # 'RdYlGn_r', 'PiYG', 'YlGn', 'binary_r', 'gist_gray_r', 'Accent', 'BuPu_r', 'gist_gray', 
    # 'flag', 'seismic_r', 'RdBu_r', 'BrBG', 'Reds', 'BuGn_r', 'summer_r', 'GnBu_r', 'BrBG_r', 
    # 'Reds_r', 'RdGy', 'PuRd', 'Accent_r', 'Blues', 'Greys', 'autumn', 'PRGn_r', 'Greys_r', 
    # 'pink', 'binary', 'winter', 'gnuplot', 'pink_r', 'prism', 'YlOrBr', 'rainbow_r', 'rainbow', 
    # 'PiYG_r', 'YlGn_r', 'Blues_r', 'YlOrBr_r', 'seismic', 'Purples', 'bwr_r', 'autumn_r', 
    # 'ocean', 'Set1_r', 'PuOr', 'PuBuGn', 'afmhot']
    # norm = colors.normalize(-mv, mv)
    # MUMAX
    norm = colors.normalize(-1, 1)
    # norm = colors.LogNorm()
    # plt.matshow(mat.result, cmap='RdBu', norm=colors.LogNorm() )
    plt.matshow(mat.result, norm=norm )
    plt.colorbar(shrink=.8)
    fig = plt.gcf()
    if (show_plot==True): plt.show()
    png_name = filename[0:(len(filename)-4)] + "_" "+.png"
    a = re.split(r'\\', png_name)
    addr = ""
    for i in range(len(a)-1):
        addr += a[i] +"\\"
    print addr
    addr += (dir+"_"+a[ len(a)-1 ])
    print addr
    #addr =  nn
    fig.savefig(addr, dpi=100)
    plt.close()
开发者ID:pgru,项目名称:scripts,代码行数:55,代码来源:process_mumax.py


示例6: make_mpl_image_properties

def make_mpl_image_properties(func_man):
    """ Create a dictionary of matplotlib AxesImage color mapping
    properties from the corresponding properties in an OverlayInterface 
    """
    from matplotlib.colors import normalize
    props = dict()
    props['cmap'] = func_man.colormap
    props['interpolation'] = func_man.interpolation
    props['alpha'] = func_man.alpha()
    props['norm'] = normalize(*func_man.norm)
    return props
开发者ID:cindeem,项目名称:xipy,代码行数:11,代码来源:interface.py


示例7: colorify

def colorify(data, vmin=None, vmax=None, cmap=plt.cm.Spectral):
    """ Associate a color map to a quantity vector """
    import matplotlib.colors as colors

    _vmin = vmin or min(data)
    _vmax = vmax or max(data)
    cNorm = colors.normalize(vmin=_vmin, vmax=_vmax)

    scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=cmap)
    colors = map(scalarMap.to_rgba, data)
    return colors, scalarMap
开发者ID:mfouesneau,项目名称:faststats,代码行数:11,代码来源:figrc.py


示例8: __init__

    def __init__(self, cmapName="hsv", indexMin=0, indexMax=1):
        """
        cmapName: color map name
        indexMin, indexMax: mininal and maximal value of index used
                            used for normalization
        """

        self.cmap = cm.cmap_d[cmapName] # color map instance
        self.norm = colors.normalize(indexMin, indexMax) # normalize instance
        
        self.set_color(indexMin) # implicit setting of point color
开发者ID:gizela,项目名称:gizela,代码行数:11,代码来源:PointStyleColorMap.py


示例9: _draw_features

 def _draw_features(self, **kwargs):
     xoffset = kwargs.get('xoffset',0)
     for feat_numb, feat2draw in enumerate(self.features):
         if feat2draw.color_by_cm:
             if feat2draw.use_score_for_color:
                 feat2draw.cm_value = feat2draw.score
                 feat2draw.fc = self.cm(feat2draw.cm_value)
             else:# color by feature number
                 if not feat2draw.cm_value:
                     self.norm = colors.normalize(1,len(self.features)+1,)
                     feat2draw.cm_value = feat_numb +1
                 feat2draw.fc = self.cm(self.norm(feat2draw.cm_value))
         feat2draw.draw_feature()
         feat2draw.draw_feat_name(xoffset = xoffset)
开发者ID:apierleoni,项目名称:BioGraPy,代码行数:14,代码来源:tracks.py


示例10: add_data

    def add_data(self, data):
        """
        Adiciona serie temporal para UFs [(UF,tempo,valor),...]
        """
        vals = array([i[2] for i in data])
        norm = normalize(vals.min(), vals.max()) 
        for i, d in enumerate(data):
            print i
            pm = self.pmdict[d[0]]
            #clone placemark to receive new data
            pm_newtime = pm.cloneNode(1)
            # Renaming placemark
            on = pm_newtime.getElementsByTagName('name')[0]
            nn = self.kmlDoc.createElement('name')
            nn.appendChild(self.kmlDoc.createTextNode(d[0]+'-'+str(d[1])))
            pm_newtime.replaceChild(nn, on)
            nl = pm_newtime.childNodes
            #extrude polygon
            pol = pm_newtime.getElementsByTagName('Polygon')[0]
            alt = self.kmlDoc.createElement('altitudeMode')
            alt.appendChild(self.kmlDoc.createTextNode('relativeToGround'))
            ex = self.kmlDoc.createElement('extrude')
            ex.appendChild(self.kmlDoc.createTextNode('1'))
            ts = self.kmlDoc.createElement('tessellate')
            ts.appendChild(self.kmlDoc.createTextNode('1'))
            pol.appendChild(alt)
            pol.appendChild(ex)
            pol.appendChild(ts)
            lr = pm_newtime.getElementsByTagName('LinearRing')[0]
            nlr = self.extrude_polygon(lr, d[2])
            ob = pm_newtime.getElementsByTagName('outerBoundaryIs')[0]
#            ob.replaceChild(nlr, lr)
            ob.removeChild(lr)
            ob.appendChild(nlr)
            #set polygon style
            col = rgb2hex(cm.Oranges(norm(d[2]))[:3])+'ff'
            st = pm_newtime.getElementsByTagName('Style')[0] #style
            nst = self.set_polygon_style(st, col)
            pm_newtime.removeChild(st)
            pm_newtime.appendChild(nst)
            
            #add timestamp
            ts = self.kmlDoc.createElement('TimeStamp')
            w = self.kmlDoc.createElement('when')
            w.appendChild(self.kmlDoc.createTextNode(str(d[1])))
            ts.appendChild(w)
            pm_newtime.appendChild(ts)
            self.folder.appendChild(pm_newtime)
        for pm in self.pmdict.itervalues():
            self.folder.removeChild(pm)
开发者ID:Ralpbezerra,项目名称:Supremo,代码行数:50,代码来源:kmlgen.py


示例11: plot_sensor_data

def plot_sensor_data(sensor, plot_type="grey", outfile="output.png"):

    # Create canvas
    print "Preparing the plot"
    fig = plt.figure()

    if (plot_type == "3d"):
        ax = fig.add_subplot(111, projection='3d')

        # Calculate 3d plot data: grid
        xedges = np.arange(0, s.pixel_rows+1)
        yedges = np.arange(0, s.pixel_columns+1)
        elements = (len(xedges) - 1) * (len(yedges) - 1)
        xpos, ypos = np.meshgrid(xedges[:-1]+0.05, yedges[:-1]+0.05)

        # Calculate starting x, y, z
        xpos = xpos.flatten()
        ypos = ypos.flatten()
        zpos = np.zeros(elements)
        # Areas of the bins, flatten the heights
        dx = 0.9 * np.ones_like(zpos)
        dy = dx.copy()
        dz = np.array(s.data()).flatten()

        print "Calculating colors..."
        norm = colors.normalize(dz.min(), dz.max())
        col = []
        for i in dz:
            col.append(cm.jet(norm(i)))

        print "Now rendering image..."
        ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color=col, zsort='average')
    else:
        ax = fig.add_subplot(111)
        dz = np.array(s.data()).flatten()

        cma = cm.jet
        if (plot_type == "grey"):
            cma = cm.Greys
        cax = ax.imshow(s.data(), interpolation='nearest', cmap=cma)

        cbar = fig.colorbar(cax, ticks=[dz.min(), (dz.max()+dz.min())/2, dz.max()], orientation='vertical')
        cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])# horizontal colorbar

    ax.set_title('Sensor Data')
    print "Saving image..."
    plt.savefig(outfile, dpi=500)
    print "All done!"
开发者ID:ruphy,项目名称:esame-lab2,代码行数:48,代码来源:program.py


示例12: db_to_logs

def db_to_logs(ano):
    """
    Extrai as decisoes do bancoe as salva em um arquivo no formato do Gource
    """
    #Q = dbdec.execute("SELECT relator,processo,tipo,proc_classe,duracao, UF,data_dec, count(*) FROM decisao WHERE DATE_FORMAT(data_dec,'%Y%')="+"%s"%ano+" GROUP BY relator,tipo,proc_classe")
    Q = dbdec.execute("SELECT relator,processo,tipo,proc_classe,duracao, UF,data_dec FROM decisao WHERE DATE_FORMAT(data_dec,'%Y%')="+"%s"%ano+" ORDER BY data_dec asc")
    decs = Q.fetchall()
    durations = [d[4] for d in decs]
    cmap = cm.jet
    norm = normalize(min(durations), max(durations)) #normalizing durations
    with open('decisoes_%s.log'%ano, 'w') as f:
        for d in decs:
            c = rgb2hex(cmap(norm(d[4]))[:3]).strip('#')
            path = "/%s/%s/%s/%s"%(d[5],d[2],d[3], d[1]) #/State/tipo/proc_classe/processo
            l = "%s|%s|%s|%s|%s\n"%(int(time.mktime(d[6].timetuple())), d[0], 'A', path, c)
            f.write(l)
开发者ID:Ralpbezerra,项目名称:Supremo,代码行数:16,代码来源:gourceviz.py


示例13: histogram

	def histogram(self):
		self.ax.set_title('Histogram of Evidence Based Scheduling [ %d ]' % len(self.H))
		self.ax.set_xlabel('Time (h)',fontstyle='italic')
		self.ax.set_ylabel('Probability (%)',fontstyle='italic')
		self.ax.set_ylim(0,110)
		self.ax.grid(True)

		self.ax.axvline(self.u, color='#90EE90', linestyle='dashed', lw=2)

		self.H += self.mc.probes(1000)
		n, bins, patches = self.ax.hist(self.H, bins=self.count , edgecolor='white', alpha=0.75)
		nmax=n.max() # najwyższy słupek

		# zmienna skala osi Y
		self.ax.set_xticks([ round(i,2) for i in bins[::self.scale] ])
		# self.ax.set_xticklabels(('a','b')) # tak można dodać label zamiast wartości
		self.figure.autofmt_xdate() # pochyłe literki

		# strzałka
		if self.arrow:
			pyplot.annotate('simple estimation', xy=(self.u, 90), xytext=(min(bins), 100),
				arrowprops=dict(facecolor='blue', shrink=0.005))

		if self.help == 1 :
			pyplot.annotate('help (h)',
				xy=(max(bins), 90),
				xytext=((self.u+max(bins))/2, 90),
				ha='left')
		elif self.help == 2 :
			pyplot.annotate('\n'.join(self.usage),
				xy=(max(bins), 90),
				xytext=((self.u+max(bins))/2, 60),
				ha='left')

		# normalizacja
		for p in patches:
			p.set_height((p.get_height() * 100.0 ) / nmax )

		# tęcza
		fracs = n.astype(float)/nmax
		norm = colors.normalize(fracs.min(), fracs.max())

		for f, p in zip(fracs, patches):
			color = cm.jet(norm(f))
			p.set_facecolor(color)
开发者ID:borzole,项目名称:borzole,代码行数:45,代码来源:ebs.py


示例14: hist_com_difference_plot

def hist_com_difference_plot(filename,image_output,graph_title=''):
	distance = []
	for line in open(filename):
                if line[0] == "#" or line[0] == "@": continue
                line_content = line.split()
		distance.append(float(line_content[1]))
	fig = figure()
	N,bins,patches = hist(distance,range(-30,30))
        fracs = N.astype(float)/N.max()
        norm = colors.normalize(fracs.min(), fracs.max())

	for thisfrac, thispatch in zip(fracs, patches):
        	color = cm.jet(norm(thisfrac))
        	thispatch.set_facecolor(color)

	xlabel('Z Distance between Protein and Bilayer centers')
	ylabel('Frequency')
	title(graph_title)
	savefig(image_output)
开发者ID:hallba,项目名称:Sidekick,代码行数:19,代码来源:AutomatedPlot.py


示例15: plot_mod

def plot_mod(x, z, yvals, ylabel, ax, ind=0, cmap=pl.cm.rainbow,
             printlabel=True):
    """ Plot column-density-derived values yvals as a function of the
    x values (NHI, nH or Z), showing variation of quantity z by
    different coloured curves. ind is the index of the value used,
    which isn't varied.
    """ 
    # Want index order to be indtype, x, z. By default it's NHI, nH,
    # Z. Otherwise it has to change...
    if (x,z) == ('NHI','Z'):
        yvals = np.swapaxes(yvals, 0, 1) 
    elif (x,z) == ('Z','NHI'):
        yvals = np.swapaxes(yvals, 0, 1)
        yvals = np.swapaxes(yvals, 1, 2) 
    elif (x,z) == ('nH','NHI'):
        yvals = np.swapaxes(yvals, 0, 2) 
    elif (x,z) == ('NHI', 'nH'):
        yvals = np.swapaxes(yvals, 0, 2)
        yvals = np.swapaxes(yvals, 1, 2)
    elif (x,z) == ('Z','nH'):
        yvals = np.swapaxes(yvals, 1, 2) 
    
    norm = colors.normalize(M[z].min(), M[z].max())
    label_indices = set((0, len(M[z])//2, len(M[z])-1))
    for i in range(len(M[z])):
        # spring, summer, autumn, winter are all good
        c = cmap(norm(M[z][i]))
        label = None
        if i in label_indices:
            label = labels[z] % M[z][i]
        #ax.plot(M[x], yvals[ind,:,i], '-', lw=2.5, color='k') 
        ax.plot(M[x], yvals[ind,:,i], '-', lw=1.5, color=c, label=label)

    val, = list(set(['nH','NHI','Z']).difference([x,z]))
    if printlabel:
        ax.set_title(labels[val] % M[val][ind], fontsize='medium')
        ax.title.set_y(1.01)

    ax.set_xlabel(xlabels[x], fontsize='small')
    ax.set_ylabel(ylabel)
    ax.minorticks_on()
    ax.set_xlim(M[x][0]+1e-3, M[x][-1]-1e-3)
开发者ID:nhmc,项目名称:H2,代码行数:42,代码来源:cloudy_plot.py


示例16: hist_tilt_data_plot

def hist_tilt_data_plot(filename,image_output,graph_title='',modifier=0.,binwidth=5):
	tilt = []
	for line in open(filename):
		if line[0] == "#" or line[0] == "@": continue
		line_content = line.split()
		if float(line_content[1]) <= 90: tilt.append(float(line_content[1]))
		else: tilt.append(180 - float(line_content[1]))
	if modifier != 0:
		tilt = [modifier-angle for angle in tilt]
	fig = figure()
	N,bins,patches = hist(tilt,range(0,90,binwidth))
	fracs = N.astype(float)/N.max()
	norm = colors.normalize(fracs.min(), fracs.max())

	for thisfrac, thispatch in zip(fracs, patches):
		color = cm.jet(norm(thisfrac))
		thispatch.set_facecolor(color)
	xlabel('Tilt angle (degrees)')
	ylabel('Frequency')
	title(graph_title)
	savefig(image_output)
开发者ID:hallba,项目名称:Sidekick,代码行数:21,代码来源:AutomatedPlot.py


示例17: _plot

 def _plot(map):
     global axis
     mpl.rcParams['xtick.labelsize'] = 'medium'
     mpl.rcParams['ytick.labelsize'] = 'medium'
     mpl.rcParams['axes.grid'] = False
     mpl.rcParams['figure.subplot.left'] = 0.06
     mpl.rcParams['figure.subplot.right'] = 0.97
     mpl.rcParams['figure.subplot.top'] = 0.9
     mpl.rcParams['figure.subplot.bottom'] = 0.1
     mpl.rcParams['axes.labelsize'] = 'medium'
     mpl.rcParams['ytick.major.pad'] = 4
     mpl.rcParams['xtick.major.pad'] = 4
     fig = plt.figure(figsize=(16, 9))
     axis = plt.gca()
     fig.canvas.set_window_title('Contacts Histogram')
     fig.canvas.mpl_connect('button_press_event', _onpick)
     bar_heights = np.array(map.values()).astype(float)
     bar_positions = np.array(map.keys())
     bar_rectangles = plt.bar(bar_positions, bar_heights, width=1.0, linewidth=0)
     plt.xlim(bar_positions.min(), bar_positions.max())
     plt.ylim(0, bar_heights.max()+1)
     plt.title('Contacts Histogram ' + '(cutoff distance = ' + str(distance_cutoff) + ur' \u00c5)' + '\n\n')
     plt.xlabel('\nResidue Index')
     plt.ylabel('Count\n')
     # Set Colors of the bar
     fractions = bar_heights/bar_heights.max()
     normalized_colors = colors.normalize(fractions.min(), fractions.max())
     count = 0
     for rect in bar_rectangles:
         c = cm.jet(normalized_colors(fractions[count]))
         rect.set_facecolor(c)
         count = count + 1
     ax_text = plt.axes([0.81, -0.02, 0.13, 0.075], frameon=False)
     Button(ax_text, 'Click to select and highlight the residue in PyMol...', color=(0.33,0.33,0.33))
     fig.show()
     # This dummy image and drawing it on the canvas is neccessary step to give back CGContextRef to the main window. Otherwise the buttons on main contact map window stops responding.
     progressbar.ax.set_visible(False)
     dummy_img = Image.new('RGBA',(x_img_length,y_img_length),(0,0,0,0))
     glob_ax.imshow(dummy_img)
     glob_ax.figure.canvas.draw()
开发者ID:emptyewer,项目名称:CMPyMOL,代码行数:40,代码来源:CMPyMOL1.0b.py


示例18: pproc

def pproc(filename, inArray, dir, max_value, padding, show_plot):
    array = dirArray(inArray[0], dir)
    #with open('1.dat', 'w') as f:
    #    for item in xArray:    
    #        f.write(str(item))
    mat = FilterMap(max_value, padding)
    mat.filter(array)
    #plt.imshow(mat.result)
    
    maxV =  max(map(max, mat.result))
    minV =  min(map(min, mat.result))
    if (maxV**2 > minV**2): mv = np.sqrt(maxV**2)
    else: mv = np.sqrt(minV**2)

    print "max value of field: ", mv
    print "half of max value of field: ", mv/2
    norm = colors.normalize(-mv, mv)
    # MUMAX
    # norm = colors.normalize(-1, 1)
    # norm = colors.LogNorm()
    # plt.matshow(mat.result, cmap='RdBu', norm=colors.LogNorm() )
    plt.matshow(mat.result, norm=norm )
    plt.colorbar(shrink=.8)
    fig = plt.gcf()
    if (show_plot==True): plt.show()
    png_name = filename[0:(len(filename)-4)] + "_" "+.png"
    a = re.split(r'\\', png_name)
    addr = ""
    for i in range(len(a)-1):
        addr += a[i] +"\\"
    print addr
    addr += (dir+"_"+a[ len(a)-1 ])
    print addr
    #addr =  nn
    fig.savefig(addr, dpi=100)
    plt.close()
开发者ID:pgru,项目名称:scripts,代码行数:36,代码来源:holes_mod_summation.py


示例19: xrange

    for ind_rate in xrange(len(X_IDX)):
        for ind_strength in xrange(len(Y_IDX)):
            tmp_mps = IDX[to1d(ind_rate, ind_strength, len(X_IDX))][2]
            Z_IDX[0][ind_rate][ind_strength] = tmp_mps[0]
            Z_IDX[1][ind_rate][ind_strength] = tmp_mps[1]
            Z_IDX[2][ind_rate][ind_strength] = tmp_mps['whole']

            tmp_sts = IDX[to1d(ind_rate, ind_strength, len(X_IDX))][3]
            Z_IDX[3][ind_rate][ind_strength] = tmp_sts[0]
            Z_IDX[4][ind_rate][ind_strength] = tmp_sts[1]
            Z_IDX[5][ind_rate][ind_strength] = tmp_sts['whole']

    # MPS plotting
    MPS_FIG, MPS_AXS = plt.subplots(1, 3, figsize=(9, 3))
    MPS_MIN_MAX = get_all_min_max([Z_IDX[i] for i in xrange(3)])
    MPS_NORM = colors.normalize(MPS_MIN_MAX[0], MPS_MIN_MAX[1])
    plot_run(MPS_FIG, "MPS", MPS_AXS, Z_IDX, range(3), MPS_NORM, IMSHOW_EXTENT)

    # STS plotting
    STS_FIG, STS_AXS = plt.subplots(1, 3, figsize=(9, 3))
    STS_MIN_MAX = get_all_min_max([Z_IDX[i] for i in xrange(3, 6)])
    STS_NORM = colors.normalize(STS_MIN_MAX[0], STS_MIN_MAX[1])
    plot_run(STS_FIG, "STS", STS_AXS, Z_IDX, range(3, 6), STS_NORM, IMSHOW_EXTENT)


    """
    FFT MAX

    """
    FFT_ATTRS = (('paramset', '_v_attrs', 'Common', 'inter_conn_rate', 0, 1),
                 ('paramset', '_v_attrs', 'Common', 'inter_conn_strength', 0, 1),
开发者ID:neuro-lyon,项目名称:multiglom-model,代码行数:31,代码来源:analysis_bigrun.py


示例20: streamplot

def streamplot(axes, x, y, u, v, density=1, linewidth=None, color=None,
               cmap=None, norm=None, arrowsize=1, arrowstyle='-|>',
               minlength=0.1, transform=None):
    """Draws streamlines of a vector flow.

    *x*, *y* : 1d arrays
        an *evenly spaced* grid.
    *u*, *v* : 2d arrays
        x and y-velocities. Number of rows should match length of y, and
        the number of columns should match x.
    *density* : float or 2-tuple
        Controls the closeness of streamlines. When `density = 1`, the domain
        is divided into a 25x25 grid---*density* linearly scales this grid.
        Each cell in the grid can have, at most, one traversing streamline.
        For different densities in each direction, use [density_x, density_y].
    *linewidth* : numeric or 2d array
        vary linewidth when given a 2d array with the same shape as velocities.
    *color* : matplotlib color code, or 2d array
        Streamline color. When given an array with the same shape as
        velocities, *color* values are converted to colors using *cmap*.
    *cmap* : :class:`~matplotlib.colors.Colormap`
        Colormap used to plot streamlines and arrows. Only necessary when using
        an array input for *color*.
    *norm* : :class:`~matplotlib.colors.Normalize`
        Normalize object used to scale luminance data to 0, 1. If None, stretch
        (min, max) to (0, 1). Only necessary when *color* is an array.
    *arrowsize* : float
        Factor scale arrow size.
    *arrowstyle* : str
        Arrow style specification.
        See :class:`~matplotlib.patches.FancyArrowPatch`.
    *minlength* : float
        Minimum length of streamline in axes coordinates.

    Returns
    -------
    *stream_container* : StreamplotSet
        Container object with attributes
            lines : `matplotlib.collections.LineCollection` of streamlines
            arrows : collection of `matplotlib.patches.FancyArrowPatch` objects
                repesenting arrows half-way along stream lines.
        This container will probably change in the future to allow changes to
        the colormap, alpha, etc. for both lines and arrows, but these changes
        should be backward compatible.
    """
    grid = Grid(x, y)
    mask = StreamMask(density)
    dmap = DomainMap(grid, mask)

    if color is None:
        color = axes._get_lines.color_cycle.next()

    if linewidth is None:
        linewidth = matplotlib.rcParams['lines.linewidth']

    line_kw = {}
    arrow_kw = dict(arrowstyle=arrowstyle, mutation_scale=10*arrowsize)

    use_multicolor_lines = isinstance(color, np.ndarray)
    if use_multicolor_lines:
        assert color.shape == grid.shape
        line_colors = []
    else:
        line_kw['color'] = color
        arrow_kw['color'] = color

    if isinstance(linewidth, np.ndarray):
        assert linewidth.shape == grid.shape
        line_kw['linewidth'] = []
    else:
        line_kw['linewidth'] = linewidth
        arrow_kw['linewidth'] = linewidth

    ## Sanity checks.
    assert u.shape == grid.shape
    assert v.shape == grid.shape

    if np.any(np.isnan(u)):
        u = np.ma.array(u, mask=np.isnan(u))
    if np.any(np.isnan(v)):
        v = np.ma.array(v, mask=np.isnan(v))

    integrate = get_integrator(u, v, dmap, minlength)

    trajectories = []
    for xm, ym in _gen_starting_points(mask.shape):
        if mask[ym, xm] == 0:
            xg, yg = dmap.mask2grid(xm, ym)
            t = integrate(xg, yg)
            if t != None:
                trajectories.append(t)

    if use_multicolor_lines:
        if norm is None:
            norm = mcolors.normalize(color.min(), color.max())
        if cmap is None:
            cmap = cm.get_cmap(matplotlib.rcParams['image.cmap'])
        else:
            cmap = cm.get_cmap(cmap)

#.........这里部分代码省略.........
开发者ID:andreas-h,项目名称:matplotlib,代码行数:101,代码来源:streamplot.py



注:本文中的matplotlib.colors.normalize函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。


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