Python PatchCollection.set_norm方法代码示例

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]
class Visualize:
    def __init__(self, v, t, e, fig, win, axesLimit=[-3,3.5,-2,2]):
        self.e = e.copy()
        self.p = [Polygon(v[ti]) for ti in t]
        self.p = PatchCollection(self.p, edgecolors='none')
        self.l = LineCollection(v[e[:,:2]])

        win = win or fig.canvas.manager.window
        if fig is None: fig = gcf()
        fig.clf()
        ax = fig.add_axes([0.02,0.02,.98,.98])
        ax.axis('scaled')
        ax.axis(axesLimit)
        ax.set_autoscale_on(False)
        self.axis, self.fig, self.win = ax, fig, win

        ax.add_collection(self.p)
        ax.add_collection(self.l)
        # ax.add_collection(self.l1)
        # ax.add_collection(self.l2)

    def update(self, title, phi):
        norm = Normalize(phi.min(), phi.max())
        self.p.set_norm(norm)
        self.l.set_norm(norm)
        self.p.set_array(phi)
        self.l.set_array(phi[self.e[:,2:]].mean(1))
        if not self.__dict__.has_key('colorbar'):
            self.colorbar = self.fig.colorbar(self.p)
        self.win.set_title(title)
        #self.fig.canvas.set_window_title(title)
        self.fig.canvas.draw()

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]
  def render(self,ax,alpha=.7,usePyLeaflet=False,
      minValueThreshold=-float('Inf'),logScale=True,colormapname='BlueRed'):
    if not usePyLeaflet or colormapname=='nothingRed':
      alpha=1.0

    patches = []
    values = []
    colorvalues = []
    for d in self.countPerGeohash.keys():
      try:
        if (self.countPerGeohash[d]>minValueThreshold):
          bbox = geohash.bbox(d)
          rect = mpatches.Rectangle([ bbox['w'],
                        bbox['s']],
                        bbox['e'] - bbox['w'],
                        bbox['n'] - bbox['s'],
                        ec='none', lw=.1, fc='red', alpha=alpha)
          patches.append(rect)
          # values.append(self.countPerGeohash[d] \
          #   if self.countPerGeohash[d]<3 else self.countPerGeohash[d]+10)
          # colorvalues.append(self.countPerGeohash[d] \
          #   if self.countPerGeohash[d]<3 else self.countPerGeohash[d]+10)
          values.append(self.countPerGeohash[d])
          colorvalues.append(self.countPerGeohash[d])
      except KeyError:
        print("'"+d +"' is not a valid geohash.")

    try:
      maxval = max(values)
      minval = min(values)
    except ValueError:
      print('heatmap appears to be empty...')
      maxval = 1
      minval = 0

    p = PatchCollection(patches,cmap=plt.get_cmap(colormapname),alpha=alpha)
  #   if usePyLeaflet:
    if (len(values)<100):
      p.set_edgecolors(np.array(['black' for x in values]))
    else:
      p.set_edgecolors(np.array(['#333333' if x<=2 \
        else ('#666666' if x<=10 else 'black') for x in values]))
  #   else:
  #     p.set_edgecolors(np.array(['white' for x in values]))
    p.set_array(np.array(colorvalues))
    if logScale:
      p.set_norm(colors.LogNorm(vmin=.01, vmax=maxval))
    else:
      p.set_norm(colors.Normalize(vmin=0, vmax=maxval))
    ax.add_collection(p)
    ax.set_xlim(self.bbox['w'], self.bbox['e'])
    ax.set_ylim(self.bbox['s'], self.bbox['n'])
    divider = make_axes_locatable(ax)
    cbar = plt.colorbar(p)
    cbar.set_clim(vmin=max(0,minval),vmax=maxval)
    cbar.update_normal(p)
    return

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]
def draw1DColumn(ax, x, val, thk, width=30, ztopo=0, cmin=1, cmax=1000,
                 cmap=None, name=None, textoffset=0.0):
    """Draw a 1D column (e.g., from a 1D inversion) on a given ax.

    Examples
    --------
    >>> import numpy as np
    >>> import matplotlib.pyplot as plt
    >>> from pygimli.mplviewer import draw1DColumn
    >>> thk = [1, 2, 3, 4]
    >>> val = thk
    >>> fig, ax = plt.subplots()
    >>> draw1DColumn(ax, 0.5, val, thk, width=0.1, cmin=1, cmax=4, name="VES")
    <matplotlib.collections.PatchCollection object at ...>
    >>> ax.set_ylim(-np.sum(thk), 0)
    (-10, 0)
    """
    z = -np.hstack((0., np.cumsum(thk), np.sum(thk) * 1.5)) + ztopo
    recs = []
    for i in range(len(val)):
        recs.append(Rectangle((x - width / 2., z[i]), width, z[i + 1] - z[i]))

    pp = PatchCollection(recs)
    col = ax.add_collection(pp)

    pp.set_edgecolor(None)
    pp.set_linewidths(0.0)

    if cmap is not None:
        if isinstance(cmap, str):
            pp.set_cmap(pg.mplviewer.cmapFromName(cmap))
        else:
            pp.set_cmap(cmap)

    pp.set_norm(colors.LogNorm(cmin, cmax))
    pp.set_array(np.array(val))
    pp.set_clim(cmin, cmax)
    if name:
        ax.text(x+textoffset, ztopo, name, ha='center', va='bottom')

    updateAxes_(ax)

    return col

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]
def showStitchedModels(mods, axes=None, cmin=None, cmax=None, **kwargs):
    """
        Show several 1d block models as (stitched) section.
    """
    x = kwargs.pop('x', np.arange(len(mods)))
    topo = kwargs.pop('topo', x*0)

    nlay = int(np.floor((len(mods[0]) - 1) / 2.)) + 1
    if cmin is None or cmax is None:
        cmin = 1e9
        cmax = 1e-9
        for model in mods:
            res = np.asarray(model)[nlay - 1:nlay * 2 - 1]
            cmin = min(cmin, min(res))
            cmax = max(cmax, max(res))

    if kwargs.pop('sameSize', True):  # all having the same width
        dx = np.ones_like(x)*np.median(np.diff(x))
    else:
        dx = np.diff(x) * 1.05
        dx = np.hstack((dx, dx[-1]))

    x1 = x - dx / 2
    if axes is None:
        fig, ax = plt.subplots()
    else:
        ax = axes
        fig = ax.figure

#    ax.plot(x, x * 0., 'k.')
    zm = kwargs.pop('zm', None)
    maxz = 0.
    if zm is not None:
        maxz = zm
    recs = []
    RES = []
    for i, mod in enumerate(mods):
        mod1 = np.asarray(mod)
        res = mod1[nlay - 1:]
        RES.extend(res)

        thk = mod1[:nlay - 1]
        thk = np.hstack((thk, thk[-1]))
        z = np.hstack((0., np.cumsum(thk)))
        if zm is not None:
            thk[-1] = zm - z[-2]
            z[-1] = zm
        else:
            maxz = max(maxz, z[-1])

        for j in range(len(thk)):
            recs.append(Rectangle((x1[i], topo[i]-z[j]), dx[i], -thk[j]))

    pp = PatchCollection(recs, edgecolors=kwargs.pop('edgecolors', 'none'))
    pp.set_edgecolor(kwargs.pop('edgecolors', 'none'))
    pp.set_linewidths(0.0)
    ax.add_collection(pp)
    if 'cmap' in kwargs:
        pp.set_cmap(kwargs['cmap'])

    print(cmin, cmax)
    norm = LogNorm(cmin, cmax)
    pp.set_norm(norm)
    pp.set_array(np.array(RES))
#    pp.set_clim(cmin, cmax)
    ax.set_ylim((-maxz, max(topo)))
    ax.set_xlim((x1[0], x1[-1] + dx[-1]))

    cbar = None
    if kwargs.pop('colorBar', True):
        cbar = plt.colorbar(pp, ax=ax, norm=norm, orientation='horizontal',
                            aspect=60)  # , ticks=[1, 3, 10, 30, 100, 300])
        if 'ticks' in kwargs:
            cbar.set_ticks(kwargs['ticks'])
#        cbar.autoscale_None()
    if axes is None:  # newly created fig+ax
        return fig, ax
    else:  # already given, better give back color bar
        return cbar

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]
def patchValMap(vals, xvec=None, yvec=None, ax=None, cMin=None, cMax=None,
                logScale=None, label=None, dx=1, dy=None, **kwargs):
    """ plot previously generated (generateVecMatrix) y map (category)

    Parameters
    ----------
    A : iterable
        to show
    xvec : dict {i:num}
        dict (must match A.shape[0])
    ymap : iterable
        vector for x axis (must match A.shape[0])
    ax : mpl.axis
        axis to plot, if not given a new figure is created
    cMin/cMax : float
        minimum/maximum color values
    logScale : bool
        logarithmic colour scale [min(A)>0]
    label : string
        colorbar label
    """
    if cMin is None:
        cMin = np.min(vals)
    if cMax is None:
        cMax = np.max(vals)
    if logScale is None:
        logScale = (cMin > 0.0)
    if logScale:
        norm = LogNorm(vmin=cMin, vmax=cMax)
    else:
        norm = Normalize(vmin=cMin, vmax=cMax)
    if 'ax' is None:
        fig, ax = plt.subplots()

    recs = []
    if dy is None:  # map y values to unique
        ymap = {xy: ii for ii, xy in enumerate(np.unique(yvec))}
        for i in range(len(vals)):
            recs.append(Rectangle((xvec[i]-dx/2, ymap[yvec[i]]-0.5), dx, 1))
    else:
        for i in range(len(vals)):
            recs.append(Rectangle((xvec[i]-dx/2, yvec[i]-dy/2), dx, dy))

    pp = PatchCollection(recs)
    col = ax.add_collection(pp)
    pp.set_edgecolor(None)
    pp.set_linewidths(0.0)
    if 'cmap' in kwargs:
        pp.set_cmap(kwargs.pop('cmap'))
    pp.set_norm(norm)
    pp.set_array(np.array(vals))
    pp.set_clim(cMin, cMax)
    ax.set_xlim(min(xvec)-dx/2, max(xvec)+dx/2)
    ax.set_ylim(len(ymap)-0.5, -0.5)

    updateAxes_(ax)
    cbar = None
    if kwargs.pop('colorBar', True):
        cbar = pg.mplviewer.createColorbar(col, cMin=cMin, cMax=cMax, nLevs=5,
                                           label=label)
    return ax, cbar, ymap

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]
def patchMatrix(A, xmap=None, ymap=None, ax=None, cMin=None, cMax=None,
                logScale=None, label=None, dx=1, **kwargs):
    """ plot previously generated (generateVecMatrix) matrix

    Parameters
    ----------
    A : numpy.array2d
        matrix to show
    xmap : dict {i:num}
        dict (must match A.shape[0])
    ymap : iterable
        vector for x axis (must match A.shape[0])
    ax : mpl.axis
        axis to plot, if not given a new figure is created
    cMin/cMax : float
        minimum/maximum color values
    logScale : bool
        logarithmic colour scale [min(A)>0]
    label : string
        colorbar label
    """
    mat = np.ma.masked_where(A == 0.0, A, False)
    if cMin is None:
        cMin = np.min(mat)
    if cMax is None:
        cMax = np.max(mat)
    if logScale is None:
        logScale = (cMin > 0.0)
    if logScale:
        norm = LogNorm(vmin=cMin, vmax=cMax)
    else:
        norm = Normalize(vmin=cMin, vmax=cMax)
    if 'ax' is None:
        fig, ax = plt.subplots()

    iy, ix = np.nonzero(A)  # != 0)
    recs = []
    vals = []
    for i in range(len(ix)):
        recs.append(Rectangle((ix[i]-dx/2, iy[i]-0.5), dx, 1))
        vals.append(A[iy[i], ix[i]])

    pp = PatchCollection(recs)
    col = ax.add_collection(pp)
    pp.set_edgecolor(None)
    pp.set_linewidths(0.0)
    if 'cmap' in kwargs:
        pp.set_cmap(kwargs.pop('cmap'))
    pp.set_norm(norm)
    pp.set_array(np.array(vals))
    pp.set_clim(cMin, cMax)
    xval = [k for k in xmap.keys()]
    ax.set_xlim(min(xval)-dx/2, max(xval)+dx/2)
    ax.set_ylim(len(ymap)+0.5, -0.5)

    updateAxes_(ax)
    cbar = None
    if kwargs.pop('colorBar', True):
        cbar = pg.mplviewer.createColorbar(col, cMin=cMin, cMax=cMax, nLevs=5,
                                           label=label)
    return ax, cbar

# 需要导入模块: from matplotlib.collections import PatchCollection [as 别名]
# 或者: from matplotlib.collections.PatchCollection import set_norm [as 别名]

#.........这里部分代码省略.........
    else:
        norm = Normalize(vmin=cMin, vmax=cMax)

    if ax is None:
        ax = plt.subplots()[1]

    recs = []

    circular = kwargs.pop('circular', False)
    if circular:
        recs = [None] * len(xvec)
        if dy is None:  # map y values to unique
            ymap = {xy: ii for ii, xy in enumerate(np.unique(yvec))}

            xyMap = {}
            for i, y in enumerate(yvec):
                if y not in xyMap:
                    xyMap[y] = []
                xyMap[y].append(i)

            # maxR = max(ymap.values())  # what's that for? not used
            dR = 1 / (len(ymap.values())+1)
            # dOff = np.pi / 2  # what's that for? not used

            for y, xIds in xyMap.items():
                r = 1. - dR*(ymap[y]+1)
                # ax.plot(r * np.cos(xvec[xIds]),
                #         r * np.sin(xvec[xIds]), 'o')

                # print(y, ymap[y])
                for i in xIds:
                    phi = xvec[i]
                    # x = r * np.cos(phi)  # what's that for? not used
                    y = r * np.sin(phi)

                    dPhi = (xvec[1] - xvec[0])

                    recs[i] = Wedge((0., 0.), r + dR/1.5,
                                    (phi - dPhi)*360/(2*np.pi),
                                    (phi + dPhi)*360/(2*np.pi),
                                    width=dR,
                                    zorder=1+r)
                    # if i < 5:
                    #     ax.text(x, y, str(i))
                    # pg.wait()
        else:
            raise("Implementme")
    else:
        if dy is None:  # map y values to unique
            ymap = {xy: ii for ii, xy in enumerate(np.unique(yvec))}
            for i in range(len(vals)):
                recs.append(Rectangle((xvec[i] - dx / 2, ymap[yvec[i]] - 0.5),
                                      dx, 1))
        else:
            for i in range(len(vals)):
                recs.append(Rectangle((xvec[i] - dx / 2, yvec[i] - dy / 2),
                                      dx, dy))
        ax.set_xlim(min(xvec) - dx / 2, max(xvec) + dx / 2)
        ax.set_ylim(len(ymap) - 0.5, -0.5)

    pp = PatchCollection(recs)
    # ax.clear()
    col = ax.add_collection(pp)
    pp.set_edgecolor(None)
    pp.set_linewidths(0.0)

    if circular:
        pp.set_edgecolor('black')
        pp.set_linewidths(0.1)

    cmap = pg.mplviewer.cmapFromName(**kwargs)
    if kwargs.pop('markOutside', False):
        cmap.set_bad('grey')
        cmap.set_under('darkgrey')
        cmap.set_over('lightgrey')
        cmap.set_bad('black')
    pp.set_cmap(cmap)

    pp.set_norm(norm)
    pp.set_array(vals)
    pp.set_clim(cMin, cMax)

    updateAxes_(ax)
    cbar = kwargs.pop('colorBar', True)
    ori = kwargs.pop('orientation', 'horizontal')
    if cbar in ['horizontal', 'vertical']:
        ori = cbar
        cbar = True

    if cbar is True:  # not for cbar=1, which is really confusing!
        cbar = pg.mplviewer.createColorBar(col, cMin=cMin, cMax=cMax,
                                           nLevs=5, label=label,
                                           orientation=ori)
    elif cbar is not False:
        # .. cbar is an already existing cbar .. so we update its values
        pg.mplviewer.updateColorBar(cbar, cMin=cMin, cMax=cMax,
                                    nLevs=5, label=label)

    updateAxes_(ax)
    return ax, cbar, ymap