def add_pmts(ax=None, color='b', linewidth=1):
x0 = 27 # 9 times the inner radius
y0 = 6 * 3 * 2 / np.sqrt(3) # 6 times the outer radius
if ax is None:
ax = plt.gca()
per_row = [9, 10, 11, 10, 11, 10, 11, 10, 9]
polys = []
for row, num_pmts in enumerate(per_row):
y = row * 3 * np.sqrt(3)
for pmt in range(num_pmts):
x = 6 * pmt
if row in (0, 8):
x += 3
elif row % 2 == 0:
x -= 3
polys.append(RegularPolygon((x - x0, y - y0), 6, radius=6 / np.sqrt(3)))
col = PatchCollection(polys)
col.set_facecolors('none')
col.set_edgecolors(color)
col.set_linewidths(linewidth)
ax.add_artist(col)
return col
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
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
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
----------
vals : iterable
Data values to show.
xvec : dict {i:num}
dict (must match vals.shape[0])
ymap : iterable
vector for x axis (must match vals.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(vals)>0]
label : string
colorbar label
** kwargs:
* circular : bool
Plot in polar coordinates.
"""
if cMin is None:
cMin = np.min(vals)
if cMax is None:
cMax = np.max(vals)
if logScale is None:
logScale = (cMin > 0.0)
norm = None
if logScale and cMin > 0:
norm = LogNorm(vmin=cMin, vmax=cMax)
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
def patchMatrix(mat,
xmap=None,
ymap=None,
ax=None,
cMin=None,
cMax=None,
logScale=None,
label=None,
dx=1,
**kwargs):
"""Plot previously generated (generateVecMatrix) matrix.
Parameters
----------
mat : 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
dx : float
width of the matrix elements (by default 1)
"""
mat = np.ma.masked_where(mat == 0.0, mat, 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:
ax = plt.subplots()[1]
iy, ix = np.nonzero(mat) # != 0)
recs = []
vals = []
for i, _ in enumerate(ix):
recs.append(Rectangle((ix[i] - dx / 2, iy[i] - 0.5), dx, 1))
vals.append(mat[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'))
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):
ori = kwargs.pop('orientation', 'horizontal')
cbar = pg.mplviewer.createColorBar(col,
cMin=cMin,
cMax=cMax,
nLevs=5,
label=label,
orientation=ori)
return ax, cbar
def showStitchedModels_Redundant(mods,
ax=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 ax is None:
fig, ax = plt.subplots()
else:
ax = ax
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 enumerate(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 = colors.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 ax is None: # newly created fig+ax
return fig, ax
else: # already given, better give back color bar
return cbar
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
----------
vals : iterable
to show
xvec : dict {i:num}
dict (must match vals.shape[0])
ymap : iterable
vector for x axis (must match vals.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(vals)>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)
norm = None
if logScale and cMin > 0:
norm = LogNorm(vmin=cMin, vmax=cMax)
else:
norm = Normalize(vmin=cMin, vmax=cMax)
if 'ax' is None:
ax = plt.subplots()[1]
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)
# ax.clear()
col = ax.add_collection(pp)
pp.set_edgecolor(None)
pp.set_linewidths(0.0)
cmap = pg.mplviewer.cmapFromName(**kwargs)
cmap.set_bad('grey')
if kwargs.pop('markOutside', True):
cmap.set_under('darkgrey')
cmap.set_bad('lightgrey')
pp.set_cmap(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 = kwargs.pop('colorBar', 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)
elif cbar is not False: # what the hell is this?
pg.mplviewer.updateColorBar(cbar, cMin=cMin, cMax=cMax,
nLevs=5, label=label)
return ax, cbar, ymap
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
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
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
def drawValMapPatches(ax, vals, xVec=None, yVec=None, dx=1, dy=None, **kwargs):
"""Show values as patches over x and y vector.
Parameters
----------
vals : iterable
values to plot
xVec/yVec : iterable
x/y axis values
dx/dy : float
patch width
circular : bool
assume circular (cyclic) positions
"""
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)
pp.set_edgecolor(None)
pp.set_linewidths(0.0)
pp.set_array(vals)
gci = ax.add_collection(pp)
if circular:
pp.set_edgecolor('black')
pp.set_linewidths(0.1)
return gci, ymap
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
----------
vals : iterable
Data values to show.
xvec : dict {i:num}
dict (must match vals.shape[0])
ymap : iterable
vector for x axis (must match vals.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(vals)>0]
label : string
colorbar label
** kwargs:
* circular : bool
Plot in polar coordinates.
"""
if cMin is None:
cMin = np.min(vals)
if cMax is None:
cMax = np.max(vals)
if logScale is None:
logScale = (cMin > 0.0)
norm = None
if logScale and cMin > 0:
norm = LogNorm(vmin=cMin, vmax=cMax)
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
def make_piechart(slices, colors, ecolors, outname, showtext=True, groups=[[0,1],[2,3]], radfraction=0.2, transparent=False):
assert len(groups) == 2
plt.close('all')
fig, ax = plt.subplots(figsize=(5,5))
wedgeprops = {'edgecolor':'k', 'linewidth':6}
patches, texts, pcts = ax.pie(slices, labeldistance=1.15, colors=colors, autopct=lambda p: '{:1.1f}\%'.format(p), wedgeprops=wedgeprops)
[pct.set_fontsize(20) for pct in pcts]
ax.axis('equal')
for patch, ecolor in zip(patches, ecolors):
patch.set_edgecolor(ecolor)
fig.savefig('{}'.format(outname), transparent=True)
plt.close('all')
fig, ax = plt.subplots(figsize=(5,5))
ax.axis('equal')
ax.axis('off')
#embed()
i = groups[0]
ang = np.deg2rad((patches[i[-1]].theta2 + patches[i[0]].theta1)/2.0)
wedges = []
for j in i:
patch = patches[j]
center = (radfraction*patch.r*np.cos(ang), radfraction*patch.r*np.sin(ang))
wedges.append(mpatches.Wedge(center, patch.r, patch.theta1, patch.theta2, edgecolor=patch.get_edgecolor(), facecolor=patch.get_facecolor()))
text_ang = np.deg2rad((patch.theta1 + patch.theta2)/2.0)
pct = pcts[j].get_text()
if slices[j] == 0:
pct = ''
fontsize = 10
elif slices[j] < 0.01:
fontsize = 10
elif slices[j] < 0.1:
fontsize = 15
else:
fontsize = 20
if text_ang > np.pi and text_ang < (3*np.pi)/2.0:
align='top'
text_pos = np.array(((1.12)*patch.r*np.cos(text_ang), (1.12)*patch.r*np.sin(text_ang))) + np.array(center)
else:
align='baseline'
text_pos = np.array(((1.08)*patch.r*np.cos(text_ang), (1.08)*patch.r*np.sin(text_ang))) + np.array(center)
if showtext:
ax.text(*text_pos, s=pct, fontsize=fontsize, verticalalignment=align)
i = groups[1]
for j in i:
try:
patch = patches[j]
except:
embed()
center = patch.center
wedges.append(mpatches.Wedge(center, patch.r, patch.theta1, patch.theta2, edgecolor=patch.get_edgecolor(), facecolor=patch.get_facecolor()))
text_ang = np.deg2rad((patch.theta1 + patch.theta2)/2.0)
pct = pcts[j].get_text()
if slices[j] == 0:
pct = ''
fontsize = 10
elif slices[j] < 0.01:
fontsize = 10
elif slices[j] < 0.1:
fontsize = 15
else:
fontsize = 20
if text_ang > np.pi and text_ang < (3*np.pi)/2.0:
align='top'
text_pos = np.array(((1.12)*patch.r*np.cos(text_ang), (1.12)*patch.r*np.sin(text_ang))) + np.array(center)
else:
align='baseline'
text_pos = np.array(((1.08)*patch.r*np.cos(text_ang), (1.08)*patch.r*np.sin(text_ang))) + np.array(center)
if showtext:
ax.text(*text_pos, s=pct, fontsize=fontsize, verticalalignment=align)
collection = PatchCollection(wedges)
collection.set_facecolors(colors)
collection.set_linewidths(6)
collection.set_edgecolors(ecolors)
#collection.set_array(np.array(colors))
ax.add_collection(collection)
ax.autoscale(True)
#ax.text(*pcts[0].get_position(), s=pcts[0].get_text())
fig.savefig('{}_nolabel'.format(outname), transparent=transparent)
plt.close('all')