def ply_fig(ts, points=False, color='jet', **kwds):
""" Convert a timespectra to plotly Figure. Figures can be then directly
plotted with plotly.iplot(figure) in the notebook. Use the layout keyword
to specify layout parameters; all other keywords are interpreted as line style
keywords (color
Parameters
----------
points: bool
If true, scatter plot; else, lineplots
color: str
Any valid matplotlib color or colormap.
layout: dict
Dictionary of keywords that go into layout.
"""
data = grobs.Data()
layoutkwds = kwds.pop('layout', {})
lout = layout(ts, **layoutkwds)
# List of colors, either single color or color map
try:
cmapper = put.cmget(color) #Validate color map
except AttributeError:
cmapper = [color for i in range(len(ts.columns))]
else:
cmapper = put._df_colormapper(ts, color, axis=0)
# Map colors to rgb
cmapper = map(put.to_normrgb, cmapper)
# Scale by 255 and string format for plotly
def _rgbplotlycolor(rgb):
r,g,b = rgb
return 'rgb(%s, %s, %s)' % (255.0*r, 255.0*g, 255.0*b)
cmapper = map(_rgbplotlycolor, cmapper)
if points:
tracefcn = make_pointtrace
else:
tracefcn = make_linetrace
for idx, clabel in enumerate(ts):
trace = tracefcn(
x = np.array(ts.index), # Not necessary to force to np.array.dtype(float)
y = np.array(ts[ts.columns[idx]]),
name=clabel,
color=cmapper[idx], #marker color
**kwds
)
data.append(trace)
return grobs.Figure(data=data, layout=lout)
def ply_fig(ts, points=False, color='jet', **kwds):
""" Convert a timespectra to plotly Figure. Figures can be then directly
plotted with plotly.iplot(figure) in the notebook. Use the layout keyword
to specify layout parameters; all other keywords are interpreted as line style
keywords (color
Parameters
----------
points: bool
If true, scatter plot; else, lineplots
color: str
Any valid matplotlib color or colormap.
layout: dict
Dictionary of keywords that go into layout.
"""
data = grobs.Data()
layoutkwds = kwds.pop('layout', {})
lout = layout(ts, **layoutkwds)
# List of colors, either single color or color map
try:
cmapper = put.cmget(color) #Validate color map
except AttributeError:
cmapper = [color for i in range(len(ts.columns))]
else:
cmapper = put._df_colormapper(ts, color, axis=0)
# Map colors to rgb
cmapper = map(put.to_normrgb, cmapper)
# Scale by 255 and string format for plotly
def _rgbplotlycolor(rgb):
r, g, b = rgb
return 'rgb(%s, %s, %s)' % (255.0 * r, 255.0 * g, 255.0 * b)
cmapper = map(_rgbplotlycolor, cmapper)
if points:
tracefcn = make_pointtrace
else:
tracefcn = make_linetrace
for idx, clabel in enumerate(ts):
trace = tracefcn(
x=np.array(
ts.index), # Not necessary to force to np.array.dtype(float)
y=np.array(ts[ts.columns[idx]]),
name=clabel,
color=cmapper[idx], #marker color
**kwds)
data.append(trace)
return grobs.Figure(data=data, layout=lout)
def spec3d(ts, projection=True, samples=5, **pltkwargs):
""" Wireframe plot with no connected clines. By default, adds an xz
projection.
Parameters
----------
projection : color/colormap
Valid colormap or solid color of contour projection.
samples : int
Number of samples to take from dataset. Defaults to 5. Must
be within 0 and the number of columns in Spectra.
Returns
-------
tuple: (Axes, SurfaceFunction)
Returns axes object and the surface function (e.g. contours for
contour plot. Surface for surface plot.)
Notes
-----
Mostly a shortcut for a very useful 3d look at data. Thus, did not add
much customizability as this plot can be assembled from _gen2d3d2d and
add_projeciton.
"""
for invalid in ['c_iso', 'r_iso', 'cstride', 'rstride']:
if invalid in pltkwargs:
raise PlotError('Unsupported Keyword %s.'
'Please use the samples argument' % invalid)
pltkwargs['kind'] = 'wire'
pltkwargs['r_iso'] = 0
pltkwargs['c_iso'] = samples
ax, mappable = _gen2d3d(ts, **pltkwargs)
if projection:
if projection == True:
projection = 'jet'
contourkwds = {}
# Parse colormap vs. color for projection
try:
contourkwds['cmap'] = pu.cmget(projection)
contourkwds['alpha'] = 0.3 #
except AttributeError:
contourkwds['colors'] = projection
ax = add_projection(ts, ax=ax, fill=True, **contourkwds)
return ax, mappable
def spec3d(ts, projection=True, samples=5, **pltkwargs):
""" Wireframe plot with no connected clines. By default, adds an xz
projection.
Parameters
----------
projection : color/colormap
Valid colormap or solid color of contour projection.
samples : int
Number of samples to take from dataset. Defaults to 5. Must
be within 0 and the number of columns in Spectra.
Returns
-------
tuple: (Axes, SurfaceFunction)
Returns axes object and the surface function (e.g. contours for
contour plot. Surface for surface plot.)
Notes
-----
Mostly a shortcut for a very useful 3d look at data. Thus, did not add
much customizability as this plot can be assembled from _gen2d3d2d and
add_projeciton.
"""
for invalid in ['c_iso', 'r_iso', 'cstride', 'rstride']:
if invalid in pltkwargs:
raise PlotError('Unsupported Keyword %s.'
'Please use the samples argument' % invalid)
pltkwargs['kind'] = 'wire'
pltkwargs['r_iso'] = 0
pltkwargs['c_iso'] = samples
ax, mappable = _gen2d3d(ts, **pltkwargs)
if projection:
if projection == True:
projection = 'jet'
contourkwds = {}
# Parse colormap vs. color for projection
try:
contourkwds['cmap'] = pu.cmget(projection)
contourkwds['alpha'] = 0.3 #
except AttributeError:
contourkwds['colors'] = projection
ax = add_projection(ts, ax=ax, fill=True, **contourkwds)
return ax, mappable
def _gen2d(xx, yy, zz, contours=6, label=None, colorbar=None,
background=None, **pltkwargs):
""" Abstract layout for 2d plot.
For convienence, a few special labels, colorbar and background keywords
have been implemented. If these are not adequate, it one can add
custom colorbars, linelabels background images etc... easily just by
using respecitve calls to plot (plt.colorbar(), plt.imshow(),
plt.clabel() ); my implementations are only for convienences and
some predefined, cool styles.
countours: Number of desired contours from output.
label: Predefined label types. For now, only integer values 1,2. Use plt.clabel to add a custom label.
background: Integers 1,2 will add gray or autumn colormap under contour plot. Use plt.imgshow() to generate
custom background, or pass a PIL-opened image (note, proper image scaling not yet implemented).
fill: bool (False)
Fill between contour lines.
**pltkwargs: Will be passed directly to plt.contour().
"""
# Boilerplate from basic_plots._genplot(); could refactor as decorator
xlabel = pltkwargs.pop('xlabel', '')
ylabel = pltkwargs.pop('ylabel', '')
title = pltkwargs.pop('title', '')
grid = pltkwargs.pop('grid', '')
fill = pltkwargs.pop('fill', True)
# pltkwargs.setdefault('legend', False) #(any purpose in 2d?)
pltkwargs.setdefault('linewidth', 1)
cbar = pltkwargs.pop('cbar', False)
fig = pltkwargs.pop('fig', plt.gcf())
ax = pltkwargs.pop('ax', None)
# Overwrites fig (desireable?)
if not ax:
fig, ax = plt.subplots(1)
labelsize = pltkwargs.pop('labelsize', 'medium') #Can also be ints
titlesize = pltkwargs.pop('titlesize', 'large')
ticksize = pltkwargs.pop('ticksize', '') #Put in default and remove bool gate
### BUG, PLT.CONTOUR() doesn't take 'color'; rather, takes 'colors' for now
### This is only for solid colors. contour takes cmap argument by default.
if 'color' in pltkwargs:
pltkwargs['colors']=pltkwargs.pop('color')
### Convienence method to pass in string colors
if 'cmap' in pltkwargs and isinstance(pltkwargs['cmap'], basestring):
pltkwargs['cmap']=pu.cmget(pltkwargs['cmap'])
### I CAN MAKE THIS GENERAL TO ANY PLOT, ADDITION OF IMAGES TO A BACKGROUND MAKE IT A GENERAL ROUTINE TO ALL MY PLOTS ###
### More here http://matplotlib.org/examples/pylab_examples/image_demo3.html ###
# Refactored with xx, yy instead of df.columns/index UNTESTED
if background:
xmin, xmax, ymin, ymax = xx.min(), xx.max(), yy.min(), yy.max()
if background==1:
im = plt.imshow(zz, interpolation='bilinear', origin='lower',
cmap=cm.gray, extent=(xmin, xmax, ymin, ymax))
elif background==2:
im = plt.imshow(zz, interpolation='bilinear', origin='lower',
cmap=cm.autumn, extent=(xmin, xmax, ymin, ymax))
### This will take a custom image opened in PIL or it will take plt.imshow() returned from somewhere else
else:
try:
im = plt.imshow(background)
### Perhaps image was not correctly opened
except Exception:
raise badvalue_error(background, 'integer 1,2 or a PIL-opened image')
else:
im=None
if fill:
contours = ax.contourf(xx, yy, zz, contours, **pltkwargs) #linewidths is a pltkwargs arg
else:
contours = ax.contour(xx, yy, zz, contours, **pltkwargs)
if cbar:
fig.colorbar(contours)
### Pick a few label styles to choose from.
if label:
if label==1:
ax.clabel(inline=1, fontsize=10)
elif label==2:
ax.clabel(levels[1::2], inline=1, fontsize=10) #label every second line
else:
raise PlotError(label, 'integer of value 1 or 2')
ax.set_xlabel(xlabel, fontsize=labelsize)
ax.set_ylabel(ylabel, fontsize=labelsize)
ax.set_title(title, fontsize=titlesize)
if grid:
ax.grid()
return (ax, contours)
def plot3d(df, kind='contour', elev=0, azim=0, proj_xy=True, proj_zy=True, proj_xz=True,
contour_color=None, contour_cmap=None, c_iso=10, r_iso=10,*args, **pltkwargs):
""" Matplotlib Axes3d wrapper for dataframe. Made to handle surface plots, so pure contour plots,
polygon plots etc... these need their own classes.
parameters:
kind
contour: Based on Axes3d.contour(x,y,z,*args,**kwargs), returns a plot_surface() with
relevant spectral projections.
contourf: Filled contour plot based on Axes3D.conourf(x,y,z,*args,**kwargs). Same a contour
except contours are filled.
pltwargs can be any Axes3d keywords, with the following extra keywords being germane to this class.
xlabel, ylabel, zlabel: Axis labels. Defaults are provided here. If none are provided, the
attributes df.index.name and df.columns.name will be examined, aftwards,
defaults are used (see below).
xlim, ylim, zlim: These can be passed, but if not, the are inferred from the data. It's smarter
to manipulate the df input than to mess with these. For now, I'm keeping them
because they are relevant to proj_padding, but otherwise, probably not too essential.
proj_padding: Padding percentage if one does not want contour projections right on the wall of the grid.
This actually needs fixed. It is intended to work as in the user says... 1.1 and this means
that the projections should be 10% outside of the axes grid. 0.9 would be 10% in.
The operation to computes the new limit is actually not correct, and if a minimum axis
value is 0, it won't move it beyond.
If this ever becomes useful again, I think it would be wise to first set the x,y,z lims
on the plot, then after that, compute the paddings and set the offset to these values.
Something like
ax.set(xlim)
newxlim=xlim*padding correction
contour(offset=newxlim)
A note on strides: Strides are step sizes. Say you have 100 curves, then a stride of 5 would give you 20
isolines over your surface. As such, a smart keyword (c_iso and r_iso) will make sure
that a fixed number of contours are drawn when the user passes in a dataframe.
c_iso, r_iso: See above. These control how man column and row iso lines will be projected onto the 3d plot.
For example, if c_iso=10, then 10 isolines will be plotted as columns, despite the actual length of the
columns. Alternatively, one can pass in c_stride directly, which is a column step size rather than
an absolute number, and c_iso will be disregarded.
contour_color/contour_cmap:
Either a solid color, or colormap, passed to the contour projections (proj_xy etc...).
For now, will be passed to all contour projections (xy, zy, xz).
"""
### Error raised by cfunc() is not very clear so here's an easier one
if contour_cmap and contour_color:
raise AttributeError('plot3d can have non-null values for attributes contour_cmap and contour_color, but not both.')
zlabel_def=''
zlabel=pltkwargs.pop('zlabel', zlabel_def)
xlabel = pltkwargs.pop('xlabel', '')
ylabel = pltkwargs.pop('ylabel', '')
title = pltkwargs.pop('title', '')
### If plane (xy) is input backwards (yx), still works
proj_xy=pltkwargs.pop('proj_yx', proj_xy)
proj_zy=pltkwargs.pop('proj_yz', proj_zy)
proj_xz=pltkwargs.pop('proj_zx', proj_xz)
### Make mesh grid based on dataframe indicies ###
fig = plt.figure()
ax = fig.gca(projection='3d')
xx,yy=np.meshgrid(df.columns, df.index)
### Set axis limits explicitly from padding and data.
### PLOT PADDING NEEDS FIXED AS OF NOW IT IS NOT CORRECT. FOR EXAMPLE, IF MIN IS 0, NEED AN OPERATION
### THAT WILL STILL REDUCE IT TO LESS THAN ZERO. ONLY WORTH FIGURING OUT IF NEED PROJECTIONS OUTSIDE OF THE GRID.
### ALSO BUGS IF THE AXIS VALUES AREN'T NUMBERS. FOR EXAMPLE, IF THEY ARE NAMED COLUMNS. FIX WITH TRY EXCEPT
proj_padding=pltkwargs.pop('projpad', 0.0)
xlim=pltkwargs.pop('xlim', (min(df.columns)*(1.0-proj_padding), max(df.columns)*(1.0+proj_padding)) )
ylim=pltkwargs.pop('ylim', (min(df.index)*(1.0-proj_padding), max(df.index)*(1.0+proj_padding)) )
### Min/max of total data (only works if the data is 2d)
zlim=pltkwargs.pop('zlim', ((1.0-proj_padding)*(df.min()).min(), (1.0+proj_padding)*(df.max().max())) )
cstride= _ir( len(df.columns)/float(c_iso) )
rstride= _ir( len(df.index)/float(r_iso) )
### This occurs if the
if cstride==0:
print "Warning, dataset is too small to accomodate c_iso of %i, setting to 1."%c_iso
cstride=1
if rstride==0:
print "Warning, dataset is too small to accomodate r_iso of %i, setting to 1."%r_iso
rstride=1 #to prevent errors
### If these values are already passed in, they won't be overwritten. Cmap here is for surface, not countour
_surface_defaults={'alpha':0.2, 'rstride':rstride, 'cstride':cstride, 'cmap':pu.cmget('autumn')} #Don't have any special
_surface_defaults.update(pltkwargs)
pltkwargs=_surface_defaults #Need to do this in two steps or it errors
ax.plot_surface(xx,yy,df, *args, **pltkwargs)
if kind=='contourf' or kind=='contour':
if kind=='contourf':
cfunc=ax.contourf
else:
cfunc=ax.contour
if proj_xy:
cset = cfunc(xx, yy, df, zdir='z', colors=contour_color, cmap=contour_cmap, offset=zlim[0]) #project z onto xy (zmid to bottom)
if proj_zy:
cset = cfunc(xx, yy, df, zdir='x',colors=contour_color, cmap=contour_cmap, offset=xlim[0]) #project x onto zy (timestart) (negative half time interval)
if proj_xz:
cset = cfunc(xx, yy, df, zdir='y',colors=contour_color, cmap=contour_cmap, offset=ylim[1]) #project y onto xz (ymid to 0) (negative mid wavelength)
else:
raise badvalue_error(kind, 'contour, contourf')
ax.set_xlabel(xlabel) #x
ax.set_ylabel(ylabel) #Y
ax.set_zlabel(zlabel) #data
ax.set_title(title)
ax.view_init(elev, azim)
return ax
def plot2d(df, contours=6, label=None, colorbar=None, background=None, **pltkwds):
''' Wrapper for plt.contour that uses np.meshgrid to generate curves. For convienence, a few special labels, colorbar and background
keywords have been implemented. If these are not adequate, it one can add custom colorbars, linelabels background images etc... easily
just by using respecitve calls to plot (plt.colorbar(), plt.imshow(), plt.clabel() ); my implementations are only for convienences and
some predefined, cool styles.
df: Dataframe.
countours: Number of desired contours from output.
label: Predefined label types. For now, only integer values 1,2. Use plt.clabel to add a custom label.
background: Integers 1,2 will add gray or autumn colormap under contour plot. Use plt.imgshow() to generate
custom background, or pass a PIL-opened image (note, proper image scaling not yet implemented).
**pltkwds: Will be passed directly to plt.contour().'''
xlabel, ylabel, title, pltkwds=pu.smart_label(df, pltkwds)
### BUG, PLT.CONTOUR() doesn't take 'color'; rather, takes 'colors' for now
### This is only for solid colors. contour takes cmap argument by default.
if 'color' in pltkwds:
pltkwds['colors']=pltkwds.pop('color')
### Convienence method to pass in string colors
if 'cmap' in pltkwds and isinstance(pltkwds['cmap'], basestring):
pltkwds['cmap']=pu.cmget(pltkwds['cmap'])
### I CAN MAKE THIS GENERAL TO ANY PLOT, ADDITION OF IMAGES TO A BACKGROUND MAKE IT A GENERAL ROUTINE TO ALL MY PLOTS ###
### More here http://matplotlib.org/examples/pylab_examples/image_demo3.html ###
if background:
xmin, xmax, ymin, ymax=min(df.columns), max(df.columns), min(df.index), max(df.index)
if background==1:
im = plt.imshow(df, interpolation='bilinear', origin='lower',
cmap=cm.gray, extent=(xmin, xmax, ymin, ymax))
elif background==2:
im = plt.imshow(df, interpolation='bilinear', origin='lower',
cmap=cm.autumn, extent=(xmin, xmax, ymin, ymax))
### This will take a custom image opened in PIL or it will take plt.imshow() returned from somewhere else
else:
try:
im = plt.imshow(background)
### Perhaps image was not correctly opened
except Exception:
raise badvalue_error(background, 'integer 1,2 or a PIL-opened image')
else:
im=None
xx,yy = np.meshgrid(df.columns, df.index)
ax = plt.contour(xx, yy, df, contours, **pltkwds) #linewidths is a pltkwds arg
### Pick a few label styles to choose from.
if label:
if label==1:
ax.clabel(inline=1, fontsize=10)
elif label==2:
ax.clabel(levels[1::2], inline=1, fontsize=10) #label every second line
else:
raise badvalue_error(label, 'integer of value 1 or 2')
### Add colorbar, for some reason need to do plt.colorbar() even though can do ax.clabel...
if colorbar:
if colorbar==1: ### WHAT OTHER COLORBAR OPTIONS ARETHERE
CB=plt.colorbar(ax, shrink=0.8) #shringk is heigh of colorbar relative ot height of plot
if im:
IMCB=plt.colorbar(im, orientation='horizontal', shrink=0.8)
### Move original colorbar to more natural to make room for image colorbar
l,b,w,h = plt.gca().get_position().bounds
ll,bb,ww,hh = CB.ax.get_position().bounds
CB.ax.set_position([ll, b+0.1*h, ww, h*0.8])
else:
raise badvalue_error(colorbar, 'integer of value 1 is only supported for now')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title)
return ax
def _gen2d3d(*args, **pltkwargs):
# UPDATE
""" Abstract layout for 2d plot.
For convienence, a few special labels, colorbar and background keywords
have been implemented. If these are not adequate, it one can add
custom colorbars, linelabels background images etc... easily just by
using respecitve calls to plot (plt.colorbar(), plt.imshow(),
plt.clabel() ); my implementations are only for convienences and
some predefined, cool styles.
countours: Number of desired contours from output.
label: Predefined label types. For now, only integer values 1,2. Use plt.clabel to add a custom label.
background: Integers 1,2 will add gray or autumn colormap under contour plot. Use plt.imgshow() to generate
custom background, or pass a PIL-opened image (note, proper image scaling not yet implemented).
c_mesh, r_mesh: These control how man column and row iso lines will be projected onto the 3d plot.
For example, if c_mesh=10, then 10 isolines will be plotted as columns, despite the actual length of the
columns. Alternatively, one can pass in c_stride directly, which is a column step size rather than
an absolute number, and c_mesh will be disregarded.
fill: bool (False)
Fill between contour lines.
**pltkwargs: Will be passed directly to plt.contour().
Returns
-------
tuple: (Axes, SurfaceFunction)
Returns axes object and the surface function (e.g. contours for
contour plot. Surface for surface plot.
"""
# Use a label mapper to allow for datetimes in any plot x/y axis
_x_dti = _ = _y_dti = False
# Passed Spectra
if len(args) == 1:
ts = args[0]
try:
index = np.array([dates.date2num(x) for x in ts.index])
_x_dti = True
except AttributeError:
index = ts.index.values #VALUES NECESSARY FOR POLY CMAP
try:
cols = np.array([dates.date2num(x) for x in ts.columns])
_y_dti = True
except AttributeError:
cols = ts.columns.values #VALUES NECESSARY FOR POLY CMAP
yy, xx = np.meshgrid(cols, index)
# Passed xx, yy, ts/zz
elif len(args) == 3:
xx, yy, ts = args
cols, index = ts.columns.values, ts.index.values
else:
raise PlotError(
"Please pass a single spectra, or xx, yy, zz. Got %s args" %
len(args))
# Boilerplate from basic_plots._genplot(); could refactor as decorator
xlabel = pltkwargs.pop('xlabel', '')
ylabel = pltkwargs.pop('ylabel', '')
zlabel = pltkwargs.pop('zlabel', '')
title = pltkwargs.pop('title', '')
labelsize = pltkwargs.pop('labelsize',
pvconfig.LABELSIZE) #Can also be ints
titlesize = pltkwargs.pop('titlesize', pvconfig.TITLESIZE)
# Choose plot kind
kind = pltkwargs.pop('kind', 'contour')
grid = pltkwargs.pop('grid', True)
# pltkwargs.setdefault('legend', False) #(any purpose in 2d?)
# LEGEND FOR 2D PLOT: http://stackoverflow.com/questions/10490302/how-do-you-create-a-legend-for-a-contour-plot-in-matplotlib
pltkwargs.setdefault('linewidth', 1)
cbar = pltkwargs.pop('cbar', False)
outline = pltkwargs.pop('outline', None)
if outline:
if kind != 'surf' and kind != 'waterfall':
raise PlotError(
'"outline" is only valid for "surf" and "waterfall"'
' plots. Please use color/cmap for all other color'
' designations.')
fig = pltkwargs.pop('fig', None)
ax = pltkwargs.pop('ax', None)
fill = pltkwargs.pop('fill', pvconfig.FILL_CONTOUR)
xlim = pltkwargs.pop('xlim', None)
ylim = pltkwargs.pop('ylim', None)
zlim = pltkwargs.pop('zlim', None)
#Private attributes
_modifyax = pltkwargs.pop('_modifyax', True)
contours = pltkwargs.pop('contours', pvconfig.NUM_CONTOURS)
label = pltkwargs.pop('label', None)
projection = None
if kind in PLOTPARSER.plots_3d:
projection = '3d'
elev = pltkwargs.pop('elev', 35)
azim = pltkwargs.pop('azim', -135)
view = pltkwargs.pop('view', None)
if view:
if view == 1:
elev, azim = 35, -135
elif view == 2:
elev, azim = 35, -45
elif view == 3:
elev, azim = 20, -10 # Side view
elif view == 4:
elev, azim = 20, -170
elif view == 5:
elev, azim = 0, -90
elif view == 6:
elev, azim = 65, -90
else:
raise PlotError('View must be between 1 and 6; otherwise set'
' "elev" and "azim" keywords.')
# Orientation of zlabel (doesn't work...)
_zlabel_rotation = 0.0
if azim < 0:
_zlabel_rotation = 90.0
if 'mesh' in pltkwargs:
pltkwargs['c_mesh'] = pltkwargs['r_mesh'] = pltkwargs.pop('mesh')
# Defaults will be ignored if mesh or ciso in kwargs
ciso_default = pvconfig.C_MESH
if len(ts.columns) < ciso_default:
ciso_default = len(ts.columns)
riso_default = pvconfig.R_MESH
if len(ts.index) < riso_default:
riso_default = len(ts.index)
c_mesh = pltkwargs.pop('c_mesh', ciso_default)
r_mesh = pltkwargs.pop('r_mesh', riso_default)
if c_mesh > ts.shape[1] or c_mesh < 0:
raise PlotError(
'"c_mesh/column mesh" must be between 0 and %s, got "%s"' %
(ts.shape[1], c_mesh))
if r_mesh > ts.shape[0] or r_mesh < 0:
raise PlotError(
'"r_mesh/row mesh" must be between 0 and %s, got "%s"' %
(ts.shape[0], r_mesh))
if c_mesh == 0:
cstride = 0
else:
cstride = _ir(ts.shape[1] / float(c_mesh))
if r_mesh == 0:
rstride = 0
else:
rstride = _ir(ts.shape[0] / float(r_mesh))
pltkwargs.setdefault('cstride', cstride)
pltkwargs.setdefault('rstride', rstride)
elif kind == 'contour':
pass
else:
raise PlotError('_gen2d3d invalid kind: "%s". '
'Choose from %s' % (kind, PLOTPARSER.plots_2d_3d))
# Is this the best logic for 2d/3d fig?
if not ax:
f = plt.figure()
# ax = f.gca(projection=projection)
ax = f.add_subplot(111, projection=projection)
if not fig:
fig = f
# PLT.CONTOUR() doesn't take 'color'; rather, takes 'colors' for now
if 'color' in pltkwargs:
if kind == 'contour' or kind == 'contour3d':
pltkwargs['colors'] = pltkwargs.pop('color')
# Convienence method to pass in string colors
if 'colormap' in pltkwargs:
pltkwargs['cmap'] = pltkwargs.pop('colormap')
if 'cmap' in pltkwargs:
if isinstance(pltkwargs['cmap'], basestring):
pltkwargs['cmap'] = pu.cmget(pltkwargs['cmap'])
# Contour Plots
# -------------
# Broken background image
### More here http://matplotlib.org/examples/pylab_examples/image_demo3.html ###
# Refactored with xx, yy instead of df.columns/index UNTESTED
#if background:
#xmin, xmax, ymin, ymax = xx.min(), xx.max(), yy.min(), yy.max()
## Could try rescaling contour rather than image:
##http://stackoverflow.com/questions/10850882/pyqt-matplotlib-plot-contour-data-on-top-of-picture-scaling-issue
#if background==1:
#im = ax.imshow(ts, interpolation='bilinear', origin='lower',
#cmap=cm.gray, extent=(xmin, xmax, ymin, ymax))
#### This will take a custom image opened in PIL or it will take plt.imshow() returned from somewhere else
#else:
#try:
#im = ax.imshow(background)
#### Perhaps image was not correctly opened
#except Exception:
#raise badvalue_error(background, 'integer 1,2 or a PIL-opened image')
# Note this overwrites the 'contours' variable from an int to array
if kind == 'contour' or kind == 'contour3d':
# Cornercase datetimeindex and offest from add projection hack
try:
pltkwargs['offset'] = dates.date2num(pltkwargs['offset'])
except Exception:
pass
if fill: #Values of DTI doesn't work
mappable = ax.contourf(xx, yy, ts.values, contours,
**pltkwargs) #linewidths is a pltkwargs arg
else:
mappable = ax.contour(xx, yy, ts.values, contours, **pltkwargs)
### Pick a few label styles to choose from.
if label:
if label == 1:
ax.clabel(inline=1, fontsize=10)
elif label == 2:
ax.clabel(levels[1::2], inline=1,
fontsize=10) #label every second line
else:
raise PlotError(label, 'integer of value 1 or 2')
elif kind == 'surf':
mappable = ax.plot_surface(xx, yy, ts, **pltkwargs)
if outline:
try:
pltkwargs['cmap'] = pu.cmget(outline)
except Exception: #Don't change; attribute error fails when outline=None
pltkwargs['color'] = outline
pltkwargs.pop('cmap')
custom_wireframe(ax, xx, yy, ts, **pltkwargs)
# Wires are thrown out, since mappable is the surface, and only mappable returned
elif kind == 'wire':
pltkwargs.setdefault('color', 'black')
mappable = custom_wireframe(ax, xx, yy, ts, **pltkwargs)
elif kind == 'waterfall':
# Parse outline color (if colormap, error!)
try:
pu.cmget(outline)
except Exception:
pltkwargs['edgecolors'] = outline
else:
raise PlotError(
'Waterfall "outline" must be a solid color, not colormap.')
pltkwargs.setdefault('closed', False)
alpha = pltkwargs.setdefault('alpha', None)
# Need to handle cmap/colors a bit differently for PolyCollection API
if 'color' in pltkwargs:
pltkwargs['facecolors'] = pltkwargs.pop('color')
cmap = pltkwargs.setdefault('cmap', None)
if alpha is None: #as opposed to 0
alpha = 0.6 * (13.0 / ts.shape[1])
if alpha > 0.6:
alpha = 0.6
#Delete stride keywords (waterfall doesn't have strides: not a surface!)
for key in ['cstride', 'rstride']:
try:
del pltkwargs[key]
except KeyError:
pass
# Verts are index dotted with data
verts = []
for col in ts.columns:
values = ts[col]
values[0], values[-1] = values.min().min(), values.min().min()
verts.append(list(zip(ts.index, values)))
mappable = PolyCollection(verts, **pltkwargs)
if cmap:
mappable.set_array(
cols) #If set array in __init__, autogens a cmap!
mappable.set_cmap(pltkwargs['cmap'])
mappable.set_alpha(alpha)
#zdir is the direction used to plot; dont' fully understand
ax.add_collection3d(mappable, zs=cols, zdir='x')
# custom limits/labels polygon plot (reverse x,y)
if not ylim:
ylim = (max(index), min(index)) #REVERSE AXIS FOR VIEWING PURPOSES
if not xlim:
xlim = (min(cols), max(cols)) #x
if not zlim:
zlim = (min(ts.min()), max(ts.max())
) #How to get absolute min/max of ts values
# Reverse labels/DTI call for correct orientaion HACK HACK HACK
xlabel, ylabel = ylabel, xlabel
_x_dti, _y_dti = _y_dti, _x_dti
azim = -1 * azim
# General Features
# ----------------
# Some applications (like add_projection) shouldn't alther axes features
if not _modifyax:
return (ax, mappable)
if cbar:
# Do I want colorbar outside of fig? Wouldn't be better on axes?
try:
cb = fig.colorbar(mappable, ax=ax)
# Label colorbar on contour since no 3d-zlabel
if kind == 'contour':
cb.set_label(zlabel)
except Exception:
raise PlotError("Colorbar failed; did you pass a colormap?")
if grid:
if grid == True:
ax.grid()
else:
ax.grid(color=grid) #Let's any supported color in
# Format datetime axis
# -------------------
if _x_dti:
ax.xaxis.set_major_formatter(mplticker.FuncFormatter(format_date))
# Uncomment for custom 3d timestamp orientation
# if projection:
# for t1 in ax.yaxis.get_ticklabels():
# t1.set_ha('right')
# t1.set_rotation(30)
# ax.yaxis._axinfo['label']['space_factor'] = _TIMESTAMPPADDING
if _y_dti:
ax.yaxis.set_major_formatter(mplticker.FuncFormatter(format_date))
# Uncomment for custom 3d timestamp orientation
# if projection:
# for t1 in ax.yaxis.get_ticklabels():
# t1.set_ha('right')
# t1.set_rotation(30)
# ax.yaxis._axinfo['label']['space_factor'] = _TIMESTAMPPADDING
if xlim:
ax.set_xlim3d(xlim)
if ylim:
ax.set_ylim3d(ylim)
if zlim:
ax.set_zlim3d(zlim)
# Set elevation/azimuth for 3d plots
if projection:
ax.view_init(elev, azim)
ax.set_zlabel(zlabel, fontsize=labelsize, rotation=_zlabel_rotation)
ax.set_xlabel(xlabel, fontsize=labelsize)
ax.set_ylabel(ylabel, fontsize=labelsize)
ax.set_title(title, fontsize=titlesize)
# Return Ax, contours/surface/polygons etc...
return (ax, mappable)
def _gen2d3d(*args, **pltkwargs):
# UPDATE
""" Abstract layout for 2d plot.
For convienence, a few special labels, colorbar and background keywords
have been implemented. If these are not adequate, it one can add
custom colorbars, linelabels background images etc... easily just by
using respecitve calls to plot (plt.colorbar(), plt.imshow(),
plt.clabel() ); my implementations are only for convienences and
some predefined, cool styles.
countours: Number of desired contours from output.
label: Predefined label types. For now, only integer values 1,2. Use plt.clabel to add a custom label.
background: Integers 1,2 will add gray or autumn colormap under contour plot. Use plt.imgshow() to generate
custom background, or pass a PIL-opened image (note, proper image scaling not yet implemented).
c_iso, r_iso: These control how man column and row iso lines will be projected onto the 3d plot.
For example, if c_iso=10, then 10 isolines will be plotted as columns, despite the actual length of the
columns. Alternatively, one can pass in c_stride directly, which is a column step size rather than
an absolute number, and c_iso will be disregarded.
fill: bool (False)
Fill between contour lines.
**pltkwargs: Will be passed directly to plt.contour().
Returns
-------
tuple: (Axes, SurfaceFunction)
Returns axes object and the surface function (e.g. contours for
contour plot. Surface for surface plot.
"""
# Use a label mapper to allow for datetimes in any plot x/y axis
_x_dti = _ = _y_dti = False
# Passed Spectra
if len(args) == 1:
ts = args[0]
try:
index = np.array([dates.date2num(x) for x in ts.index])
_x_dti = True
except AttributeError:
index = ts.index.values #VALUES NECESSARY FOR POLY CMAP
try:
cols = np.array([dates.date2num(x) for x in ts.columns])
_y_dti = True
except AttributeError:
cols = ts.columns.values #VALUES NECESSARY FOR POLY CMAP
yy, xx = np.meshgrid(cols, index)
# Passed xx, yy, ts/zz
elif len(args) == 3:
xx, yy, ts = args
cols, index = ts.columns.values, ts.index.values
else:
raise PlotError("Please pass a single spectra, or xx, yy, zz. Got %s args"
% len(args))
# Boilerplate from basic_plots._genplot(); could refactor as decorator
xlabel = pltkwargs.pop('xlabel', '')
ylabel = pltkwargs.pop('ylabel', '')
zlabel = pltkwargs.pop('zlabel', '')
title = pltkwargs.pop('title', '')
# Choose plot kind
kind = pltkwargs.pop('kind', 'contour')
grid = pltkwargs.pop('grid', '')
# pltkwargs.setdefault('legend', False) #(any purpose in 2d?)
# LEGEND FOR 2D PLOT: http://stackoverflow.com/questions/10490302/how-do-you-create-a-legend-for-a-contour-plot-in-matplotlib
pltkwargs.setdefault('linewidth', 1)
cbar = pltkwargs.pop('cbar', False)
fig = pltkwargs.pop('fig', None)
ax = pltkwargs.pop('ax', None)
fill = pltkwargs.pop('fill', False)
xlim = pltkwargs.pop('xlim', None)
ylim = pltkwargs.pop('ylim', None)
zlim = pltkwargs.pop('zlim', None)
#Private attributes
_modifyax = pltkwargs.pop('_modifyax', True)
contours = pltkwargs.pop('contours', 6)
label = pltkwargs.pop('label', None)
projection = None
if kind in PLOTPARSER.plots_3d:
projection = '3d'
elev = pltkwargs.pop('elev', 35)
azim = pltkwargs.pop('azim', -135)
view = pltkwargs.pop('view', None)
if view:
if view == 1:
elev, azim = 35, -135
elif view == 2:
elev, azim = 35, -45
elif view == 3:
elev, azim = 20, -10 # Side view
elif view == 4:
elev, azim = 20, -170
elif view == 5:
elev, azim = 0,-90
elif view == 6:
elev, azim = 65, -90
else:
raise PlotError('View must be between 1 and 6; otherwise set'
' "elev" and "azim" keywords.')
# Orientation of zlabel (doesn't work...)
_zlabel_rotation = 0.0
if azim < 0:
_zlabel_rotation = 90.0
c_iso = pltkwargs.pop('c_iso', 10)
r_iso = pltkwargs.pop('r_iso', 10)
if c_iso > ts.shape[1] or c_iso < 0:
raise PlotError('"c_iso" must be between 0 and %s, got "%s"' %
(ts.shape[1], c_iso))
if r_iso > ts.shape[0] or r_iso < 0:
raise PlotError('"r_iso" must be between 0 and %s, got "%s"' %
(ts.shape[0], r_iso))
if c_iso == 0:
cstride = 0
else:
cstride = _ir(ts.shape[1]/float(c_iso) )
if r_iso == 0:
rstride = 0
else:
rstride = _ir(ts.shape[0]/float(r_iso) )
pltkwargs.setdefault('cstride', cstride)
pltkwargs.setdefault('rstride', rstride)
elif kind == 'contour':
pass
else:
raise PlotError('_gen2d3d invalid kind: "%s". '
'Choose from %s' % (kind, PLOTPARSER.plots_2d_3d))
# Is this the best logic for 2d/3d fig?
if not ax:
f = plt.figure()
# ax = f.gca(projection=projection)
ax = f.add_subplot(111, projection=projection)
if not fig:
fig = f
labelsize = pltkwargs.pop('labelsize', 'medium') #Can also be ints
titlesize = pltkwargs.pop('titlesize', 'large')
ticksize = pltkwargs.pop('ticksize', '') #Put in default and remove bool gate
# PLT.CONTOUR() doesn't take 'color'; rather, takes 'colors' for now
if 'color' in pltkwargs:
if kind == 'contour':
pltkwargs['colors'] = pltkwargs.pop('color')
# Convienence method to pass in string colors
if 'colormap' in pltkwargs:
pltkwargs['cmap'] = pltkwargs.pop('colormap')
if 'cmap' in pltkwargs:
if isinstance(pltkwargs['cmap'], basestring):
pltkwargs['cmap'] = pu.cmget(pltkwargs['cmap'])
# Contour Plots
# -------------
# Broken background image
### More here http://matplotlib.org/examples/pylab_examples/image_demo3.html ###
# Refactored with xx, yy instead of df.columns/index UNTESTED
#if background:
#xmin, xmax, ymin, ymax = xx.min(), xx.max(), yy.min(), yy.max()
## Could try rescaling contour rather than image:
##http://stackoverflow.com/questions/10850882/pyqt-matplotlib-plot-contour-data-on-top-of-picture-scaling-issue
#if background==1:
#im = ax.imshow(ts, interpolation='bilinear', origin='lower',
#cmap=cm.gray, extent=(xmin, xmax, ymin, ymax))
#### This will take a custom image opened in PIL or it will take plt.imshow() returned from somewhere else
#else:
#try:
#im = ax.imshow(background)
#### Perhaps image was not correctly opened
#except Exception:
#raise badvalue_error(background, 'integer 1,2 or a PIL-opened image')
# Note this overwrites the 'contours' variable from an int to array
if kind == 'contour' or kind == 'contour3d':
if fill:
mappable = ax.contourf(xx, yy, ts, contours, **pltkwargs) #linewidths is a pltkwargs arg
else:
mappable = ax.contour(xx, yy, ts, contours, **pltkwargs)
### Pick a few label styles to choose from.
if label:
if label==1:
ax.clabel(inline=1, fontsize=10)
elif label==2:
ax.clabel(levels[1::2], inline=1, fontsize=10) #label every second line
else:
raise PlotError(label, 'integer of value 1 or 2')
elif kind == 'surf':
mappable = ax.plot_surface(xx, yy, ts, **pltkwargs)
# pltkwargs.pop('edgecolors')
wires = overload_plot_wireframe(ax, xx, yy, ts, **pltkwargs)
# print np.shape(wires._segments3d)
wires = wire_cmap(wires, ax, cmap='jet')
elif kind == 'wire':
pltkwargs.setdefault('color', 'black')
mappable = overload_plot_wireframe(ax, xx, yy, ts, **pltkwargs)
elif kind == 'waterfall':
edgecolors = pltkwargs.setdefault('edgecolors', None)
pltkwargs.setdefault('closed', False)
alpha = pltkwargs.setdefault('alpha', None)
# Need to handle cmap/colors a bit differently for PolyCollection API
if 'color' in pltkwargs:
pltkwargs['facecolors']=pltkwargs.pop('color')
cmap = pltkwargs.setdefault('cmap', None)
if alpha is None: #as opposed to 0
alpha = 0.6 * (13.0/ts.shape[1])
if alpha > 0.6:
alpha = 0.6
#Delete stride keywords
for key in ['cstride', 'rstride']:
try:
del pltkwargs[key]
except KeyError:
pass
# Verts are index dotted with data
verts = []
for col in ts.columns:
values = ts[col]
values[0], values[-1] = values.min().min(), values.min().min()
verts.append(list(zip(ts.index, values)))
mappable = PolyCollection(verts, **pltkwargs)
if cmap:
mappable.set_array(cols) #If set array in __init__, autogens a cmap!
mappable.set_cmap(pltkwargs['cmap'])
mappable.set_alpha(alpha)
#zdir is the direction used to plot; dont' fully understand
ax.add_collection3d(mappable, zs=cols, zdir='x' )
# custom limits/labels polygon plot (reverse x,y)
if not ylim:
ylim = (max(index), min(index)) #REVERSE AXIS FOR VIEWING PURPOSES
if not xlim:
xlim = (min(cols), max(cols)) #x
if not zlim:
zlim = (min(ts.min()), max(ts.max())) #How to get absolute min/max of ts values
# Reverse labels/DTI call for correct orientaion HACK HACK HACK
xlabel, ylabel = ylabel, xlabel
_x_dti, _y_dti = _y_dti, _x_dti
azim = -1 * azim
# General Features
# ----------------
# Some applications (like add_projection) shouldn't alther axes features
if not _modifyax:
return (ax, mappable)
if cbar:
# Do I want colorbar outside of fig? Wouldn't be better on axes?
try:
fig.colorbar(mappable, ax=ax)
except Exception:
raise PlotError("Colorbar failed; did you pass a colormap?")
if grid:
ax.grid()
# Format datetime axis
# -------------------
if _x_dti:
ax.xaxis.set_major_formatter(mplticker.FuncFormatter(format_date))
# Uncomment for custom 3d timestamp orientation
# if projection:
# for t1 in ax.yaxis.get_ticklabels():
# t1.set_ha('right')
# t1.set_rotation(30)
# ax.yaxis._axinfo['label']['space_factor'] = _TIMESTAMPPADDING
if _y_dti:
ax.yaxis.set_major_formatter(mplticker.FuncFormatter(format_date))
# Uncomment for custom 3d timestamp orientation
# if projection:
# for t1 in ax.yaxis.get_ticklabels():
# t1.set_ha('right')
# t1.set_rotation(30)
# ax.yaxis._axinfo['label']['space_factor'] = _TIMESTAMPPADDING
if xlim:
ax.set_xlim3d(xlim)
if ylim:
ax.set_ylim3d(ylim)
if zlim:
ax.set_zlim3d(zlim)
# Set elevation/azimuth for 3d plots
if projection:
ax.view_init(elev, azim)
ax.set_zlabel(zlabel, fontsize=labelsize, rotation= _zlabel_rotation)
ax.set_xlabel(xlabel, fontsize=labelsize)
ax.set_ylabel(ylabel, fontsize=labelsize)
ax.set_title(title, fontsize=titlesize)
# Return Ax, contours/surface/polygons etc...
return (ax, mappable)