def wireframe(*args, **kwargs):
"""
Wireframe plot of 2D data.
Wire(fileID,fileNumber,plotLimits,viewingAngles,figSize):
Args:
fileID: ID for data files where files look like fileID_fileNum.dat e.g.
if data files for SQ_RT data are SQ_RT_0.dat,SQ_RT_1.dat,SQ_RT_2.dat,...
then the fileID is simply 'SQ_RT'
fileNumber: Specifies which data file number to plot e.g. Wire('RT',10)
will make a surface plot of the data file 'RT_10.dat' if this data file
is available
plotLimits = [minX,maxX,minY,maxY,minZ,maxZ]
plotLimits: Specifies the Wire plot limits
minX: Minimum x value limit
maxX: Maximum x value limit
minY: Minimum y value limit
maxY: Maximum y value limit
minZ: Minimum z value limit
maxZ: Maximum z value limit
If no plotLimit list is given, then all data is used in the plots and
then minimum and maximum graph limits will depend on the minimum and
maximum data limits of the input and output variables. The plotLimits
list can be empty, contain just xmin and xmax limits, contain just
xmin,xmax,ymin,and ymax, or contain all limits
e.g. Wire('RT',10,[0,1]) will plot data with x-limits between
0 and 1
e.g. Wire('RT',10,[0,1,-2,2]) will plot data with x-limits between
0 and 1 and y-limits between -2 and 2.
e.g. Wire('RT',10,[0,1,-2,2,0,10]) will plot data with x-limits
between 0 and 1, y-limits between -2 and 2, and z-limits from
0 to 10
e.g. Wire('RT',10,[]) is the same as Wire('RT',10)
**kwargs (optional)
figsize : array or tuple containing width and height of figure
overwrite : np.bool
True -> current wireframe graph will be overwritten if it exists
False -> new figure created for each wireframe graph
elev : float
figure elevation as used in view_init
azim : float
figure azimuth as used in view_init
"""
x, y, Z, auxDict = GetData2D(*args)
x, y, Z, auxDict = ProcessData2D(x, y, Z, auxDict)
X, Y = np.meshgrid(x, y)
elev, azim = GetView(*args)
auxDict['elev'] = elev
auxDict['azim'] = azim
width, height = _WireSize(*args)
if 'overwrite' in kwargs and kwargs['overwrite']:
fig = plt.figure("Wireframe", figsize=(width, height))
fig.clf()
else:
fig = plt.figure(figsize=(width, height))
ax = fig.gca(projection='3d')
ax.w_xaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.w_yaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.w_zaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
surf = ax.plot_wireframe(X, Y, Z, rstride=1, cstride=1, color='black')
AuxAxes3DLabel(ax, auxDict)
plt.ion()
plt.show()
return surf
def plot(filename,figsize=None,xlim=None,ylim=None,\
overwrite=False,complex_op=None,**kwargs):
"""
Graph of 1D data file using Matplotlib plt.plot
INPUTS:
filename: string
name of file containing 1D data to be plotted
figsize: tuple (width,height)
size of figure to be displayed
xlim: np.array
x-axis limits of graph
ylim: np.array
y-axis limits of graph
overwrite: bool
add lines to an existing plt.plot graph if it exists
(default is False which will plot graph on a new figure)
complex_op : string in the following list ('real','imag','power','absolute','angle')
complex operation used to plot complex data
**kwargs: dictionary
(optional) arguments to be passed onto plt.loglog plot
OUTPUTS:
ax : matplotlib.axes.Axes
Matplotlib axes object, allows for setting limits and other manipulation of the axes
(e.g. ax.set_xlim([0,1]) would set the graph x-limits to be between 0 and 1)
"""
x, y, auxDict = LoadData1D(filename)
if complex_op is not None:
y = ProcessComplex(complex_op, y)
ExtendDictionary(auxDict,
figsize=figsize,
xlim=xlim,
ylim=ylim,
overwrite=overwrite)
x, y, auxDict = ProcessData1D(x, y, auxDict)
figsize = PlotSize(figsize)
if xlim is None:
xlim = [x[0], x[-1]]
if ylim is None:
ylim = [np.min(y), np.max(y)]
labs = plt.get_figlabels()
if overwrite:
if "Plot" not in labs:
configs.defaultLS()
else:
configs.toggleLS()
plt.figure("Plot", figsize=figsize)
if (configs.LS == 'k--'):
plt.plot(x, y, configs.LS, dashes=(4, 2), **kwargs)
else:
plt.plot(x, y, configs.LS, **kwargs)
else:
plt.figure(figsize=figsize)
configs.defaultLS()
plt.plot(x, y, configs.LS, **kwargs)
AuxPlotLabel1D(auxDict)
if 'legend' in auxDict and configs._G['legend'] == 'on':
plt.legend([str(auxDict["legend"])], loc='best')
if xlim:
plt.xlim(xlim)
if ylim:
plt.ylim(ylim)
plt.ion()
plt.show()
ax = plt.gca()
return ax
def contourflog(filename,
numlevels,
decades,
figsize=None,
xlim=None,
ylim=None,
complex_op=None,
overwrite=False,
**kwargs):
"""
Logged data contour plot of 2D data file using Matplotlib plt.contourf
INPUTS:
filename: string
name of file containing 2D data to be plotted
numlevels : int
number of contour levels to plot
decades: int
maximum number of log10 decades to be plotted (starting with max value)
figsize: tuple (width,height)
size of figure to be displayed
xlim: np.array
x-axis limits of graph
ylim: np.array
y-axis limits of graph
complex_op : string (note this parameter is not used unless the data is complex)
cop = 'power' -> for complex data graph the surface of the power of the data
cop = 'absolute' -> for complex data graph the surface of the absolute value (abs(data))
cop = 'angle' -> for complex data graph the surface of the absolute value (angle(data))
overwrite: bool
false (default) -> create new contourf plot figure
true -> clear figure named 'Contourf' and make new contourf plot
**kwargs: dictionary
(optional) arguments to be passed onto plt.contourf plot
OUTPUTS:
None
"""
x, y, Z, auxDict = LoadData2D(filename)
if complex_op is not None:
Z = ProcessComplex(complex_op, Z)
ExtendDictionary(auxDict,decades=decades,figsize=figsize,\
xlim=xlim,ylim=ylim,overwrite=overwrite)
x, y, Z, auxDict = ProcessData2D(x, y, Z, auxDict)
# Z = ProcessDecadeLimits(decades,Z)
figsize = ContourfSize(figsize)
X, Y = np.meshgrid(x, y)
levels, levelTicks, _ = ContourLevelsL(numlevels, decades, Z)
if overwrite:
fig = plt.figure("Contourflog", figsize=figsize)
fig.clf()
else:
fig = plt.figure(figsize=figsize)
if 'cmap' in kwargs:
cmap = kwargs['cmap']
del kwargs['cmap']
else:
cmap = str(configs._G["cmap"])
plt.contourf(X,
Y,
Z,
levels,
cmap=cmap,
locator=ticker.LogLocator(),
**kwargs)
ax = plt.gca()
ax.set_xlabel(LabelX(auxDict))
ax.set_ylabel(LabelY(auxDict))
plt.colorbar(ticks=ticker.LogLocator())
plt.ion()
plt.show()
def contourf(filename,levels=None,figsize=None,xlim=None,ylim=None,zlim=None,\
decades=None,complex_op=None,overwrite=False,**kwargs):
"""
Graph of 2D data file using Matplotlib plt.contourf
INPUTS:
filename: string
name of file containing 2D data to be plotted
levels : int or array-like (optional)
determines number and position of contour lines/regions
figsize: tuple (width,height)
size of figure to be displayed
xlim: np.array
x-axis limits of graph
ylim: np.array
y-axis limits of graph
zlim: np.array [zmin,zmax]
zmin -> minimum value data can take
zmax -> maximum value data can take
decades: int
maximum number of log10 decades to be plotted (starting with max value)
overwrite: bool
false (default) -> create new contourf plot figure
true -> clear figure named 'Contourf' and make new contourf plot
complex_op : string in the following list ('real','imag','power','absolute','angle')
complex operation used to plot complex data
**kwargs: dictionary
(optional) arguments to be passed onto plt.contourf plot
OUTPUTS:
None
"""
x, y, Z, auxDict = LoadData2D(filename)
if complex_op is not None:
Z = ProcessComplex(complex_op, Z)
ExtendDictionary(auxDict,levels=levels,figsize=figsize,xlim=xlim,ylim=ylim,zlim=zlim,\
decades=decades,overwrite=overwrite)
x, y, Z, auxDict = ProcessData2D(x, y, Z, auxDict)
figsize = ContourfSize(figsize)
X, Y = np.meshgrid(x, y)
if zlim is not None:
Z = ProcessContourLimitZ(zlim, Z)
levels, levelTicks, _ = ContourLevels(levels, Z)
if overwrite:
fig = plt.figure("Contourf", figsize=figsize)
fig.clf()
else:
fig = plt.figure(figsize=figsize)
if 'cmap' in kwargs:
cmap = kwargs['cmap']
del kwargs['cmap']
else:
cmap = str(configs._G["cmap"])
plt.contourf(X, Y, Z, levels, cmap=cmap, **kwargs)
ax = plt.gca()
ax.set_xlabel(LabelX(auxDict))
ax.set_ylabel(LabelY(auxDict))
plt.colorbar(ticks=levelTicks, format='%0.2e')
plt.ion()
plt.show()
def loglog(filename,figsize=None,decades=None,xlim=None,ylim=None,\
complex_op=None,overwrite=False,**kwargs):
"""
Loglog graph of 1D data file using Matplotlib plt.loglog
INPUTS:
filename: string
name of file containing 1D data to be plotted
figsize: tuple (width,height)
size of figure to be displayed
xlim: np.array
x-axis limits of graph
ylim: np.array
x-axis limits of graph
decades: int
number of decades of data below maximum to plot
overwrite: bool
add lines to an existing plt.semilogy graph if it exists
(default is False which will create graph on a new figure)
**kwargs: dictionary
(optional) arguments to be passed onto plt.loglog plot
OUTPUTS:
ax : matplotlib.axes.Axes
Matplotlib axes object, allows for setting limits and other manipulation of the axes
(e.g. ax.set_xlim([0,1]) would set the graph x-limits to be between 0 and 1)
"""
x, y, auxDict = LoadData1D(filename)
if complex_op is not None:
y = ProcessComplex(complex_op, y)
if decades is None:
decades = configs._G['decades']
if xlim is None:
xlim = [x[0], x[-1]]
if ylim is None:
ylim = [np.min(y), np.max(y)]
figsize = LogLogSize(figsize)
ExtendDictionary(auxDict,figsize=figsize,decades=decades,\
xlim=xlim,ylim=ylim,overwrite=overwrite)
x, y, auxDict = ProcessData1D(x, y, auxDict)
figsize = LogLogSize(figsize)
if overwrite:
labs = plt.get_figlabels()
if "LogLog" not in labs:
configs.defaultLS()
else:
configs.toggleLS()
plt.figure("LogLog", figsize=figsize)
else:
configs.defaultLS()
plt.figure(figsize=figsize)
fig = plt.loglog(x, y, configs.LS, **kwargs)
plt.grid(True)
AuxPlotLabelLL1D(auxDict)
if xlim:
plt.xlim(xlim)
if ylim:
plt.ylim(ylim)
plt.ion()
plt.show()
return fig
def surface(filename,figsize=None,xlim=None,ylim=None,zlim=None,\
overwrite=False,complex_op=None,**kwargs):
"""
Graph of 2D data file using Matplotlib plt.surface
INPUTS:
filename: string
name of file containing 2D data to be plotted
figsize: tuple (width,height)
size of figure to be displayed
xlim: np.array
x-axis limits of graph
ylim: np.array
y-axis limits of graph
zlim: np.array
z-axis limits of graph
overwrite: bool
false (default) -> create new surface plot figure
true -> clear figure named 'Surface' and make new surface plot
complex_op : string in the following list ('real','imag','power','absolute','angle')
complex operation used to plot complex data
**kwargs: dictionary
(optional) arguments to be passed onto plt.surface plot
OUTPUTS:
None
"""
x, y, Z, auxDict = LoadData2D(filename)
if complex_op is not None:
Z = ProcessComplex(complex_op, Z)
ExtendDictionary(auxDict,
figsize=figsize,
xlim=xlim,
ylim=ylim,
overwrite=overwrite)
x, y, Z, auxDict = ProcessData2D(x, y, Z, auxDict)
figsize = SurfaceSize(figsize)
elev, azim = GetView(**kwargs)
auxDict['elev'] = elev
auxDict['azim'] = azim
if xlim is None:
xlim = [x[0], x[-1]]
if ylim is None:
ylim = [y[0], y[-1]]
X, Y = np.meshgrid(x, y)
if 'cmap' in kwargs:
cmap = kwargs['cmap']
else:
cmap = str(configs._G["cmap"])
if overwrite:
fig = plt.figure("Surface", figsize=figsize)
fig.clf()
else:
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(projection='3d')
ax.w_xaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.w_yaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.w_zaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.plot_surface(X,
Y,
Z,
rstride=1,
cstride=1,
cmap=cmap,
linewidth=0,
antialiased=True,
shade=True,
**kwargs)
if zlim:
ax.set_zlim3d(zlim)
xlabel, ylabel, zlabel = Labels2D(auxDict)
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
ax.set_zlabel(zlabel)
ax.view_init(auxDict['elev'], auxDict['azim'])
numTicks = int(configs._G['NumberSurfaceTicks'])
ax.xaxis.set_major_locator(ticker.LinearLocator(numTicks))
ax.yaxis.set_major_locator(ticker.LinearLocator(numTicks))
ax.zaxis.set_major_locator(ticker.LinearLocator(4))
labelType = str(configs._G['SurfaceTickFormat'])
ax.xaxis.set_major_formatter(ticker.FormatStrFormatter(labelType))
ax.yaxis.set_major_formatter(ticker.FormatStrFormatter(labelType))
ax.zaxis.set_major_formatter(ticker.FormatStrFormatter(labelType))
plt.ion()
plt.show()
def waterfall(fileID : str, fileNumbers : list,figsize=None,xlim=None,ylim=None,\
complex_op=None,zvalstr=None,aspect=None,**kwargs):
"""
INPUTS:
fileID: str
ID for data files where files look like fileID_fileNum.dat e.g.
if data files for T data are T_0.dat,T_1.dat, T_2.dat,..., then the
fileID is simply 'T' (extension is a catchall, doesnt have to be dat)
fileNumbers: list[int]
Specifies which data file numbers to plot
e.g. waterfall('T',[0:2:100]) will plot files T_0.dat,T_2.dat,...,T_100.dat
(see graphdata.plot.plot for info on other arguments)
xlim: np.array
x-axis limits of graph
zlim: np.array
z-axis limits of graph
complex_op : string in the following list ('real','imag','power','absolute','angle')
complex operation used to plot complex data
zvalstr: str
looks for metadata labeled zvalstr in the files, and will use these to plot z-axis with units
aspect: tuple
aspect ratio to use for xyz graph, e.g. (1,1,1) corresponds to a box
**kwargs: dictionary
(optional) arguments to be passed onto plt.plot plots
OUTPUTS:
ax : matplotlib.axes.Axes
Matplotlib axes object, allows for setting limits and other manipulation of the axes
(e.g. ax.set_xlim([0,1]) would set the graph x-limits to be between 0 and 1)
"""
fileList = GetDataFileList(fileID, fileNumbers)
fileLen = len(fileList)
count = 0
auxDict = dict()
x1 = [0] * len(fileList)
figsize = WaterfallSize(figsize)
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(projection='3d')
ax.w_xaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.w_yaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.w_zaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
count = 0
normFact = 1.0
for i, filename in enumerate(fileList):
x, y, auxDict = LoadData1D(filename)
if complex_op is not None:
y = ProcessComplex(complex_op, y)
ExtendDictionary(auxDict,figsize=figsize,xlim=xlim,\
ylim=ylim,complex_op=complex_op)
x, y, auxDict = ProcessData1D(x, y, auxDict)
if zvalstr is not None and zvalstr in auxDict:
x1[i] = float(auxDict[zvalstr])
else:
x1[i] = i
ax.plot(x, x1[i] * np.ones_like(x), y, color='black', **kwargs)
if xlim is None:
xlim = [x[0], x[-1]]
plt.xlim(xlim)
if ylim is not None:
ax.set_zlim3d(ylim)
zmin = np.amin(x1)
zmax = np.amax(x1)
plt.ylim([zmin, zmax])
if 'xlabel' in auxDict:
ax.set_xlabel(auxDict['xlabel'])
else:
ax.set_xlabel('x')
if 'ylabel' in auxDict:
ax.set_zlabel(auxDict['ylabel'])
else:
ax.set_zlabel('y')
if zvalstr is not None:
ax.set_ylabel(zvalstr)
else:
ax.set_ylabel('file')
elev, azim = GetView(**kwargs)
ax.view_init(elev, azim)
if aspect is not None:
ax.set_box_aspect(aspect=aspect)
plt.ion()
plt.show()
plt.tight_layout()
return ax