From: Michael J Gruber <michaeljgruber+<gmane@fa...>  20080606 13:34:59

We introduce analogues of graph.data.function etc. to be used as data sources for graph.graphxy. Naming is changed in order to make things more consistent with grah/graphxy. * rename functionxy to functionlambda (2D function given as lambda expression) * rename paramfunctionxy to paramfunctionlambda (2D parametric function given as lambda expression) * new functionxy (3D function given as textual expression) * new functionxylambda (3D function given as lambda expression) * new paramtsfunction (function of 2 parameters given as textual expression) * new paramtsfunctionlambda (function of 2 parameters given as lambda expression) Note that all parametric functions can provide 2D as well 3D data. Signedoffby: Michael J Gruber <michaeljgruber@...>  pyx/graph/data.py  134 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 files changed, 132 insertions(+), 2 deletions() diff git a/pyx/graph/data.py b/pyx/graph/data.py index 9e525ba..8ce2607 100644  a/pyx/graph/data.py +++ b/pyx/graph/data.py @@ 573,7 +573,7 @@ class function(_data): return dynamiccolumns class functionxy(function): +class functionlambda(function): def __init__(self, f, min=None, max=None, **kwargs): function.__init__(self, "y(x)=f(x)", context={"f": f}, min=min, max=max, **kwargs) @@ 606,7 +606,137 @@ class paramfunction(_data): self.columnnames = self.columns.keys() class paramfunctionxy(paramfunction): +class paramfunctionlambda(paramfunction): def __init__(self, f, min, max, **kwargs): paramfunction.__init__(self, "t", min, max, "x, y = f(t)", context={"f": f}, **kwargs) + + +class functionxy(_data): + + defaultstyles = defaultlines + + assignmentpattern = re.compile(r"\s*([az_][az09_]*)\s*\(\s*([az_][az09_]*)\s*,\s*([az_][az09_]*)\s*\)\s*=", re.IGNORECASE) + + def __init__(self, expression, title=_notitle, xmin=None, xmax=None, ymin=None, ymax=None, + points=10, context={}): + + if title is _notitle: + self.title = expression + else: + self.title = title + self.xmin = xmin + self.xmax = xmax + self.ymin = ymin + self.ymax = ymax + self.numberofpoints = points + self.context = context.copy() # be safe on late evaluations + m = self.assignmentpattern.match(expression) + if m: + self.zname, self.xname, self.yname = m.groups() + expression = expression[m.end():] + else: + raise ValueError("z(x,y)=... or similar expected") + if context.has_key(self.xname): + raise ValueError("xname in context") + if context.has_key(self.yname): + raise ValueError("yname in context") + self.expression = compile(expression.strip(), __file__, "eval") + self.columns = {} + self.columnnames = [self.xname, self.yname, self.zname] + + def dynamiccolumns(self, graph): + dynamiccolumns = {self.xname: [], self.yname: [], self.zname: []} + + xaxis = graph.axes[self.xname] + yaxis = graph.axes[self.yname] + from pyx.graph.axis import logarithmic + logxaxis = isinstance(xaxis.axis, logarithmic) + logyaxis = isinstance(yaxis.axis, logarithmic) + if self.xmin is not None: + xmin = self.xmin + else: + xmin = xaxis.data.min + if self.xmax is not None: + xmax = self.xmax + else: + xmax = xaxis.data.max + if logxaxis: + xmin = math.log(xmin) + xmax = math.log(xmax) + if self.ymin is not None: + ymin = self.ymin + else: + ymin = yaxis.data.min + if self.ymax is not None: + ymax = self.ymax + else: + ymax = yaxis.data.max + if logyaxis: + ymin = math.log(ymin) + ymax = math.log(ymax) + for i in range(self.numberofpoints): + x = xmin + (xmaxxmin)*i / (self.numberofpoints1.0) + if logxaxis: + x = math.exp(x) + self.context[self.xname] = x + for j in range(self.numberofpoints): + y = ymin + (ymaxymin)*j / (self.numberofpoints1.0) + if logyaxis: + y = math.exp(y) + dynamiccolumns[self.xname].append(x) + dynamiccolumns[self.yname].append(y) + self.context[self.yname] = y + try: + z = eval(self.expression, _mathglobals, self.context) + except (ArithmeticError, ValueError): + z = None + dynamiccolumns[self.zname].append(z) + return dynamiccolumns + + +class functionxylambda(functionxy): + + def __init__(self, f, xmin=None, xmax=None, ymin=None, ymax=None, **kwargs): + functionxy.__init__(self, "z(x,y)=f(x,y)", context={"f": f}, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, **kwargs) + + +class paramtsfunction(_data): + + defaultstyles = defaultlines + + def __init__(self, tname, tmin, tmax, sname, smin, smax, expression, title=_notitle, points=10, context={}): + if context.has_key(tname): + raise ValueError("tname in context") + if context.has_key(sname): + raise ValueError("sname in context") + if title is _notitle: + self.title = expression + else: + self.title = title + varlist, expression = expression.split("=") + expression = compile(expression.strip(), __file__, "eval") + keys = [key.strip() for key in varlist.split(",")] + self.columns = dict([(key, []) for key in keys]) + context = context.copy() + for i in range(points): + tparam = tmin + (tmaxtmin)*i / (points1.0) + context[tname] = tparam + for j in range(points): + sparam = smin + (smaxsmin)*j / (points1.0) + context[sname] = sparam + values = eval(expression, _mathglobals, context) + for key, value in zip(keys, values): + self.columns[key].append(value) + if len(keys) != len(values): + raise ValueError("unpack tuple of wrong size") + self.columnnames = self.columns.keys() + + +class paramtsfunctionlambda(paramtsfunction): + + def __init__(self, f, tmin, tmax, smin, smax, **kwargs): + paramtsfunction.__init__(self, "t", tmin, tmax, "s", smin, smax, "x, y, z = f(t,s)", context={"f": f}, **kwargs) + + + 