def hist(x, bins, density, weights, cumulative, bottom, histtype, color, key, label, linewidth,
underflows, overflows, minvalue, maxvalue):
swtplot.assert_is_native_chart()
# check if we really got a precomputed histogram, using the trick documented for pyplot.hist
if not np.array_equal(x, bins[:-1]):
raise ValueError("Only precomputed histograms are accepted: the values in `x` must equal the values in `bins`, without the last one.")
if weights is None or len(weights) != len(x):
raise ValueError("The `weights` parameter must not be omitted, and it must have the same number of elements as `x`")
props = {}
props["Hist.Cumulative"] = str(cumulative)
props["Hist.Density"] = str(density)
props["Hist.Color"] = _translate_color(color)
props["Hist.Bar"] = _translate_histtype(histtype)
props["Bars.Baseline"] = str(bottom)
plot_histograms(pd.DataFrame({
"key": [key],
"label": [label],
"binedges": [np.array(bins)],
"binvalues": [np.array(weights)],
"underflows": [underflows],
"overflows": [overflows],
"min": [float(np.min(bins)) if math.isnan(minvalue) else minvalue],
"max": [float(np.max(bins)) if math.isnan(maxvalue) else maxvalue]
}), props)
def bar(x, height, width, key, label, color, edgecolor):
swtplot.assert_is_native_chart()
props = {}
if color:
props["Bar.Color"] = _translate_color(color)
plot_bars(pd.DataFrame(
{
"key": [key],
"label": [str(label)],
"values": [np.array(height)]
}
), props)
def plot(xs, ys, key, label, drawstyle, linestyle, linewidth, color, marker, markersize):
swtplot.assert_is_native_chart()
props = {}
if drawstyle:
props["Line.DrawStyle"] = _translate_drawstyle(drawstyle)
if linestyle:
props["Line.Style"] = _translate_linestyle(linestyle)
if linewidth:
props["Line.Width"] = str(linewidth)
if color:
props["Line.Color"] = _translate_color(color)
if marker:
props["Symbols.Type"] = _translate_marker(marker)
if markersize:
props["Symbols.Size"] = str(markersize)
plot_lines(pd.DataFrame({
"key": [key],
"label": [label],
"xs": [np.array(xs)],
"ys": [np.array(ys)]
}
), props)