def test_time_markers(): return tstoolbox.plot(type='time', columns=[2, 3], linestyles=' ', markerstyles='auto', input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_double_mass_marker(): return tstoolbox.plot(type='double_mass', columns=[2, 3, 3, 2], linestyles=' ', markerstyles='auto', input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_lag_plot(): plt.close("all") return tstoolbox.plot(columns=1, type="lag_plot", input_ts=df, ofilename=None, plot_styles="classic")
def test_time_multiple_traces_new_style_plot(): return tstoolbox.plot(type='time', columns=[2,3], markerstyles=' ,*', linestyles='-, ', input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_xy_multiple_traces_markers(): return tstoolbox.plot(type='xy', columns=[2,3,3,2], linestyles=' ', markerstyles='auto', input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_histogram(): plt.close("all") return tstoolbox.plot( type="histogram", clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, )
def test_xy_multiple_traces(): plt.close("all") return tstoolbox.plot( type="xy", columns=[2, 3, 3, 2], input_ts="tests/data_daily_sample.csv", ofilename=None, )
def test_double_mass(): plt.close("all") return tstoolbox.plot( type="double_mass", clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, )
def test_double_mass_mult(): plt.close("all") return tstoolbox.plot( type="double_mass", columns=[2, 3, 3, 2], input_ts="tests/data_daily_sample.csv", ofilename=None, )
def test_scatter_matrix(): plt.close("all") return tstoolbox.plot( type="scatter_matrix", clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, )
def test_probability_density(): plt.close("all") return tstoolbox.plot( type="probability_density", clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, )
def test_weibull_yaxis(): plt.close("all") return tstoolbox.plot( type="weibull_yaxis", columns=2, clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, )
def test_xy(): plt.close("all") return tstoolbox.plot( type="xy", clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, plot_styles="classic", )
def test_time_plot(): plt.close("all") return tstoolbox.plot( type="time", columns=1, clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, )
def test_autocorrelation(): plt.close("all") return tstoolbox.plot( type="autocorrelation", columns=2, input_ts=df, ofilename=None, plot_styles="classic", )
def test_time_multiple_traces_plot(): plt.close("all") return tstoolbox.plot( type="time", columns=[2, 3], style="b-,r*", input_ts="tests/data_daily_sample.csv", ofilename=None, )
def test_kde_time_multiple_traces(): ndf = tstoolbox.read(['tests/daily.csv', 'tests/02325000_flow.csv']) return tstoolbox.plot(type='kde_time', columns=[2, 3], clean=True, input_ts=ndf, ytitle='Flow', ofilename=None)
def test_heatmap(): plt.close("all") return tstoolbox.plot( type="heatmap", columns=2, clean=True, input_ts=df, ofilename=None, plot_styles="classic", )
def test_lognorm_yaxis(): plt.close("all") return tstoolbox.plot( type="lognorm_yaxis", columns=2, clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, plot_styles="classic", )
def test_time_multiple_traces_new_style_plot(): plt.close("all") return tstoolbox.plot( type="time", columns=[2, 3], markerstyles=" ,*", linestyles="-, ", input_ts="tests/data_daily_sample.csv", ofilename=None, )
def test_double_mass_marker(): plt.close("all") return tstoolbox.plot( type="double_mass", columns=[2, 3, 3, 2], linestyles=" ", markerstyles="auto", input_ts="tests/data_daily_sample.csv", ofilename=None, )
def test_boxplot(): ndf = tstoolbox.read(['tests/02234500_65_65.csv', 'tests/02325000_flow.csv'], clean=True, append='combine') return tstoolbox.plot(input_ts=ndf, clean=True, columns=[2, 3], type='boxplot', ofilename=None)
def test_xy_multiple_traces_logx(): plt.close("all") return tstoolbox.plot( type="xy", columns=[2, 3, 3, 2], xaxis="log", input_ts="tests/data_daily_sample.csv", ofilename=None, plot_styles="classic", )
def test_histogram(): plt.close("all") return tstoolbox.plot( type="histogram", clean=True, input_ts="tests/02234500_65_65.csv", ofilename=None, sharex=False, plot_styles="classic", )
def test_kde_time_multiple_traces(): plt.close("all") ndf = tstoolbox.read(["tests/daily.csv", "tests/02325000_flow.csv"]) return tstoolbox.plot( type="kde_time", columns=[2, 3], clean=True, input_ts=ndf, ytitle="Flow", ofilename=None, )
def test_time_markers(): plt.close("all") return tstoolbox.plot( type="time", columns=[2, 3], linestyles=" ", markerstyles="auto", input_ts="tests/data_daily_sample.csv", ofilename=None, plot_styles="classic", )
def test_boxplot(): plt.close("all") xdf = tstoolbox.read( ["tests/02234500_65_65.csv", "tests/02325000_flow.csv"], clean=True, append="combine", ) return tstoolbox.plot(input_ts=xdf, clean=True, columns=[2, 3], type="boxplot", ofilename=None)
def test_autocorrelation(): return tstoolbox.plot(type='autocorrelation', columns=2, input_ts=df, ofilename=None)
def test_double_mass_mult(): return tstoolbox.plot(type='double_mass', columns=[2,3,3,2], input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_time_multiple_traces_style_plot(): return tstoolbox.plot(type='time', columns=[2,3], style='b-,r ', input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_weibull_yaxis(): return tstoolbox.plot(type='weibull_yaxis', columns=2, clean=True, input_ts='tests/02234500_65_65.csv', ofilename=None)
def test_scatter_matrix(): return tstoolbox.plot(type='scatter_matrix', clean=True, input_ts='tests/02234500_65_65.csv', ofilename=None)
def test_barh_stacked(): return tstoolbox.plot(type='barh_stacked', input_ts=dfa, ofilename=None)
def test_barh_stacked(): plt.close("all") return tstoolbox.plot(type="barh_stacked", input_ts=dfa, ofilename=None)
def test_probability_density(): return tstoolbox.plot(type='probability_density', clean=True, input_ts='tests/02234500_65_65.csv', ofilename=None)
def test_bar_stacked(): plt.close("all") return tstoolbox.plot(type="bar_stacked", input_ts=dfa, plot_styles="classic", ofilename=None)
def test_bar(): return tstoolbox.plot(type='bar', input_ts=dfa, ofilename=None)
def test_heatmap(): return tstoolbox.plot(type='heatmap', columns=2, clean=True, input_ts=df, ofilename=None)
def test_xy(): return tstoolbox.plot(type='xy', clean=True, input_ts='tests/02234500_65_65.csv', ofilename=None)
def test_xy_multiple_traces_logx(): return tstoolbox.plot(type='xy', columns=[2,3,3,2], xaxis='log', input_ts='tests/data_daily_sample.csv', ofilename=None)
def test_lag_plot(): return tstoolbox.plot(columns=1, type='lag_plot', input_ts=df, ofilename=None)
def test_kde_time(): return tstoolbox.plot(type='kde_time', columns=2, clean=True, input_ts='tests/02234500_65_65.csv', ofilename=None)
def test_double_mass(): return tstoolbox.plot(type='double_mass', clean=True, input_ts='tests/02234500_65_65.csv', ofilename=None)