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plakrisenkoplakrisenko
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Update visualization example notebooks (#146)
* remove plot_data_and_simulation * move scatterplots to a separate visualization specification file * add scatterplot test * scatterplot can be plotted only if both measurements and simulations are available * fix plotting barplots with only simulation data * code style * un-exclude in doc/conf.py and add to examples.rst * remove jupyter notebook outputs
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‎doc/conf.py‎

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'**.ipynb_checkpoints',
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'logo/LICENSE.md',
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# TODO update and un-exclude
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'example/example_visualization.ipynb',
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'example/example_visualization_without_visspec.ipynb',
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]
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‎doc/example.rst‎

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@@ -9,6 +9,7 @@ The following examples should help to get a better idea of how to use the PEtab
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:maxdepth: 1
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example/example_petablint.ipynb
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example/example_visualization.ipynb
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example/example_visualization_with_visspec.ipynb
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Examples of systems biology parameter estimation problems specified in PEtab

‎doc/example/example_Isensee/Isensee_visualizationSpecification.tsv‎

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@@ -30,6 +30,6 @@ plot4 JI09_151102_Drg421_418_Age LinePlot MeanAndSD JI09_151102_Drg421_418_Age__
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plot5 JI09_160126_Drg449_444_CycNuc BarPlot MeanAndSD JI09_160126_Drg449_444_CycNuc__ctrl condition 0 Condition pRII_Western 0 pRII_Western Ctrl lin lin
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plot5 JI09_160126_Drg449_444_CycNuc BarPlot MeanAndSD JI09_160126_Drg449_444_CycNuc__Fsk10_and_IBMX100 condition 0 Condition pRII_Western 0 pRII_Western IBMX(100)/Fsk(10) lin lin
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plot5 JI09_160126_Drg449_444_CycNuc BarPlot MeanAndSD JI09_160126_Drg449_444_CycNuc__Sp8_Br_cAMPS_AM10 condition 0 Condition pRII_Western 0 pRII_Western Sp8-Br-cAMPS-AM(10) lin lin
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plot6 JI09_160201_Drg453-452_CycNuc ScatterPlot MeanAndSD JI09_160201_Drg453-452_CycNuc__ctrl time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Ctrl lin lin
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plot6 JI09_160201_Drg453-452_CycNuc ScatterPlot MeanAndSD JI09_160201_Drg453-452_CycNuc__Fsk time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Fsk(10) lin lin
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plot6 JI09_160201_Drg453-452_CycNuc ScatterPlot MeanAndSD JI09_160201_Drg453-452_CycNuc__Sp8_Br_cAMPS_AM time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Sp8-Br-cAMPS-AM(10) lin lin
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plot6 JI09_160201_Drg453-452_CycNuc LinePlot MeanAndSD JI09_160201_Drg453-452_CycNuc__ctrl time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Ctrl lin lin
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plot6 JI09_160201_Drg453-452_CycNuc LinePlot MeanAndSD JI09_160201_Drg453-452_CycNuc__Fsk time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Fsk(10) lin lin
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plot6 JI09_160201_Drg453-452_CycNuc LinePlot MeanAndSD JI09_160201_Drg453-452_CycNuc__Sp8_Br_cAMPS_AM time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Sp8-Br-cAMPS-AM(10) lin lin

‎doc/example/example_Isensee/Isensee_visualizationSpecification_scatterplot.tsv‎

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plotId plotName plotTypeSimulation plotTypeData datasetId xValues xOffset xLabel yValues yOffset yLabel legendEntry xScale yScale
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plot5 JI09_160126_Drg449_444_CycNuc ScatterPlot MeanAndSD JI09_160126_Drg449_444_CycNuc__ctrl condition 0 Condition pRII_Western 0 pRII_Western Ctrl lin lin
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plot5 JI09_160126_Drg449_444_CycNuc ScatterPlot MeanAndSD JI09_160126_Drg449_444_CycNuc__Fsk10_and_IBMX100 condition 0 Condition pRII_Western 0 pRII_Western IBMX(100)/Fsk(10) lin lin
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plot5 JI09_160126_Drg449_444_CycNuc ScatterPlot MeanAndSD JI09_160126_Drg449_444_CycNuc__Sp8_Br_cAMPS_AM10 condition 0 Condition pRII_Western 0 pRII_Western Sp8-Br-cAMPS-AM(10) lin lin
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plot6 JI09_160201_Drg453-452_CycNuc ScatterPlot MeanAndSD JI09_160201_Drg453-452_CycNuc__ctrl time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Ctrl lin lin
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plot6 JI09_160201_Drg453-452_CycNuc ScatterPlot MeanAndSD JI09_160201_Drg453-452_CycNuc__Fsk time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Fsk(10) lin lin
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plot6 JI09_160201_Drg453-452_CycNuc ScatterPlot MeanAndSD JI09_160201_Drg453-452_CycNuc__Sp8_Br_cAMPS_AM time 0 Time [min] Calpha_Microscopy 0 Calpha_Microscopy Sp8-Br-cAMPS-AM(10) lin lin

‎doc/example/example_visualization.ipynb‎

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‎petab/visualize/plotter.py‎

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@@ -170,7 +170,6 @@ def generate_barplot(self, ax: 'matplotlib.pyplot.Axes',
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# TODO: plotTypeData == REPLICATE?
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noise_col = self._error_column_for_plot_type_data(plotTypeData)
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simu_colors = None
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measurements_to_plot, simulations_to_plot = \
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self.data_provider.get_data_to_plot(dataplot,
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plotTypeData == PROVIDED)
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color = plt.rcParams["axes.prop_cycle"].by_key()["color"][0]
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if measurements_to_plot is not None:
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p = ax.bar(x_name, measurements_to_plot.data_to_plot['mean'],
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yerr=measurements_to_plot.data_to_plot[noise_col],
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color=color, **bar_kwargs, label='measurement')
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simu_colors = p[0].get_facecolor()
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ax.bar(x_name, measurements_to_plot.data_to_plot['mean'],
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yerr=measurements_to_plot.data_to_plot[noise_col],
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color=color, **bar_kwargs, label='measurement')
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if simulations_to_plot is not None:
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bar_kwargs['width'] = -bar_kwargs['width']
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ax.bar(x_name, simulations_to_plot.data_to_plot['mean'],
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color='white', edgecolor=simu_colors, **bar_kwargs,
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color='white', edgecolor=color, **bar_kwargs,
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label='simulation')
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def generate_scatterplot(self, ax: 'matplotlib.pyplot.Axes',
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self.data_provider.get_data_to_plot(dataplot,
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plotTypeData == PROVIDED)
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if simulations_to_plot is None:
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if simulations_to_plot is None or measurements_to_plot is None:
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raise NotImplementedError('Scatter plots do not work without'
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' simulation data')
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ax.scatter(measurements_to_plot.data_to_plot['mean'],

‎tests/test_visualization.py‎

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/ "Isensee_visualizationSpecification_replicates.tsv"
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@pytest.fixture
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def vis_spec_file_Isensee_scatterplot():
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return EXAMPLE_DIR / "example_Isensee" \
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/ "Isensee_visualizationSpecification_scatterplot.tsv"
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@pytest.fixture
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def simulation_file_Isensee():
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return EXAMPLE_DIR / "example_Isensee" / "Isensee_simulationData.tsv"
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data_file_Isensee, simulation_file_Isensee)
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def test_visualization_scatterplot(data_file_Isensee,
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condition_file_Isensee,
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vis_spec_file_Isensee_scatterplot,
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simulation_file_Isensee):
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plot_with_vis_spec(vis_spec_file_Isensee_scatterplot,
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condition_file_Isensee,
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data_file_Isensee, simulation_file_Isensee)
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def test_visualization_small_visu_file_w_datasetid(data_file_Fujita,
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condition_file_Fujita,
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visu_file_Fujita_small):

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