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Artifact raw data and set plot limits
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.github/workflows/analysis.yml

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@@ -42,6 +42,13 @@ jobs:
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python -m pytest -m slow --saveFileName test_output.csv --SNR 10 30 50 100 200 --fitCount 300 --saveDurationFileName test_duration.csv
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- name: Generate figures
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run: Rscript --vanilla tests/IVIMmodels/unit_tests/analyze.r test_output.csv test_duration.csv
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- name: Upload raw data
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uses: actions/upload-artifact@v3
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with:
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name: Raw data
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path: |
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test_output.csv
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test_duration.csv
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- name: Upload figures
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uses: actions/upload-artifact@v3
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with:

tests/IVIMmodels/unit_tests/analyze.r

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@@ -25,7 +25,7 @@ plot_ivim <- function(data, fileExtension) {
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f_plot <- ggplot(data, aes(x=Algorithm)) + geom_boxplot(aes(y=f_fitted)) + geom_boxplot(color="red", aes(y=f)) + facet_grid(SNR ~ Region) + scale_x_discrete(guide = guide_axis(angle = 90)) + ylim(0, 1) + ggtitle("Perfusion fraction grid") + ylab("Perfusion fraction")
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print(f_plot)
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ggsave(paste("f", fileExtension, sep=""), plot=f_plot, width = 50, height = 50, units = "cm")
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D_plot <- ggplot(data, aes(x=Algorithm)) + geom_boxplot(aes(y=D_fitted)) + geom_boxplot(color="red", aes(y=D)) + facet_grid(SNR ~ Region) + scale_x_discrete(guide = guide_axis(angle = 90)) + ggtitle("Diffusion grid") + ylab("Diffusion")
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D_plot <- ggplot(data, aes(x=Algorithm)) + geom_boxplot(aes(y=D_fitted)) + geom_boxplot(color="red", aes(y=D)) + facet_grid(SNR ~ Region) + scale_x_discrete(guide = guide_axis(angle = 90)) + ylim(0, 0.005) + ggtitle("Diffusion grid") + ylab("Diffusion")
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print(D_plot)
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ggsave(paste("D", fileExtension, sep=""), plot=D_plot, width = 50, height = 50, units = "cm")
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Dp_plot <- ggplot(data, aes(x=Algorithm)) + geom_boxplot(aes(y=Dp_fitted)) + geom_boxplot(color="red", aes(y=Dp)) + facet_grid(SNR ~ Region) + scale_x_discrete(guide = guide_axis(angle = 90)) + ylim(0, 0.25) + ggtitle("Perfusion grid") + ylab("Perfusion")

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