Similar to one of the previous issues raised here, I am having problems with ploty_surface_plot(). I am working with drug combination data for 2 drugs and I am getting a plot with multiple surfaces as seen in Figure 1. There are no replicates.
However, when I uninstall synergy and install Synergy 4.7.0, the surface plot comes out just fine as seen in Figure 2.
Residuals may be used to evaluate how well the model has fit to a given dataset, are there any more available functionalities for us to evaluate the given dataset? For example, other platforms such as SynergyFinder, outline a square of 4 conc. Combinations on the heatmap as the most practical and synergistic area to test further.
When using cell inhibition data, there are often negative or large values and these lead to runtime warnings indicating overflow in log/multiply/divide etc. How can I troubleshoot these problems? Maybe I have to change the dtype when loading the dataset?
How can we change the concentration values in the axis of the surface and heatmap plots?
How can it be that when the model is fit, when we use model.get_parameters(confidence_interval=95) we get multiple parameters but then when we call model.summary(confidence_interval=95) we only get a few of those parameters. How does the model choose which parameters to print in the summary?
Thank you for your time and for creating the Synergy package! It has been great to use and I was hoping to get some clarification on these questions above.
Similar to one of the previous issues raised here, I am having problems with ploty_surface_plot(). I am working with drug combination data for 2 drugs and I am getting a plot with multiple surfaces as seen in Figure 1. There are no replicates.
However, when I uninstall synergy and install Synergy 4.7.0, the surface plot comes out just fine as seen in Figure 2.
Residuals may be used to evaluate how well the model has fit to a given dataset, are there any more available functionalities for us to evaluate the given dataset? For example, other platforms such as SynergyFinder, outline a square of 4 conc. Combinations on the heatmap as the most practical and synergistic area to test further.
When using cell inhibition data, there are often negative or large values and these lead to runtime warnings indicating overflow in log/multiply/divide etc. How can I troubleshoot these problems? Maybe I have to change the dtype when loading the dataset?
How can we change the concentration values in the axis of the surface and heatmap plots?
How can it be that when the model is fit, when we use model.get_parameters(confidence_interval=95) we get multiple parameters but then when we call model.summary(confidence_interval=95) we only get a few of those parameters. How does the model choose which parameters to print in the summary?
Thank you for your time and for creating the Synergy package! It has been great to use and I was hoping to get some clarification on these questions above.