CompoundPye
0.93
Modelling and Simulation Framework for Neural Networks of Arthropod Compound Eyes
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This class is designed to analyze several simulations, with exact same parameters but stimulus speed. More...
Public Member Functions | |
def | __init__ |
Initializes and AnalyzeCompare object. More... | |
def | get_max_min_lines |
Reads maximum, minimum, and mean response of one cell for each simulation. More... | |
def | plot_individuals |
NOT IMPLEMENTED YET. More... | |
def | plot_max_resp |
Plots a tuning curve using maximum responses (AnalyzeCompare.max_lines). More... | |
def | plot_min_resp |
Plots a tuning curve using minimum responses (AnalyzeCompare.min_lines). More... | |
This class is designed to analyze several simulations, with exact same parameters but stimulus speed.
It expects data to be created with the file cp_non_GUI_wrapper.py, or to be arranged in the same way as the non-GUI wrapper would do.
def CompoundPye.src.Analyzer.analyze_compare.AnalyzeCompare.__init__ | ( | self, | |
path, | |||
memory_friendly = False |
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) |
Initializes and AnalyzeCompare object.
path | Path to folder, in which the output folders of the different simulations belonging to the set to be analyzed lie. |
memory_friendly | If True, Analyze objects of individual simulations will be deleted after necessary values have been read. |
def CompoundPye.src.Analyzer.analyze_compare.AnalyzeCompare.get_max_min_lines | ( | self, | |
neuron_name = 'tangential HS' , |
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skip = 0.4 |
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) |
Reads maximum, minimum, and mean response of one cell for each simulation.
These values (usually only mean) can be used to plot tuning curves. The default parameter changing among simulations is stimulus speed. Thus, speed tuning curves can be generated this way.
def CompoundPye.src.Analyzer.analyze_compare.AnalyzeCompare.plot_individuals | ( | self, | |
ax, | |||
plot_dict, | |||
plot_kwargs_excluding_color = {} , |
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colors = {} |
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) |
NOT IMPLEMENTED YET.
plot neurons' responses for simulations with different movement speeds idea: plot_dict={'one neurons name':[list,of,speed,indices],'another neurons name':[another,list,of,indices],...}
def CompoundPye.src.Analyzer.analyze_compare.AnalyzeCompare.plot_max_resp | ( | self, | |
ax_max, | |||
neuron_name, | |||
scale = 'normal' , |
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plot_kwargs = {'linestyle':'dashed' , |
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color | |||
) |
Plots a tuning curve using maximum responses (AnalyzeCompare.max_lines).
ax_max | Axis object in which to plot. |
neuron_name | Name of neuron to read the response from. |
scale | 'normal' for normal scale, 'log' for logarithmic scale. |
plot_kwargs | Dictionary of keyword parameters to be passed on to the plot function. |
normalize_0_to_1 | If True, data will be linearly stretched and shifted to cover values between 0 and 1. |
min_max_speeds | List of lower and upper speed boundaries, if you wish to inlcude only stimuli in a certain interval. |
def CompoundPye.src.Analyzer.analyze_compare.AnalyzeCompare.plot_min_resp | ( | self, | |
ax_min, | |||
neuron_name, | |||
scale = 'normal' , |
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plot_kwargs = {'linestyle':'dashed' , |
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color | |||
) |
Plots a tuning curve using minimum responses (AnalyzeCompare.min_lines).
ax_min | Axis object in which to plot. |
neuron_name | Name of neuron to read the response from. |
scale | 'normal' for normal scale, 'log' for logarithmic scale. |
plot_kwargs | Dictionary of keyword parameters to be passed on to the plot function. |
normalize_0_to_1 | If True, data will be linearly stretched and shifted to cover values between 0 and 1. |
min_max_speeds | List of lower and upper speed boundaries, if you wish to inlcude only stimuli in a certain interval. |