def apply(self, experiment):
if not self.statistic_name:
raise util.CytoflowOpError("Summary function isn't set")
self.function = summary_functions[self.statistic_name]
return ChannelStatisticOp.apply(self, experiment)
def get_notebook_code(self, idx):
op = ChannelStatisticOp()
op.copy_traits(self, op.copyable_trait_names())
fn_import = {"Mean" : "from numpy import mean",
"Geom.Mean" : None,
"Count" : None,
"Std.Dev" : "from numpy import std",
"Geom.SD" : None,
"SEM" : "from scipy.stats import sem",
"Geom.SEM" : None,
"Mean 95% CI" : "from numpy import mean\nmean_ci = lambda x: ci(x, mean, boots = 100)",
"Geom.Mean 95% CI" : "geom_mean_ci = lambda x: ci(x, geom_mean, boots = 100)"
}
fn_name = {"Mean" : "mean",
"Geom.Mean" : "geom_mean",
"Count" : "len",
"Std.Dev" : "std",
"Geom.SD" : "geom_sd_range",
"SEM" : "sem",
"Geom.SEM" : "geom_sem_range",
"Mean 95% CI" : "mean_ci",
"Geom.Mean 95% CI" : "geom_mean_ci"
}
op.function = summary_functions[self.statistic_name]
try:
# this doesn't work for builtins like "len"
op.function.__name__ = fn_name[self.statistic_name]
except:
pass
return dedent("""
{import_statement}
op_{idx} = {repr}
ex_{idx} = op_{idx}.apply(ex_{prev_idx})
"""
.format(import_statement = (fn_import[self.statistic_name] + "\n"
if fn_import[self.statistic_name] is not None
else ""),
repr = repr(op),
idx = idx,
prev_idx = idx - 1))