from builtins import object
import pandas as pd
import numpy as np
from threeML.io.table import long_path_formatter
from threeML.io.rich_display import display
from threeML.io.uncertainty_formatter import uncertainty_formatter
[docs]
class ResultsTable(object):
def __init__(
self, parameter_paths, values, negative_errors, positive_errors, units
):
values_s = pd.Series([], dtype=np.float64)
negative_error_s = pd.Series([], dtype=np.float64)
positive_error_s = pd.Series([], dtype=np.float64)
units_s = pd.Series([], dtype=np.float64)
for i, this_path in enumerate(parameter_paths):
# Check if this parameter has a dex() unit, i.e., if it is in log10 scale
# If it is, we display the transformed value, not the logarithm
units_s[this_path] = units[i]
if units_s[this_path].to_string().find("dex") < 0:
# A normal parameter
values_s[this_path] = values[i]
negative_error_s[this_path] = negative_errors[i]
positive_error_s[this_path] = positive_errors[i]
else:
# A dex() parameter (logarithmic parameter)
values_s[this_path] = 10 ** values[i]
negative_error_s[this_path] = (
10 ** (values[i] + negative_errors[i]) - values_s[this_path]
)
positive_error_s[this_path] = (
10 ** (values[i] + positive_errors[i]) - values_s[this_path]
)
self._data_frame = pd.DataFrame()
self._data_frame["value"] = values_s
self._data_frame["negative_error"] = negative_error_s
self._data_frame["positive_error"] = positive_error_s
self._data_frame["error"] = (
np.abs(negative_error_s.values) + positive_error_s.values
) / 2.0
self._data_frame["unit"] = units_s
@property
def frame(self):
return self._data_frame
[docs]
def display(self, key_formatter=long_path_formatter):
def row_formatter(row):
value = row["value"]
lower_bound = value + row["negative_error"]
upper_bound = value + row["positive_error"]
pretty_string = uncertainty_formatter(value, lower_bound, upper_bound)
return pretty_string
# Make another data frame with the keys
new_frame = self._data_frame.copy(deep=True) # type: pd.DataFrame
# Add new column which will become the new index
new_frame["parameter"] = [key_formatter(x) for x in new_frame.index.values]
# Set it as the index
new_frame.set_index("parameter", drop=True, inplace=True)
# compute the display
new_frame["result"] = new_frame.apply(row_formatter, axis=1)
# Display
display(new_frame[["result", "unit"]])