Initial version

LICENCE

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+Copyright (C) 2018-2021 RISE Research Institute of Sweden AB
+
+MIT License
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
+LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+

README

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+This repository contains the code used for data analysis in the BONSAI
+project (Financed by the Swedish funding agency Vinnova, 2018 - 2020).
+
+The objective of the project was to explore methods for causal
+inference for finding causal links between child cancer treatment and
+late effects. The idea is to use a constraint based causal inference
+method adapted for small data sets (most medical data sets are small
+from a machine learning perspective), to distinguish whether a late
+effect is caused by personal predisposition, the primary cancer
+diagnosis, or one of the treatments for the cancer.
+
+This repository contains two parts. One part contains the code for
+arranging the data from several registers (person info, control person
+info, diagnosis, treatments, in-patient care registry, out-patient
+care registry, death registry, and drug prescription, into a common
+file with all information about a patient or control person on one
+line each. The other part contains the analysis and visualization code
+based on that common file.
+
+The actual data is not included here, since it contains sensitive
+personal information and is therefore not publicly available.
+
+All the code is "research project quality", not production quality,
+which means that it is patchy, inconsistent, unclearn, not well
+documented, and thus not easy to use by someone else. Neverthelsee, it
+is included here for transparency of the methods used in the project.
+
+For questions about the code and how to use reuse snippets of it in
+other projects, contact Anders Holst: anders.holst@ri.se
+
+For questions about availability of data, contact Helena Linge:
+helena.linge@med.lu.se
+
+For suggestion for future research collaboration around these issues,
+you can contact any of the above.

dataanalysis/Color.py

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+"""
+Copyright (C) 2018-2021 RISE Research Institute of Sweden AB
+
+File: Color.py
+
+Author: anders.holst@ri.se
+
+"""
+
+import numpy as np
+
+def colorgamma(x):
+    if x < 0.0031308:
+        return x*12.92
+    else:
+        return 1.055 * np.power(x, 0.416667) - 0.055
+
+def invcolorgamma(x):
+    if x < 0.04045:
+        return x / 12.92
+    else:
+        return np.power((x + 0.055)/1.055, 2.4)
+
+def rgb_color(r, g, b):
+    return tuple(list(map(colorgamma, [r,g,b])))
+
+# mimics color.scm with 6color, bluebased, and smooth
+def hsl_color(h, s, l):
+    hramp = [0, 1/12, 1/6, 1/3, 2/3, 7/9, 1]
+    iramp = [(2.410996, 0.16, 0, 0, 1), (0.862552, 0.79, 0, 1, 1),
+             (-0.252442, 0.63, 0, 1, 0), (-1.981885, 0.84, 1, 1, 0),
+             (1.786451, 0.21, 1, 0, 0), (1.571190, 0.37, 1, 0, 1),
+             (2.410996, 0.16, 0, 0, 1)]
+    i = 0
+    while h > hramp[i+1]:
+        i += 1
+    p = (h - hramp[i])/(hramp[i+1] - hramp[i])
+    (a, br, r, g, b) = tuple(map(lambda x1, x2: p*(x2 - x1) + x1, iramp[i], iramp[i+1]))
+    ll0 = (l + 1.0)*0.5
+    ll = (np.exp(a*ll0) - 1.0)/(np.exp(a) - 1.0) if not a==0 else ll0
+    if ll < br:
+        t1 = s * ll / br
+        t2 = ll0 * (1.0 - s)
+    else:
+        t1 = s * (1.0 - ll) / (1.0 - br)
+        t2 = ll0 * (1.0 - s) + s * (ll - br) / (1.0 - br)
+    return rgb_color(r*t1+t2, g*t1+t2, b*t1+t2)
+
+def gencolor(light=0.0, starthue=0.0, startsat=1.0, unsat=False):
+    h = starthue
+    s = startsat
+    if unsat:
+        ss = s*s
+    l = light
+    gs1 = (3.0 - np.sqrt(5))/2.0
+    gs2 = gs1/np.sqrt(3)
+    while True:
+        yield hsl_color(h, s, l)
+        h -= gs1
+        if h < 0.0:
+            h += 1.0
+        if unsat:
+            ss -= gs2
+            if ss <= 0:
+                ss += 1.0
+            s = np.sqrt(ss)
+