who-mid-parental-height

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 4.3.0
+current_version = 4.3.1
 tag = False
 commit = True
 

rcpchgrowth/chart_functions.py

@@ -351,6 +351,10 @@ def create_uk_who_chart(
                 sex=sex)
         except:
             lms_array_for_measurement = []
+
+        # truncate the who_child data to stop at 4y
+        if len(lms_array_for_measurement) > 0:
+            lms_array_for_measurement = [obj for obj in lms_array_for_measurement if obj["decimal_age"] <= 4.0]
 
         for centile_index, centile_sds in enumerate(centile_sds_collection):
             # we must create a z for each requested centile

rcpchgrowth/mid_parental_height.py

@@ -1,4 +1,4 @@
-from .constants import HEIGHT, MALE, FEMALE, UK_WHO
+from .constants import HEIGHT, MALE, FEMALE, UK_WHO, WHO
 from .global_functions import sds_for_measurement
 """
 Functions to calculate mid-parental height
@@ -23,8 +23,12 @@ def mid_parental_height_z(maternal_height, paternal_height, reference=UK_WHO):
     """
 
     # convert parental heights to z-scores
-    maternal_height_z = sds_for_measurement(reference=reference, age=20.0, measurement_method=HEIGHT, observation_value=maternal_height, sex=FEMALE)
-    paternal_height_z = sds_for_measurement(reference=reference, age=20.0, measurement_method=HEIGHT, observation_value=paternal_height, sex=MALE)
+    adult_age = 20.0
+    if reference == WHO:
+        adult_age = 19.0
+
+    maternal_height_z = sds_for_measurement(reference=reference, age=adult_age, measurement_method=HEIGHT, observation_value=maternal_height, sex=FEMALE)
+    paternal_height_z = sds_for_measurement(reference=reference, age=adult_age, measurement_method=HEIGHT, observation_value=paternal_height, sex=MALE)
 
     # take the means of the z-scores and apply the regression coefficient of 0.5 - simplifed: (MatHtz +PatHtz)/4
     mid_parental_height_z_score = (maternal_height_z + paternal_height_z) / 4.0

rcpchgrowth/who.py

@@ -170,7 +170,7 @@ def select_reference_data_for_who_chart(
     elif who_reference_name == WHO_2006_CHILD:
         try:
             who_2006_children_reference = who_lms_array_for_measurement_and_sex(
-                age=1.0,
+                age=3.0,
                 measurement_method=measurement_method,
                 sex=sex,
                 default_youngest_reference=default_youngest_reference # should never need younger reference in this calculation