added binomial distribution function

.vscode/settings.json

@@ -0,0 +1,5 @@
+{
+    "python.linting.pylintEnabled": false,
+    "python.linting.flake8Enabled": true,
+    "python.linting.enabled": true
+}

mathgenerator/funcs/__init__.py

@@ -111,3 +111,4 @@ from .decimal_to_bcd import *
 from .circumference import *
 from .combine_like_terms import *
 from .conditional_probability import *
+from .binomial_distribution import *

mathgenerator/funcs/binomial_distribution.py

@@ -0,0 +1,42 @@
+from .__init__ import *
+
+
+def factorial(n):
+
+    if n == 1 or n == 0:
+        return 1
+    else:
+        return n*factorial(n-1)
+
+
+def newton_symbol(n, k):
+    return factorial(n)/(factorial(k)*factorial(n-k))
+
+
+def binomialDistFunc():
+
+    rejected_fraction = float(random.randint(30, 40)) + random.random()
+    batch = random.randint(10, 20)
+    rejections = random.randint(1, 9)
+
+    answer = 0
+
+    rejected_fraction = round(rejected_fraction, 2)
+
+    problem = "A manufacturer of metal pistons finds that, on average, {0:}% "\
+        "of the pistons they manufacture are rejected because " \
+        "they are incorrectly sized. What is the probability that a "\
+        "batch of {1:} pistons will contain no more than {2:} " \
+        "rejected pistons?".format(rejected_fraction, batch, rejections)
+
+    for i in range(0, rejections+1):
+        answer += newton_symbol(batch, i)*((rejected_fraction/100.)**i) * \
+                                ((1 - (rejected_fraction/100.))**(batch-i))
+
+    answer = round(100*answer, 2)
+
+    return problem, answer
+
+
+binomial_distribution = Generator("Binomial distribution", 107, 
+                                  "P(X<x)=", "c", binomialDistFunc)

test.py

@@ -10,4 +10,6 @@ from mathgenerator import mathgen
 #     print(item[2])
 
 # print(mathgen.getGenList())
-print(mathgen.circumference())
+# print(mathgen.circumference())
+
+print(mathgen.binomialDistFunc())