diff --git a/distribution.py b/distribution.py
index 09e578d..e4ca4f9 100644
--- a/distribution.py
+++ b/distribution.py
@@ -104,23 +104,29 @@ def gd_std(p):
 	return gd_var(p) ** 0.5
 
 
-def gd_upto(x, p):
+def gd_upto(x, p, q=None):
 	"""
 	Computes the cumulative probability of getting upto x trials until the first success.
 	:param x: Number of trials until the first success.
 	:param p: Probability of success.
+	:param q: Probability of failure.
 	:return: Returns the cumulative probability of getting upto x trials until the first success.
 	"""
+	if q is not None:
+		return sum(gd(i, p, q) for i in range(1, x + 1))
 	return sum(gd(i, p) for i in range(1, x + 1))
 
 
-def gd_from(x, p):
+def gd_from(x, p, q=None):
 	"""
 	Computes the cumulative probability of getting from x trials until the first success.
 	:param x: Number of trials until the first success.
 	:param p: Probability of success.
+	:param q: Probability of failure.
 	:return: Returns the cumulative probability of getting from x trials until the first success.
 	"""
+	if q is not None:
+		return 1 - gd_upto(x - 1, p, q)
 	return 1 - gd_upto(x - 1, p)
 
 
@@ -251,31 +257,35 @@ def pd_from(x, l):
 
 
 def man():
-	print("This module contains functions for computing the total probability of events.")
-	print("The functions are:")
-	print("bnd(x, n, p) - The binomial distribution")
-	print("bnd_mean(n, p) - The mean of the binomial distribution")
-	print("bnd_var(n, p) - The variance of the binomial distribution")
-	print("bnd_std(n, p) - The standard deviation of the binomial distribution")
-	print("bnd_upto(x, n, p) - The cumulative probability of getting upto x successes in n trials")
-	print("bnd_from(x, n, p) - The cumulative probability of getting from x successes in n trials")
-	print("gd(x, p, q) - The geometric distribution")
-	print("gd_mean(p) - The mean of the geometric distribution")
-	print("gd_var(p) - The variance of the geometric distribution")
-	print("gd_std(p) - The standard deviation of the geometric distribution")
-	print("gd_upto(x, p) - The cumulative probability of getting upto x trials until the first success")
-	print("gd_from(x, p) - The cumulative probability of getting from x trials until the first success")
-	print("hgd(x, N, n, k) - The hyper geometric distribution")
-	print("hgd_mean(N, n, k) - The mean of the hyper geometric distribution")
-	print("hgd_var(N, n, k) - The variance of the hyper geometric distribution")
-	print("hgd_std(N, n, k) - The standard deviation of the hyper geometric distribution")
+	"""
+	Prints the manual for the module.
+	"""
 	print(
-		"hgd_upto(x, N, n, k) - The cumulative probability of getting upto x successes in n draws from a population of size N with k successes")
-	print(
-		"hgd_from(x, N, n, k) - The cumulative probability of getting from x successes in n draws from a population of size N with k successes")
-	print("pd(x, l) - The poisson distribution")
-	print("pd_mean(l) - The mean of the poisson distribution")
-	print("pd_var(l) - The variance of the poisson distribution")
-	print("pd_std(l) - The standard deviation of the poisson distribution")
-	print("pd_upto(x, l) - The cumulative probability of getting upto x occurrences")
-	print("pd_from(x, l) - The cumulative probability of getting from x occurrences")
+		"""
+This module contains functions for computing the total probability of events.
+The functions are:
+bnd(x, n, p) - The binomial distribution
+bnd_mean(n, p) - The mean of the binomial distribution
+bnd_var(n, p) - The variance of the binomial distribution
+bnd_std(n, p) - The standard deviation of the binomial distribution
+bnd_upto(x, n, p) - The cumulative probability of getting upto x successes in n trials
+bnd_from(x, n, p) - The cumulative probability of getting from x successes in n trials
+gd(x, p, q) - The geometric distribution
+gd_mean(p) - The mean of the geometric distribution
+gd_var(p) - The variance of the geometric distribution
+gd_std(p) - The standard deviation of the geometric distribution
+gd_upto(x, p, q) - The cumulative probability of getting upto x trials until the first success
+gd_from(x, p, q) - The cumulative probability of getting from x trials until the first success
+hgd(x, N, n, k) - The hyper geometric distribution
+hgd_mean(N, n, k) - The mean of the hyper geometric distribution
+hgd_var(N, n, k) - The variance of the hyper geometric distribution
+hgd_std(N, n, k) - The standard deviation of the hyper geometric distribution
+hgd_upto(x, N, n, k) - The cumulative probability of getting upto x successes in n draws from a population of size N with k successes
+hgd_from(x, N, n, k) - The cumulative probability of getting from x successes in n draws from a population of size N with k successes
+pd(x, l) - The poisson distribution
+pd_mean(l) - The mean of the poisson distribution
+pd_var(l) - The variance of the poisson distribution
+pd_std(l) - The standard deviation of the poisson distribution
+pd_upto(x, l) - The cumulative probability of getting upto x occurrences
+pd_from(x, l) - The cumulative probability of getting from x occurrences
+""")
diff --git a/law_total_probability.py b/law_total_probability.py
index 156f221..95fe120 100644
--- a/law_total_probability.py
+++ b/law_total_probability.py
@@ -34,9 +34,14 @@ def n(A):
 
 
 def man():
-	print("This module contains functions for computing the total probability of events.")
-	print("The functions are:")
-	print("i(A, B) - The intersection of A and B")
-	print("u(A, B) - The union of A and B")
-	print("g(A, B) - The conditional probability of A given B")
-	print("n(A) - The negation of A")
+	"""
+	Prints the manual for the module.
+	"""
+	print("""
+This module contains functions for computing the total probability of events.
+The functions are:
+i(A, B) - The intersection of A and B
+u(A, B) - The union of A and B
+g(A, B) - The conditional probability of A given B
+n(A) - The negation of A
+""")