def frame_reducers(ip, port):
# Connect to h2o
h2o.init(ip, port)
data = [[random.uniform(-10000, 10000) for r in range(10)]
for c in range(10)]
h2o_data = h2o.H2OFrame(python_obj=data)
np_data = np.array(data)
row, col = h2o_data.dim()
c = random.randint(0, col - 1)
h2o_val = h2o.min(h2o_data[c])
num_val = np.min(np_data[:, c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.max(h2o_data[c])
num_val = np.max(np_data[:, c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.sum(h2o_data[c])
num_val = np.sum(np_data[:, c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.sd(h2o_data[c])
num_val = np.std(np_data[:, c], axis=0, ddof=1)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sd values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.var(h2o_data[c])
num_val = np.var(np_data[:, c], ddof=1)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal var values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.mean(h2o_data[c])
num_val = np.mean(np_data[:, c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal mean values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.median(h2o_data[c])
num_val = np.median(np_data[:, c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal median values between h2o and " \
"numpy".format(h2o_val,num_val)
def frame_reducers(ip,port):
# Connect to h2o
h2o.init(ip,port)
data = [[random.uniform(-10000,10000) for r in range(10)] for c in range(10)]
h2o_data = h2o.H2OFrame(python_obj=data)
np_data = np.array(data)
row, col = h2o_data.dim()
c = random.randint(0,col-1)
h2o_val = h2o.min(h2o_data[c])
num_val = np.min(np_data[:,c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.max(h2o_data[c])
num_val = np.max(np_data[:,c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.sum(h2o_data[c])
num_val = np.sum(np_data[:,c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.sd(h2o_data[c])
num_val = np.std(np_data[:,c], axis=0, ddof=1)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sd values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.var(h2o_data[c])
num_val = np.var(np_data[:,c], ddof=1)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal var values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.mean(h2o_data[c])
num_val = np.mean(np_data[:,c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal mean values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.median(h2o_data[c])
num_val = np.median(np_data[:,c])
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal median values between h2o and " \
"numpy".format(h2o_val,num_val)
def expr_reducers(ip, port):
# Connect to h2o
h2o.init(ip, port)
data = [[random.uniform(-10000, 10000) for r in range(10)]
for c in range(10)]
h2o_data = h2o.H2OFrame(python_obj=data)
np_data = np.array(data)
row, col = h2o_data.dim()
h2o_data = h2o_data + 2
np_data = np_data + 2
def check_values(h2o_data, numpy_data):
success = True
for i in range(10):
r = random.randint(0, row - 1)
c = random.randint(0, col - 1)
h2o_val = h2o_data[r, c]
num_val = numpy_data[r, c]
if not abs(h2o_val - num_val) < 1e-06:
success = False
print "check unsuccessful! h2o computed {0} and numpy computed {1}".format(
h2o_val, num_val)
return success
h2o_val = h2o.min(h2o_data)
num_val = np.min(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.max(h2o_data)
num_val = np.max(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.sum(h2o_data)
num_val = np.sum(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o.np_comparison_check(h2o.var(h2o_data), np.cov(np_data, rowvar=0, ddof=1), 10), \
"expected equal var values between h2o and numpy"
def expr_reducers(ip,port):
# Connect to h2o
h2o.init(ip,port)
data = [[random.uniform(-10000,10000) for r in range(10)] for c in range(10)]
h2o_data = h2o.H2OFrame(python_obj=data)
np_data = np.array(data)
row, col = h2o_data.dim()
h2o_data = h2o_data + 2
np_data = np_data + 2
def check_values(h2o_data, numpy_data):
success = True
for i in range(10):
r = random.randint(0,row-1)
c = random.randint(0,col-1)
h2o_val = h2o_data[r,c]
num_val = numpy_data[r,c]
if not abs(h2o_val - num_val) < 1e-06:
success = False
print "check unsuccessful! h2o computed {0} and numpy computed {1}".format(h2o_val,num_val)
return success
h2o_val = h2o.min(h2o_data)
num_val = np.min(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal min values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.max(h2o_data)
num_val = np.max(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal max values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o_val = h2o.sum(h2o_data)
num_val = np.sum(np_data)
assert abs(h2o_val - num_val) < 1e-06, \
"check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal sum values between h2o and " \
"numpy".format(h2o_val,num_val)
h2o.np_comparison_check(h2o.var(h2o_data), np.cov(np_data, rowvar=0, ddof=1), 10), \
"expected equal var values between h2o and numpy"