def show(self, header=True):
"""Print the contents of this table."""
# if h2o.can_use_pandas():
# import pandas
# pandas.options.display.max_rows = 20
# print pandas.DataFrame(self._cell_values,columns=self._col_header)
# return
if header and self._table_header:
print(self._table_header + ":", end=' ')
if self._table_description: print(self._table_description)
print()
table = copy.deepcopy(self._cell_values)
nr = 0
if _is_list_of_lists(table):
nr = len(
table
) # only set if we truly have multiple rows... not just one long row :)
if nr > 20: # create a truncated view of the table, first/last 5 rows
trunc_table = []
trunc_table += [v for v in table[:5]]
trunc_table.append(["---"] * len(table[0]))
trunc_table += [v for v in table[(nr - 5):]]
table = trunc_table
H2ODisplay(table, self._col_header, numalign="left", stralign="left")
if nr > 20 and can_use_pandas():
print('\nSee the whole table with table.as_data_frame()')
def show_status(self, detailed=False):
"""
Print current cluster status information.
:param detailed: if True, then also print detailed information about each node.
"""
keys = _cluster_status_info_keys
values = self._get_cluster_status_info_values()
table = [[k + ":", values[i]] for i, k in enumerate(keys)]
H2ODisplay(table)
if detailed:
keys = _cluster_status_detailed_info_keys
header = ["Nodes info:"] + [
"Node %d" % (i + 1) for i in range(len(self.nodes))
]
table = [[k] + [node[k] for node in self.nodes] for k in keys]
H2ODisplay(table=table, header=header)
def show_status(self, detailed=False):
"""
Print current cluster status information.
:param detailed: if True, then also print detailed information about each node.
"""
if self._retrieved_at + self.REFRESH_INTERVAL < time.time():
# Info is stale, need to refresh
new_info = h2o.api("GET /3/Cloud")
self._fill_from_h2ocluster(new_info)
ncpus = sum(node["num_cpus"] for node in self.nodes)
allowed_cpus = sum(node["cpus_allowed"] for node in self.nodes)
free_mem = sum(node["free_mem"] for node in self.nodes)
unhealthy_nodes = sum(not node["healthy"] for node in self.nodes)
status = "locked" if self.locked else "accepting new members"
if unhealthy_nodes == 0:
status += ", healthy"
else:
status += ", %d nodes are not healthy" % unhealthy_nodes
H2ODisplay([
["H2O cluster uptime:", get_human_readable_time(self.cloud_uptime_millis)],
["H2O cluster version:", self.version],
["H2O cluster version age:", "{} {}".format(self.build_age, ("!!!" if self.build_too_old else ""))],
["H2O cluster name:", self.cloud_name],
["H2O cluster total nodes:", self.cloud_size],
["H2O cluster free memory:", get_human_readable_bytes(free_mem)],
["H2O cluster total cores:", str(ncpus)],
["H2O cluster allowed cores:", str(allowed_cpus)],
["H2O cluster status:", status],
["H2O connection url:", h2o.connection().base_url],
["H2O connection proxy:", h2o.connection().proxy],
["H2O internal security:", self.internal_security_enabled],
["Python version:", "%d.%d.%d %s" % tuple(sys.version_info[:4])],
])
if detailed:
keys = ["h2o", "healthy", "last_ping", "num_cpus", "sys_load", "mem_value_size", "free_mem", "pojo_mem",
"swap_mem", "free_disk", "max_disk", "pid", "num_keys", "tcps_active", "open_fds", "rpcs_active"]
header = ["Nodes info:"] + ["Node %d" % (i + 1) for i in range(len(self.nodes))]
table = [[k] for k in keys]
for node in self.nodes:
for i, k in enumerate(keys):
table[i].append(node[k])
H2ODisplay(table=table, header=header)
def show(self, header=True):
"""Print the contents of this table."""
print()
if header and self._table_header:
print(self._table_header + ":", end=' ')
if self._table_description: print(self._table_description)
(table, nr, is_pandas) = self._as_show_table()
H2ODisplay(table, is_pandas=is_pandas, header=self._col_header, numalign="left", stralign="left")
if nr > 20 and can_use_pandas(): print('\nSee the whole table with table.as_data_frame()')
def _as_show_table(self):
if H2ODisplay.prefer_pandas() and can_use_pandas():
pd = self.as_data_frame()
return self.as_data_frame().head(20), pd.shape[0], True
else:
table = copy.deepcopy(self._cell_values)
nr = 0
if _is_list_of_lists(table): nr = len(
table) # only set if we truly have multiple rows... not just one long row :)
if nr > 20: # create a truncated view of the table, first/last 5 rows
trunc_table = []
trunc_table += [v for v in table[:5]]
trunc_table.append(["---"] * len(table[0]))
trunc_table += [v for v in table[(nr - 5):]]
table = trunc_table
return table, nr, False
def summary(self, header=True):
"""Print a detailed summary of the explored models."""
table = []
for model in self.models:
model_summary = model._model_json["output"]["model_summary"]
r_values = list(model_summary.cell_values[0])
r_values[0] = model.model_id
table.append(r_values)
# if h2o.can_use_pandas():
# import pandas
# pandas.options.display.max_rows = 20
# print pandas.DataFrame(table,columns=self.col_header)
# return
print()
if header:
print('Grid Summary:')
print()
H2ODisplay(table, ['Model Id'] + model_summary.col_header[1:], numalign="left", stralign="left")