"""Beware! you need PyTables >= 2.3 to run this script!"""

from time import perf_counter as clock

import numpy as np

import tables as tb

# NEVENTS = 10000
NEVENTS = 20_000
MAX_PARTICLES_PER_EVENT = 100

# Particle description


class Particle(tb.IsDescription):
    # event_id = tables.Int32Col(pos=1, indexed=True) # event id (indexed)
    event_id = tb.Int32Col(pos=1)  # event id (not indexed)
    particle_id = tb.Int32Col(pos=2)  # particle id in the event
    parent_id = tb.Int32Col(pos=3)  # the id of the parent
    # particle (negative
    # values means no parent)
    momentum = tb.Float64Col(shape=3, pos=4)  # momentum of the particle
    mass = tb.Float64Col(pos=5)  # mass of the particle


# Create a new table for events
t1 = clock()
print(
    f"Creating a table with {NEVENTS * MAX_PARTICLES_PER_EVENT // 2} "
    f"entries aprox.. Wait please..."
)
fileh = tb.open_file("particles-pro.h5", mode="w")
group = fileh.create_group(fileh.root, "events")
table = fileh.create_table(group, "table", Particle, "A table", tb.Filters(0))
# Choose this line if you want data compression
# table = fileh.create_table(group, 'table', Particle, "A table", Filters(1))

# Fill the table with events
np.random.seed(1)  # In order to have reproducible results
particle = table.row
for i in range(NEVENTS):
    for j in range(np.random.randint(0, MAX_PARTICLES_PER_EVENT)):
        particle["event_id"] = i
        particle["particle_id"] = j
        particle["parent_id"] = j - 10  # 10 root particles (max)
        particle["momentum"] = np.random.normal(5.0, 2.0, size=3)
        particle["mass"] = np.random.normal(500.0, 10.0)
        # This injects the row values.
        particle.append()
table.flush()
print(f"Added {table.nrows} entries --- Time: {clock() - t1:.3f} sec")

t1 = clock()
print("Creating index...")
table.cols.event_id.create_index(optlevel=0, _verbose=True)
print(f"Index created --- Time: {clock() - t1:.3f} sec")
# Add the number of events as an attribute
table.attrs.nevents = NEVENTS

fileh.close()

# Open the file en read only mode and start selections
print("Selecting events...")
fileh = tb.open_file("particles-pro.h5", mode="r")
table = fileh.root.events.table

print("Particles in event 34:", end=" ")
nrows = 0
t1 = clock()
for row in table.where("event_id == 34"):
    nrows += 1
print(nrows)
print(f"Done --- Time: {clock() - t1:.3f} sec")

print("Root particles in event 34:", end=" ")
nrows = 0
t1 = clock()
for row in table.where("event_id == 34"):
    if row["parent_id"] < 0:
        nrows += 1
print(nrows)
print(f"Done --- Time: {clock() - t1:.3f} sec")

print("Sum of masses of root particles in event 34:", end=" ")
smass = 0.0
t1 = clock()
for row in table.where("event_id == 34"):
    if row["parent_id"] < 0:
        smass += row["mass"]
print(smass)
print(f"Done --- Time: {clock() - t1:.3f} sec")

print(
    "Sum of masses of daughter particles for particle 3 in event 34:", end=" "
)
smass = 0.0
t1 = clock()
for row in table.where("event_id == 34"):
    if row["parent_id"] == 3:
        smass += row["mass"]
print(smass)
print(f"Done --- Time: {clock() - t1:.3f} sec")

print("Sum of module of momentum for particle 3 in event 34:", end=" ")
smomentum = 0.0
t1 = clock()
# for row in table.where("(event_id == 34) & ((parent_id) == 3)"):
for row in table.where("event_id == 34"):
    if row["parent_id"] == 3:
        smomentum += np.sqrt(np.add.reduce(row["momentum"] ** 2))
print(smomentum)
print(f"Done --- Time: {clock() - t1:.3f} sec")

# This is the same than above, but using generator expressions
# Python >= 2.4 needed here!
print("Sum of module of momentum for particle 3 in event 34 (2):", end=" ")
t1 = clock()
print(
    sum(
        np.sqrt(np.add.reduce(row["momentum"] ** 2))
        for row in table.where("event_id == 34")
        if row["parent_id"] == 3
    )
)
print(f"Done --- Time: {clock() - t1:.3f} sec")


fileh.close()