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However, in order to implement this, we need a list of bonds. We will do this by taking a system minimized under our original harmonic_morse potential:
R_temp, max_force_component = run_minimization(harmonic_morse_pair(displacement,D0=5.0,alpha=10.0,r0=1.0,k=500.0), R, shift) print('largest component of force after minimization = {}'.format(max_force_component)) plot_system( R_temp, box_size )
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
We now place a bond between all particle pairs that are separated by less than 1.3. calculate_bond_data returns a list of such bonds, as well as a list of the corresponding current length of each bond.
bonds, lengths = calculate_bond_data(displacement, R_temp, 1.3) print(bonds[:5]) # list of particle index pairs that form bonds print(lengths[:5]) # list of the current length of each bond
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
We use this length as the r0 parameter, meaning that initially each bond is at the unstable local maximum $r=r_0$.
bond_energy_fn = bistable_spring_bond(displacement, bonds, r0=lengths)
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
We now use our new bond_energy_fn to minimize the energy of the system. The expectation is that nearby particles should either move closer together or further apart, and the choice of which to do should be made collectively due to the constraint of constant volume. This is exactly what we see.
Rfinal, max_force_component = run_minimization(bond_energy_fn, R_temp, shift) print('largest component of force after minimization = {}'.format(max_force_component)) plot_system( Rfinal, box_size )
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Specifying bonds dynamically As with species or parameters, bonds can be specified dynamically, i.e. when the energy function is called. Importantly, note that this does NOT override bonds that were specified statically in smap.bond.
# Specifying the bonds dynamically ADDS additional bonds. # Here, we dynamically pass the same bonds that were passed statically, which # has the effect of doubling the energy print(bond_energy_fn(R)) print(bond_energy_fn(R,bonds=bonds, r0=lengths))
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
We won't go thorugh a further example as the implementation is exactly the same as specifying species or parameters dynamically, but the ability to employ bonds both statically and dynamically is a very powerful and general framework. Combining potentials Most JAX MD functionality (e.g. simulations, energy minimizations) relies on a function that calculates energy for a set of positions. Importantly, while this cookbook focus on simple and robust ways of defining such functions, JAX MD is not limited to these methods; users can implement energy functions however they like. As an important example, here we consider the case where the energy includes both a pair potential and a bond potential. Specifically, we combine harmonic_morse_pair with bistable_spring_bond.
# Note, the code in the "Bonds" section must be run prior to this. energy_fn = harmonic_morse_pair(displacement,D0=0.,alpha=10.0,r0=1.0,k=1.0) bond_energy_fn = bistable_spring_bond(displacement, bonds, r0=lengths) def combined_energy_fn(R): return energy_fn(R) + bond_energy_fn(R)
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Here, we have set $D_0=0$, so the pair potential is just a one-sided repulsive harmonic potential. For particles connected with a bond, this raises the energy of the "contracted" minimum relative to the "extended" minimum.
drs = np.arange(0,2,0.01) U = harmonic_morse(drs,D0=0.,alpha=10.0,r0=1.0,k=1.0)+bistable_spring(drs) plt.plot(drs,U) format_plot(r'$r$', r'$V(r)$') finalize_plot()
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
This new energy function can be passed to the minimization routine (or any other JAX MD simulation routine) in the usual way.
Rfinal, max_force_component = run_minimization(combined_energy_fn, R_temp, shift) print('largest component of force after minimization = {}'.format(max_force_component)) plot_system( Rfinal, box_size )
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Specifying forces instead of energies So far, we have defined functions that calculate the energy of the system, which we then pass to JAX MD. Internally, JAX MD uses automatic differentiation to convert these into functions that calculate forces, which are necessary to evolve a system under a given dynamics. However, JAX MD has the option to pass force functions directly, rather than energy functions. This creates additional flexibility because some forces cannot be represented as the gradient of a potential. As a simple example, we create a custom force function that zeros out the force of some particles. During energy minimization, where there is no stochastic noise, this has the effect of fixing the position of these particles. First, we break the system up into two species, as before.
N_0 = N // 2 # Half the particles in species 0 N_1 = N - N_0 # The rest in species 1 species = np.array([0]*N_0 + [1]*N_1, dtype=np.int32) print(species)
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Next, we we creat our custom force function. Starting with our harmonic_morse pair potential, we calculate the force manually (i.e. using built-in automatic differentiation), and then multiply the force by the species id, which has the desired effect.
energy_fn = harmonic_morse_pair(displacement,D0=5.0,alpha=10.0,r0=1.0,k=500.0) force_fn = quantity.force(energy_fn) def custom_force_fn(R, **kwargs): return vmap(lambda a,b: a*b)(force_fn(R),species)
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Running simulations with custom forces is as easy as passing this force function to the simulation.
def run_minimization_general(energy_or_force, R_init, shift, num_steps=5000): dt_start = 0.001 dt_max = 0.004 init,apply=minimize.fire_descent(jit(energy_or_force),shift,dt_start=dt_start,dt_max=dt_max) apply = jit(apply) @jit def scan_fn(state, i): return apply(state), 0. state = init(R_init) state, _ = lax.scan(scan_fn,state,np.arange(num_steps)) return state.position, np.amax(np.abs(quantity.canonicalize_force(energy_or_force)(state.position)))
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
We run this as usual,
key, split = random.split(key) Rfinal, _ = run_minimization_general(custom_force_fn, R, shift) plot_system( Rfinal, box_size, species )
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
After the above minimization, the blue particles have the same positions as they did initially:
plot_system( R, box_size, species )
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Note, this method for fixing particles only works when there is no stochastic noise (e.g. in Langevin or Brownian dynamics) because such noise affects partices whether or not they have a net force. A safer way to fix particles is to create a custom shift function. Coupled ensembles For a final example that demonstrates the flexibility within JAX MD, lets do something that is particularly difficult in most standard MD packages. We will create a "coupled ensemble" -- i.e. a set of two identical systems that are connected via a $Nd$ dimensional spring. An extension of this idea is used, for example, in the Doubly Nudged Elastic Band method for finding transition states. If the "normal" energy of each system is \begin{equation} U(R) = \sum_{i,j} V( r_{ij} ), \end{equation} where $r_{ij}$ is the distance between the $i$th and $j$th particles in $R$ and the $V(r)$ is a standard pair potential, and if the two sets of positions, $R_0$ and $R_1$, are coupled via the potential \begin{equation} U_\mathrm{spr}(R_0,R_1) = \frac 12 k_\mathrm{spr} \left| R_1 - R_0 \right|^2, \end{equation} so that the total energy of the system is \begin{equation} U_\mathrm{total} = U(R_0) + U(R_1) + U_\mathrm{spr}(R_0,R_1). \end{equation}
energy_fn = harmonic_morse_pair(displacement,D0=5.0,alpha=10.0,r0=0.5,k=500.0) def spring_energy_fn(Rall, k_spr=50.0, **kwargs): metric = vmap(space.canonicalize_displacement_or_metric(displacement), (0, 0), 0) dr = metric(Rall[0],Rall[1]) return 0.5*k_spr*np.sum((dr)**2) def total_energy_fn(Rall, **kwargs): return np.sum(vmap(energy_fn)(Rall)) + spring_energy_fn(Rall)
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
We now have to define a new shift function that can handle arrays of shape $(2,N,d)$. In addition, we make two copies of our initial positions R, one for each system.
def shift_all(Rall, dRall, **kwargs): return vmap(shift)(Rall, dRall) Rall = np.array([R,R])
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Now, all we have to do is pass our custom energy and shift functions, as well as the $(2,N,d)$ dimensional initial position, to JAX MD, and proceed as normal. As a demonstration, we define a simple and general Brownian Dynamics simulation function, similar to the simulation routines above except without the special cases (e.g. chaning r0 or species).
def run_brownian_simple(energy_or_force, R_init, shift, key, num_steps): init, apply = simulate.brownian(energy_or_force, shift, dt=0.00001, kT=1.0, gamma=0.1) apply = jit(apply) @jit def scan_fn(state, t): return apply(state), 0 key, split = random.split(key) state = init(split, R_init) state, _ = lax.scan(scan_fn, state, np.arange(num_steps)) return state.position
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
Note that nowhere in this function is there any indication that we are simulating an ensemble of systems. This comes entirely form the inputs: i.e. the energy function, the shift function, and the set of initial positions.
key, split = random.split(key) Rall_final = run_brownian_simple(total_energy_fn, Rall, shift_all, split, num_steps=10000)
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
The output also has shape $(2,N,d)$. If we display the results, we see that the two systems are in similar, but not identical, positions, showing that we have succeeded in simulating a coupled ensemble.
for Ri in Rall_final: plot_system( Ri, box_size ) finalize_plot((0.5,0.5))
notebooks/customizing_potentials_cookbook.ipynb
google/jax-md
apache-2.0
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืชื•ื›ืœื• ืœื™ืฆื•ืจ ื‘ืขืฆืžื›ื ืคื•ื ืงืฆื™ื” ืฉื™ื•ืฆืจืช ืžืฉืชืžืฉ ื—ื“ืฉ?<br> ื–ื” ืœื ืžืกื•ื‘ืš ืžื“ื™: </p>
def create_user(first_name, last_name, nickname, current_age): return { 'first_name': first_name, 'last_name': last_name, 'nickname': nickname, 'age': current_age, } # ื ืงืจื ืœืคื•ื ืงืฆื™ื” ื›ื“ื™ ืœืจืื•ืช ืฉื”ื›ืœ ืขื•ื‘ื“ ื›ืžืฆื•ืคื” new_user = create_user('Bayta', 'Darell', 'Bay', 24) print(new_user)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> <mark>ื ื•ื›ืœ ื’ื ืœืžืžืฉ ืคื•ื ืงืฆื™ื•ืช ืฉื™ืขื–ืจื• ืœื ื• ืœื‘ืฆืข ืคืขื•ืœื•ืช ืขืœ ื›ืœ ืื—ื“ ืžื”ืžืฉืชืžืฉื™ื.</mark><br> ืœื“ื•ื’ืžื”: ื”ืคื•ื ืงืฆื™ื” <var>describe_as_a_string</var> ืชืงื‘ืœ ืžืฉืชืžืฉ ื•ืชื—ื–ื™ืจ ืœื ื• ืžื—ืจื•ื–ืช ืฉืžืชืืจืช ืื•ืชื•,<br> ื•ื”ืคื•ื ืงืฆื™ื” <var>celeberate_birthday</var> ืชืงื‘ืœ ืžืฉืชืžืฉ ื•ืชื’ื“ื™ืœ ืืช ื’ื™ืœื• ื‘ึพ1: </p>
def describe_as_a_string(user): first_name = user['first_name'] last_name = user['last_name'] full_name = f'{first_name} {last_name}' nickname = user['nickname'] age = user['age'] return f'{nickname} ({full_name}) is {age} years old.' def celebrate_birthday(user): user['age'] = user['age'] + 1 print(describe_as_a_string(new_user)) celebrate_birthday(new_user) print("--- After birthday") print(describe_as_a_string(new_user))
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<div class="align-center" style="display: flex; text-align: right; direction: rtl;"> <div style="display: flex; width: 10%; float: right; "> <img src="images/recall.svg" style="height: 50px !important;" alt="ืชื–ื›ื•ืจืช" title="ืชื–ื›ื•ืจืช"> </div> <div style="width: 90%"> <p style="text-align: right; direction: rtl;"> ื”ืฆืœื—ื ื• ืœืขืจื•ืš ืืช ืขืจื›ื• ืฉืœ <code>user['age']</code> ืžื‘ืœื™ ืœื”ื—ื–ื™ืจ ืขืจืš, ื›ื™ื•ื•ืŸ ืฉืžื™ืœื•ื ื™ื ื”ื mutable.<br> ืื ื–ื” ื ืจืื” ืœื›ื ืžื•ื–ืจ, ื—ื–ืจื• ืœืžื—ื‘ืจืช ืขืœ mutability ื•ึพimmutability. </p> </div> </div> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืฉืœื‘ ื”ื–ื” ื‘ืชื•ื›ื ื™ืชื ื• ืงื™ื™ืžื•ืช ืงื‘ื•ืฆืช ืคื•ื ืงืฆื™ื•ืช ืฉืžื˜ืจืชืŸ ื”ื™ื ื ื™ื”ื•ืœ ืฉืœ ืžืฉืชืžืฉื™ื ื•ืฉืœ ืชื›ื•ื ื•ืชื™ื”ื.<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื•ื›ืœ ืœื”ื•ืกื™ืฃ ืœืžืฉืชืžืฉ ืชื›ื•ื ื•ืช ื ื•ืกืคื•ืช, ื›ืžื• ื“ื•ื"ืœ ื•ืžืฉืงืœ, ืœื“ื•ื’ืžื”,<br> ืื• ืœื”ื•ืกื™ืฃ ืœื• ืคืขื•ืœื•ืช ืฉื™ื”ื™ื” ืืคืฉืจ ืœื‘ืฆืข ืขืœื™ื•, ื›ืžื• ื”ืคืขื•ืœื” <var>eat_bourekas</var>, ืฉืžื•ืกื™ืคื” ืœืชื›ื•ื ืช ื”ืžืฉืงืœ ืฉืœ ื”ืžืฉืชืžืฉ ื—ืฆื™ ืงื™ืœื•.<br> </p> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื—ืกืจื•ื ื•ืช</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืืฃ ืขืœ ืคื™ ืฉื”ืจืขื™ื•ืŸ ื ื—ืžื“, ื›ื›ืœ ืฉื ืจื‘ื” ืœื”ื•ืกื™ืฃ ืคืขื•ืœื•ืช ื•ืชื›ื•ื ื•ืช, ืชื’ื‘ืจ ืชื—ื•ืฉืช ื”ืื™ึพืกื“ืจ ืฉืื•ืคืคืช ืืช ื”ืงื•ื“ ื”ื–ื”.<br> ืงืœ ืœืจืื•ืช ืฉื”ืงื•ื“ ืฉื›ืชื‘ื ื• ืžืคื•ื–ืจ ืขืœ ืคื ื™ ืคื•ื ืงืฆื™ื•ืช ืจื‘ื•ืช ื‘ืฆื•ืจื” ืœื ืžืื•ืจื’ื ืช.<br> ื‘ืžื™ืœื™ื ืื—ืจื•ืช โ€“ ืื™ืŸ ืืฃ ืžื‘ื ื” ื‘ืงื•ื“ ืฉืชื—ืชื™ื• ืžืื•ื’ื“ื•ืช ื›ืœ ื”ืคื•ื ืงืฆื™ื•ืช ื•ื”ืชื›ื•ื ื•ืช ืฉืฉื™ื™ื›ื•ืช ืœื˜ื™ืคื•ืœ ื‘ืžืฉืชืžืฉ. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื‘ืขื™ื” ืชืฆื•ืฃ ื›ืฉื ืจืฆื” ืœื”ื•ืกื™ืฃ ืœืชื•ื›ื ื” ืฉืœื ื• ืขื•ื“ ืžื‘ื ื™ื ืฉื›ืืœื•.<br> ืœื“ื•ื’ืžื”, ื›ืฉื ืจืฆื” ืœื”ื•ืกื™ืฃ ืœืฆ'ื™ืงืฆ'ื•ืง ื™ื›ื•ืœืช ืœื ื™ื”ื•ืœ ืกืจื˜ื•ื ื™ื โ€“ ืฉืชื›ื•ื ื•ืชื™ื”ื ืื•ืจืš ืกืจื˜ื•ืŸ ื•ืžืกืคืจ ืœื™ื™ืงื™ื, ื•ื”ืคืขื•ืœื” ืขืœื™ื”ื ื”ื™ื ื”ื™ื›ื•ืœืช ืœืขืฉื•ืช Like ืœืกืจื˜ื•ืŸ.<br> ื”ืงื•ื“ ืœื ื™ื”ื•ืœ ื”ืžืฉืชืžืฉ ื•ื”ืงื•ื“ ืœื ื™ื”ื•ืœ ื”ืกืจื˜ื•ื ื™ื ืขืœื•ืœื™ื ืœื”ืชืขืจื‘ื‘, ื™ื•ื•ืฆืจื• ืชืœื•ื™ื•ืช ื‘ื™ื ื™ื”ื ื•ื—ื•ื•ื™ื™ืช ื”ื”ืชืžืฆืื•ืช ื‘ืงื•ื“ ืชื”ืคื•ืš ืœืœื ื ืขื™ืžื” ื‘ืขืœื™ืœ.<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื—ื•ืกืจ ื‘ืื™ื’ื•ื“ ื”ืชื›ื•ื ื•ืช ื•ื”ืคื•ื ืงืฆื™ื•ืช ืืฃ ืžืงืฉื” ืขืœ ื”ืงื•ืจื ืœื”ื‘ื™ืŸ ืœืืŸ ืฉื™ื™ื›ื•ืช ื›ืœ ืื—ืช ืžื”ืชื›ื•ื ื•ืช ื•ื”ืคื•ื ืงืฆื™ื•ืช, ื•ืžื” ืชืคืงื™ื“ืŸ ื‘ืงื•ื“.<br> ืžื™ ืฉืžืกืชื›ืœ ืขืœ ื”ืงื•ื“ ืฉืœื ื• ืœื ื™ื›ื•ืœ ืœื”ื‘ื™ืŸ ืžื™ื™ื“ ืฉึพ<var>describe_as_a_string</var> ืžื™ื•ืขื“ืช ืœืคืขื•ืœ ืจืง ืขืœ ืžื‘ื ื™ื ืฉื ื•ืฆืจื• ืžึพ<var>create_user</var>.<br> ื”ื•ื ืขืœื•ืœ ืœื ืกื•ืช ืœื”ื›ื ื™ืก ืžื‘ื ื™ื ืื—ืจื™ื ื•ืœื”ืงืจื™ืก ืืช ื”ืชื•ื›ื ื™ืช, ืื• ื’ืจื•ืข ืžื›ืš โ€“ ืœื”ื™ืชืงืœ ื‘ื‘ืื’ื™ื ื‘ืขืชื™ื“, ื‘ืขืงื‘ื•ืช ืฉื™ืžื•ืฉ ืœื ื ื›ื•ืŸ ื‘ืคื•ื ืงืฆื™ื”. </p> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื”ื’ื“ืจื”</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืžื”ืœืš ื”ืžื—ื‘ืจืช ืจืื™ื ื• ื“ื•ื’ืžืื•ืช ืœืžื‘ื ื™ื ืฉื”ื’ื“ืจื ื• <mark>ื›ืื•ืกืคื™ื ืฉืœ ืชื›ื•ื ื•ืช ื•ืฉืœ ืคืขื•ืœื•ืช</mark>.<br> ืžืฉืชืžืฉ ื‘ืืคืœื™ืงืฆื™ื™ืช ืฆ'ื™ืงืฆ'ื•ืง, ืœื“ื•ื’ืžื”, ืžื•ืจื›ื‘ ืžื”ืชื›ื•ื ื•ืช ืฉื ืคืจื˜ื™, ืฉื ืžืฉืคื—ื”, ื›ื™ื ื•ื™ ื•ื’ื™ืœ, ื•ืžื”ืคืขื•ืœื•ืช "ื—ื’ื•ื’ ื™ื•ื ื”ื•ืœื“ืช" ื•"ืชืืจ ื›ืžื—ืจื•ื–ืช".<br> ื ื•ืจื” ืขืฉื•ื™ื” ืœื”ื™ื•ืช ืžื•ืจื›ื‘ืช ืžื”ืชื›ื•ื ื•ืช ืฆื‘ืข ื•ืžืฆื‘ (ื“ื•ืœืงืช ืื• ืœื), ื•ืžื”ืคืขื•ืœื•ืช "ื”ื“ืœืง ื ื•ืจื”" ื•"ื›ื‘ื” ื ื•ืจื”".<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> <dfn>ืžื—ืœืงื”</dfn> ื”ื™ื ื“ืจืš ืœืชืืจ ืœืคื™ื™ืชื•ืŸ ืื•ืกืฃ ื›ื–ื” ืฉืœ ืชื›ื•ื ื•ืช ื•ืฉืœ ืคืขื•ืœื•ืช, ื•ืœืื’ื“ ืื•ืชืŸ ืชื—ืช ืžื‘ื ื” ืื—ื“.<br> ืื—ืจื™ ืฉืชื™ืืจื ื• ื‘ืขื–ืจืช ืžื—ืœืงื” ืื™ืœื• ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช ืžืืคื™ื™ื ื•ืช ืขืฆื ืžืกื•ื™ื, ื ื•ื›ืœ ืœื”ืฉืชืžืฉ ื‘ื” ื›ื“ื™ ืœื™ื™ืฆืจ ื›ืžื” ืขืฆืžื™ื ื›ืืœื• ืฉื ืจืฆื”.<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื“ืžื™ื™ืŸ ืžื—ืœืงื” ื›ืžื• ืฉื‘ืœื•ื ื” โ€“ <mark>ืชื‘ื ื™ืช</mark> ืฉืžืชืืจืช ืื™ืœื• ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช ืžืืคื™ื™ื ื•ืช ืกื•ื’ ืขืฆื ืžืกื•ื™ื.<br> ืžื—ืœืงื” ืฉืขื•ืกืงืช ื‘ืžืฉืชืžืฉื™ื, ืœื“ื•ื’ืžื”, ืชืชืืจ ืขื‘ื•ืจ ืคื™ื™ืชื•ืŸ ืžืื™ืœื• ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช ืžื•ืจื›ื‘ ื›ืœ ืžืฉืชืžืฉ.<br> </p> <figure> <img src="images/user_class.svg?v=1" style="max-width: 650px; margin-right: auto; margin-left: auto; text-align: center;" alt="ื‘ืžืจื›ื– ื”ืชืžื•ื ื” ื ื™ืฆื‘ืช ืฆืœืœื™ืช ืฉืœ ืื“ื (ืžืฉืชืžืฉ). ื‘ืฆื“ ื™ืžื™ืŸ ืฉืœื• ื™ืฉ ืชื™ื‘ื” ืขื ื”ื›ื•ืชืจืช 'ืชื›ื•ื ื•ืช', ื•ื‘ืชื•ื›ื” ื”ืžื™ืœื™ื 'ืฉื ืคืจื˜ื™', 'ืฉื ืžืฉืคื—ื”', 'ื›ื™ื ื•ื™' ื•'ื’ื™ืœ'. ื‘ืฆื“ ืฉืžืืœ ืฉืœื• ื™ืฉ ืชื™ื‘ื” ื ื•ืกืคืช ื”ื ื•ืฉืืช ืืช ื”ื›ื•ืชืจืช 'ืคืขื•ืœื•ืช', ื•ื‘ืชื•ื›ื” ื”ืžื™ืœื™ื 'ื—ื’ื•ื’ ื™ื•ื ื”ื•ืœื“ืช' ื•'ืชืืจ ืžืฉืชืžืฉ'."/> <figcaption style="margin-top: 2rem; text-align: center; direction: rtl;">ืื™ื•ืจ ื”ืžืชืืจ ืืช ื”ืชื›ื•ื ื•ืช ื•ืืช ื”ืคืขื•ืœื•ืช ื”ืฉื™ื™ื›ื•ืช ืœืžื—ืœืงื” "ืžืฉืชืžืฉ".</figcaption> </figure> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืขื–ืจืช ืื•ืชื” ืžื—ืœืงืช ืžืฉืชืžืฉื™ื (ืื• ืฉื‘ืœื•ื ืช ืžืฉืชืžืฉื™ื, ืื ืชืจืฆื•), ื ื•ื›ืœ ืœื™ืฆื•ืจ ืžืฉืชืžืฉื™ื ืจื‘ื™ื.<br> ื›ืœ ืžืฉืชืžืฉ ืฉื ื™ืฆื•ืจ ื‘ืืžืฆืขื•ืช ื”ืฉื‘ืœื•ื ื” ื™ื™ืงืจื "<dfn>ืžื•ืคืข</dfn>" (ืื• <dfn>Instance</dfn>) โ€“ ื™ื—ื™ื“ื” ืื—ืช, ืขืฆืžืื™ืช, ืฉืžื›ื™ืœื” ืืช ื”ืชื›ื•ื ื•ืช ื•ื”ืคืขื•ืœื•ืช ืฉืชื™ืืจื ื•.<br> ืื ื—ื ื• ื ืฉืชืžืฉ ื‘ืžื—ืœืงื” ืฉื•ื‘ ื•ืฉื•ื‘ ื›ื“ื™ ืœื™ืฆื•ืจ ื›ืžื” ืžืฉืชืžืฉื™ื ืฉื ืจืฆื”, ื‘ื“ื™ื•ืง ื›ืžื• ืฉื ืฉืชืžืฉ ื‘ืฉื‘ืœื•ื ื”. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื™ืฉ ืขื•ื“ ื”ืจื‘ื” ืžื” ืœื”ื’ื™ื“ ื•ื”ืจื‘ื” ืžื” ืœื”ื’ื“ื™ืจ, ืื‘ืœ ื ืฉืžืข ืฉืžืชื—ืชื™ ืืชื›ื ืžืกืคื™ืง.<br> ื‘ื•ืื• ื ื™ื’ืฉ ืœืงื•ื“! </p> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื™ืฆื™ืจืช ืžื—ืœืงื•ืช</span> <span style="text-align: right; direction: rtl; float: right; clear: both;">ืžื—ืœืงื” ื‘ืกื™ืกื™ืช</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืจืืฉื™ืช, ื ื™ืฆื•ืจ ืืช ื”ืžื—ืœืงื” ื”ืคืฉื•ื˜ื” ื‘ื™ื•ืชืจ ืฉืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื‘ื ื•ืช, ื•ื ืงืจื ืœื” <var>User</var>.<br> ื‘ื”ืžืฉืš ื”ืžื—ื‘ืจืช ื ืจื—ื™ื‘ ืืช ื”ืžื—ืœืงื”, ื•ื”ื™ื ืชื”ื™ื” ื–ื• ืฉืžื˜ืคืœืช ื‘ื›ืœ ื”ืงืฉื•ืจ ื‘ืžืฉืชืžืฉื™ื ืฉืœ ืฆ'ื™ืงืฆ'ื•ืง: </p>
class User: pass
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<div class="align-center" style="display: flex; text-align: right; direction: rtl;"> <div style="display: flex; width: 10%; float: right; "> <img src="images/recall.svg" style="height: 50px !important;" alt="ืชื–ื›ื•ืจืช" title="ืชื–ื›ื•ืจืช"> </div> <div style="width: 90%"> <p style="text-align: right; direction: rtl;"> ื ื™ืกื™ื ื• ืœื™ืฆื•ืจ ืืช ื”ืžื‘ื ื” ื”ื›ื™ ืงืฆืจ ืฉืืคืฉืจ, ืื‘ืœ <code>class</code> ื—ื™ื™ื‘ ืœื”ื›ื™ืœ ืงื•ื“.<br> ื›ื“ื™ ืœืขืงื•ืฃ ืืช ื”ืžื’ื‘ืœื” ื”ื–ื•, ื”ืฉืชืžืฉื ื• ื‘ืžื™ืœืช ื”ืžืคืชื— <code>pass</code>, ืฉืื•ืžืจืช ืœืคื™ื™ืชื•ืŸ "ืืœ ืชืขืฉื™ ื›ืœื•ื". </p> </div> </div> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืงื•ื“ ืฉืœืžืขืœื” ื”ืฉืชืžืฉื ื• ื‘ืžื™ืœืช ื”ืžืคืชื— <code>class</code> ื›ื“ื™ ืœื”ืฆื”ื™ืจ ืขืœ ืžื—ืœืงื” ื—ื“ืฉื”.<br> ืžื™ื™ื“ ืœืื—ืจ ืžื›ืŸ ืฆื™ื™ื ื• ืืช ืฉื ื”ืžื—ืœืงื” ืฉืื ื—ื ื• ืจื•ืฆื™ื ืœื™ืฆื•ืจ โ€“ <var>User</var> ื‘ืžืงืจื” ืฉืœื ื•.<br> ืฉื ื”ืžื—ืœืงื” ื ืชื•ืŸ ืœื—ืœื•ื˜ื™ืŸ ืœื‘ื—ื™ืจืชื ื•, ื•ื”ืžื™ืœื” <var>User</var> ืœื ืื•ืžืจืช ืœืคื™ื™ืชื•ืŸ ืฉื•ื ื“ื‘ืจ ืžื™ื•ื—ื“. ื‘ืื•ืชื” ื”ืžื™ื“ื” ื™ื›ื•ืœื ื• ืœื‘ื—ื•ืจ ื›ืœ ืฉื ืื—ืจ. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื“ื‘ืจ ืฉื—ืฉื•ื‘ ืœื–ื›ื•ืจ ื”ื•ื ืฉื”ืžื—ืœืงื” ื”ื™ื <em>ืœื</em> ื”ืžืฉืชืžืฉ ืขืฆืžื•, ืืœื ืจืง ื”ืฉื‘ืœื•ื ื” ืฉืœืคื™ื” ืคื™ื™ืชื•ืŸ ืชื‘ื ื” ืืช ื”ืžืฉืชืžืฉ.<br> ืืžื ื ื›ืจื’ืข ื”ืžื—ืœืงื” <var>User</var> ืจื™ืงื” ื•ืœื ืžืชืืจืช ื›ืœื•ื, ืื‘ืœ ืคื™ื™ืชื•ืŸ ืขื“ื™ื™ืŸ ืชื“ืข ืœื™ืฆื•ืจ ืžืฉืชืžืฉ ื—ื“ืฉ ืื ื ื‘ืงืฉ ืžืžื ื” ืœืขืฉื•ืช ื–ืืช.<br> ื ื‘ืงืฉ ืžื”ืžื—ืœืงื” ืœื™ืฆื•ืจ ืขื‘ื•ืจื ื• ืžืฉืชืžืฉ ื—ื“ืฉ. ื ืงืจื ืœื” ื‘ืฉืžื” ื•ื ื•ืกื™ืฃ ืกื•ื’ืจื™ื™ื, ื‘ื“ื•ืžื” ืœืงืจื™ืื” ืœืคื•ื ืงืฆื™ื”: </p>
user1 = User()
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื›ืขืช ื™ืฆืจื ื• ืžืฉืชืžืฉ, ื•ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืฉื ื•ืช ืืช ื”ืชื›ื•ื ื•ืช ืฉืœื•.<br> ืžื‘ื—ื™ื ื” ืžื™ืœื•ืœื™ืช, ื ื”ื•ื’ ืœื”ื’ื™ื“ ืฉื™ืฆืจื ื• <dfn>ืžื•ืคืข</dfn> (<dfn>Instance</dfn>) ืื• <dfn>ืขืฆื</dfn> (ืื•ื‘ื™ื™ืงื˜, <dfn>Object</dfn>) ืžืกื•ื’ <var>User</var>, ืฉืฉืžื• <var>user1</var>.<br> ื”ืฉืชืžืฉื ื• ืœืฉื ื›ืš ื‘<dfn>ืžื—ืœืงื”</dfn> ื‘ืฉื <var>User</var>. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ืฉื ื” ืืช ืชื›ื•ื ื•ืช ื”ืžืฉืชืžืฉ.<br> ื›ื“ื™ ืœื”ืชื™ื™ื—ืก ืœืชื›ื•ื ื” ืฉืœ ืžื•ืคืข ื›ืœืฉื”ื• ื‘ืคื™ื™ืชื•ืŸ, ื ื›ืชื•ื‘ ืืช ืฉื ื”ืžืฉืชื ื” ืฉืžืฆื‘ื™ืข ืœืžื•ืคืข, ื ืงื•ื“ื”, ื•ืื– ืฉื ื”ืชื›ื•ื ื”.<br> ืื ื ืจืฆื” ืœืฉื ื•ืช ืืช ื”ืชื›ื•ื ื” โ€“ ื ื‘ืฆืข ืืœื™ื” ื”ืฉืžื”: </p>
user1.first_name = "Miles" user1.last_name = "Prower" user1.age = 8 user1.nickname = "Tails"
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื•ื›ืœ ืœืื—ื–ืจ ืืช ื”ืชื›ื•ื ื•ืช ื”ืœืœื• ื‘ืงืœื•ืช, ื‘ืื•ืชื” ื”ืฆื•ืจื”: </p>
print(user1.age)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื•ืื ื ื‘ื“ื•ืง ืžื” ื”ืกื•ื’ ืฉืœ ื”ืžืฉืชื ื” <var>user1</var>, ืžืฆืคื” ืœื ื• ื”ืคืชืขื” ื ื—ืžื“ื”: </p>
type(user1)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืื™ื–ื” ื™ื•ืคื™! ื”ืžื—ืœืงื” ื’ืจืžื” ืœื›ืš ืฉึพ<var>User</var> ื”ื•ื ืžืžืฉ ืกื•ื’ ืžืฉืชื ื” ื‘ืคื™ื™ืชื•ืŸ ืขื›ืฉื™ื•.<br> ืงื—ื• ืœืขืฆืžื›ื ืจื’ืข ืœื”ืชืคืขืœ โ€“ ื™ืฆืจื ื• ืกื•ื’ ืžืฉืชื ื” ื—ื“ืฉ ื‘ืคื™ื™ืชื•ืŸ!<br> ืื ื›ืš, ื”ืžืฉืชื ื” <var>user1</var> ืžืฆื‘ื™ืข ืขืœ ืžื•ืคืข ืฉืœ ืžืฉืชืžืฉ, ืฉืกื•ื’ื• <var>User</var>. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื ืกื” ืœื™ืฆื•ืจ ืžื•ืคืข ื ื•ืกืฃ, ื”ืคืขื ืฉืœ ืžืฉืชืžืฉ ืื—ืจ: </p>
user2 = User() user2.first_name = "Harry" user2.last_name = "Potter" user2.age = 39 user2.nickname = "BoyWhoLived1980"
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื•ื ืฉื™ื ืœื‘ ืฉืฉื ื™ ื”ืžื•ืคืขื™ื ืžืชืงื™ื™ืžื™ื ื–ื” ืœืฆื“ ื–ื”, ื•ืœื ื“ื•ืจืกื™ื ืืช ื”ืขืจื›ื™ื ื–ื” ืฉืœ ื–ื”: </p>
print(f"{user1.first_name} {user1.last_name} is {user1.age} years old.") print(f"{user2.first_name} {user2.last_name} is {user2.age} years old.")
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ืžืฆื‘ ื”ื–ื” ืžืชืงื™ื™ื ื›ื™ื•ื•ืŸ ืฉื›ืœ ืงืจื™ืื” ืœืžื—ืœืงื” <var>User</var> ื™ื•ืฆืจืช ืžื•ืคืข ื—ื“ืฉ ืฉืœ ืžืฉืชืžืฉ.<br> ื›ืœ ืื—ื“ ืžื”ืžื•ืคืขื™ื ื”ื•ื ื™ืฉื•ืช ื ืคืจื“ืช ืฉืžืชืงื™ื™ืžืช ื‘ื–ื›ื•ืช ืขืฆืžื”. </p> <div class="align-center" style="display: flex; text-align: right; direction: rtl; clear: both;"> <div style="display: flex; width: 10%; float: right; clear: both;"> <img src="images/exercise.svg" style="height: 50px !important;" alt="ืชืจื’ื•ืœ"> </div> <div style="width: 70%"> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฆืจื• ืžื—ืœืงื” ื‘ืฉื <var>Point</var> ืฉืžื™ื™ืฆื’ืช ื ืงื•ื“ื”.<br> ืฆืจื• 2 ืžื•ืคืขื™ื ืฉืœ ื ืงื•ื“ื•ืช: ืื—ืช ื‘ืขืœืช <var>x</var> ืฉืขืจื›ื• 3 ื•ึพ<var>y</var> ืฉืขืจื›ื• 1, ื•ื”ืฉื ื™ื™ื” ื‘ืขืœืช <var>x</var> ืฉืขืจื›ื• 4 ื•ึพ<var>y</var> ืฉืขืจื›ื• 1. </p> </div> <div style="display: flex; width: 20%; border-right: 0.1rem solid #A5A5A5; padding: 1rem 2rem;"> <p style="text-align: center; direction: rtl; justify-content: center; align-items: center; clear: both;"> <strong>ื—ืฉื•ื‘!</strong><br> ืคืชืจื• ืœืคื ื™ ืฉืชืžืฉื™ื›ื•! </p> </div> </div> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฉืžื•ืช ืžื—ืœืงื” ื™ื™ื›ืชื‘ื• ื‘ืื•ืช ื’ื“ื•ืœื” ื‘ืชื—ื™ืœืชื, ื›ื“ื™ ืœื”ื‘ื“ื™ืœื ืžืคื•ื ืงืฆื™ื•ืช ื•ืžืžืฉืชื ื™ื ืจื’ื™ืœื™ื.<br> ืื ืฉื ื”ืžื—ืœืงื” ืžื•ืจื›ื‘ ืžื›ืžื” ืžื™ืœื™ื, ื”ืื•ืช ื”ืจืืฉื•ื ื” ื‘ื›ืœ ืžื™ืœื” ืชื”ื ืื•ืช ื’ื“ื•ืœื”. ื‘ืฉื ืœื ื™ื•ืคื™ืขื• ืงื•ื•ื™ื ืชื—ืชื•ื ื™ื.<br> ืœื“ื•ื’ืžื”, ืžื—ืœืงืช <var>PopSong</var>. </p> <span style="text-align: right; direction: rtl; float: right; clear: both;">ืžื—ืœืงื” ืขื ืคืขื•ืœื•ืช</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื™ืฆื™ืจืช ืžื—ืœืงื” ืจื™ืงื” ื–ื” ื ื—ืžื“, ืื‘ืœ ื–ื” ืœื ืžืจื’ื™ืฉ ืฉืขืฉื™ื ื• ืฆืขื“ ืžืกืคื™ืง ืžืฉืžืขื•ืชื™ ื›ื“ื™ ืœืฉืคืจ ืืช ืื™ื›ื•ืช ื”ืงื•ื“ ืžืชื—ื™ืœืช ื”ืžื—ื‘ืจืช.<br> ืœื“ื•ื’ืžื”, ืื ืื ื—ื ื• ืจื•ืฆื™ื ืœื”ื“ืคื™ืก ืืช ื”ืคืจื˜ื™ื ืฉืœ ืžืฉืชืžืฉ ืžืกื•ื™ื, ืขื“ื™ื™ืŸ ื ืฆื˜ืจืš ืœื›ืชื•ื‘ ืคื•ื ืงืฆื™ื” ื›ื–ื•: </p>
def describe_as_a_string(user): full_name = f'{user.first_name} {user.last_name}' return f'{user.nickname} ({full_name}) is {user.age} years old.' print(describe_as_a_string(user2))
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ืคื•ื ืงืฆื™ื” ืขื“ื™ื™ืŸ ืžืกืชื•ื‘ื‘ืช ืœื” ื—ื•ืคืฉื™ื™ื” ื•ืœื ืžืื•ื’ื“ืช ืชื—ืช ืืฃ ืžื‘ื ื” โ€“ ื•ื–ื” ื‘ื“ื™ื•ืง ื”ืžืฆื‘ ืฉื ื™ืกื™ื ื• ืœืžื ื•ืข.<br> ืœืžื–ืœื ื• ื”ืคืชืจื•ืŸ ืœื‘ืขื™ื™ืช ืื™ื’ื•ื“ ื”ืงื•ื“ ื”ื•ื ืคืฉื•ื˜. ื ื•ื›ืœ ืœื”ื“ื‘ื™ืง ืืช ืงื•ื“ ื”ืคื•ื ืงืฆื™ื” ืชื—ืช ื”ืžื—ืœืงื” <code>User</code>: </p>
class User: def describe_as_a_string(user): full_name = f'{user.first_name} {user.last_name}' return f'{user.nickname} ({full_name}) is {user.age} years old.' user3 = User() user3.first_name = "Anthony John" user3.last_name = "Soprano" user3.age = 61 user3.nickname = "Tony"
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืชื ืฉืœืžืขืœื” ื”ื’ื“ืจื ื• ืืช ื”ืคื•ื ืงืฆื™ื” <var>describe_as_a_string</var> ื‘ืชื•ืš ื”ืžื—ืœืงื” <var>User</var>.<br> ืคื•ื ืงืฆื™ื” ืฉืžื•ื’ื“ืจืช ื‘ืชื•ืš ืžื—ืœืงื” ื ืงืจืืช <dfn>ืคืขื•ืœื”</dfn> (<dfn>Method</dfn>), ืฉื ืฉื ื™ืชืŸ ืœื” ื›ื“ื™ ืœื‘ื“ืœ ืื•ืชื” ืžื™ืœื•ืœื™ืช ืžืคื•ื ืงืฆื™ื” ืจื’ื™ืœื”. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืœืžืขืฉื”, ื‘ืชื ืฉืœืžืขืœื” ื”ื•ืกืคื ื• ืืช ื”ืคืขื•ืœื” <var>describe_as_a_string</var> ืœืฉื‘ืœื•ื ื” ืฉืœ ื”ืžืฉืชืžืฉ.<br> ืžืขื›ืฉื™ื•, ื›ืœ ืžื•ืคืข ื—ื“ืฉ ืฉืœ ืžืฉืชืžืฉ ื™ื•ื›ืœ ืœืงืจื•ื ืœืคืขื•ืœื” <var>describe_as_a_string</var> ื‘ืฆื•ืจื” ื”ื‘ืื”: </p>
user3.describe_as_a_string()
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื—ื“ื™ ื”ืขื™ืŸ ืฉืžื• ื•ื“ืื™ ืœื‘ ืœืžืฉื”ื• ืžืขื˜ ืžืฉื•ื ื” ื‘ืงืจื™ืื” ืœืคืขื•ืœื” <var>describe_as_a_string</var>.<br> ื”ืคืขื•ืœื” ืžืฆืคื” ืœืงื‘ืœ ืคืจืžื˜ืจ (ืงืจืื ื• ืœื• <var>user</var>), ืื‘ืœ ื›ืฉืงืจืื ื• ืœื” ื‘ืชื ื”ืื—ืจื•ืŸ ืœื ื”ืขื‘ืจื ื• ืœื” ืืฃ ืืจื’ื•ืžื ื˜!<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื–ื”ื• ืงืกื ื™ื“ื•ืข ื•ื ื—ืžื“ ืฉืœ ืžื—ืœืงื•ืช: ื›ืฉืžื•ืคืข ืงื•ืจื ืœืคืขื•ืœื” ื›ืœืฉื”ื™ โ€“ ืื•ืชื• ืžื•ืคืข ืขืฆืžื• ืžื•ืขื‘ืจ ืื•ื˜ื•ืžื˜ื™ืช ื›ืืจื’ื•ืžื ื˜ ื”ืจืืฉื•ืŸ ืœืคืขื•ืœื”.<br> ืœื“ื•ื’ืžื”, ื‘ืงืจื™ืื” <code dir="ltr">user3.describe_as_a_string()</code>, ื”ืžื•ืคืข <var>user3</var> ื”ื•ืขื‘ืจ ืœืชื•ืš ื”ืคืจืžื˜ืจ <var>user</var> ืฉืœ <var>describe_as_a_string</var>.<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ืžื•ืกื›ืžื” ื”ื™ื ืœืงืจื•ื ืชืžื™ื“ ืœืคืจืžื˜ืจ ื”ืงืกื•ื ื”ื–ื”, ื–ื” ืฉื”ื•ืœืš ืœืงื‘ืœ ืืช ื”ืžื•ืคืข, ื‘ืฉื <var>self</var>.<br> ื ืฉื ื” ืืช ื”ื”ื’ื“ืจื” ืฉืœื ื• ื‘ื”ืชืื ืœืžื•ืกื›ืžื”: </p>
class User: def describe_as_a_string(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' user3 = User() user3.first_name = "Anthony John" user3.last_name = "Soprano" user3.age = 61 user3.nickname = "Tony" user3.describe_as_a_string()
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<div class="align-center" style="display: flex; text-align: right; direction: rtl;"> <div style="display: flex; width: 10%; float: right; "> <img src="images/warning.png" style="height: 50px !important;" alt="ืื–ื”ืจื”!"> </div> <div style="width: 90%"> <p style="text-align: right; direction: rtl;"> ื˜ืขื•ืช ื ืคื•ืฆื” ื”ื™ื ืœืฉื›ื•ื— ืœืฉื™ื <var>self</var> ื›ืคืจืžื˜ืจ ื”ืจืืฉื•ืŸ ื‘ืคืขื•ืœื•ืช ืฉื ื’ื“ื™ืจ. </p> </div> </div> <div class="align-center" style="display: flex; text-align: right; direction: rtl; clear: both;"> <div style="display: flex; width: 10%; float: right; clear: both;"> <img src="images/exercise.svg" style="height: 50px !important;" alt="ืชืจื’ื•ืœ"> </div> <div style="width: 70%"> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฆืจื• ืคืขื•ืœื” ื‘ืฉื <var>describe_as_a_string</var> ืขื‘ื•ืจ ืžื—ืœืงืช <var>Point</var> ืฉื™ืฆืจืชื.<br> ื”ืคืขื•ืœื” ืชื—ื–ื™ืจ ืžื—ืจื•ื–ืช ื‘ืฆื•ืจืช <samp dir="ltr">(x, y)</samp>. </p> </div> <div style="display: flex; width: 20%; border-right: 0.1rem solid #A5A5A5; padding: 1rem 2rem;"> <p style="text-align: center; direction: rtl; justify-content: center; align-items: center; clear: both;"> <strong>ื—ืฉื•ื‘!</strong><br> ืคืชืจื• ืœืคื ื™ ืฉืชืžืฉื™ื›ื•! </p> </div> </div> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื™ืฆื™ืจืช ืžื•ืคืข</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ืคื™ืกื” ื”ื—ืกืจื” ื‘ืคืื–ืœ ื”ื™ื ื™ืฆื™ืจืช ื”ืžื•ืคืข.<br> ืื ื ืจืฆื” ืœื™ืฆื•ืจ ืžืฉืชืžืฉ ื—ื“ืฉ, ืขื“ื™ื™ืŸ ื ืฆื˜ืจืš ืœื”ืฆื™ื‘ ื‘ื• ืชื›ื•ื ื•ืช ืื—ืชึพืื—ืช โ€“ ื•ื–ื” ืœื ื›ื–ื” ื›ื™ืฃ.<br> ื ืฉื“ืจื’ ืืช ืขืฆืžื ื• ื•ื ื›ืชื•ื‘ ืคื•ื ืงืฆื™ื” ืฉืงื•ืจืืช ืœึพ<var>User</var> ื•ื™ื•ืฆืจืช ืžื•ืคืข ืขื ื›ืœ ื”ืชื›ื•ื ื•ืช ืฉืœื•:<br> </p>
def create_user(first_name, last_name, nickname, current_age): user = User() user.first_name = first_name user.last_name = last_name user.nickname = nickname user.age = current_age return user user4 = create_user('Daenerys', 'Targaryen', 'Mhysa', 23) print(f"{user4.first_name} {user4.last_name} is {user4.age} years old.")
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืื‘ืœ ื”ื’ื“ืจื” ืฉื›ื–ื•, ื›ืžื• ืฉื›ื‘ืจ ืืžืจื ื•, ืกื•ืชืจืช ืืช ื›ืœ ื”ืจืขื™ื•ืŸ ืฉืœ ืžื—ืœืงื•ืช.<br> ื”ืจื™ ื”ืžื˜ืจื” ืฉืœ ืžื—ืœืงื•ืช ื”ื™ื ืงื™ื‘ื•ืฅ ื›ืœ ืžื” ืฉืงืฉื•ืจ ื‘ื ื™ื”ื•ืœ ื”ืชื›ื•ื ื•ืช ื•ื”ืคืขื•ืœื•ืช ืชื—ืช ื”ืžื—ืœืงื”. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ืขืชื™ืง ืืช <var>create_user</var> ืœืชื•ืš ืžื—ืœืงืช <var>User</var>, ื‘ืฉื™ื ื•ื™ื™ื ืงืœื™ื: </p> <ol style="text-align: right; direction: rtl; float: right; clear: both;"> <li>ืœื ื ืฉื›ื— ืœืฉื™ื ืืช <var>self</var> ื›ืคืจืžื˜ืจ ืจืืฉื•ืŸ ื‘ื—ืชื™ืžืช ื”ืคืขื•ืœื”.</li> <li>ื›ืคื™ ืฉืจืื™ื ื•, ืคืขื•ืœื•ืช ื‘ืžื—ืœืงื” ืžืงื‘ืœื•ืช ืžื•ืคืข ื•ืขื•ื‘ื“ื•ืช ื™ืฉื™ืจื•ืช ืขืœื™ื•, ื•ืœื›ืŸ ื ืฉืžื™ื˜ ืืช ื”ืฉื•ืจื•ืช <code dir="ltr">user = User()</code> ื•ึพ<code dir="ltr">return user</code>.</li> </ol>
class User: def describe_as_a_string(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' def create_user(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืขื›ืฉื™ื• ื ื•ื›ืœ ืœื™ืฆื•ืจ ืžืฉืชืžืฉ ื—ื“ืฉ, ื‘ืฆื•ืจื” ื”ื—ื‘ื™ื‘ื” ื•ื”ืžืงื•ืฆืจืช ื”ื‘ืื”: </p>
user4 = User() user4.create_user('Daenerys', 'Targaryen', 'Mhysa', 23) user4.describe_as_a_string()
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<span style="text-align: right; direction: rtl; float: right; clear: both;">ืชืจื’ื™ืœ ื‘ื™ื ื™ื™ื: ืžื—ืœืงืช ื ืงื•ื“ื•ืช</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืžื™ื ืจื•ื•ื” ืžืงื’ื•ื ื’ืœ ื™ืฆืื” ืœื‘ื™ืœื•ื™ ืœื™ืœื™ ื‘ืกืžื˜ืช ื“ื™ืื’ื•ืŸ,<br> ื•ืื—ืจื™ ืœื™ืœื” ืขืžื•ืก ื‘ืฉืชื™ื™ืช ืฉื™ื›ืจ ื‘ืงืœื—ืช ื”ืจื•ืชื—ืช, ื”ื™ื ืžืขื˜ ืžืชืงืฉื” ืœื—ื–ื•ืจ ืœื”ื•ื’ื•ื•ืจื˜ืก. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื•ืกื™ืคื• ืืช ื”ืคืขื•ืœื•ืช <var>create_point</var> ื•ึพ<var>distance</var> ืœืžื—ืœืงืช ื”ื ืงื•ื“ื” ืฉื™ืฆืจืชื.<br> ื”ืคืขื•ืœื” <var>create_point</var> ืชืงื‘ืœ ื›ืคืจืžื˜ืจื™ื <var>x</var> ื•ึพ<var>y</var>, ื•ืชื™ืฆื•ืง ืชื•ื›ืŸ ืœืžื•ืคืข ืฉื™ืฆืจืชื.<br> ื”ืคืขื•ืœื” <var>distance</var> ืชื—ื–ื™ืจ ืืช ื”ืžืจื—ืง ืฉืœ ืžืงื’ื•ื ื’ืœ ืžื”ื•ื’ื•ื•ืจื˜ืก, ื”ืžืžื•ืงื ื‘ื ืงื•ื“ื” <span dir="ltr">(0, 0)</span>. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื•ืกื—ืช ื”ืžืจื—ืง ื”ื™ื ื—ื™ื‘ื•ืจ ื‘ื™ืŸ ื”ืขืจื›ื™ื ื”ืžื•ื—ืœื˜ื™ื ืฉืœ ื ืงื•ื“ื•ืช ื”ึพ<var>x</var> ื•ื”ึพ<var>y</var>.<br> ืœื“ื•ื’ืžื”: </p> <ul style="text-align: right; direction: rtl; float: right; clear: both;"> <li>ื”ืžืจื—ืง ืžื”ื ืงื•ื“ื” <pre dir="ltr" style="display: inline; margin: 0 0.5em;">x = 5, y = 3</pre> ื”ื•ื <samp>8</samp>.</li> <li>ื”ืžืจื—ืง ืžื”ื ืงื•ื“ื” <pre dir="ltr" style="display: inline; margin: 0 0.5em;">x = 0, y = 3</pre> ื”ื•ื <samp>3</samp>.</li> <li>ื”ืžืจื—ืง ืžื”ื ืงื•ื“ื” <pre dir="ltr" style="display: inline; margin: 0 0.5em;">x = -3, y = 3</pre> ื”ื•ื <samp>6</samp>.</li> <li>ื”ืžืจื—ืง ืžื”ื ืงื•ื“ื” <pre dir="ltr" style="display: inline; margin: 0 0.5em;">x = -5, y = 0</pre> ื”ื•ื <samp>5</samp>.</li> <li>ื”ืžืจื—ืง ืžื”ื ืงื•ื“ื” <pre dir="ltr" style="display: inline; margin: 0 0.5em;">x = 0, y = 0</pre> ื”ื•ื <samp>0</samp>.</li> </ul> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื•ื“ืื• ืฉื”ืชื•ื›ื ื™ืช ืฉืœื›ื ืžื—ื–ื™ืจื” <samp dir="ltr">Success!</samp> ืขื‘ื•ืจ ื”ืงื•ื“ ื”ื‘ื: </p>
current_location = Point() current_location.create_point(5, 3) if current_location.distance() == 8: print("Success!")
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<span style="text-align: right; direction: rtl; float: right; clear: both;">ืคืขื•ืœื•ืช ืงืกื</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื›ื“ื™ ืœื”ืงืœ ืืคื™ืœื• ืขื•ื“ ื™ื•ืชืจ ืขืœ ื”ืžืœืื›ื”, ื‘ืคื™ื™ืชื•ืŸ ื™ืฉ <dfn>ืคืขื•ืœื•ืช ืงืกื</dfn> (<dfn>Magic Methods</dfn>).<br> ืืœื• ืคืขื•ืœื•ืช ืขื ืฉื ืžื™ื•ื—ื“, ืฉืื ื ื’ื“ื™ืจ ืื•ืชืŸ ื‘ืžื—ืœืงื”, ื”ืŸ ื™ืฉื ื• ืืช ื”ื”ืชื ื”ื’ื•ืช ืฉืœื” ืื• ืฉืœ ื”ืžื•ืคืขื™ื ื”ื ื•ืฆืจื™ื ื‘ืขื–ืจืชื”. </p> <h4 style="text-align: right; direction: rtl; float: right; clear: both;">ื”ืคืขื•ืœื” <code>__str__</code></h4> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ืชื—ื™ืœ, ืœื“ื•ื’ืžื”, ืžื”ื™ื›ืจื•ืช ืงืฆืจื” ืขื ืคืขื•ืœืช ื”ืงืกื <code>__str__</code> (ืขื ืงื• ืชื—ืชื•ืŸ ื›ืคื•ืœ, ืžื™ืžื™ืŸ ื•ืžืฉืžืืœ ืœืฉื ื”ืคืขื•ืœื”).<br> ืื ื ื ืกื” ืกืชื ื›ื›ื” ืœื”ืžื™ืจ ืœืžื—ืจื•ื–ืช ืืช <var>user4</var> ืฉื™ืฆืจื ื• ืงื•ื“ื ืœื›ืŸ, ื ืงื‘ืœ ื‘ื”ืœื” ื•ื”ื™ืกื˜ืจื™ื”:
user4 = User() user4.create_user('Daenerys', 'Targaryen', 'Mhysa', 23) str(user4)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืคื™ื™ืชื•ืŸ ืืžื ื ืื•ืžืจืช ื“ื‘ืจื™ื ื ื›ื•ื ื™ื, ื›ืžื• ืฉืžื“ื•ื‘ืจ ื‘ืื•ื‘ื™ื™ืงื˜ (ืžื•ืคืข) ืžื”ืžื—ืœืงื” <var>User</var> ื•ืืช ื”ื›ืชื•ื‘ืช ืฉืœื• ื‘ื–ื™ื›ืจื•ืŸ, ืื‘ืœ ื–ื” ืœื ื‘ืืžืช ืžื•ืขื™ืœ.<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื›ื™ื•ื•ืŸ ืฉืคื•ื ืงืฆื™ื™ืช ื”ื”ื“ืคืกื” <var>print</var>, ืžืื—ื•ืจื™ ื”ืงืœืขื™ื, ืžื‘ืงืฉืช ืืช ืฆื•ืจืช ื”ืžื—ืจื•ื–ืช ืฉืœ ื”ืืจื’ื•ืžื ื˜ ืฉืžื•ืขื‘ืจ ืืœื™ื”,<br> ื’ื ืงืจื™ืื” ืœึพ<var>print</var> ื™ืฉื™ืจื•ืช ืขืœ <var>user4</var> ืชื™ืฆื•ืจ ืืช ืื•ืชื” ืชื•ืฆืื” ืœื ืกืกื’ื•ื ื™ืช: </p>
print(user4)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ืžื—ืœืงื” ืฉืœื ื•, ื›ืžื•ื‘ืŸ, ื›ื‘ืจ ืขืจื•ื›ื” ืœื”ืชืžื•ื“ื“ ืขื ื”ืžืฆื‘.<br> ื‘ื–ื›ื•ืช ื”ืคืขื•ืœื” <var>describe_as_a_string</var> ืฉื”ื’ื“ืจื ื• ืงื•ื“ื ืœื›ืŸ ื ื•ื›ืœ ืœื”ื“ืคื™ืก ืืช ืคืจื˜ื™ ื”ืžืฉืชืžืฉ ื‘ืงืœื•ืช ื™ื—ืกื™ืช: </p>
print(user4.describe_as_a_string())
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืื‘ืœ ื™ืฉ ื“ืจืš ืงืœื” ืขื•ื“ ื™ื•ืชืจ!<br> ื ื™ื—ืฉืชื ื ื›ื•ืŸ โ€“ ืคืขื•ืœืช ื”ืงืกื <code>__str__</code>.<br> ื ื—ืœื™ืฃ ืืช ื”ืฉื ืฉืœ ื”ืคืขื•ืœื” <var>describe_as_a_string</var>, ืœึพ<code>__str__</code>: </p>
class User: def __str__(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' def create_user(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age user5 = User() user5.create_user('James', 'McNulty', 'Jimmy', 49) print(user5)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืจืื• ืื™ื–ื” ืงืกื! ืขื›ืฉื™ื• ื”ืžืจื” ืฉืœ ื›ืœ ืžื•ืคืข ืžืกื•ื’ <var>User</var> ืœืžื—ืจื•ื–ืช ื”ื™ื ืคืขื•ืœื” ืžืžืฉ ืคืฉื•ื˜ื”!<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืชื ืฉืœืžืขืœื”, ื”ื’ื“ืจื ื• ืืช ืคืขื•ืœืช ื”ืงืกื <code>__str__</code>.<br> ื”ืคืขื•ืœื” ืžืงื‘ืœืช ื›ืคืจืžื˜ืจ ืืช <var>self</var>, ื”ืžื•ืคืข ืฉื‘ื™ืงืฉื ื• ืœื”ืžื™ืจ ืœืžื—ืจื•ื–ืช,<br> ื•ืžื—ื–ื™ืจื” ืœื ื• ืžื—ืจื•ื–ืช ืฉืื ื—ื ื• ื”ื’ื“ืจื ื• ื›ืžื—ืจื•ื–ืช ืฉืžืชืืจืช ืืช ื”ืžื•ืคืข. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื’ื“ืจืช ืคืขื•ืœืช ื”ืงืกื <code>__str__</code> ืขื‘ื•ืจ ืžื—ืœืงื” ืžืกื•ื™ืžืช ืžืืคืฉืจืช ืœื ื• ืœื”ืžื™ืจ ืžื•ืคืขื™ื ืœืžื—ืจื•ื–ื•ืช ื‘ืฆื•ืจื” ื˜ื‘ืขื™ืช. </p> <h4 style="text-align: right; direction: rtl; float: right; clear: both;">ื”ืคืขื•ืœื” <code>__init__</code></h4> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืคืขื•ืœืช ืงืกื ื—ืฉื•ื‘ื” ืืฃ ื™ื•ืชืจ, ื•ืื•ืœื™ ื”ืžืคื•ืจืกืžืช ื‘ื™ื•ืชืจ, ื ืงืจืืช <code>__init__</code>.<br> ื”ื™ื ืžืืคืฉืจืช ืœื ื• ืœื”ื’ื“ื™ืจ ืžื” ื™ืงืจื” ื‘ืจื’ืข ืฉื ื™ืฆื•ืจ ืžื•ืคืข ื—ื“ืฉ: </p>
class User: def __init__(self): print("New user has been created!") def __str__(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' def create_user(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age user5 = User() user5.create_user('Lorne', 'Malvo', 'Mick', 23) print(user5)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ื“ื•ื’ืžืช ื”ืงื•ื“ ืฉืœืžืขืœื” ื”ื’ื“ืจื ื• ืืช ืคืขื•ืœืช ื”ืงืกื <code>__init__</code>, ืฉืชืจื•ืฅ ืžื™ื™ื“ ื›ืฉื ื•ืฆืจ ืžื•ืคืข ื—ื“ืฉ.<br> ื”ื—ืœื˜ื ื• ืฉื‘ืจื’ืข ืฉื™ื™ื•ื•ืฆืจ ืžื•ืคืข ืฉืœ ืžืฉืชืžืฉ, ืชื•ื“ืคืก ื”ื”ื•ื“ืขื” <samp dir="ltr">New user has been created!</samp>. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื›ื™ืฃ ื”ื’ื“ื•ืœ ื‘ึพ<code>__init__</code> ื”ื•ื ื”ื™ื›ื•ืœืช ืฉืœื” ืœืงื‘ืœ ืคืจืžื˜ืจื™ื.<br> ื ื•ื›ืœ ืœื”ืขื‘ื™ืจ ืืœื™ื” ืืช ื”ืืจื’ื•ืžื ื˜ื™ื ื‘ืงืจื™ืื” ืœืฉื ื”ืžื—ืœืงื”, ื‘ืขืช ื™ืฆื™ืจืช ื”ืžื•ืคืข ๐Ÿคฏ </p>
class User: def __init__(self, message): self.creation_message = message print(self.creation_message) def __str__(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' def create_user(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age user5 = User("New user has been created!") # ืชืจืื• ืื™ื–ื” ืžื’ื ื™ื‘ user5.create_user('Lorne', 'Malvo', 'Mick', 58) print(user5) print(f"We still have the message: {user5.creation_message}")
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืชื ืฉืœืžืขืœื” ื”ื’ื“ืจื ื• ืฉืคืขื•ืœืช ื”ืงืกื <code>__init__</code> ืชืงื‘ืœ ื›ืคืจืžื˜ืจ ื”ื•ื“ืขื” ืœื”ื“ืคืกื”.<br> ื”ื”ื•ื“ืขื” ืชื™ืฉืžืจ ื‘ืชื›ื•ื ื” <var>creation_message</var> ื”ืฉื™ื™ื›ืช ืœืžื•ืคืข, ื•ืชื•ื“ืคืก ืžื™ื™ื“ ืœืื—ืจ ืžื›ืŸ.<br> ืืช ื”ื”ื•ื“ืขื” ื”ืขื‘ืจื ื• ื›ืืจื’ื•ืžื ื˜ ื‘ืขืช ื”ืงืจื™ืื” ืœืฉื ื”ืžื—ืœืงื”, <var>User</var>, ืฉื™ื•ืฆืจืช ืืช ื”ืžื•ืคืข. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื•ืื ื›ื‘ืจ ื™ืฉ ืœื ื• ืžืฉื”ื• ืฉืจืฅ ื›ืฉืื ื—ื ื• ื™ื•ืฆืจื™ื ืืช ื”ืžื•ืคืข... ื•ื”ื•ื ื™ื•ื“ืข ืœืงื‘ืœ ืคืจืžื˜ืจื™ื...<br> ืืชื ื—ื•ืฉื‘ื™ื ืขืœ ืžื” ืฉืื ื™ ื—ื•ืฉื‘?<br> ื‘ื•ืื• ื ืฉื ื” ืืช ื”ืฉื ืฉืœ <var>create_user</var> ืœึพ<code>__init__</code>!<br> ื‘ืฆื•ืจื” ื”ื–ื• ื ื•ื›ืœ ืœืฆืงืช ืืช ื”ืชื›ื•ื ื•ืช ืœืžื•ืคืข ืžื™ื™ื“ ืขื ื™ืฆื™ืจืชื•, ื•ืœื•ื•ืชืจ ืขืœ ืงืจื™ืื” ื ืคืจื“ืช ืœืคืขื•ืœื” ืฉืžื˜ืจืชื” ืœืžืœื ืืช ื”ืขืจื›ื™ื: </p>
class User: def __init__(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age print("Yayy! We have just created a new instance! :D") def __str__(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' user5 = User('Lorne', 'Malvo', 'Mick', 58) print(user5)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ืื™ื’ื“ื ื• ืืช ื™ืฆื™ืจืช ืชื›ื•ื ื•ืช ื”ืžื•ืคืข ืชื—ืช ืคืขื•ืœื” ืื—ืช, ืฉืจืฆื” ื›ืฉื”ื•ื ื ื•ืฆืจ.<br> ื”ืจืขื™ื•ืŸ ื”ื ืคืœื ื”ื–ื” ื ืคื•ืฅ ืžืื•ื“ ื‘ืฉืคื•ืช ืชื›ื ื•ืช ืฉืชื•ืžื›ื•ืช ื‘ืžื—ืœืงื•ืช, ื•ืžื•ื›ืจืช ื‘ืฉื <dfn>ืคืขื•ืœืช ืืชื—ื•ืœ</dfn> (<dfn>Initialization Method</dfn>).<br> ื–ื• ื’ื ื”ืกื™ื‘ื” ืœืฉื ื”ืคืขื•ืœื” โ€“ ื”ืžื™ืœื” init ื ื’ื–ืจืช ืžื”ืžื™ืœื” initialization, ืืชื—ื•ืœ. </p> <div class="align-center" style="display: flex; text-align: right; direction: rtl; clear: both;"> <div style="display: flex; width: 10%; float: right; clear: both;"> <img src="images/exercise.svg" style="height: 50px !important;" alt="ืชืจื’ื•ืœ"> </div> <div style="width: 70%"> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฉืคืฆื• ืืช ืžื—ืœืงืช ื”ื ืงื•ื“ื” ืฉื™ืฆืจืชื, ื›ืš ืฉืชื›ื™ืœ <code>__init__</code> ื•ึพ<code>__str__</code>. </p> </div> <div style="display: flex; width: 20%; border-right: 0.1rem solid #A5A5A5; padding: 1rem 2rem;"> <p style="text-align: center; direction: rtl; justify-content: center; align-items: center; clear: both;"> <strong>ื—ืฉื•ื‘!</strong><br> ืคืชืจื• ืœืคื ื™ ืฉืชืžืฉื™ื›ื•! </p> </div> </div> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื™ื™ืฆื•ืจ ืžืกื—ืจื™</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฆ'ื™ืงืฆ'ื•ืง ืฉืžื” ืืช ื™ื“ื” ืขืœ ืคืจื˜ื™ ื”ืžืฉืชืžืฉื™ื ืฉืœ ื”ืจืฉืช ื”ื—ื‘ืจืชื™ืช ื”ืžืชื—ืจื”, ืกื ื™ื™ืœืฆ'ืื˜.<br> ืจืฉื™ืžืช ื”ืžืฉืชืžืฉื™ื ื ืจืื™ืช ื›ืš: </p>
snailchat_users = [ ['Mike', 'Shugarberg', 'Marker', 36], ['Hammer', 'Doorsoy', 'Tzweetz', 43], ['Evan', 'Spygirl', 'Odd', 30], ]
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื ื™ื—, ืœื›ืื•ืจื” ื‘ืœื‘ื“, ืฉืื ื—ื ื• ืจื•ืฆื™ื ืœื”ืขืชื™ืง ืืช ืื•ืชื” ืจืฉื™ืžืช ืžืฉืชืžืฉื™ื ื•ืœืฆืจืฃ ืื•ืชื” ืœืจืฉืช ื”ื—ื‘ืจืชื™ืช ืฉืœื ื•.<br> ืงื—ื• ื“ืงื” ื•ื—ืฉื‘ื• ืื™ืš ื”ื™ื™ืชื ืขื•ืฉื™ื ืืช ื–ื”. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื–ื›ืจื• ืฉืงืจื™ืื” ืœืžื—ืœืงื” <var>User</var> ื”ื™ื ื›ื›ืœ ืงืจื™ืื” ืœืคื•ื ืงืฆื™ื” ืื—ืจืช,<br> ื•ืฉื”ืžื•ืคืข ืฉื—ื•ื–ืจ ืžืžื ื” ื”ื•ื ืขืจืš ื‘ื“ื™ื•ืง ื›ืžื• ื›ืœ ืขืจืš ืื—ืจ. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื•ื›ืœ ืœื™ืฆื•ืจ ืจืฉื™ืžืช ืžื•ืคืขื™ื ืฉืœ ืžืฉืชืžืฉื™ื. ืœื“ื•ื’ืžื”: </p>
our_users = [] for user_details in snailchat_users: new_user = User(*user_details) # Unpacking โ€“ ื”ืชื ื”ืจืืฉื•ืŸ ืขื•ื‘ืจ ืœืคืจืžื˜ืจ ื”ืชื•ืื, ื•ื›ืš ื’ื ื”ืฉื ื™, ื”ืฉืœื™ืฉื™ ื•ื”ืจื‘ื™ืขื™ our_users.append(new_user) print(new_user)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืงื•ื“ ืฉืœืžืขืœื” ื™ืฆืจื ื• ืจืฉื™ืžื” ืจื™ืงื”, ืฉืื•ืชื” ื ืžืœื ื‘ืžืฉืชืžืฉื™ื <strike>ืฉื ื’ื ื•ื‘</strike> ืฉื ืฉืื™ืœ ืžืกื ื™ื™ืœืฆ'ืื˜.<br> ื ืขื‘ื™ืจ ืืช ื”ืคืจื˜ื™ื ืฉืœ ื›ืœ ืื—ื“ ืžื”ืžืฉืชืžืฉื™ื ื”ืžื•ืคื™ืขื™ื ื‘ึพ<var>snailchat_users</var>, ืœึพ<code>__init__</code> ืฉืœ <var>User</var>,<br> ื•ื ืฆืจืฃ ืืช ื”ืžื•ืคืข ื”ื—ื“ืฉ ืฉื ื•ืฆืจ ืœืชื•ืš ื”ืจืฉื™ืžื” ื”ื—ื“ืฉื” ืฉื™ืฆืจื ื•. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืขื›ืฉื™ื• ื”ืจืฉื™ืžื” <var>our_users</var> ื”ื™ื ืจืฉื™ืžื” ืœื›ืœ ื“ื‘ืจ, ืฉื›ื•ืœืœืช ืืช ื›ืœ ื”ืžืฉืชืžืฉื™ื ื”ื—ื“ืฉื™ื ืฉื”ืฆื˜ืจืคื• ืœืจืฉืช ื”ื—ื‘ืจืชื™ืช ืฉืœื ื•: </p>
print(our_users[0]) print(our_users[1]) print(our_users[2])
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<div class="align-center" style="display: flex; text-align: right; direction: rtl; clear: both;"> <div style="display: flex; width: 10%; float: right; clear: both;"> <img src="images/exercise.svg" style="height: 50px !important;" alt="ืชืจื’ื•ืœ"> </div> <div style="width: 70%"> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฆืจื• ืืช ืจืฉื™ืžืช ื›ืœ ื”ื ืงื•ื“ื•ืช ืฉื”ึพx ื•ื”ึพy ืฉืœื”ืŸ ื”ื•ื ืžืกืคืจ ืฉืœื ื‘ื™ืŸ 0 ืœึพ6.<br> ืœื“ื•ื’ืžื”, ืจืฉื™ืžืช ื›ืœ ื”ื ืงื•ื“ื•ืช ืฉื”ึพx ื•ื”ึพy ืฉืœื”ืŸ ื”ื•ื ื‘ื™ืŸ 0 ืœึพ2 ื”ื™ื:<br> <samp dir="ltr">[(0, 0), (0, 1), (1, 0), (1, 1), (0, 2), (1, 2), (2, 0), (2, 1), (2, 2)]</samp> </p> </div> <div style="display: flex; width: 20%; border-right: 0.1rem solid #A5A5A5; padding: 1rem 2rem;"> <p style="text-align: center; direction: rtl; justify-content: center; align-items: center; clear: both;"> <strong>ื—ืฉื•ื‘!</strong><br> ืคืชืจื• ืœืคื ื™ ืฉืชืžืฉื™ื›ื•! </p> </div> </div> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื˜ืขื•ื™ื•ืช ื ืคื•ืฆื•ืช</span> <span style="text-align: right; direction: rtl; float: right; clear: both;">ื’ื‘ื•ืœื•ืช ืžืจื—ื‘ ื”ืขืจื›ื™ื</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ืกืงื•ืจ ื›ืžื” ื“ื•ื’ืžืื•ืช ื›ื“ื™ ืœื•ื•ื“ื ืฉื‘ืืžืช ื”ื‘ื ื• ื›ื™ืฆื“ ืžืชื ื”ื’ื•ืช ืžื—ืœืงื•ืช.<br> ื ื’ื“ื™ืจ ืืช ืžื—ืœืงืช <var>User</var> ืฉืื ื—ื ื• ืžื›ื™ืจื™ื, ื•ื ืฆืจืฃ ืœื” ืืช ื”ืคืขื•ืœื” <var>celebrate_birthday</var>, ืฉื›ื–ื›ื•ืจ, ืžื’ื“ื™ืœื” ืืช ื’ื™ืœ ื”ืžืฉืชืžืฉ ื‘ึพ1: </p>
class User: def __init__(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age def celebrate_birthday(self): age = age + 1 def __str__(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.'
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื™ืกื™ื•ืŸ ืœื™ืฆื•ืจ ืžื•ืคืข ืฉืœ ืžืฉืชืžืฉ ื•ืœื—ื’ื•ื’ ืœื• ื™ื•ื ื”ื•ืœื“ืช ื™ื’ืจื•ื ืœืฉื’ื™ืื”.<br> ืชื•ื›ืœื• ืœื ื—ืฉ ืžื” ืชื”ื™ื” ื”ืฉื’ื™ืื” ืขื•ื“ ืœืคื ื™ ืฉืชืจื™ืฆื•? </p>
user6 = User('Winston', 'Smith', 'Jeeves', 39) user6.celebrate_birthday()
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื™ืกื™ื ื• ืœืฉื ื•ืช ืืช ื”ืžืฉืชื ื” <var>age</var> โ€“ ืืš ื”ื•ื ืื™ื ื• ืžื•ื’ื“ืจ.<br> ื›ื“ื™ ืœืฉื ื•ืช ืืช ื”ื’ื™ืœ ืฉืœ ื”ืžืฉืชืžืฉ ืฉื™ืฆืจื ื•, ื ื”ื™ื” ื—ื™ื™ื‘ื™ื ืœื”ืชื™ื™ื—ืก ืœึพ<code>self.age</code>.<br> ืื ืœื ื ืฆื™ื™ืŸ ื‘ืžืคื•ืจืฉ ืฉืื ื—ื ื• ืจื•ืฆื™ื ืœืฉื ื•ืช ืืช ื”ืชื›ื•ื ื” <var>age</var> ืฉืฉื™ื™ื›ืช ืœึพ<var>self</var>, ืคื™ื™ืชื•ืŸ ืœื ืชื“ืข ืœืื™ื–ื” ืžื•ืคืข ืื ื—ื ื• ืžืชื›ื•ื•ื ื™ื.<br> ื ืชืงืŸ: </p>
class User: def __init__(self, first_name, last_name, nickname, current_age): self.first_name = first_name self.last_name = last_name self.nickname = nickname self.age = current_age def celebrate_birthday(self): self.age = self.age + 1 def __str__(self): full_name = f'{self.first_name} {self.last_name}' return f'{self.nickname} ({full_name}) is {self.age} years old.' user6 = User('Winston', 'Smith', 'Jeeves', 39) print(f"User before birthday: {user6}") user6.celebrate_birthday() print(f"User after birthday: {user6}")
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืื•ืชื” ื”ืžื™ื“ื”, ืชื›ื•ื ื•ืช ืฉื”ื•ื’ื“ืจื• ื›ื—ืœืง ืžืžื•ืคืข ืœื ืžื•ื’ื“ืจื•ืช ืžื—ื•ืฆื” ืœื•.<br> ืืคืฉืจ ืœื”ืฉืชืžืฉ, ืœื“ื•ื’ืžื”, ื‘ืฉื ื”ืžืฉืชื ื” <var>age</var> ืžื‘ืœื™ ืœื—ืฉื•ืฉ ืœืคื’ื•ืข ื‘ืชืคืงื•ื“ ื”ืžื—ืœืงื” ืื• ื‘ืชืคืงื•ื“ ื”ืžื•ืคืขื™ื: </p>
user6 = User('Winston', 'Smith', 'Jeeves', 39) print(user6) age = 10 print(user6)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื›ื“ื™ ืœืฉื ื•ืช ืืช ื’ื™ืœื• ืฉืœ ื”ืžืฉืชืžืฉ, ื ืฆื˜ืจืš ืœื”ืชื™ื™ื—ืก ืืœ ื”ืชื›ื•ื ื” ืฉืœื• ื‘ืฆื•ืจืช ื”ื›ืชื™ื‘ื” ืฉืœืžื“ื ื•: </p>
user6.age = 10 print(user6)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<span style="text-align: right; direction: rtl; float: right; clear: both;">ืชื›ื•ื ื” ืื• ืคืขื•ืœื” ืฉืœื ืงื™ื™ืžื•ืช</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืฉื’ื™ืื” ืฉืžืชืจื—ืฉืช ืœื ืžืขื˜ ื”ื™ื ืคื ื™ื™ื” ืœืชื›ื•ื ื” ืื• ืœืคืขื•ืœื” ืฉืœื ืงื™ื™ืžื•ืช ืขื‘ื•ืจ ื”ืžื•ืคืข.<br> ืœื“ื•ื’ืžื”: </p>
class Dice: def __init__(self, number): if 1 <= number <= 6: self.is_valid = True dice_bag = [Dice(roll_result) for roll_result in range(7)]
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื™ืฆืจื ื• ืจืฉื™ืžืช ืงื•ื‘ื™ื•ืช ื•ื‘ื™ืฆืขื ื• ื”ืฉืžื” ื›ืš ืฉึพ<var>dice_bag</var> ืชืฆื‘ื™ืข ืขืœื™ื”.<br> ื›ืขืช ื ื“ืคื™ืก ืืช ื”ืชื›ื•ื ื” <var>is_valid</var> ืฉืœ ื›ืœ ืื—ืช ืžื”ืงื•ื‘ื™ื•ืช: </p>
for dice in dice_bag: print(dice.is_valid)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ื‘ืขื™ื” ื”ื™ื ืฉื”ืงื•ื‘ื™ื” ื”ืจืืฉื•ื ื” ืฉื™ืฆืจื ื• ืงื™ื‘ืœื” ืืช ื”ืžืกืคืจ 0.<br> ื‘ืžืงืจื” ื›ื–ื”, ื”ืชื ืื™ ื‘ืคืขื•ืœืช ื”ืืชื—ื•ืœ (<code>__init__</code>) ืœื ื™ืชืงื™ื™ื, ื•ื”ืชื›ื•ื ื” <var>is_valid</var> ืœื ืชื•ื’ื“ืจ.<br> ื›ืฉื”ืœื•ืœืื” ืชื’ื™ืข ืœืงื•ื‘ื™ื™ื” 0 ื•ืชื ืกื” ืœื’ืฉืช ืœืชื›ื•ื ื” <var>is_valid</var>, ื ื’ืœื” ืฉื”ื™ื ืœื ืงื™ื™ืžืช ืขื‘ื•ืจ ื”ืงื•ื‘ื™ื™ื” 0, ื•ื ืงื‘ืœ <var>AttributeError</var>. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ืชืงืŸ: </p>
class Dice: def __init__(self, number): self.is_valid = (1 <= number <= 6) # ืœื ื—ื™ื™ื‘ื™ื ืกื•ื’ืจื™ื™ื dice_bag = [Dice(roll_result) for roll_result in range(7)] for dice in dice_bag: print(dice.is_valid)
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<span style="text-align: right; direction: rtl; float: right; clear: both;">ืกื™ื›ื•ื</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืžื—ื‘ืจืช ื–ื• ืจื›ืฉื ื• ื›ืœื™ื ืœืขื‘ื•ื“ื” ืขื ืžื—ืœืงื•ืช ื•ืขืฆืžื™ื, ื•ืœื™ื™ืฆื•ื’ ืื•ืกืคื™ื ืฉืœ ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช.<br> ื›ืœื™ื ืืœื• ื™ืขื–ืจื• ืœื ื• ืœืืจื’ืŸ ื˜ื•ื‘ ื™ื•ืชืจ ืืช ื”ืชื•ื›ื ื™ืช ืฉืœื ื• ื•ืœื™ื™ืฆื’ ื™ืฉื•ื™ื•ืช ืžื”ืขื•ืœื ื”ืืžื™ืชื™ ื‘ืฆื•ืจื” ืื™ื ื˜ื•ืื™ื˜ื™ื‘ื™ืช ื™ื•ืชืจ. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื ื”ื•ื’ ืœื›ื ื•ืช ืืช ืขื•ืœื ื”ืžื—ืœืงื•ืช ื‘ืฉื "<dfn>ืชื›ื ื•ืช ืžื•ื ื—ื” ืขืฆืžื™ื</dfn>" (<dfn>Object Oriented Programming</dfn>, ืื• <dfn>OOP</dfn>).<br> ื–ื• ืคืจื“ื™ื’ืžืช ืชื›ื ื•ืช ื”ื“ื•ื’ืœืช ื‘ื™ืฆื™ืจืช ืžื—ืœืงื•ืช ืœืฆื•ืจืš ื—ืœื•ืงืช ืงื•ื“ ื˜ื•ื‘ื” ื™ื•ืชืจ,<br> ื•ื‘ืชื™ืื•ืจ ืขืฆืžื™ื ืžื”ืขื•ืœื ื”ืืžื™ืชื™ ื‘ืฆื•ืจื” ื˜ื•ื‘ื” ื™ื•ืชืจ, ื›ืื•ืกืคื™ื ืฉืœ ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืชื›ื ื•ืช ืžื•ื ื—ื” ืขืฆืžื™ื ื”ื•ื ืคื™ืชื•ื— ืžืื•ื—ืจ ื™ื•ืชืจ ืฉืœ ืคืจื“ื™ื’ืžืช ืชื›ื ื•ืช ืื—ืจืช ืฉืืชื ื›ื‘ืจ ืžื›ื™ืจื™ื, ื”ื ืงืจืืช "<dfn>ืชื›ื ื•ืช ืคืจื•ืฆื“ื•ืจืœื™</dfn>".<br> ืคืจื“ื™ื’ืžื” ื–ื• ื“ื•ื’ืœืช ื‘ื—ืœื•ืงืช ื”ืงื•ื“ ืœืชืชื™ึพืชื•ื›ื ื™ื•ืช ืงื˜ื ื•ืช (ืžื” ืฉืืชื ืžื›ื™ืจื™ื ื›ืคื•ื ืงืฆื™ื•ืช), ื›ื“ื™ ืœื™ืฆื•ืจ ืงื•ื“ ืฉืžื—ื•ืœืง ื˜ื•ื‘ ื™ื•ืชืจ ื•ืงืœ ื™ื•ืชืจ ืœืชื—ื–ื•ืง. </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืคื™ื™ืชื•ืŸ ืชื•ืžื›ืช ื”ืŸ ื‘ืชื›ื ื•ืช ืคืจื•ืฆื“ื•ืจืœื™ ื•ื”ืŸ ื‘ืชื›ื ื•ืช ืžื•ื ื—ื” ืขืฆืžื™ื. </p> <span style="text-align: right; direction: rtl; float: right; clear: both;">ืžื•ื ื—ื™ื</span> <dl style="text-align: right; direction: rtl; float: right; clear: both;"> <dt>ืžื—ืœืงื” (Class)</dt> <dd> ืชื‘ื ื™ืช, ืื• ืฉื‘ืœื•ื ื”, ืฉืžืชืืจืช ืื•ืกืฃ ืฉืœ ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช ืฉื™ืฉ ื‘ื™ื ื™ื”ืŸ ืงืฉืจ.<br> ื”ืžื—ืœืงื” ืžื’ื“ื™ืจื” ืžื‘ื ื” ืฉื‘ืขื–ืจืชื• ื ื•ื›ืœ ืœื™ืฆื•ืจ ื‘ืงืœื•ืช ืขืฆื ืžื•ื’ื“ืจ, ืฉื•ื‘ ื•ืฉื•ื‘.<br> ืœื“ื•ื’ืžื”: ืžื—ืœืงื” ื”ืžืชืืจืช ืžืฉืชืžืฉ ื‘ืจืฉืช ื—ื‘ืจืชื™ืช, ืžื—ืœืงื” ื”ืžืชืืจืช ื›ืœื™ ืจื›ื‘, ืžื—ืœืงื” ื”ืžืชืืจืช ื ืงื•ื“ื” ื‘ืžื™ืฉื•ืจ. </dd> <dt>ืžื•ืคืข (Instance)</dt> <dd> ื ืงืจื ื’ื <dfn>ืขืฆื</dfn> (<dfn>Object</dfn>).<br> ืขืจืš ืฉื ื•ืฆืจ ืขืœ ื™ื“ื™ ืžื—ืœืงื” ื›ืœืฉื”ื™. ืกื•ื’ ื”ืขืจืš ื™ื™ืงื‘ืข ืœืคื™ ื”ืžื—ืœืงื” ืฉื™ืฆืจื” ืื•ืชื•.<br> ื”ืขืจืš ื ื•ืฆืจ ืœืคื™ ื”ืชื‘ื ื™ืช ("ื”ืฉื‘ืœื•ื ื”") ืฉืœ ื”ืžื—ืœืงื” ืฉืžืžื ื” ื”ื•ื ื ื•ืฆืจ, ื•ืžื•ืฆืžื“ื•ืช ืœื• ื”ืคืขื•ืœื•ืช ืฉื”ื•ื’ื“ืจื• ื‘ืžื—ืœืงื”.<br> ื”ืžื•ืคืข ื”ื•ื ื™ื—ื™ื“ื” ืขืฆืžืื™ืช ืฉืขื•ืžื“ืช ื‘ืคื ื™ ืขืฆืžื”. ืœืจื•ื‘ ืžื—ืœืงื” ืชืฉืžืฉ ืื•ืชื ื• ืœื™ืฆื™ืจืช ืžื•ืคืขื™ื ืจื‘ื™ื.<br> ืœื“ื•ื’ืžื”: ื”ืžื•ืคืข "ื ืงื•ื“ื” ืฉื ืžืฆืืช ื‘ึพ<span dir="ltr">(5, 3)</span>" ื™ื”ื™ื” ืžื•ืคืข ืฉื ื•ืฆืจ ืžื”ืžื—ืœืงื” "ื ืงื•ื“ื”". </dd> <dt>ืชื›ื•ื ื” (Property, Member)</dt> <dd> ืขืจืš ืื•ืคื™ื™ื ื™ ืœืžื•ืคืข ืฉื ื•ืฆืจ ืžื”ืžื—ืœืงื”.<br> ืžืฉืชื ื™ื ื”ืฉื™ื™ื›ื™ื ืœืžื•ืคืข ืฉื ื•ืฆืจ ืžื”ืžื—ืœืงื”, ื•ืžื›ื™ืœื™ื ืขืจื›ื™ื ืฉืžืชืืจื™ื ืื•ืชื•.<br> ืœื“ื•ื’ืžื”: ืœื ืงื•ื“ื” ื‘ืžื™ืฉื•ืจ ื™ืฉ ืขืจืš x ื•ืขืจืš y. ืืœื• 2 ืชื›ื•ื ื•ืช ืฉืœ ื”ื ืงื•ื“ื”.<br> ื ื•ื›ืœ ืœื”ื—ืœื™ื˜ ืฉืชื›ื•ื ื•ืชื™ื” ืฉืœ ืžื—ืœืงืช ืžื›ื•ื ื™ืช ื™ื”ื™ื• ืฆื‘ืข, ื“ื’ื ื•ื™ืฆืจืŸ. </dd> <dt>ืคืขื•ืœื” (Method)</dt> <dd> ืคื•ื ืงืฆื™ื” ืฉืžื•ื’ื“ืจืช ื‘ื’ื•ืฃ ื”ืžื—ืœืงื”.<br> ืžืชืืจืช ื”ืชื ื”ื’ื•ื™ื•ืช ืืคืฉืจื™ื•ืช ืฉืœ ื”ืžื•ืคืข ืฉื™ื™ื•ื•ืฆืจ ืžื”ืžื—ืœืงื”.<br> ืœื“ื•ื’ืžื”: ืคืขื•ืœื” ืขืœ ื ืงื•ื“ื” ื‘ืžื™ืฉื•ืจ ื™ื›ื•ืœื” ืœื”ื™ื•ืช ืžืฆื™ืืช ืžืจื—ืงื” ืžืจืืฉื™ืช ื”ืฆื™ืจื™ื.<br> ืคืขื•ืœื” ืขืœ ืฉื•ืœื—ืŸ ื™ื›ื•ืœื” ืœื”ื™ื•ืช "ืงืฆืฅ 5 ืกื ื˜ื™ืžื˜ืจ ืžื’ื•ื‘ื”ื•". </dd> <dt>ืฉื“ื” (Field, Attribute)</dt> <dd> ืฉื ื›ืœืœื™ ื”ื ื•ืขื“ ืœืชืืจ ืชื›ื•ื ื” ืื• ืคืขื•ืœื”.<br> ืฉื“ื•ืช ืฉืœ ืžื•ืคืข ืžืกื•ื™ื ื™ื”ื™ื• ื›ืœืœ ื”ืชื›ื•ื ื•ืช ื•ื”ืคืขื•ืœื•ืช ืฉืืคืฉืจ ืœื’ืฉืช ืืœื™ื”ืŸ ืžืื•ืชื• ืžื•ืคืข.<br> ืœื“ื•ื’ืžื”: ื”ืฉื“ื•ืช ืฉืœ ื ืงื•ื“ื” ื™ื”ื™ื• ื”ืชื›ื•ื ื•ืช x ื•ึพy, ื•ื”ืคืขื•ืœื” ืฉื‘ื•ื“ืงืช ืืช ืžืจื—ืงื” ืžืจืืฉื™ืช ื”ืฆื™ืจื™ื. </dd> <dt>ืคืขื•ืœื” ืžื™ื•ื—ื“ืช (Special Method)</dt> <dd> ื™ื“ื•ืขื” ื’ื ื›ึพ<dfn>dunder method</dfn> (double under, ืงื• ืชื—ืชื•ืŸ ื›ืคื•ืœ) ืื• ื›ึพ<dfn>magic method</dfn> (ืคืขื•ืœืช ืงืกื).<br> ืคืขื•ืœื” ืฉื”ื’ื“ืจืชื” ื‘ืžื—ืœืงื” ื’ื•ืจืžืช ืœืžื—ืœืงื” ืื• ืœืžื•ืคืขื™ื ื”ื ื•ืฆืจื™ื ืžืžื ื” ืœื”ืชื ื”ื’ื•ืช ืžื™ื•ื—ื“ืช.<br> ื“ื•ื’ืžืื•ืช ืœืคืขื•ืœื•ืช ืฉื›ืืœื• ื”ืŸ <code>__init__</code> ื•ึพ<code>__str__</code>. </dd> <dt>ืคืขื•ืœืช ืืชื—ื•ืœ (Initialization Method)</dt> <dd> ืคืขื•ืœื” ืฉืจืฆื” ืขื ื™ืฆื™ืจืช ืžื•ืคืข ื—ื“ืฉ ืžืชื•ืš ืžื—ืœืงื”.<br> ืœืจื•ื‘ ืžืฉืชืžืฉื™ื ื‘ืคืขื•ืœื” ื–ื• ื›ื“ื™ ืœื”ื–ื™ืŸ ื‘ืžื•ืคืข ืขืจื›ื™ื ื”ืชื—ืœืชื™ื™ื. </dd> <dt>ืชื›ื ื•ืช ืžื•ื ื—ื” ืขืฆืžื™ื (Object Oriented Programming)</dt> <dd> ืคืจื“ื™ื’ืžืช ืชื›ื ื•ืช ืฉืžืฉืชืžืฉืช ื‘ืžื—ืœืงื•ืช ื‘ืงื•ื“ ื›ื›ืœื™ ื”ืขื™ืงืจื™ ืœื”ืคืฉื˜ื” ืฉืœ ื”ืขื•ืœื ื”ืืžื™ืชื™.<br> ื‘ืคืจื“ื™ื’ืžื” ื–ื• ื ื”ื•ื’ ืœื™ืฆื•ืจ ืžื—ืœืงื•ืช ื”ืžื™ื™ืฆื’ื•ืช ืชื‘ื ื™ื•ืช ืฉืœ ืขืฆืžื™ื, ื•ืœืืคื™ื™ืŸ ืืช ื”ืขืฆืžื™ื ื‘ืืžืฆืขื•ืช ืชื›ื•ื ื•ืช ื•ืคืขื•ืœื•ืช.<br> ื‘ืขื–ืจืช ื”ืžื—ืœืงื•ืช ืืคืฉืจ ืœื™ืฆื•ืจ ืžื•ืคืขื™ื, ืฉื”ื ื™ื™ืฆื•ื’ ืฉืœ ืคืจื™ื˜ ื‘ื•ื“ื“ (ืขืฆื, ืื•ื‘ื™ื™ืงื˜) ืฉื ื•ืฆืจ ืœืคื™ ืชื‘ื ื™ืช ื”ืžื—ืœืงื”. </dd> </dl> <span style="text-align: right; direction: rtl; float: right; clear: both;">ืชืจื’ื™ืœ ืœื“ื•ื’ืžื”</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื›ืชื‘ื• ืžื—ืœืงื” ื”ืžื™ื™ืฆื’ืช ื ืชื™ื‘ ืชืงื™ืŸ ื‘ืžืขืจื›ืช ื”ื”ืคืขืœื” ื—ืœื•ื ื•ืช.<br> ื”ื ืชื™ื‘ ืžื—ื•ืœืง ืœื—ืœืงื™ื ื‘ืืžืฆืขื•ืช ื”ืชื• / ืื• ื”ืชื• \.<br> ื”ื—ืœืง ื”ืจืืฉื•ืŸ ื‘ื ืชื™ื‘ ื”ื•ื ืชืžื™ื“ ืื•ืช ื”ื›ื•ื ืŸ ื•ืื—ืจื™ื” ื ืงื•ื“ืชื™ื™ื.<br> ื”ื—ืœืงื™ื ืฉื ืžืฆืื™ื ืื—ืจื™ ื”ื—ืœืง ื”ืจืืฉื•ืŸ, ื›ื›ืœ ืฉื™ืฉ ื›ืืœื•, ื”ื ืชื™ืงื™ื•ืช ื•ืงื‘ืฆื™ื.<br> ื“ื•ื’ืžืื•ืช ืœื ืชื™ื‘ื™ื ืชืงื™ื ื™ื: </p> <ul style="text-align: right; direction: rtl; float: right; clear: both;"> <li><span dir="ltr">C:\Users\Yam\python.jpg</span></li> <li><span dir="ltr">C:/Users/Yam/python.jpg</span></li> <li><span dir="ltr">C:</span></li> <li><span dir="ltr">C:\</span></li> <li><span dir="ltr">C:/</span></li> <li><span dir="ltr">C:\User/</span></li> <li><span dir="ltr">D:/User/</span></li> <li><span dir="ltr">C:/User</span></li> </ul> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื”ืžื—ืœืงื” ืชื›ืœื•ืœ ืืช ื”ืคืขื•ืœื•ืช ื”ื‘ืื•ืช: </p> <ul style="text-align: right; direction: rtl; float: right; clear: both;"> <li>ืื—ื–ืจ ืืช ืื•ืช ื”ื›ื•ื ืŸ ื‘ืขื–ืจืช ื”ืคืขื•ืœื” <var>get_drive_letter</var>.</li> <li>ืื—ื–ืจ ืืช ื”ื ืชื™ื‘ ืœืœื ื—ืœืงื• ื”ืื—ืจื•ืŸ ื‘ืขื–ืจืช ื”ืคืขื•ืœื” <var>get_dirname</var>.</li> <li>ืื—ื–ืจ ืืช ืฉื ื”ื—ืœืง ื”ืื—ืจื•ืŸ ื‘ื ืชื™ื‘, ื‘ืขื–ืจืช ื”ืคืขื•ืœื” <var>get_basename</var>.</li> <li>ืื—ื–ืจ ืืช ืกื™ื•ืžืช ื”ืงื•ื‘ืฅ ื‘ืขื–ืจืช ื”ืคืขื•ืœื” <var>get_extension</var>.</li> <li>ืื—ื–ืจ ืื ื”ื ืชื™ื‘ ืงื™ื™ื ื‘ืžื—ืฉื‘ ื‘ืขื–ืจืช ื”ืคืขื•ืœื” <var>is_exists</var>.</li> <li>ืื—ื–ืจ ืืช ื”ื ืชื™ื‘ ื›ื•ืœื• ื›ืžื—ืจื•ื–ืช, ื›ืฉื”ืชื• ื”ืžืคืจื™ื“ ื”ื•ื <samp>/</samp>, ื•ืœืœื <samp>/</samp> ื‘ืกื•ืฃ ื”ื ืชื™ื‘.</li> </ul>
import os class Path: def __init__(self, path): self.fullpath = path self.parts = list(self.get_parts()) def get_parts(self): current_part = "" for char in self.fullpath: if char in r"\/": yield current_part current_part = "" else: current_part = current_part + char if current_part != "": yield current_part def get_drive_letter(self): return self.parts[0].rstrip(":") def get_dirname(self): path = "/".join(self.parts[:-1]) return Path(path) def get_basename(self): return self.parts[-1] def get_extension(self): name = self.get_basename() i = name.rfind('.') if 0 < i < len(name) - 1: return name[i + 1:] return '' def is_exists(self): return os.path.exists(str(self)) def normalize_path(self): normalized = "\\".join(self.parts) return normalized.rstrip("\\") def info_message(self): return f""" Some info about "{self}": Drive letter: {self.get_drive_letter()} Dirname: {self.get_dirname()} Last part of path: {self.get_basename()} File extension: {self.get_extension()} Is exists?: {self.is_exists()} """.strip() def __str__(self): return self.normalize_path() EXAMPLES = ( r"C:\Users\Yam\python.jpg", r"C:/Users/Yam/python.jpg", r"C:", r"C:\\", r"C:/", r"C:\Users/", r"D:/Users/", r"C:/Users", ) for example in EXAMPLES: path = Path(example) print(path.info_message()) print()
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
<span style="text-align: right; direction: rtl; float: right; clear: both;">ืชืจื’ื™ืœื™ื</span> <span style="text-align: right; direction: rtl; float: right; clear: both;">ืกืงืจื ื•ืช</span> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ืžื—ืœืงืช ื”ืžื•ืฆืจ ื‘ืฆ'ื™ืงืฆ'ื•ืง ื”ื—ืœื™ื˜ื” ืœื”ื•ืกื™ืฃ ืคื™ืฆ'ืจ ืฉืžืืคืฉืจ ืœืžืฉืชืžืฉื™ื ืœื™ืฆื•ืจ ืกืงืจื™ื, ื•ื›ืจื’ื™ืœ ื›ืœ ื”ืขื‘ื•ื“ื” ื ื•ืคืœืช ืขืœื™ื›ื.<br> ื›ืชื‘ื• ืžื—ืœืงื” ื‘ืฉื <var>Poll</var> ืฉืžื™ื™ืฆื’ืช ืกืงืจ.<br> ืคืขื•ืœืช ื”ืืชื—ื•ืœ ืฉืœ ื”ืžื—ืœืงื” ืชืงื‘ืœ ื›ืคืจืžื˜ืจ ืืช ืฉืืœืช ื”ืกืงืจ, ื•ื›ืคืจืžื˜ืจ ื ื•ืกืฃ iterable ืขื ื›ืœ ืืคืฉืจื•ื™ื•ืช ื”ื”ืฆื‘ืขื” ืœืกืงืจ.<br> ื›ืœ ืืคืฉืจื•ืช ื”ืฆื‘ืขื” ื‘ืกืงืจ ืžื™ื•ืฆื’ืช ืขืœ ื™ื“ื™ ืžื—ืจื•ื–ืช.<br> ื”ืžื—ืœืงื” ืชื›ื™ืœ ืืช ื”ืคืขื•ืœื•ืช ื”ื‘ืื•ืช: </p> <ol style="text-align: right; direction: rtl; float: right; clear: both;"> <li><var>vote</var> ืฉืžืงื‘ืœืช ื›ืคืจืžื˜ืจ ืืคืฉืจื•ืช ื”ืฆื‘ืขื” ืœืกืงืจ ื•ืžื’ื“ื™ืœื” ืืช ืžืกืคืจ ื”ื”ืฆื‘ืขื•ืช ื‘ื• ื‘ึพ1.</li> <li><var>add_option</var>, ืฉืžืงื‘ืœืช ื›ืคืจืžื˜ืจ ืืคืฉืจื•ืช ื”ืฆื‘ืขื” ืœืกืงืจ ื•ืžื•ืกื™ืคื” ืื•ืชื”.</li> <li><var>remove_option</var> ืฉืžืงื‘ืœืช ื›ืคืจืžื˜ืจ ืืคืฉืจื•ืช ื”ืฆื‘ืขื” ืœืกืงืจ ื•ืžื•ื—ืงืช ืื•ืชื”.</li> <li><var>get_votes</var> ื”ืžื—ื–ื™ืจื” ืืช ื›ืœ ื”ืืคืฉืจื•ื™ื•ืช ื›ืจืฉื™ืžื” ืฉืœ tuple, ื”ืžืกื•ื“ืจื™ื ืœืคื™ ื›ืžื•ืช ื”ื”ืฆื‘ืขื•ืช.<br> ื‘ื›ืœ tuple ื”ืชื ื”ืจืืฉื•ืŸ ื™ื”ื™ื” ืฉื ื”ืืคืฉืจื•ืช ื‘ืกืงืจ, ื•ื”ืชื ื”ืฉื ื™ ื™ื”ื™ื” ืžืกืคืจ ื”ื”ืฆื‘ืขื•ืช.</li> <li><var>get_winner</var> ื”ืžื—ื–ื™ืจื” ืืช ืฉื ื”ืืคืฉืจื•ืช ืฉืงื™ื‘ืœื” ืืช ืžืจื‘ ื”ื”ืฆื‘ืขื•ืช.</li> </ol> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื‘ืžืงืจื” ืฉืœ ืชื™ืงื•, ื”ื—ื–ื™ืจื• ืžึพ<var>get_winner</var> ืืช ืื—ืช ื”ืืคืฉืจื•ื™ื•ืช ื”ืžื•ื‘ื™ืœื•ืช.<br> ื”ื—ื–ื™ืจื• ืžื”ืคืขื•ืœื•ืช <var>vote</var>, <var>add_option</var> ื•ึพ<var>remove_option</var> ืืช ื”ืขืจืš <samp>True</samp> ืื ื”ืคืขื•ืœื” ืขื‘ื“ื” ื›ืžืฆื•ืคื”.<br> ื‘ืžืงืจื” ืฉืœ ื”ืฆื‘ืขื” ืœืืคืฉืจื•ืช ืฉืื™ื ื” ืงื™ื™ืžืช, ืžื—ื™ืงืช ืืคืฉืจื•ืช ืฉืื™ื ื” ืงื™ื™ืžืช ืื• ื”ื•ืกืคืช ืืคืฉืจื•ืช ืฉื›ื‘ืจ ืงื™ื™ืžืช, ื”ื—ื–ื™ืจื• <samp>False</samp>.<br> </p> <p style="text-align: right; direction: rtl; float: right; clear: both;"> ื•ื“ืื• ืฉื”ืงื•ื“ ื”ื‘ื ืžื“ืคื™ืก ืจืง <samp>True</samp> ืขื‘ื•ืจ ื”ืชื•ื›ื ื™ืช ืฉื›ืชื‘ืชื: </p>
def cast_multiple_votes(poll, votes): for vote in votes: poll.vote(vote) bridge_question = Poll('What is your favourite colour?', ['Blue', 'Yellow']) cast_multiple_votes(bridge_question, ['Blue', 'Blue', 'Yellow']) print(bridge_question.get_winner() == 'Blue') cast_multiple_votes(bridge_question, ['Yellow', 'Yellow']) print(bridge_question.get_winner() == 'Yellow') print(bridge_question.get_votes() == [('Yellow', 3), ('Blue', 2)]) bridge_question.remove_option('Yellow') print(bridge_question.get_winner() == 'Blue') print(bridge_question.get_votes() == [('Blue', 2)]) bridge_question.add_option('Yellow') print(bridge_question.get_votes() == [('Blue', 2), ('Yellow', 0)]) print(not bridge_question.add_option('Blue')) print(bridge_question.get_votes() == [('Blue', 2), ('Yellow', 0)])
week07/1_Classes.ipynb
PythonFreeCourse/Notebooks
mit
The command %matplotlib inline is not a Python command, but an IPython command. When using the console, or the notebook, it makes the plots appear inline. You do not want to use this in a plain Python code.
from math import sin, pi x = [] y = [] for i in range(201): x.append(0.01*i) y.append(sin(pi*x[-1])**2) pyplot.plot(x, y) pyplot.show()
04-basic-plotting.ipynb
jamesmarva/maths-with-python
mit
We have defined two sequences - in this case lists, but tuples would also work. One contains the $x$-axis coordinates, the other the data points to appear on the $y$-axis. A basic plot is produced using the plot command of pyplot. However, this plot will not automatically appear on the screen, as after plotting the data you may wish to add additional information. Nothing will actually happen until you either save the figure to a file (using pyplot.savefig(&lt;filename&gt;)) or explicitly ask for it to be displayed (with the show command). When the plot is displayed the program will typically pause until you dismiss the plot. This plotting interface is straightforward, but the results are not particularly nice. The following commands illustrate some of the ways of improving the plot:
from math import sin, pi x = [] y = [] for i in range(201): x.append(0.01*i) y.append(sin(pi*x[-1])**2) pyplot.plot(x, y, marker='+', markersize=8, linestyle=':', linewidth=3, color='b', label=r'$\sin^2(\pi x)$') pyplot.legend(loc='lower right') pyplot.xlabel(r'$x$') pyplot.ylabel(r'$y$') pyplot.title('A basic plot') pyplot.show()
04-basic-plotting.ipynb
jamesmarva/maths-with-python
mit
Whilst most of the commands are self-explanatory, a note should be made of the strings line r'$x$'. These strings are in LaTeX format, which is the standard typesetting method for professional-level mathematics. The $ symbols surround mathematics. The r before the definition of the string is Python notation, not LaTeX. It says that the following string will be "raw": that backslash characters should be left alone. Then, special LaTeX commands have a backslash in front of them: here we use \pi and \sin. Most basic symbols can be easily guess (eg \theta or \int), but there are useful lists of symbols, and a reverse search site available. We can also use ^ to denote superscripts (used here), _ to denote subscripts, and use {} to group terms. By combining these basic commands with other plotting types (semilogx and loglog, for example), most simple plots can be produced quickly. Here are some more examples:
from math import sin, pi, exp, log x = [] y1 = [] y2 = [] for i in range(201): x.append(1.0+0.01*i) y1.append(exp(sin(pi*x[-1]))) y2.append(log(pi+x[-1]*sin(x[-1]))) pyplot.loglog(x, y1, linestyle='--', linewidth=4, color='k', label=r'$y_1=e^{\sin(\pi x)}$') pyplot.loglog(x, y2, linestyle='-.', linewidth=4, color='r', label=r'$y_2=\log(\pi+x\sin(x))$') pyplot.legend(loc='lower right') pyplot.xlabel(r'$x$') pyplot.ylabel(r'$y$') pyplot.title('A basic logarithmic plot') pyplot.show() from math import sin, pi, exp, log x = [] y1 = [] y2 = [] for i in range(201): x.append(1.0+0.01*i) y1.append(exp(sin(pi*x[-1]))) y2.append(log(pi+x[-1]*sin(x[-1]))) pyplot.semilogy(x, y1, linestyle='None', marker='o', color='g', label=r'$y_1=e^{\sin(\pi x)}$') pyplot.semilogy(x, y2, linestyle='None', marker='^', color='r', label=r'$y_2=\log(\pi+x\sin(x))$') pyplot.legend(loc='lower right') pyplot.xlabel(r'$x$') pyplot.ylabel(r'$y$') pyplot.title('A different logarithmic plot') pyplot.show()
04-basic-plotting.ipynb
jamesmarva/maths-with-python
mit
File browser
Image('images/lego-filebrowser.png', width='80%')
12-JupyterLab.ipynb
ellisonbg/talk-2015
mit
Terminal
Image('images/lego-terminal.png', width='80%')
12-JupyterLab.ipynb
ellisonbg/talk-2015
mit
Text editor (a place to type code)
Image('images/lego-texteditor.png', width='80%')
12-JupyterLab.ipynb
ellisonbg/talk-2015
mit
Output
Image('images/lego-output.png', width='80%')
12-JupyterLab.ipynb
ellisonbg/talk-2015
mit
์‚ฌ์ „ ์ œ์ž‘ Estimator <table class="tfo-notebook-buttons" align="left"> <td><a target="_blank" href="https://www.tensorflow.org/tutorials/estimator/premade"><img src="https://www.tensorflow.org/images/tf_logo_32px.png">TensorFlow.org์—์„œ ๋ณด๊ธฐ</a></td> <td><a target="_blank" href="https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/estimator/premade.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png">Google Colab์—์„œ ์‹คํ–‰ํ•˜๊ธฐ</a></td> <td><a target="_blank" href="https://github.com/tensorflow/docs/blob/master/site/en/tutorials/estimator/premade.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png">GitHub์—์„œ์†Œ์Šค ๋ณด๊ธฐ</a></td> <td><a href="https://storage.googleapis.com/tensorflow_docs/docs/site/en/tutorials/estimator/premade.ipynb"><img src="https://www.tensorflow.org/images/download_logo_32px.png">๋…ธํŠธ๋ถ ๋‹ค์šด๋กœ๋“œํ•˜๊ธฐ</a></td> </table> ์ด ํŠœํ† ๋ฆฌ์–ผ์—์„œ๋Š” Estimator๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ TensorFlow์—์„œ Iris ๋ถ„๋ฅ˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. Estimator๋Š” ์™„์ „ํ•œ ๋ชจ๋ธ์„ TensorFlow์—์„œ ๋†’์€ ์ˆ˜์ค€์œผ๋กœ ํ‘œํ˜„ํ•œ ๊ฒƒ์ด๋ฉฐ, ๊ฐ„ํŽธํ•œ ํฌ๊ธฐ ์กฐ์ •๊ณผ ๋น„๋™๊ธฐ์‹ ํ›ˆ๋ จ์— ๋ชฉ์ ์„ ๋‘๊ณ  ์„ค๊ณ„๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ž์„ธํ•œ ๋‚ด์šฉ์€ Estimator๋ฅผ ์ฐธ์กฐํ•˜์„ธ์š”. TensorFlow 2.0์—์„œ Keras API๋Š” ์ด๋Ÿฌํ•œ ์ž‘์—…์„ ์ƒ๋‹น ๋ถ€๋ถ„ ๋™์ผํ•˜๊ฒŒ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ๋ฐฐ์šฐ๊ธฐ ์‰ฌ์šด API๋กœ ์—ฌ๊ฒจ์ง‘๋‹ˆ๋‹ค. ์ƒˆ๋กœ ์‹œ์ž‘ํ•˜๋Š” ๊ฒฝ์šฐ Keras๋กœ ์‹œ์ž‘ํ•˜๋Š” ๊ฒƒ์ด ์ข‹์Šต๋‹ˆ๋‹ค. TensorFlow 2.0์—์„œ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ ๊ณ ๊ธ‰ API์— ๋Œ€ํ•œ ์ž์„ธํ•œ ์ •๋ณด๋Š” Keras์— ํ‘œ์ค€ํ™”๋ฅผ ์ฐธ์กฐํ•˜์„ธ์š”. ์‹œ์ž‘์„ ์œ„ํ•œ ์ค€๋น„ ์‹œ์ž‘ํ•˜๋ ค๋ฉด ๋จผ์ € TensorFlow์™€ ํ•„์š”ํ•œ ์—ฌ๋Ÿฌ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋ฅผ ๊ฐ€์ ธ์˜ต๋‹ˆ๋‹ค.
import tensorflow as tf import pandas as pd
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
๋ฐ์ดํ„ฐ์„ธํŠธ ์ด ๋ฌธ์„œ์˜ ์ƒ˜ํ”Œ ํ”„๋กœ๊ทธ๋žจ์€ ์•„์ด๋ฆฌ์Šค ๊ฝƒ์„ ๊ฝƒ๋ฐ›์นจ์žŽ๊ณผ ๊ฝƒ์žŽ์˜ ํฌ๊ธฐ์— ๋”ฐ๋ผ ์„ธ ๊ฐ€์ง€ ์ข…์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜๋Š” ๋ชจ๋ธ์„ ๋นŒ๋“œํ•˜๊ณ  ํ…Œ์ŠคํŠธํ•ฉ๋‹ˆ๋‹ค. Iris ๋ฐ์ดํ„ฐ์„ธํŠธ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ชจ๋ธ์„ ํ›ˆ๋ จํ•ฉ๋‹ˆ๋‹ค. Iris ๋ฐ์ดํ„ฐ์„ธํŠธ์—๋Š” ๋„ค ๊ฐ€์ง€ ํŠน์„ฑ๊ณผ ํ•˜๋‚˜์˜ ๋ ˆ์ด๋ธ”์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๋„ค ๊ฐ€์ง€ ํŠน์„ฑ์€ ๊ฐœ๋ณ„ ์•„์ด๋ฆฌ์Šค ๊ฝƒ์˜ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์‹๋ฌผ ํŠน์„ฑ์„ ์‹๋ณ„ํ•ฉ๋‹ˆ๋‹ค. ๊ฝƒ๋ฐ›์นจ์žŽ ๊ธธ์ด ๊ฝƒ๋ฐ›์นจ์žŽ ๋„ˆ๋น„ ๊ฝƒ์žŽ ๊ธธ์ด ๊ฝƒ์žŽ ๋„ˆ๋น„ ์ด ์ •๋ณด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ฐ์ดํ„ฐ๋ฅผ ๊ตฌ๋ฌธ ๋ถ„์„ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ๋ช‡ ๊ฐ€์ง€ ์ƒ์ˆ˜๋ฅผ ์ •์˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
CSV_COLUMN_NAMES = ['SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth', 'Species'] SPECIES = ['Setosa', 'Versicolor', 'Virginica']
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
๊ทธ ๋‹ค์Œ, Keras ๋ฐ Pandas๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ Iris ๋ฐ์ดํ„ฐ์„ธํŠธ๋ฅผ ๋‹ค์šด๋กœ๋“œํ•˜๊ณ  ๊ตฌ๋ฌธ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ํ›ˆ๋ จ ๋ฐ ํ…Œ์ŠคํŠธ๋ฅผ ์œ„ํ•ด ๋ณ„๋„์˜ ๋ฐ์ดํ„ฐ์„ธํŠธ๋ฅผ ์œ ์ง€ํ•ฉ๋‹ˆ๋‹ค.
train_path = tf.keras.utils.get_file( "iris_training.csv", "https://storage.googleapis.com/download.tensorflow.org/data/iris_training.csv") test_path = tf.keras.utils.get_file( "iris_test.csv", "https://storage.googleapis.com/download.tensorflow.org/data/iris_test.csv") train = pd.read_csv(train_path, names=CSV_COLUMN_NAMES, header=0) test = pd.read_csv(test_path, names=CSV_COLUMN_NAMES, header=0)
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
๋ฐ์ดํ„ฐ๋ฅผ ๊ฒ€์‚ฌํ•˜์—ฌ ๋„ค ๊ฐœ์˜ float ํŠน์„ฑ ์—ด๊ณผ ํ•˜๋‚˜์˜ int32 ๋ ˆ์ด๋ธ”์ด ์žˆ๋Š”์ง€ ํ™•์ธํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
train.head()
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
๊ฐ ๋ฐ์ดํ„ฐ์„ธํŠธ์— ๋Œ€ํ•ด ์˜ˆ์ธกํ•˜๋„๋ก ๋ชจ๋ธ์„ ํ›ˆ๋ จํ•  ๋ ˆ์ด๋ธ”์„ ๋ถ„ํ• ํ•ฉ๋‹ˆ๋‹ค.
train_y = train.pop('Species') test_y = test.pop('Species') # The label column has now been removed from the features. train.head()
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
Estimator๋ฅผ ์‚ฌ์šฉํ•œ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ๊ฐœ์š” ์ด์ œ ๋ฐ์ดํ„ฐ๊ฐ€ ์„ค์ •๋˜์—ˆ์œผ๋ฏ€๋กœ TensorFlow Estimator๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ชจ๋ธ์„ ์ •์˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. Estimator๋Š” tf.estimator.Estimator์—์„œ ํŒŒ์ƒ๋œ ์ž„์˜์˜ ํด๋ž˜์Šค์ž…๋‹ˆ๋‹ค. TensorFlow๋Š” ์ผ๋ฐ˜์ ์ธ ML ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜๊ธฐ ์œ„ํ•ด tf.estimator(์˜ˆ: LinearRegressor) ๋ชจ์Œ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๊ทธ ์™ธ์—๋„ ๊ณ ์œ ํ•œ ์‚ฌ์šฉ์ž ์ •์˜ Estimator๋ฅผ ์ž‘์„ฑํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ฒ˜์Œ ์‹œ์ž‘ํ•  ๋•Œ๋Š” ์‚ฌ์ „ ์ œ์ž‘๋œ Estimator๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์ด ์ข‹์Šต๋‹ˆ๋‹ค. ์‚ฌ์ „ ์ œ์ž‘๋œ Estimator๋ฅผ ๊ธฐ์ดˆ๋กœ TensorFlow ํ”„๋กœ๊ทธ๋žจ์„ ์ž‘์„ฑํ•˜๋ ค๋ฉด ๋‹ค์Œ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ํ•˜๋‚˜ ์ด์ƒ์˜ ์ž…๋ ฅ ํ•จ์ˆ˜๋ฅผ ์ž‘์„ฑํ•ฉ๋‹ˆ๋‹ค. ๋ชจ๋ธ์˜ ํŠน์„ฑ ์—ด์„ ์ •์˜ํ•ฉ๋‹ˆ๋‹ค. ํŠน์„ฑ ์—ด๊ณผ ๋‹ค์–‘ํ•œ ํ•˜์ดํผ ๋งค๊ฐœ๋ณ€์ˆ˜๋ฅผ ์ง€์ •ํ•˜์—ฌ Estimator๋ฅผ ์ธ์Šคํ„ด์Šคํ™”ํ•ฉ๋‹ˆ๋‹ค. Estimator ๊ฐ์ฒด์—์„œ ํ•˜๋‚˜ ์ด์ƒ์˜ ๋ฉ”์„œ๋“œ๋ฅผ ํ˜ธ์ถœํ•˜์—ฌ ์ ํ•ฉํ•œ ์ž…๋ ฅ ํ•จ์ˆ˜๋ฅผ ๋ฐ์ดํ„ฐ ์†Œ์Šค๋กœ ์ „๋‹ฌํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ž‘์—…์ด Iris ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•ด ์–ด๋–ป๊ฒŒ ๊ตฌํ˜„๋˜๋Š”์ง€ ์•Œ์•„๋ณด๊ฒ ์Šต๋‹ˆ๋‹ค. ์ž…๋ ฅ ํ•จ์ˆ˜ ์ž‘์„ฑํ•˜๊ธฐ ํ›ˆ๋ จ, ํ‰๊ฐ€ ๋ฐ ์˜ˆ์ธก์„ ์œ„ํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ์ œ๊ณตํ•˜๋ ค๋ฉด ์ž…๋ ฅ ํ•จ์ˆ˜๋ฅผ ์ž‘์„ฑํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ์ž…๋ ฅ ํ•จ์ˆ˜๋Š” ๋‹ค์Œ ๋‘ ์š”์†Œ ํŠœํ”Œ์„ ์ถœ๋ ฅํ•˜๋Š” tf.data.Dataset ๊ฐ์ฒด๋ฅผ ๋ฐ˜ํ™˜ํ•˜๋Š” ํ•จ์ˆ˜์ž…๋‹ˆ๋‹ค. features -๋‹ค์Œ๊ณผ ๊ฐ™์€ Python ์‚ฌ์ „: ๊ฐ ํ‚ค๊ฐ€ ํŠน์„ฑ์˜ ์ด๋ฆ„์ž…๋‹ˆ๋‹ค. ๊ฐ ๊ฐ’์€ ํ•ด๋‹น ํŠน์„ฑ ๊ฐ’์„ ๋ชจ๋‘ ํฌํ•จํ•˜๋Š” ๋ฐฐ์—ด์ž…๋‹ˆ๋‹ค. label - ๋ชจ๋“  ์˜ˆ์ œ์˜ ๋ ˆ์ด๋ธ” ๊ฐ’์„ ํฌํ•จํ•˜๋Š” ๋ฐฐ์—ด์ž…๋‹ˆ๋‹ค. ์ž…๋ ฅ ํ•จ์ˆ˜์˜ ํ˜•์‹์„ ๋ณด์—ฌ์ฃผ๊ธฐ ์œ„ํ•ด ์—ฌ๊ธฐ์— ๊ฐ„๋‹จํ•œ ๊ตฌํ˜„์„ ๋‚˜ํƒ€๋ƒˆ์Šต๋‹ˆ๋‹ค.
def input_evaluation_set(): features = {'SepalLength': np.array([6.4, 5.0]), 'SepalWidth': np.array([2.8, 2.3]), 'PetalLength': np.array([5.6, 3.3]), 'PetalWidth': np.array([2.2, 1.0])} labels = np.array([2, 1]) return features, labels
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
์ž…๋ ฅ ํ•จ์ˆ˜์—์„œ ์›ํ•˜๋Š” ๋Œ€๋กœ features ์‚ฌ์ „ ๋ฐ label ๋ชฉ๋ก์ด ์ƒ์„ฑ๋˜๋„๋ก ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ชจ๋“  ์ข…๋ฅ˜์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๊ตฌ๋ฌธ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋Š” TensorFlow์˜ Dataset API๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์ด ์ข‹์Šต๋‹ˆ๋‹ค. Dataset API๋Š” ๋งŽ์€ ์ผ๋ฐ˜์ ์ธ ๊ฒฝ์šฐ๋ฅผ ์ž๋™์œผ๋กœ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, Dataset API๋ฅผ ์‚ฌ์šฉํ•˜๋ฉด ๋Œ€๊ทœ๋ชจ ํŒŒ์ผ ๋ชจ์Œ์—์„œ ๋ ˆ์ฝ”๋“œ๋ฅผ ๋ณ‘๋ ฌ๋กœ ์‰ฝ๊ฒŒ ์ฝ๊ณ  ์ด๋ฅผ ๋‹จ์ผ ์ŠคํŠธ๋ฆผ์œผ๋กœ ๊ฒฐํ•ฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์˜ˆ์ œ์—์„œ๋Š” ์ž‘์—…์„ ๋‹จ์ˆœํ™”ํ•˜๊ธฐ ์œ„ํ•ด pandas ๋ฐ์ดํ„ฐ๋ฅผ ๋กœ๋“œํ•˜๊ณ  ์ด ์ธ๋ฉ”๋ชจ๋ฆฌ ๋ฐ์ดํ„ฐ์—์„œ ์ž…๋ ฅ ํŒŒ์ดํ”„๋ผ์ธ์„ ๋นŒ๋“œํ•ฉ๋‹ˆ๋‹ค.
def input_fn(features, labels, training=True, batch_size=256): """An input function for training or evaluating""" # Convert the inputs to a Dataset. dataset = tf.data.Dataset.from_tensor_slices((dict(features), labels)) # Shuffle and repeat if you are in training mode. if training: dataset = dataset.shuffle(1000).repeat() return dataset.batch(batch_size)
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
ํŠน์„ฑ ์—ด ์ •์˜ํ•˜๊ธฐ ํŠน์„ฑ ์—ด์€ ๋ชจ๋ธ์ด ํŠน์„ฑ ์‚ฌ์ „์˜ ์›์‹œ ์ž…๋ ฅ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ์‹์„ ์„ค๋ช…ํ•˜๋Š” ๊ฐ์ฒด์ž…๋‹ˆ๋‹ค. Estimator ๋ชจ๋ธ์„ ๋นŒ๋“œํ•  ๋•Œ๋Š” ๋ชจ๋ธ์—์„œ ์‚ฌ์šฉํ•  ๊ฐ ํŠน์„ฑ์„ ์„ค๋ช…ํ•˜๋Š” ํŠน์„ฑ ์—ด ๋ชฉ๋ก์„ ์ „๋‹ฌํ•ฉ๋‹ˆ๋‹ค. tf.feature_column ๋ชจ๋“ˆ์€ ๋ชจ๋ธ์— ๋ฐ์ดํ„ฐ๋ฅผ ๋‚˜ํƒ€๋‚ด๊ธฐ ์œ„ํ•œ ๋งŽ์€ ์˜ต์…˜์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. Iris์˜ ๊ฒฝ์šฐ 4๊ฐœ์˜ ์›์‹œ ํŠน์„ฑ์€ ์ˆซ์ž ๊ฐ’์ด๋ฏ€๋กœ, ๋„ค ๊ฐœ์˜ ํŠน์„ฑ ๊ฐ๊ฐ์„ 32-bit ๋ถ€๋™ ์†Œ์ˆ˜์  ๊ฐ’์œผ๋กœ ๋‚˜ํƒ€๋‚ด๋„๋ก Estimator ๋ชจ๋ธ์— ์•Œ๋ ค์ฃผ๋Š” ํŠน์„ฑ ์—ด ๋ชฉ๋ก์„ ๋นŒ๋“œํ•ฉ๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ํŠน์„ฑ ์—ด์„ ์ž‘์„ฑํ•˜๋Š” ์ฝ”๋“œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค.
# Feature columns describe how to use the input. my_feature_columns = [] for key in train.keys(): my_feature_columns.append(tf.feature_column.numeric_column(key=key))
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
ํŠน์„ฑ ์—ด์€ ์—ฌ๊ธฐ์— ํ‘œ์‹œ๋œ ๊ฒƒ๋ณด๋‹ค ํ›จ์”ฌ ์ •๊ตํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๊ฐ€์ด๋“œ์—์„œ ํŠน์„ฑ ์—ด์— ๋Œ€ํ•œ ์ž์„ธํ•œ ๋‚ด์šฉ์„ ์ฝ์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ชจ๋ธ์ด ์›์‹œ ํŠน์„ฑ์„ ๋‚˜ํƒ€๋‚ด๋„๋ก ํ•  ๋ฐฉ์‹์— ๋Œ€ํ•œ ์„ค๋ช…์ด ์ค€๋น„๋˜์—ˆ์œผ๋ฏ€๋กœ Estimator๋ฅผ ๋นŒ๋“œํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. Estimator ์ธ์Šคํ„ด์Šคํ™”ํ•˜๊ธฐ Iris ๋ฌธ์ œ๋Š” ๊ณ ์ „์ ์ธ ๋ถ„๋ฅ˜ ๋ฌธ์ œ์ž…๋‹ˆ๋‹ค. ๋‹คํ–‰ํžˆ๋„ TensorFlow๋Š” ๋‹ค์Œ์„ ํฌํ•จํ•˜์—ฌ ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์‚ฌ์ „ ์ œ์ž‘๋œ ๋ถ„๋ฅ˜์ž Estimator๋ฅผ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋‹ค์ค‘ ํด๋ž˜์Šค ๋ถ„๋ฅ˜๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ์‹ฌ์ธต ๋ชจ๋ธ์„ ์œ„ํ•œ tf.estimator.DNNClassifier ๋„“๊ณ  ๊นŠ์€ ๋ชจ๋ธ์„ ์œ„ํ•œ tf.estimator.DNNLinearCombinedClassifier ์„ ํ˜• ๋ชจ๋ธ์— ๊ธฐ์ดˆํ•œ ๋ถ„๋ฅ˜์ž๋ฅผ ์œ„ํ•œ tf.estimator.LinearClassifier Iris ๋ฌธ์ œ์˜ ๊ฒฝ์šฐ tf.estimator.DNNClassifier๊ฐ€ ์ตœ์„ ์˜ ์„ ํƒ์ธ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง‘๋‹ˆ๋‹ค. ์ด Estimator๋ฅผ ์ธ์Šคํ„ด์Šคํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์€ ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค.
# Build a DNN with 2 hidden layers with 30 and 10 hidden nodes each. classifier = tf.estimator.DNNClassifier( feature_columns=my_feature_columns, # Two hidden layers of 30 and 10 nodes respectively. hidden_units=[30, 10], # The model must choose between 3 classes. n_classes=3)
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
ํ›ˆ๋ จ, ํ‰๊ฐ€ ๋ฐ ์˜ˆ์ธกํ•˜๊ธฐ ์ด์ œ Estimator ๊ฐ์ฒด๊ฐ€ ์ค€๋น„๋˜์—ˆ์œผ๋ฏ€๋กœ ๋ฉ”์„œ๋“œ๋ฅผ ํ˜ธ์ถœํ•˜์—ฌ ๋‹ค์Œ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ชจ๋ธ์„ ํ›ˆ๋ จํ•ฉ๋‹ˆ๋‹ค. ํ›ˆ๋ จํ•œ ๋ชจ๋ธ์„ ํ‰๊ฐ€ํ•ฉ๋‹ˆ๋‹ค. ํ›ˆ๋ จํ•œ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์˜ˆ์ธก์„ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค. ๋ชจ๋ธ ํ›ˆ๋ จํ•˜๊ธฐ ๋‹ค์Œ๊ณผ ๊ฐ™์ด Estimator์˜ train ๋ฉ”์„œ๋“œ๋ฅผ ํ˜ธ์ถœํ•˜์—ฌ ๋ชจ๋ธ์„ ํ›ˆ๋ จํ•ฉ๋‹ˆ๋‹ค.
# Train the Model. classifier.train( input_fn=lambda: input_fn(train, train_y, training=True), steps=5000)
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
Estimator๊ฐ€ ์˜ˆ์ƒํ•œ ๋Œ€๋กœ ์ธ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์ง€ ์•Š๋Š” ์ž…๋ ฅ ํ•จ์ˆ˜๋ฅผ ์ œ๊ณตํ•˜๋ฉด์„œ ์ธ์ˆ˜๋ฅผ ํฌ์ฐฉํ•˜๊ธฐ ์œ„ํ•ด lambda์—์„œ input_fn ํ˜ธ์ถœ์„ ๋ž˜ํ•‘ํ•ฉ๋‹ˆ๋‹ค. steps ์ธ์ˆ˜๋Š” ์—ฌ๋Ÿฌ ํ›ˆ๋ จ ๋‹จ๊ณ„๋ฅผ ๊ฑฐ์นœ ํ›„์— ํ›ˆ๋ จ์„ ์ค‘์ง€ํ•˜๋„๋ก ๋ฉ”์„œ๋“œ์— ์ง€์‹œํ•ฉ๋‹ˆ๋‹ค. ํ›ˆ๋ จํ•œ ๋ชจ๋ธ ํ‰๊ฐ€ํ•˜๊ธฐ ๋ชจ๋ธ์„ ํ›ˆ๋ จํ–ˆ์œผ๋ฏ€๋กœ ์„ฑ๋Šฅ์— ๋Œ€ํ•œ ํ†ต๊ณ„๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋‹ค์Œ ์ฝ”๋“œ ๋ธ”๋ก์€ ํ…Œ์ŠคํŠธ ๋ฐ์ดํ„ฐ์—์„œ ํ›ˆ๋ จํ•œ ๋ชจ๋ธ์˜ ์ •ํ™•๋„๋ฅผ ํ‰๊ฐ€ํ•ฉ๋‹ˆ๋‹ค.
eval_result = classifier.evaluate( input_fn=lambda: input_fn(test, test_y, training=False)) print('\nTest set accuracy: {accuracy:0.3f}\n'.format(**eval_result))
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
train ๋ฉ”์„œ๋“œ์— ๋Œ€ํ•œ ํ˜ธ์ถœ๊ณผ ๋‹ฌ๋ฆฌ ํ‰๊ฐ€ํ•  steps ์ธ์ˆ˜๋ฅผ ์ „๋‹ฌํ•˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. eval์— ๋Œ€ํ•œ input_fn์€ ๋‹จ ํ•˜๋‚˜์˜ ๋ฐ์ดํ„ฐ epoch๋งŒ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค. eval_result ์‚ฌ์ „์—๋Š” average_loss(์ƒ˜ํ”Œ๋‹น ํ‰๊ท  ์†์‹ค), loss(๋ฏธ๋‹ˆ ๋ฐฐ์น˜๋‹น ํ‰๊ท  ์†์‹ค) ๋ฐ Estimator์˜ global_step ๊ฐ’(๋ฐ›์€ ํ›ˆ๋ จ ๋ฐ˜๋ณต ํšŸ์ˆ˜)๋„ ํฌํ•จ๋ฉ๋‹ˆ๋‹ค. ํ›ˆ๋ จํ•œ ๋ชจ๋ธ์—์„œ ์˜ˆ์ธก(์ถ”๋ก )ํ•˜๊ธฐ ์šฐ์ˆ˜ํ•œ ํ‰๊ฐ€ ๊ฒฐ๊ณผ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ํ›ˆ๋ จํ•œ ๋ชจ๋ธ์„ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค. ์ด์ œ ํ›ˆ๋ จํ•œ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ ˆ์ด๋ธ”์ด ์ง€์ •๋˜์ง€ ์•Š์€ ์ผ๋ถ€ ์ธก์ •์„ ๋ฐ”ํƒ•์œผ๋กœ ์•„์ด๋ฆฌ์Šค ๊ฝƒ์˜ ์ข…์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํ›ˆ๋ จ ๋ฐ ํ‰๊ฐ€์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ๋‹จ์ผ ํ•จ์ˆ˜ ํ˜ธ์ถœ์„ ์‚ฌ์šฉํ•˜์—ฌ ์˜ˆ์ธกํ•ฉ๋‹ˆ๋‹ค.
# Generate predictions from the model expected = ['Setosa', 'Versicolor', 'Virginica'] predict_x = { 'SepalLength': [5.1, 5.9, 6.9], 'SepalWidth': [3.3, 3.0, 3.1], 'PetalLength': [1.7, 4.2, 5.4], 'PetalWidth': [0.5, 1.5, 2.1], } def input_fn(features, batch_size=256): """An input function for prediction.""" # Convert the inputs to a Dataset without labels. return tf.data.Dataset.from_tensor_slices(dict(features)).batch(batch_size) predictions = classifier.predict( input_fn=lambda: input_fn(predict_x))
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
predict ๋ฉ”์„œ๋“œ๋Š” Python iterable์„ ๋ฐ˜ํ™˜ํ•˜์—ฌ ๊ฐ ์˜ˆ์ œ์— ๋Œ€ํ•œ ์˜ˆ์ธก ๊ฒฐ๊ณผ ์‚ฌ์ „์„ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค. ๋‹ค์Œ ์ฝ”๋“œ๋Š” ๋ช‡ ๊ฐ€์ง€ ์˜ˆ์ธก๊ณผ ํ•ด๋‹น ํ™•๋ฅ ์„ ์ถœ๋ ฅํ•ฉ๋‹ˆ๋‹ค.
for pred_dict, expec in zip(predictions, expected): class_id = pred_dict['class_ids'][0] probability = pred_dict['probabilities'][class_id] print('Prediction is "{}" ({:.1f}%), expected "{}"'.format( SPECIES[class_id], 100 * probability, expec))
site/ko/tutorials/estimator/premade.ipynb
tensorflow/docs-l10n
apache-2.0
Generating a click example Lets start by degradating some audio files with some clicks of different amplitudes
fs = 44100. audio_dir = '../../audio/' audio = es.MonoLoader(filename='{}/{}'.format(audio_dir, 'recorded/vignesh.wav'), sampleRate=fs)() originalLen = len(audio) jumpLocation1 = int(originalLen / 4.) jumpLocation2 = int(originalLen / 2.) jumpLocation3 = int(originalLen * 3 / 4.) audio[jumpLocation1] += .5 audio[jumpLocation2] += .15 audio[jumpLocation3] += .05 groundTruth = esarr([jumpLocation1, jumpLocation2, jumpLocation3]) / fs for point in groundTruth: l1 = plt.axvline(point, color='g', alpha=.5) times = np.linspace(0, len(audio) / fs, len(audio)) plt.plot(times, audio) l1.set_label('Click locations') plt.legend() plt.title('Signal with artificial clicks of different amplitudes')
src/examples/tutorial/example_clickdetector.ipynb
carthach/essentia
agpl-3.0
Lets listen to the clip to have an idea on how audible the clips are
Audio(audio, rate=fs)
src/examples/tutorial/example_clickdetector.ipynb
carthach/essentia
agpl-3.0
The algorithm This algorithm outputs the starts and ends timestapms of the clicks. The following plots show how the algorithm performs in the previous examples
starts, ends = compute(audio) fig, ax = plt.subplots(len(groundTruth)) plt.subplots_adjust(hspace=.4) for idx, point in enumerate(groundTruth): l1 = ax[idx].axvline(starts[idx], color='r', alpha=.5) ax[idx].axvline(ends[idx], color='r', alpha=.5) l2 = ax[idx].axvline(point, color='g', alpha=.5) ax[idx].plot(times, audio) ax[idx].set_xlim([point-.001, point+.001]) ax[idx].set_title('Click located at {:.2f}s'.format(point)) fig.legend((l1, l2), ('Detected click', 'Ground truth'), 'upper right')
src/examples/tutorial/example_clickdetector.ipynb
carthach/essentia
agpl-3.0
BigQuery Data If you have not gone through the KFP Walkthrough lab, you will need to run the following cell to create a BigQuery dataset and table containing the data required for this lab. NOTE If you already have the covertype data in a bigquery table at &lt;PROJECT_ID&gt;.covertype_dataset.covertype you may skip to Understanding the pipeline design.
%%bash DATASET_LOCATION=US DATASET_ID=covertype_dataset TABLE_ID=covertype DATA_SOURCE=gs://workshop-datasets/covertype/small/dataset.csv SCHEMA=Elevation:INTEGER,\ Aspect:INTEGER,\ Slope:INTEGER,\ Horizontal_Distance_To_Hydrology:INTEGER,\ Vertical_Distance_To_Hydrology:INTEGER,\ Horizontal_Distance_To_Roadways:INTEGER,\ Hillshade_9am:INTEGER,\ Hillshade_Noon:INTEGER,\ Hillshade_3pm:INTEGER,\ Horizontal_Distance_To_Fire_Points:INTEGER,\ Wilderness_Area:STRING,\ Soil_Type:STRING,\ Cover_Type:INTEGER bq --location=$DATASET_LOCATION --project_id=$PROJECT mk --dataset $DATASET_ID bq --project_id=$PROJECT --dataset_id=$DATASET_ID load \ --source_format=CSV \ --skip_leading_rows=1 \ --replace \ $TABLE_ID \ $DATA_SOURCE \ $SCHEMA
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Understanding the pipeline design The workflow implemented by the pipeline is defined using a Python based Domain Specific Language (DSL). The pipeline's DSL is in the pipeline_vertex/pipeline_vertex_automl_batch_preds.py file that we will generate below. The pipeline's DSL has been designed to avoid hardcoding any environment specific settings like file paths or connection strings. These settings are provided to the pipeline code through a set of environment variables. Building and deploying the pipeline Let us write the pipeline to disk:
%%writefile ./pipeline_vertex/pipeline_vertex_automl_batch_preds.py """Kubeflow Covertype Pipeline.""" import os from google_cloud_pipeline_components.aiplatform import ( AutoMLTabularTrainingJobRunOp, TabularDatasetCreateOp, ModelBatchPredictOp ) from kfp.v2 import dsl PIPELINE_ROOT = os.getenv("PIPELINE_ROOT") PROJECT = os.getenv("PROJECT") DATASET_SOURCE = os.getenv("DATASET_SOURCE") PIPELINE_NAME = os.getenv("PIPELINE_NAME", "covertype") DISPLAY_NAME = os.getenv("MODEL_DISPLAY_NAME", PIPELINE_NAME) TARGET_COLUMN = os.getenv("TARGET_COLUMN", "Cover_Type") BATCH_PREDS_SOURCE_URI = os.getenv("BATCH_PREDS_SOURCE_URI") @dsl.pipeline( name=f"{PIPELINE_NAME}-vertex-automl-pipeline-batch-preds", description=f"AutoML Vertex Pipeline for {PIPELINE_NAME}", pipeline_root=PIPELINE_ROOT, ) def create_pipeline(): dataset_create_task = TabularDatasetCreateOp( display_name=DISPLAY_NAME, bq_source=DATASET_SOURCE, project=PROJECT, ) automl_training_task = AutoMLTabularTrainingJobRunOp( project=PROJECT, display_name=DISPLAY_NAME, optimization_prediction_type="classification", dataset=dataset_create_task.outputs["dataset"], target_column=TARGET_COLUMN, ) batch_predict_op = ModelBatchPredictOp( project=PROJECT, job_display_name="batch_predict_job", model=automl_training_task.outputs["model"], bigquery_source_input_uri=BATCH_PREDS_SOURCE_URI, instances_format="bigquery", predictions_format="bigquery", bigquery_destination_output_uri=f'bq://{PROJECT}', )
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Understanding the ModelBatchPredictOp When working with an AutoML Tabular model, the ModelBatchPredictOp can take the following inputs: * model: The model resource to serve batch predictions with * bigquery_source_uri: A URI to a BigQuery table containing examples to serve batch predictions on in the format bq://PROJECT.DATASET.TABLE * instances_format: "bigquery" to serve batch predictions on BigQuery data. * predictions_format: "bigquery" to store the results of the batch prediction in BigQuery. * bigquery_destination_output_uri: In the format bq://PROJECT_ID. This is the project that the results of the batch prediction will be stored. The ModelBatchPredictOp will create a dataset in this project. Upon completion of the ModelBatchPredictOp you will see a new BigQuery dataset with name prediction_&lt;model-display-name&gt;_&lt;job-create-time&gt;. Inside this dataset you will see a predictions table, containing the batch prediction examples and predicted labels. If there were any errors in the batch prediction, you will also see an errors table. The errors table contains rows for which the prediction has failed. Create BigQuery table with data for batch predictions Before we compile and run the pipeline, let's create a BigQuery table with data we want to serve batch predictions on. To simulate "new" data we will simply query the existing table for all columns except the label and create a table called newdata. The URI to this table will be the bigquery_source_input_uri input to the ModelBatchPredictOp.
%%bigquery CREATE OR REPLACE TABLE covertype_dataset.newdata AS SELECT * EXCEPT(Cover_Type) FROM covertype_dataset.covertype LIMIT 10000
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Compile the pipeline Let's start by defining the environment variables that will be passed to the pipeline compiler:
ARTIFACT_STORE = f"gs://{PROJECT}-kfp-artifact-store" PIPELINE_ROOT = f"{ARTIFACT_STORE}/pipeline" DATASET_SOURCE = f"bq://{PROJECT}.covertype_dataset.covertype" BATCH_PREDS_SOURCE_URI = f"bq://{PROJECT}.covertype_dataset.newdata" %env PIPELINE_ROOT={PIPELINE_ROOT} %env PROJECT={PROJECT} %env REGION={REGION} %env DATASET_SOURCE={DATASET_SOURCE} %env BATCH_PREDS_SOURCE_URI={BATCH_PREDS_SOURCE_URI}
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Let us make sure that the ARTIFACT_STORE has been created, and let us create it if not:
!gsutil ls | grep ^{ARTIFACT_STORE}/$ || gsutil mb -l {REGION} {ARTIFACT_STORE}
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Use the CLI compiler to compile the pipeline We compile the pipeline from the Python file we generated into a JSON description using the following command:
PIPELINE_JSON = "covertype_automl_vertex_pipeline_batch_preds.json" !dsl-compile-v2 --py pipeline_vertex/pipeline_vertex_automl_batch_preds.py --output $PIPELINE_JSON
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Note: You can also use the Python SDK to compile the pipeline: ```python from kfp.v2 import compiler compiler.Compiler().compile( pipeline_func=create_pipeline, package_path=PIPELINE_JSON, ) ``` The result is the pipeline file.
!head {PIPELINE_JSON}
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Deploy the pipeline package
aiplatform.init(project=PROJECT, location=REGION) pipeline = aiplatform.PipelineJob( display_name="automl_covertype_kfp_pipeline_batch_predictions", template_path=PIPELINE_JSON, enable_caching=True, ) pipeline.run()
notebooks/kubeflow_pipelines/pipelines/solutions/kfp_pipeline_vertex_automl_batch_predictions.ipynb
GoogleCloudPlatform/asl-ml-immersion
apache-2.0
Import raw data The user needs to specify the directories containing the data of interest. Each sample type should have a key which corresponds to the directory path. Additionally, each object should have a list that includes the channels of interest.
# -------------------------------- # -------- User input ------------ # -------------------------------- data = { # Specify sample type key 'wt': { # Specify path to data directory 'path': 'path\to\data\directory\sample1', # Specify which channels are in the directory and are of interest 'channels': ['AT','ZRF'] }, 'stype2': { 'path': 'path\to\data\directory\sample2', 'channels': ['AT','ZRF'] } }
experiments/templates/TEMP-landmarks.ipynb
msschwartz21/craniumPy
gpl-3.0
We'll generate a list of pairs of stypes and channels for ease of use.
data_pairs = [] for s in data.keys(): for c in data[s]['channels']: data_pairs.append((s,c))
experiments/templates/TEMP-landmarks.ipynb
msschwartz21/craniumPy
gpl-3.0
We can now read in all datafiles specified by the data dictionary above.
D = {} for s in data.keys(): D[s] = {} for c in data[s]['channels']: D[s][c] = ds.read_psi_to_dict(data[s]['path'],c)
experiments/templates/TEMP-landmarks.ipynb
msschwartz21/craniumPy
gpl-3.0
Calculate landmark bins
# -------------------------------- # -------- User input ------------ # -------------------------------- # Pick an integer value for bin number based on results above anum = 25 # Specify the percentiles which will be used to calculate landmarks percbins = [50]
experiments/templates/TEMP-landmarks.ipynb
msschwartz21/craniumPy
gpl-3.0
Calculate landmark bins based on user input parameters and the previously specified control sample.
lm = ds.landmarks(percbins=percbins, rnull=np.nan) lm.calc_bins(D[s_ctrl][c_ctrl], anum, theta_step) print('Alpha bins') print(lm.acbins) print('Theta bins') print(lm.tbins)
experiments/templates/TEMP-landmarks.ipynb
msschwartz21/craniumPy
gpl-3.0
Calculate landmarks
lmdf = pd.DataFrame() # Loop through each pair of stype and channels for s,c in tqdm.tqdm(data_pairs): print(s,c) # Calculate landmarks for each sample with this data pair for k,df in tqdm.tqdm(D[s][c].items()): lmdf = lm.calc_perc(df, k, '-'.join([s,c]), lmdf) # Set timestamp for saving data tstamp = time.strftime("%m-%d-%H-%M",time.localtime()) # Save completed landmarks to a csv file lmdf.to_csv(tstamp+'_landmarks.csv') # Save landmark bins to json file bins = { 'acbins':list(lm.acbins), 'tbins':list(lm.tbins) } with open(tstamp+'_landmarks_bins.json', 'w') as outfile: json.dump(bins, outfile)
experiments/templates/TEMP-landmarks.ipynb
msschwartz21/craniumPy
gpl-3.0
EEG forward operator with a template MRI This tutorial explains how to compute the forward operator from EEG data using the standard template MRI subject fsaverage. .. caution:: Source reconstruction without an individual T1 MRI from the subject will be less accurate. Do not over interpret activity locations which can be off by multiple centimeters. Adult template MRI (fsaverage) First we show how fsaverage can be used as a surrogate subject.
# Authors: Alexandre Gramfort <[email protected]> # Joan Massich <[email protected]> # Eric Larson <[email protected]> # # License: BSD-3-Clause import os.path as op import numpy as np import mne from mne.datasets import eegbci from mne.datasets import fetch_fsaverage # Download fsaverage files fs_dir = fetch_fsaverage(verbose=True) subjects_dir = op.dirname(fs_dir) # The files live in: subject = 'fsaverage' trans = 'fsaverage' # MNE has a built-in fsaverage transformation src = op.join(fs_dir, 'bem', 'fsaverage-ico-5-src.fif') bem = op.join(fs_dir, 'bem', 'fsaverage-5120-5120-5120-bem-sol.fif')
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
Load the data We use here EEG data from the BCI dataset. <div class="alert alert-info"><h4>Note</h4><p>See `plot_montage` to view all the standard EEG montages available in MNE-Python.</p></div>
raw_fname, = eegbci.load_data(subject=1, runs=[6]) raw = mne.io.read_raw_edf(raw_fname, preload=True) # Clean channel names to be able to use a standard 1005 montage new_names = dict( (ch_name, ch_name.rstrip('.').upper().replace('Z', 'z').replace('FP', 'Fp')) for ch_name in raw.ch_names) raw.rename_channels(new_names) # Read and set the EEG electrode locations, which are already in fsaverage's # space (MNI space) for standard_1020: montage = mne.channels.make_standard_montage('standard_1005') raw.set_montage(montage) raw.set_eeg_reference(projection=True) # needed for inverse modeling # Check that the locations of EEG electrodes is correct with respect to MRI mne.viz.plot_alignment( raw.info, src=src, eeg=['original', 'projected'], trans=trans, show_axes=True, mri_fiducials=True, dig='fiducials')
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
Setup source space and compute forward
fwd = mne.make_forward_solution(raw.info, trans=trans, src=src, bem=bem, eeg=True, mindist=5.0, n_jobs=None) print(fwd)
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
From here on, standard inverse imaging methods can be used! Infant MRI surrogates We don't have a sample infant dataset for MNE, so let's fake a 10-20 one:
ch_names = \ 'Fz Cz Pz Oz Fp1 Fp2 F3 F4 F7 F8 C3 C4 T7 T8 P3 P4 P7 P8 O1 O2'.split() data = np.random.RandomState(0).randn(len(ch_names), 1000) info = mne.create_info(ch_names, 1000., 'eeg') raw = mne.io.RawArray(data, info)
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
Get an infant MRI template To use an infant head model for M/EEG data, you can use :func:mne.datasets.fetch_infant_template to download an infant template:
subject = mne.datasets.fetch_infant_template('6mo', subjects_dir, verbose=True)
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
It comes with several helpful built-in files, including a 10-20 montage in the MRI coordinate frame, which can be used to compute the MRI<->head transform trans:
fname_1020 = op.join(subjects_dir, subject, 'montages', '10-20-montage.fif') mon = mne.channels.read_dig_fif(fname_1020) mon.rename_channels( {f'EEG{ii:03d}': ch_name for ii, ch_name in enumerate(ch_names, 1)}) trans = mne.channels.compute_native_head_t(mon) raw.set_montage(mon) print(trans)
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
There are also BEM and source spaces:
bem_dir = op.join(subjects_dir, subject, 'bem') fname_src = op.join(bem_dir, f'{subject}-oct-6-src.fif') src = mne.read_source_spaces(fname_src) print(src) fname_bem = op.join(bem_dir, f'{subject}-5120-5120-5120-bem-sol.fif') bem = mne.read_bem_solution(fname_bem)
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause
You can ensure everything is as expected by plotting the result:
fig = mne.viz.plot_alignment( raw.info, subject=subject, subjects_dir=subjects_dir, trans=trans, src=src, bem=bem, coord_frame='mri', mri_fiducials=True, show_axes=True, surfaces=('white', 'outer_skin', 'inner_skull', 'outer_skull')) mne.viz.set_3d_view(fig, 25, 70, focalpoint=[0, -0.005, 0.01])
dev/_downloads/1242d47b65d952f9f80cf19fb9e5d76e/35_eeg_no_mri.ipynb
mne-tools/mne-tools.github.io
bsd-3-clause