readme had old optimizer calls in it

Author: pavelkomarov

README.md

@@ -121,30 +121,31 @@ So you can see more details about the API usage [there](https://pynumdiff.readth
 ### Basic usages
 
 * Basic Usage: you provide the parameters
-```bash
-        x_hat, dxdt_hat = pynumdiff.sub_module.method(x, dt, params, options)     
+```python
+    from pynumdiff.submodule import method
+
+    x_hat, dxdt_hat = method(x, dt, params, options)     
 ```
 * Intermediate usage: automated parameter selection through multi-objective optimization
-```bash
-        params, val = pynumdiff.optimize.sub_module.method(x, dt, params=None, 
-                                                           tvgamma=tvgamma, # hyperparameter
-                                                           dxdt_truth=None, # no ground truth data
-                                                           options={})
-        print('Optimal parameters: ', params)
-        x_hat, dxdt_hat = pynumdiff.sub_module.method(x, dt, params, options={'smooth': True})`
+```python
+    from pynumdiff.optimize import optimize
+
+    params, val = optimize(method, x, dt, search_space={'param1':[options], 'param2':[options], ...},
+                                            tvgamma=tvgamma, # hyperparameter, defaults to None if dxdt_truth given
+                                            dxdt_truth=None) # or give ground truth data, in which case tvgamma unused
+    print('Optimal parameters: ', params)
+    x_hat, dxdt_hat = method(x, dt, **params)`
 ```
 * Advanced usage: automated parameter selection through multi-objective optimization using a user-defined cutoff frequency
-```bash
-        # cutoff_freq: estimate by (a) counting the number of true peaks per second in the data or (b) look at power spectra and choose cutoff
-        log_gamma = -1.6*np.log(cutoff_frequency) -0.71*np.log(dt) - 5.1 # see: https://ieeexplore.ieee.org/abstract/document/9241009
-        tvgamma = np.exp(log_gamma) 
-
-        params, val = pynumdiff.optimize.sub_module.method(x, dt, params=None, 
-                                                           tvgamma=tvgamma, # hyperparameter
-                                                           dxdt_truth=None, # no ground truth data
-                                                           options={})
-        print('Optimal parameters: ', params)
-        x_hat, dxdt_hat = pynumdiff.sub_module.method(x, dt, params, options={'smooth': True})`
+```python
+    # cutoff_freq: estimate by (a) counting the number of true peaks per second in the data or (b) look at power spectra and choose cutoff
+    log_gamma = -1.6*np.log(cutoff_frequency) -0.71*np.log(dt) - 5.1 # see: https://ieeexplore.ieee.org/abstract/document/9241009
+    tvgamma = np.exp(log_gamma) 
+
+    params, val = optimize(method, x, dt, search_space={'param1':[options], 'param2':[options], ...},
+                                            tvgamma=tvgamma)
+    print('Optimal parameters: ', params)
+    x_hat, dxdt_hat = method(x, dt, **params)`
 ```
 
 ### Notebook examples
@@ -170,7 +171,7 @@ To run tests locally, type:
 > pytest pynumdiff
 ```
 
-Add the flag `--plot` to see plots of the methods against test functions.
+Add the flag `--plot` to see plots of the methods against test functions. Add the flag `--bounds` to print log error bounds (useful when changing method behavior).
 
 ## License