Update README and fix pixel plotter

README.md

@@ -29,10 +29,7 @@ The simplest way of using YATSM would be the pixel-by-pixel command line interfa
 We'll use the example [Landsat stack from Chiapas, Mexico](https://github.com/ceholden/landsat_stack) for this demonstration:
 
 ``` bash
-    > run_yatsm.py --consecutive=5 --threshold=3 --min_obs=16 \
-    ... --freq=1 --min_rmse 100 --test_indices "2 4 5" --screening RLM \
-    ... --plot_index=2 --plot_style xkcd \
-    ... ../landsat_stack/p022r049/images/ 133 106
+    > yatsm pixel --band 2 --style xkcd examples/p022r049/p022r049.yaml 133 106
 ```
 
 Produces:

yatsm/cli/pixel.py

@@ -90,7 +90,7 @@ def pixel(ctx, config, px, py, band, plot, ylim, style, cmap,
                       (cfg_key, kw, cfg[cfg_key][kw], value))
                 cfg[cfg_key][kw] = value
                 revalidate = True
-                
+
     if revalidate:
         cfg = convert_config(cfg)
 
@@ -146,13 +146,11 @@ def pixel(ctx, config, px, py, band, plot, ylim, style, cmap,
             plt.show()
 
     # Eliminate config parameters not algorithm and fit model
-    yatsm = cfg['YATSM']['algorithm_cls'](
-        fit_indices,
-        design_info,
-        lm=cfg['YATSM']['prediction_object'],
-        px=px, py=py,
-        **cfg[cfg['YATSM']['algorithm']])
-    yatsm.fit(X, Y)
+    yatsm = cfg['YATSM']['algorithm_cls'](lm=cfg['YATSM']['prediction_object'],
+                                          **cfg[cfg['YATSM']['algorithm']])
+    yatsm.px = px
+    yatsm.py = py
+    yatsm.fit(X, Y, np.asarray(df['date'][valid]))
 
     # Plot after predictions
     with plt.xkcd() if style == 'xkcd' else mpl.style.context(style):