锁屏总结

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1:基本原理。

与大多数第三方锁屏软件一样，通过广播启动锁屏服务，然后监听屏幕黑屏或者亮屏的广播来执行锁屏动作。

这是注册开机启动的广播，与其他一些静态广播接收者，来实现服务的不死与开机快速启动。

<intent-filter android:priority="2147483647" >

</intent-filter>

</receiver>

如果是做方案的定制应用，那么有root权限的情况下，我们可以在主配置文件中加上一些参数来达到不被第三方清理应用杀死的功能。

<manifest xmlns:android="http://schemas.android.com/apk/res/android"

package="yourpackagename"

android:versionCode="1"

android:versionName="1.0" >

coreApp="true"

android:sharedUserId="android.uid.systemui"

<application

android:allowBackup="true"

android:icon="@drawable/ic_launcher"

android:installLocation="internalOnly"

android:label="@string/app_name"

android:largeHeap="true"

android:persistent="true"

android:process="com.android.systemui"

android:theme="@android:style/Theme.NoTitleBar" >

如果是应用可以仿照go锁屏，使用的是android:process=“android.process.acore”。我试过，在vivo手机上，具有该标志的应用将会被识别成系统级别的应用，使用系统一键清理不会去杀死运行在这个进程中的程序。

服务KeyGuradService

这个服务是在开机或者第一次打开应用程序的时候就会启动，在注册的静态广播中，根据判断服务运行状态，通过监听系统的各种广播来实现服务不死的原理。

锁屏类别：

锁屏开发视图有两种方式，一种是采用Activity，一种是采用悬浮窗口。前者承载力强，对于复杂的视图运行力度较为流畅，缺点是需要考虑屏蔽Home按键与下拉状态栏事件的处理，对于安卓碎片化的问题来说，使用这种方式做第三方锁屏简直就是噩梦。第二种方式是使用悬浮窗口。给出配置代码。

private WindowManager mWindowManager;

private WindowManager.LayoutParams mParams;

this.mWindowManager = ((WindowManager) context.getApplicationContext()

.getSystemService(Context.WINDOW_SERVICE));

mParams = new WindowManager.LayoutParams();

mParams.screenOrientation = ActivityInfo.SCREEN_ORIENTATION_PORTRAIT;

mParams.width = -1;

mParams.height = -1;

mParams.type = WindowManager.LayoutParams.TYPE_SYSTEM_ERROR;

if (Preferences.isFullScreen(context))

mParams.flags = WindowManager.LayoutParams.FLAG_FULLSCREEN

| WindowManager.LayoutParams.FLAG_LAYOUT_IN_SCREEN;

else

mParams.flags = WindowManager.LayoutParams.FLAG_FORCE_NOT_FULLSCREEN;

mWindowManager.addView(v, mParams);

使用error类别的悬浮窗口可以忽略按键的处理，因为不根据锁屏逻辑来解锁的话，锁屏视图是一致会叠加在窗口的最顶层。优点固然明显，缺点也显而易见。比如我在开发带密码锁的滑动锁屏时，涉及到ViewGroup的使用，在添加两个子视图的时候，流程度远没有在Activity上的使用的流畅。

如果使用Activity的锁屏方式，首先要解决的是Home按键的屏蔽，我在网上找到这样一种解决方式

public static final int FLAG_HOMEKEY_DISPATCHED = 0x80000000;

getWindow().setFlags(FLAG_HOMEKEY_DISPATCHED, FLAG_HOMEKEY_DISPATCHED);

在我们公司的手机上是可用的，其他手机没有测试过。再次说明，如果是定制手机的话，我们大可以在frameworks中的PhoneWindowManager.java中来解决这个问题。

至于下拉状态栏，我的处理方法是，如果是双锁屏我使用Activity的情况下，使用全屏布局，将状态栏dismiss调，如果是单个视图的锁屏，使用悬浮框的模式。当然，如果是你的应用能够push到System/app当中去，作为系统级别应用。那就大可以使用系统隐藏的API函数 StatusBarManager来实现。

源码路径在frameworks/base/core/java/android/app/

实现代码：

  /**
     * Disable some features in the status bar.  Pass the bitwise-or of the DISABLE_* flags.
     * To re-enable everything, pass {@link #DISABLE_NONE}.
     */
    public void disable(int what) {
        try {
            final IStatusBarService svc = getService();
            if (svc != null) {
                svc.disable(what, mToken, mContext.getPackageName());
            }
        } catch (RemoteException ex) {
            // system process is dead anyway.
            throw new RuntimeException(ex);
        }
    }

如果开发的锁屏可以在源码中编译，可直接使用该函数。

如果您使用的是eclipse开发的话，可以在编译的out目录下面找到frameworks与core编译的过程文件class.jar。通过User Library的方式关联到你的代码中。编译通过后，直接push到System/app下，可以看到效果，注意您的主配置文件需要添加我前面所写的标志。

图片的高斯模糊：

开源的力量真是伟大的，我的背景高斯模糊处理使用的是网上提供的一种通用方法，将图片压缩后高斯模糊处理再还原。添加一个View，透明度为0,设置背景为高斯模糊后的背景。添加在FrameLayout为父布局的layout中，叠加在锁屏视图上，通过监听锁屏滑动，来计算他的透明度，来实现高斯模糊。

网上提供的高斯模糊处理

public static Bitmap doBlur(Bitmap sentBitmap, int radius, boolean canReuseInBitmap) {

// Stack Blur v1.0 from

// http://www.quasimondo.com/StackBlurForCanvas/StackBlurDemo.html

// Java Author: Mario Klingemann <mario at quasimondo.com>

// http://incubator.quasimondo.com

// created Feburary 29, 2004

// Android port : Yahel Bouaziz <yahel at kayenko.com>

// http://www.kayenko.com

// ported april 5th, 2012

// This is a compromise between Gaussian Blur and Box blur

// It creates much better looking blurs than Box Blur, but is

// 7x faster than my Gaussian Blur implementation.

// I called it Stack Blur because this describes best how this

// filter works internally: it creates a kind of moving stack

// of colors whilst scanning through the image. Thereby it

// just has to add one new block of color to the right side

// of the stack and remove the leftmost color. The remaining

// colors on the topmost layer of the stack are either added on

// or reduced by one, depending on if they are on the right or

// on the left side of the stack.

// If you are using this algorithm in your code please add

// the following line:

// Stack Blur Algorithm by Mario Klingemann <mario@quasimondo.com>

Bitmap bitmap;

if (canReuseInBitmap) {

bitmap = sentBitmap;

} else {

bitmap = sentBitmap.copy(sentBitmap.getConfig(), true);

}

if (radius < 1) {

return (null);

}

int w = bitmap.getWidth();

int h = bitmap.getHeight();

int[] pix = new int[w * h];

bitmap.getPixels(pix, 0, w, 0, 0, w, h);

int wm = w - 1;

int hm = h - 1;

int wh = w * h;

int div = radius + radius + 1;

int r[] = new int[wh];

int g[] = new int[wh];

int b[] = new int[wh];

int rsum, gsum, bsum, x, y, i, p, yp, yi, yw;

int vmin[] = new int[Math.max(w, h)];

int divsum = (div + 1) >> 1;

divsum *= divsum;

int dv[] = new int[256 * divsum];

for (i = 0; i < 256 * divsum; i++) {

dv[i] = (i / divsum);

}

yw = yi = 0;

int[][] stack = new int[div][3];

int stackpointer;

int stackstart;

int[] sir;

int rbs;

int r1 = radius + 1;

int routsum, goutsum, boutsum;

int rinsum, ginsum, binsum;

for (y = 0; y < h; y++) {

rinsum = ginsum = binsum = routsum = goutsum = boutsum = rsum = gsum = bsum = 0;

for (i = -radius; i <= radius; i++) {

p = pix[yi + Math.min(wm, Math.max(i, 0))];

sir = stack[i + radius];

sir[0] = (p & 0xff0000) >> 16;

sir[1] = (p & 0x00ff00) >> 8;

sir[2] = (p & 0x0000ff);

rbs = r1 - Math.abs(i);

rsum += sir[0] * rbs;

gsum += sir[1] * rbs;

bsum += sir[2] * rbs;

if (i > 0) {

rinsum += sir[0];

ginsum += sir[1];

binsum += sir[2];

} else {

routsum += sir[0];

goutsum += sir[1];

boutsum += sir[2];

}

stackpointer = radius;

for (x = 0; x < w; x++) {

r[yi] = dv[rsum];

g[yi] = dv[gsum];

b[yi] = dv[bsum];

rsum -= routsum;

gsum -= goutsum;

bsum -= boutsum;

stackstart = stackpointer - radius + div;

sir = stack[stackstart % div];

routsum -= sir[0];

goutsum -= sir[1];

boutsum -= sir[2];

if (y == 0) {

vmin[x] = Math.min(x + radius + 1, wm);

}

p = pix[yw + vmin[x]];

sir[0] = (p & 0xff0000) >> 16;

sir[1] = (p & 0x00ff00) >> 8;

sir[2] = (p & 0x0000ff);

rinsum += sir[0];

ginsum += sir[1];

binsum += sir[2];

rsum += rinsum;

gsum += ginsum;

bsum += binsum;

stackpointer = (stackpointer + 1) % div;

sir = stack[(stackpointer) % div];

routsum += sir[0];

goutsum += sir[1];

boutsum += sir[2];

rinsum -= sir[0];

ginsum -= sir[1];

binsum -= sir[2];

yi++;

}

yw += w;

}

for (x = 0; x < w; x++) {

rinsum = ginsum = binsum = routsum = goutsum = boutsum = rsum = gsum = bsum = 0;

yp = -radius * w;

for (i = -radius; i <= radius; i++) {

yi = Math.max(0, yp) + x;

sir = stack[i + radius];

sir[0] = r[yi];

sir[1] = g[yi];

sir[2] = b[yi];

rbs = r1 - Math.abs(i);

rsum += r[yi] * rbs;

gsum += g[yi] * rbs;

bsum += b[yi] * rbs;

if (i > 0) {

rinsum += sir[0];

ginsum += sir[1];

binsum += sir[2];

} else {

routsum += sir[0];

goutsum += sir[1];

boutsum += sir[2];

}

if (i < hm) {

yp += w;

}

yi = x;

stackpointer = radius;

for (y = 0; y < h; y++) {

// Preserve alpha channel: ( 0xff000000 & pix[yi] )

pix[yi] = (0xff000000 & pix[yi]) | (dv[rsum] << 16) | (dv[gsum] << 8) | dv[bsum];

rsum -= routsum;

gsum -= goutsum;

bsum -= boutsum;

stackstart = stackpointer - radius + div;

sir = stack[stackstart % div];

routsum -= sir[0];

goutsum -= sir[1];

boutsum -= sir[2];

if (x == 0) {

vmin[y] = Math.min(y + r1, hm) * w;

}

p = x + vmin[y];

sir[0] = r[p];

sir[1] = g[p];

sir[2] = b[p];

rinsum += sir[0];

ginsum += sir[1];

binsum += sir[2];

rsum += rinsum;

gsum += ginsum;

bsum += binsum;

stackpointer = (stackpointer + 1) % div;

sir = stack[stackpointer];

routsum += sir[0];

goutsum += sir[1];

boutsum += sir[2];

rinsum -= sir[0];

ginsum -= sir[1];

binsum -= sir[2];

yi += w;

}

bitmap.setPixels(pix, 0, w, 0, 0, w, h);

return (bitmap);

}

这是是网友提供的，先对Bitmap进行压缩处理，然后进行高斯模糊的算法，我稍微修改了一下。

public static BitmapDrawable doGassicBitmap(Resources resources,

Bitmap bkg, View view) {

float radius = 50;

float scaleFactor = 8;

Bitmap overlay = Bitmap.createBitmap(

(int) (view.getMeasuredWidth() / scaleFactor),

(int) (view.getMeasuredHeight() / scaleFactor),

Bitmap.Config.ARGB_8888);

Canvas canvas = new Canvas(overlay);

canvas.translate(-view.getLeft() / scaleFactor, -view.getTop()

/ scaleFactor);

canvas.scale(1 / scaleFactor, 1 / scaleFactor);

Paint paint = new Paint();

paint.setFlags(Paint.FILTER_BITMAP_FLAG);

canvas.drawBitmap(bkg, 0, 0, paint);

overlay = FastBlur.doBlur(overlay, (int) radius, true);

return new BitmapDrawable(resources, overlay);

}

这是我程序直接调用的在异步中进行高斯模糊处理

public static void doAyncTaskGassicBitmap(final Context context,

final View view) {

new AsyncTask<Void, Void, BitmapDrawable>() {

@Override

protected BitmapDrawable doInBackground(Void... v) {

// TODO Auto-generated method stub

Resources resources = context.getResources();

Bitmap bkg = BitmapFactory.decodeResource(resources,

R.drawable.picture10);

return doGassicBitmap(resources, bkg, view);

}

@Override

protected void onPostExecute(BitmapDrawable result) {

super.onPostExecute(result);

if (result != null)

view.setBackground(result);

}

}.execute();

}

其他一些视图包括时间更新控件，日期更新控件，滑动高亮控件，和仿ViewPager写的弹簧模式的视图组控件这里就不赘述。都是使用系统控件上修改的,直接给出源文件。

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